MK 0004 Marketing Research Contents

MK 0004Marketing Research

Contents

Unit 1

An Overview of Marketing Research 1

Unit 2

Research Process and Design 13

Unit 3

Sources of Research Data 40

Unit 4

Measurement Techniques in Marketing Research 77

Unit 5

Sampling and Data Analysis 104

Unit 6

Hypothesis Formation and Testing 124

Unit 7

Techniques of Quantitative Data Analysis 140

Unit 8

Writing a Research Report 147

Unit 9

Ethical Issues in Marketing Research 162

Unit 10

Contemporary Issues in Marketing Research 170

Edition: Fall 2007

BKID – B0798 8th Nov. 2007

Brig. (Dr). R. S. Grewal VSM (Retd.)Pro Vice ChancellorSikkim Manipal University of Health, Medical & Technological Sciences

Board of StudiesMr. Rajen PadukoneMember – Academic Senate, Sikkim Manipal UniversityMs. Vimala Parthasarathy Prof. K. V. VaramballyHOD DirectorConvener Manipal Institute of ManagementDepartment of Management & Commerce ManipalDirectorate of Distance EducationSikkim Manipal UniversityProf. Raj Dorai Mr. JagadeeshIndustry Consultant and Assistant ProfessorVisiting Faculty, IBA, IFIM and BIM, Department of Management &Bangalore Commerce, Directorate of Distance

Education, Sikkim Manipal UniversityMr. Umesh Maiya Mr. R. Ravindra RaoAssistant Professor Senior FacultyDepartment of Management & Commerce Manipal Institute of Management Directorate of Distance Education ManipalSikkim Manipal University

Content Preparation TeamContent Writing and CompilationProf. Xavier V. K.Christ CollegeBangaloreFormat Editing Language EditingMs. Shulagna Sarkar Mr. Radhakrishna RaoLecturer Lecturer in EnglishDept. of Management & Commerce UPMC, UdupiSikkim Manipal University ofHealth, Medical & Technological Sciences (SMU)Manipal – 576 104

Edition: Fall 2007

This book is a distance education module comprising of collection of learning material for our students.

All rights reserved. No part of this work may be reproduced in any form by any means without permission in writing from Sikkim Manipal University of Health, Medical and Technological Sciences, Gangtok, Sikkim.

Printed and Published on behalf of Sikkim Manipal University of Health, Medical and Technological Sciences, Gangtok, Sikkim by Mr. Rajkumar Mascreen, GM, Manipal Universal Learning Pvt. Ltd., Manipal – 576 104. Printed at Manipal Press Limited, Manipal.

SUBJECT INTRODUCTION

Marketing research is a critical part of such a marketing intelligence system;

it helps to improve management decision making by providing relevant,

accurate, and timely (RAT) information. Every decision poses unique needs

for information, and relevant strategies can be developed based on the

information gathered through marketing research.

In practice, marketing research department’s goal can be grouped into three

major categories: programmatic, selective or evaluative. Programmatic

research is performed to develop marketing options through market

segmentation, market opportunity analysis, or consumer attitude and

product usage studies. Selective research is done to test different decision

alternatives such as new product concept testing, advertising copy testing,

pretest marketing, and test marketing. Evaluative research is carried out to

evaluate performance of programs, including tracking advertising recall,

corporate and brand image studies, and measuring customer satisfaction

with the quality of the product ad service.

The research process consists of stages or steps that guide the project form

its conception through the final analysis, recommendation, and ultimate

action. The research process provides a systematic, planned approach to

the research project and ensures that all aspects of the research project are

consistence with each other. It is especially important that the research

design and implementation be consistent with the research purpose and

objectives. Otherwise, results will not help the client.

Unit 1:

An overview of marketing research

Meaning, Definition, and terminologies

The function of marketing research

Information and decision making

Marketing information systems

Marketing decision support systems

Types of research, areas of research etc

Unit 2:

The research process and design

Steps in research design process

Potential errors affecting the research design

Unit 3:

Sources of research data

Primary data and its types

Secondary data and its types

Commercial surveys, audits and panels

Survey research

Experimentation and experiment environment

Unit 4:

Measurement techniques in marketing research

The concept of measurement

Scales of measurement

Components of measurement

Measurement accuracy

Measurement development

Questionnaire design

Direct response attitude scales

Derived attitude scales

Observation and psychological measures

Unit 5:

Sampling and data analysis

The sampling process

Sample size determination

Unit 6:

Hypothesis and its test

Unit 7:

Issues and techniques of quantitative data analysis

Cross tabulation

Multiple Regression Analysis

Perceptual mapping

Conjoint analysis

Unit 8:

Writing a research report

Preparing the research report and approaches to research report

Preparing oral presentation

Reading research reports

Unit 9:

Ethical issues in marketing research

Corporate Espionage

Unit 10:

Contemporary issues in marketing research

Role of marketing research in industry

Ethical issues- code of conduct, data-protection act

Role of agency and client

Role of in-house researcher

Marketing Research Unit 1

Sikkim Manipal University Page No. 1

Unit 1 An Overview of Marketing Research

Structure

1. 1 Introduction: Meaning, Definition, and Terminologies

Objectives

1. 2 The Function of Marketing Research

1.2.1 Situation Analysis

1.2.2 Strategy Development

1.2.3 Market Program Development

1.2.4 Implementation

1. 3 Information and Decision Making

1. 4 Marketing Information Systems

1. 5 Marketing Decision Support Systems

1. 6 Types of research, areas of research

Self Assessment Questions

1. 7 Summary

1. 8 Terminal Question

1. 9 Answers to SAQs and TQs

1.1 Introduction: Meaning Definition and Terminologies

Marketing is the process of planning and executing the conception, pricing,

promotion, and distribution of ideas, goods, and services to create

exchanges that satisfy individual and organizational objectives. The

marketing concept requires that customer satisfaction rather than profit

maximization, be the goal of an organisation. In other words, the

organisation should be consumer oriented and should try to understand

consumer’s requirements and satisfy them quickly and efficiently, in ways

that are beneficial to both the consumer and the organisation. This means

that any research organisation should try to obtain information on consumer



needs and gather marketing intelligence to help satisfy these needs

efficiently.

Marketing research is a critical part of such a marketing intelligence system;

it helps to improve management decision making by providing relevant,

accurate, and timely (RAT) information. Every decision poses unique needs

for information, and relevant strategies can be developed based on the

information gathered through marketing research.

Objectives:

After studying this unit, the student should be able to:

understand the Function of Marketing Research

discuss the information and Decision Making

explain the Situation Analysis

understand Strategy Development

explain Market Program Development

discuss Marketing Information Systems

explain Marketing Decision Support Systems

discuss types of research, areas of research

Definition of Marketing Research

American Marketing Association officially defines marketing research as

follows: Marketing research is the function that links the consumer,

customer, and public to the marketer through information - information used

to identify and define marketing opportunities and problems; generate,

refine, and evaluate marketing actions; monitor marketing performance; and

improve understanding of marketing as a process. Marketing research

specifies the information required to address these issues, designs the

method for collecting information, manages and implements the data

collection process, analyses, and communicates the findings and their

implications.



This definition highlights the role of marketing research as an id to decision

making. An important feature is the inclusion of the specification ad

interpretation of needed information. Too often, marketing research is

considered narrowly as gathering and analyzing of data for someone to use.

Firms can achieve and sustain a competitive advantage through the creative

use of marketing information. Hence, marketing research is defined as

information input to decisions, not simply the evaluation of decisions that

have been made. Market research alone, however, does not guarantee

success; the intelligent use of market research is likely for business

achievement. A competitive edge is more the result of how information is

used than of who does or does not nave the information.

1.2 The Function of Marketing Research

Marketing decisions involve issues that range from fundamental shifts in the

positioning of a business or the decision to enter a new market to narrow

tactical questions of how best to stock a grocery shelf. The context for these

decisions is the market planning process, which proceeds sequentially

through four stages:

Situation analysis

Strategy development

Marketing program development

Implementation

This is a never-ending process, so the evaluation of past strategic decisions

serves as an input to the situation assessment.

1. 2.1 Situation Analysis

Effective marketing strategies are built on an in-depth understanding of the

market environment of the business, and the specific characteristics of the

market. The micro-environment includes political and regulatory trends,



economic and social trends, and technological trends. Marketing

researchers tend to focus on those trends that affect the demand for

products and services.

1.2.2 Strategy Development

During the strategy development stage the management team of the

business decides on answers to three critical questions. Marketing research

provides significant help in finding the answers to these questions.

What business should we be in? Specifically, what products or services

should we offer? What technologies will we utilize? Which market segments

should we emphasize? What channels should we use to reach the market?

These questions are compelling in markets that are mature and saturated,

including not only most packaged goods but also household appliances,

automobiles, and services such as banking and air travel. Research

supports this search for niches with large-scale quantitative market studies

that describe buying behaviors, consumer beliefs and attitudes, and

exposure to communication media. Large samples are needed to delineate

the segments, indicate their size, and determine what the people in each

segment are seeking in a product.

What will we compete? The management team has to decide why the

business is better than the competition in serving the needs of the target

segment, and what has to be done to keep it in front. Competitive superiority

is revealed in the market as either differentiation along attributes that are

important to target customers, or the lowest delivered cost position.

Marketing research is essential for getting answers to three key questions

about differentiation: what are the attributes of the product or services that

create value for the customer? Which attributes are most important? How do

we compare to the competition? An understanding of competitive advantage

also requires detailed knowledge of the capabilities, strategies, and



intentions of present and prospective competitors. Marketing research

contributes here in two ways: identifying the competitive set, and collecting

detailed information about each competitor.

What are the objectives for the business? An objective is a desired

performance result that can be quantified and monitored. There are usually

objectives of revenue growth, market share, and profitability. Increasingly,

firms are adopting objectives for service levels, and customer satisfaction.

Marketing research is needed to establish both the market share and the

level of customer satisfaction.

1.2.3 Marketing Program Development

Programs embrace specific tasks, such as developing a new product or

launching a new advertising campaign. An action program usually focuses

on a single objective in support of one element of the overall business

strategy. This is where the bulk of ongoing marketing research is directed.

Developing the marketing program – representative decisions that draw on

marketing research:

i) Segmentation decisions

Which segment should be the target?

What benefits are most important for each segment?

When geographic area should be entered?

ii) Product decisions

What product features should be included?

How should the price be positioned?

What type of package is preferred by the customers?

iii) Distribution decisions

What type of retailer should be used?

What should be the mark up policy?

Should a few outlets be employed or many?



iv) Advertising and promotion decisions

What appeals should be used in the advertising?

In which vehicles should the advertising be placed?

What should the budget be?

What sales promotion should be used, and when should it be

scheduled?

v) Personal selling decisions

What customer types have the most potential?

How many sales people are needed?

vi) Price decisions

What price level should be changed?

What sales should e offered during the year?

What response should be made to a competitor’s price?

vii) Branding decisions

What should be the name, symbol, logo and slogan that will be

associated with the product?

What is the position that the brand should adopt vis-à-vis the

competition?

How can brand loyalty be increased?

viii)Customer satisfaction decisions

How should customer satisfaction be measured?

How often should it be measured?

How should customer complaints be handled?

1.2.4 Implementation

The beginning of the implementation phase is signalled by a decision to

proceed with a new program or strategy and by the related commitments to

objectives, budgets, and timetables. At this point, the focus of marketing

research shifts to such questions as:



i) Did the elements of the marketing program achieve their objectives?

How id sales compare with objectives?

In what areas were sales disappointing? Why?

Were the advertising objectives met?

Did the product achieve its distribution objectives?

Are any supermarkets discounting the product?

ii) Should the marketing program be continued, revised, or expanded?

Are customers satisfied with the product?

Should the product be changed? More features added?

Should the advertising budget be changed?

Is the price appropriate?

For research to be effective at this stage, it is important that specific

measurable objectives be set for all elements of the marketing program.

There should be sales goals by geographic area; distribution goals, perhaps

in terms of the number of stores carrying the product; and advertising goals,

such as achieving certain levels of awareness. The role of marketing

research is to provide measures against these objectives and to provide

more focused studies to determine why results are below or above

expectations.

1.3 Information and Decision Making

The decision whether to conduct marketing research depends on the type

and nature of the information sought. If the information required for decision

making already exists within the organisation in the form of results of a study

conducted for a different problem or in the form of managerial experience

and talents, marketing research is not called for. Under these

circumstances, further research would be redundant and a waste of money.



1.4 Marketing Information system

An information system is a continuing and interacting structure of people,

equipment and procedures designed to gather, sort, analyze, evaluate and

distribute pertinent, timely and accurate information to decision makers.

While marketing research is concerned mainly with the actual content of the

information and how it is to be generated, the information system is

concerned with managing the flow of data from many different projects and

secondary sources to the managers who will use it. The required databases

organize and store the information and the decision support systems

(DSS) to retrieve the data, transform it into usable information and

disseminate it to users.

Information systems contain three types of information. The first is recurring

day-to-day information, for example, the market and accounting data that

flow into the organisation as a result of market analysis research ad

accounting activities. Automobiles firms use government sources for

monthly data on new cars sales by brand and geographic area. In addition,

surveys are conducted yearly to determine the ages and types of

automobiles currently being driven, the lifestyles of the drivers, their media

habits, and their intentions to replace their cars. The accounting department

submits sales and inventory data for each of its dealers on a continuing

basis to update and supplement the information system.

A second type of information is intelligence relevant to the future strategy of

the business. Automobile firms collect reports about new sources of fuel to

power automobiles. This information might come from scientific meetings,

trade organizations, or perhaps form government reports. It also includes

information from salespersons or dealers about new product tests being

conducted by competitive firms. Intelligence is difficult to develop, because it

usually involves diverse and changing sets of topic and information sources

and is rarely collected systematically.



A third input to the information system is research studies that are not of a

recurring nature. The potential usefulness of a marketing research study can

be multiplied manifold if the information is accessible instead of filed and

forgotten.

1.5 Marketing Decision Support Systems

Databases have no value if the insights they contain cannot be retrieved. A

decision support system not only allows the manager to interact directly with

the database to retrieve what is wanted, it also provides a modelling function

to help make sense of what has been retrieved.

A common example of a DSS in action is that used by many industrial sales

people – especially those selling products that require significant

customization. The salesperson frequently will be asked whether or not the

price and delivery time of a unique product configuration will meet or exceed

a competitor’s promises. Without leaving the customer’s office, the

salesperson can plug a laptop computer into a phone jack and begin

communicating with a database stored in the company’s main computer

memory. The salesperson types in the product configuration and desired

delivery data, and these requirements are compared to the costs, inventory,

and assembly time contained in the data bank. In a matter of minutes, the

sales person can propose a price and delivery date – and perhaps close the

sales.

Each firm has to develop or adapt a model to support its own decision

problems.

A sales force turnover model, which revealed that the most significant

variable influencing the turnover rate was the level of the appointment fee

that representatives pay for initial materials.



An order model is that which explains the components of the average order

and isolates the actionable variables such as the size and timing of the

catalogue and the gift incentives.

A procurement model is that which helps determine how much of a new

product to buy, when to purchase it and the risks involved.

1.6 Types of Research, Areas of Research

In practice, marketing research department’s goal can be grouped into three

major categories: programmatic, selective or evaluative.

Programmatic research is performed to develop marketing options through

market segmentation, market opportunity analysis, or consumer attitude and

product usage studies.

Selective research is done to test different decision alternatives such as

new product concept testing, advertising copy testing, pre-test marketing,

and test marketing.

Evaluative research is carried out to evaluate performance of programs,

including tracking advertising recall, corporate and brand image studies, and

measuring customer satisfaction with the quality of the product and service.

Self Assessment Questions I

State whether the following statements are true or false:

1. An information system is a continuing and interacting structure of

people, equipment and procedures designed to gather, sort, analyze,

evaluate and distribute pertinent, timely and accurate information to

decision makers.

2. A decision support system allows the manager to interact directly with

the database to retrieve what is wanted, and provides a modelling

function to help make sense of what has been retrieved.



3. Marketing research can be grouped into three major categories:

programmatic, selective or evaluative

1.7 Summary

Marketing research is the function that links the consumer, customer, and

public to the marketer through information- information used to identify and

define marketing opportunities and problems; generate refine, and evaluate

marketing actions; monitor marketing performance; and improve

understanding of marketing as a process. Marketing research specifies the

information required to address these issues, designs the method for

collecting information, manages and implements the data collection process,

analyses, and communicates the findings and their implications. The market

planning process, which proceeds sequentially through four stages:

Situation analysis

Strategy development

Marketing program development

Implementation

An information system is a continuing and interacting structure of people,

equipment and procedures designed to gather, sort, analyze, evaluate and

distribute pertinent, timely and accurate information to decision makers. A

decision support system allows the manager to interact directly with the

database to retrieve what is wanted, and provides a modeling function to

help make sense of what has been retrieved. Marketing research can be

grouped into three major categories: programmatic, selective or evaluative

1.8 Terminal Questions

1. Define market research.

2. What are decision support systems?



3. What are marketing program development?

4. What is strategy development?

5. What is situation analysis?

6. What are the marketing information systems in market research?

7. Explain the functions of marketing research.

8. What are the major questions to be addressed in conducting a marketing

research?

1.9 Answers to SAQs and TQs

SAQs

1. True

2. True

3. True

TQs

1. Section 1.2.

2. Section 1.6

3. Section 1.3.3

4. Section 1.3.2

5. Section 1.3.1

6. Section 1.5

7. Section 1.3

8. Section 1.3.3



Unit 10 Contemporary Issues in

Marketing Research

Structure

10.1 Introduction: Role of Marketing Research in Industry

Objectives

10.2 Assessing Competitive Advantage

10.3 Market Based Assessment

10.3.1 Market Share

10.3.2 Recall Share

10.3.3 Advertisement Share

10.3.4 R&D Share

10.4 Process Based Assessment

10.4.1 Market Skills Audit

10.4.2 Comparison Relative to Cost

10.4.3 Comparison of Winners vs. Losing Competitors

10.4.4 Brand Equity

10.5 Customer Satisfaction

10.6 Total Quality Management

10.7 Identifying High Leverage Phenomena

10.8 Ethical Issues- Code of Conduct, Data-Protection Act

10.9 Role of Agency and Client

10.10 Role of In-House Researcher


10.11 Summary





10.1 Introduction: Role of Marketing Research in Industry

To survive in twentieth century, firms must not only provide goods and

services to the customer efficiency but should also possess sustainable

competitive advantage. Hence, there has been a shift of focus in marketing,

from delivering goods and services to consumers (satisfying their needs) to

achieve a competitive advantage. Companies are embracing new tools,

techniques and strategies in order to remain competitive

A strategy that companies have begun to adopt is total quality management

(TQM). To decide on and implement this strategy, mangers require

dramatically different information than they need for making marketing-mix

decisions. Hence, marketing research has to rise to the challenge and

provide managers with requisite information. Moreover, tremendous

advances in the field of statistics and computational capabilities have led

market researchers to adopt more and more sophisticated techniques.

Objectives:

After studying this unit, the students should be able to understand various

researches related to:

Assessing competitive advantage

Market based assessment

Market share

Recall share

Advertisement share

R&D share

Process based assessment

Market skills audit

Comparison relative to cost

Comparison of winners vs. losing competitors

Brand equity



Customer satisfaction

Total Quality Management

Identifying high leverage phenomena

Ethical issues- code of conduct, data-protection act

Role of agency and client

Role of in-house researcher

10.2 Assessing Competitive Advantage

Assessing competitive advantage can be done in different ways. The

methods can be broadly classified as market based assessment and

process based assessment. Market based assessment is direct comparison

with a few target competitors; whereas, process based assessment is

comparison of the methods employed by the competitors in achieving their

distinctive advantage.

10.3 Market-based Assessment

10.3.1 Market Share

Market share is measured as a percentage of total industry sales over a

specified period. Clearly, there are problems in assessing competitive

advantage using market share. A company’s market share can change

dramatically depending on whether the market is defined as global, a

particular export market, domestic market, regional market ,a city, a

segment of users, or is based on product usage.

The change in market share over time is a vital indicator of competitive

dynamics, particular during the growth stage of a product or market. It

indicates whether the firm is ahead, abreast, or behind the market’s total

growth rate.



10.3.2 Recall Share

Recall share is the percentage of customers who name the brand when they

are asked to name the first brand that comes to mind when they consider

buying a particular type of product. This indicates the consumer’s top-of-

mind brand awareness and preferences and gives a measure of advantage

to that brand over others in the market.

10.3.3 Advertising Share

Advertising share is the percentage of media space or time a brand has of

the total media share for that industry, often measured simply as dollars

spent on advertising. This is likely to lead to a change in recall share.

Advertising share is another measure of the current competition that a firm

faces

10.3.4 R&D Share

R&D share is a company’s research and development expenditure as a

percentage of total industry R&D expenditures. This is a long-term predictor

of new-product development, improvements in quality, cost reductions, and

hence market share. It is very important measure of future competitiveness

in many high-technology markets. All of these shares can be obtained from

either survey data or secondary data.

10.4 Process-based Assessment

10.4.1 Marketing Skills Audit

Skills are the most distinctive encapsulation of the organization’s way of

doing business. One vehicle for assessing skills is the marketing audit. This

is a comprehensive, systematic, independent, and periodic examination of a

business unit’s marketing environment, objectives, strategies and activities.

The audit should be based on customer orientation or focus on customer

satisfaction as its overriding theme. The audit is simply a marketing

research project whose objective is to critically evaluate the way the firm

performs in its environment.



10.4.2 Comparison of relative to Cost

Another measure of advantage is a comparison of the firm’s costs versus

those of competitors. The company gains a cost advantage when its

cumulative costs are lower than its competitor’s. Competitors’ costs can be

estimated from public data or interviews with suppliers and distributors.

Secondary data can be used to obtain such a data.

10.4.3 Comparison of Winning vs. Losing Competitors

Key success factors can be inferred by analyzing differences in performance

among competitors. For this approach to yield useful insights, three difficult

questions must be answered. First, which competitors should be included in

the comparison set? Second, which criteria should be used to distinguish

the winners form the losers (e.g. profitability, growth, market share, creation

of markets)? Third, what are the reasons for the differences in performance?

10.4.4 Brand Equity

Brand equity is defined as a set of assets and liabilities linked to a brand

that add to or subtract form the value of a product or service to a company

and/or its customers. The assets or liabilities that underlie brand equity must

be linked to the name and symbol of the brand. They can be grouped into

five categories:

Brand loyalty

Name awareness

Perceived quality

Brand associations in addition to perceived quality

Other proprietary brand assets: patents, trademarks, channel

relationships etc.

10.5 Customer Satisfaction

In recent years, American business has become increasingly committed to

the idea of customer satisfaction and product serve quality. The



measurement of customer satisfaction and its link to product/service

attributes is the vehicle for developing a market driven approach. Customer

satisfaction research has been around for a long time, but it has become a

fixture at most large corporation only in recent years.

10.6 Total Quality Management

Recent years have witnessed a renewed emphasis on delivering superior

quality products and services to customers. With foreign competition

steadily eating away the profitability and the market shares of Indian

companies, more and more of them are adopting total quality management

(TQM) to become more competitive. TQM is a process of managing

complex changes in the organisation with the aim of improving quality.

10.7 Identifying High-Leverage Phenomena

Ideally, these are causal relationships that describe how controllable

variables such as plant scale, production-run length, and sales costs per

unit.

10.8 Ethical Issues- Code of Conduct, Data-Protection Act

The Code of Ethics of Marketing Research Association

a. Ethics refers to moral principles or values that generally govern the

conduct of an individual or group. Researchers have responsibilities to

their profession, clients, and respondents and must adhere to high

ethical standards to ensure that both the function and information are

not brought into disrepute. The marketing Research association, Inc

(Chicago, Illinois) has instituted a code of ethics of professional Ethics

and Practices for marketing ethical decisions.

b. The code of Professional Ethics and Practices

c. To maintain high standard of competence and integrity in marketing and

survey research.



d. To maintain the highest level of business and professional conduct and

to comply with Federal State and local laws, regulations and ordinances

applicable to my business practice and those of my company.

e. To exercise all reasonable care to observe the best standards of

objectivity and accuracy in the development, collection, processing and

reporting of marketing and survey research information.

f. To thoroughly instruct and supervise all persons for whose work I am

responsible in accordance with study specifications and general

research techniques.

g. To observe the rights of ownership of all materials received from and /or

developed for clients, and to keep in confidence all research techniques,

data and other information considered confidential by their owners.

h. To make available to clients such details on the research methods and

techniques of an assignment as may be reasonably required for proper

interpretation of the data, providing this reporting does not violate the

confidence of respondents of clients.

i. To promote the trust of the public for marketing and survey research

activities and to avoid any procedure which, misrepresents the activities

of a respondents, the rewards of cooperation or the uses of data.

j. To refrain from referring to membership in this organisation as proof of

competence, since the organisation does not so certify any person or

organisation.

k. To encourage the observance of principles of this code among all

people engaged in marketing and survey research.

10.9 Role of Agency and Client

A respondent who participate in a marketing research project has the ethical

obligation to provide the supplier, and hence the client, with honest and

truthful answers. The respondent could refrain from answering a sensitive

question, but falsifying the answer is ethically improper.



Any respondent who participates in a research project has the following

rights:

The right to privacy

The right to safety

The right to know the true purpose of the research

The right to the research results

The right to decide which questions to answer

10.10 Role of In-House Researcher

The marketing manager’s essential task is to develop a marketing strategy

that involves combining the marketing mix elements in such a way that they

complement each other and positively influence customer’s value

perceptions and behaviours. This task should be much simpler if all

elements that affect customer’s perceptions of value were under the

manager’s control and if customer reaction to any contemplated change

could be predicted with certainty. However, a number of factors affecting the

success of the marketing effort, including economic, political and legal,

social, natural, technological and competitive environments are beyond the

marketing manager’s control and the behaviour of individual customers is

largely unpredictable.



1. Market share is measured as a percentage of total industry sales over a

specified time period.

2. Recall share is the percentage of customers who name the brand when

they are asked to name the first brand that comes to mind when they

consider buying a particular type of product.



3. Advertising share is the percentage of media space or time a brand has

of the total media share for that industry, often measured simply as

dollars spent on advertising.

4. R&D share is a company’s research and development expenditure as a

percentage of total industry R&D expenditures

10.11 Summary

To survive in twentieth century, firms must not only provide goods and

services to the customer efficiency but should also possess sustainable

competitive advantage. Companies are embracing new tools, techniques

and strategies in order to remain competitive. A strategy that companies

have begun to adopt is total quality management (TQM). Assessing

competitive advantage can be done in different ways. The methods can be

broadly classified as market based assessment and process based

assessment. Market based assessment is direct comparison with a few

target competitors; whereas, process based assessment is comparison of

the methods employed by the competitors in achieving their distinctive

advantage. Market share is measured as a percentage of total industry

sales over a specified time period. The change in market share over time is

a vital indicator of competitive dynamics, particular during the growth stage

of a product or market. It indicates whether the firm is ahead, abreast, or

behind the market’s total growth rate. Recall share is the percentage of

customers who name the brand when they are asked to name the first brand

that comes to mind when they consider buying a particular type of product.

Advertising share is the percentage of media space or time a rand has of

the total media share for that industry, often measured simply as dollars

spent on advertising. R&D share is a company’s research and development

expenditure as a percentage of total industry R&D expenditures. Skills are

the most distinctive encapsulation of the organization’s way of doing



business. One vehicle for assessing skills is the marketing audit. Another

measure of advantage is a comparison of the firm’s costs versus those of

competitors. Key success factors can be inferred by analyzing differences in

performance among competitors. Brand equity is defined as a set of assets

and liabilities linked to a brand that add to or subtract form the value of a

product or service to a company and/or its customers. They can be grouped

into five categories:

Brand loyalty

Name awareness

Perceived quality

Brand associations in addition to perceived quality

Other proprietary brand assets: patents, trademarks, channel relationships

etc. In recent years, American business has become increasingly committed

to the idea of customer satisfaction and product serve quality. Recent years

have witnessed a renewed emphasis on delivering superior quality products

and services to customers. With foreign competition steadily eating away

the profitability and the market shares of Indian companies, more and more

of them are adopting total quality management (TQM) to become more

competitive.

Ethics refers to moral principles or values that generally govern the conduct

of an individual or group. Researchers have responsibilities to their

profession, clients, and respondents and must adhere to high ethical

standards to ensure that both the function and information are not brought

into disrepute. A respondent who participate in a marketing research project

has the ethical obligation to provide the supplier, and hence the client, with

honest and truthful answers. The marketing manager’s essential task if to

develop a marketing strategy that involves combining the marketing mix

elements in such a way that they complement each other and positively

influence customer’s value perceptions and behaviours.




1. Explain the Role of Marketing Research in Industry

2. How Competitive Advantage is assessed?

3. What is Market-based Assessment research?

4. How do we find out Brand Equity?

5. What is Customer Satisfaction?

6. What is Total Quality Management?

7. Explain The Code of Ethics of Marketing Research Association

8. What is the role of Agency and Client with respect to marketing research

ethics?

9. What is the role of in-house researcher?


SAQs

1. True

2. True

3. True

4. True

TQs

1. Section 10. 1

2. Section 10.3

3. Section 10.3

4. Section 10.4.3

5. Section 10. 5.

6. Section 10.6

7. Section 10.8.

8. Section 10.9.

9. Section 10.10



References:

1. Gilbert A. Churchill, Dawn Iacobucci, Marketing Research –

Methodological Foundations, Thomson, United States, 2004.

2. John R. Sparks and Shelly D. Hunt, Marketing Researcher Ethical

Sensitivity; Conceptualisation, Measurement and Exploratory Investigation,

Journal of Marketing, pp. 92-109.

–––––––––––––––––––––



Unit 2 Research Process and Design

Structure

2.1 Introduction: Nature of Research Process

Objectives

2.2 Steps in research design process

2.2.1 Step 1. Research Purpose

2.2.2 Step 2. Research Objectives

2.2.3 Step 3.Estimating the value of information

2.3 Research Design

2.3.1 Needs of research Design

2.3.2 Characteristics of good research design

2.3.3 Important concepts relating to research design

2.3.4 Types of research design

2.3.5 Principles of research design

2.3.6 Important experimental designs

2.3.7 Formal experimental design

2.4 Potential errors affecting the research design

2.4.1 Sampling error

2.4.2 Non-sampling error

2.4.3 Design error

2.4.4 Selection error

2.4.5 Population specific error

2.4.6 Sampling frame error

2.4.7 Surrogate information error

2.4.8 Measurement error

2.4.9 Experimental error

2.4.10 Data analysis error

2.4.11 Administration error



2.4.12 Questioning error

2.4.13 Recording error

2.4.14 Interference error

2.4.15 Response error

2.4.16 Non-response error

Self assessment Questions

2.5 Summary

2.6 Terminal Question


2.1 Introduction: Nature of Research Process

The research process consists of stages or steps that guide the project form


action. The research process provides a systematic, planned approach to

the research project and ensures that all aspects of the research project are

consistent with each other. It is especially important that the research design

and implementation be consistent with the research purpose and objectives.

Otherwise, results will not help the client.

Research studies evolve through a series of steps, each representing the

answer to a key question.

1. Why should we do research? This establishes the research purpose as

seen by the management team that will be using the results. This step

requires the understanding the decisions to be made and the problems

or opportunities to be diagnosed.

2. What research should be done? Here the management purpose is

translated into objectives that tell the researchers exactly what questions

need to be answered by the research study or project.



3. Is it worth doing research? The decision has to be made here about

whether the value of the information that is likely to be obtained is going

to be greater than the cost of collecting it.

4. How should the research be designed to achieve the research

objectives? Design issues include the choice of research approach –

reliance on secondary data versus conducting a survey or experiment-

and the specifics of how to collect the data.

5. What will we do with the research? Once the data have been collected,

how will it be analysed, interpreted, and used to make recommendations

for action.

Objectives:

After studying this unit, the student should be able to:

explain the Steps in research design process

discuss the Research Design

understand the needs of research Design

explain the characteristics of good research design

discuss the important concepts relating to research design

explain the types of research design

discuss the principles of research design

understand the important experimental designs

understand the formal experimental design

identify the potential errors affecting the research design

2.2 Steps in Marketing Research Design Process

2. 2.1 Step 1- Research Purpose

It is in the best interest of both the researcher and managers paying for the

research to be sure that the research purpose is fully understood. One of

the hallmarks of a competent researcher is the ability to get the heart of the

management problem.



The research purpose comprises a shared understanding between the

manager and the researcher of:

1. Problems or opportunities to be studied

Which problems or opportunities are anticipated?

What is the scope of the problems and the possible reasons?

2. Decision alternatives to be evaluated

What are the alternatives being studied?

What are the criteria for choosing among the alternatives?

What is the timing or importance of the decision?

3. Users of the research results

Who are the decision makers?

Are there any covet purpose?

Problem or Opportunity Analysis: In analyzing problems or opportunities

to be studied, constant contact with customers to monitor trends is very

important. Research is often motivated by problem or opportunity. The fact

that people are consuming fewer sweets might be a problem or a potential

opportunity for a candy company. Increased leisure time might be viewed as

an opportunity by a recreation oriented organisation. In such cases the

research purpose should specify the problem or opportunity to be explored.

The manager should make sure that real problem is being addressed.

Decision Alternatives: For research to be effective, it must be associated

with a decision. Marketing research is committed to the principle of utility. In

general, if the research is not going to have an effect on decisions, it is an

exercise in futility. The researcher should be always sensitive to the

possibility that either there are no decision alternatives – and therefore no

decision – or that the research findings will not affect the decision, usually

because of resource or organizational constraints. In such circumstances,

the research will have no practical value and probably should not be

conducted.



Criteria for Choosing among Alternatives: It is essential for the

researcher to know how the decision maker will choose among the available

alternatives. Suppose the product manager is considering three possible

packages redesigning for a health-care product with declining sales. The

following criteria to choose the best of the three alternative packages:

1. Long run sales

2. Trial purchases by users f competing brands

3. Amount of shelf space assigned to the brand

4. Differentiation from competitive packages

5. Brand-name recognition.

Research Users: When the research results will be used to guide internal

problem solving, the researcher must know the objectives and expectations

of the actual decision makers. The bigger the problem, the more difficult this

becomes, for not only are a large number of people likely to be involved, but

the contact person may simply be acting as a liaison whose interpretation of

the problem and the need for research may be second-hand. The major

benefit from making an effort to reach all the decision makers is that the

research purpose is likely to be specified more adequately.

2.2.2 Step 2 – Research Objective

The research objective is a statement, in as precise terminology as possible,

of what information is needed. The research objective should be framed so

that obtaining the information will ensure that the research purpose is

satisfied.

Research objectives have three components. The first is the research

question. It specifies the information the decision maker needs. The second

and the third elements help the researcher make the research question as

specific and precise as possible. The second is the development of

hypotheses that are basically alternative answers to the research questions.



The research determines which of these alternative answers is correct. It is

not always possible to develop hypothesis, but an effort should be made.

The third is the scope or boundaries of the research.

2.2.3 Step 3 – Estimating the Value of Information

Before a research approach can be selected, it is necessary to have an

estimate of the value of information – that is, the value of obtaining answers

to the research questions. Such an estimate will help determine how much,

if anything, should be spent on the research.

The value will depend on the importance of the decision as noted in the

research purpose, the uncertainty that surrounds it, and the influence of the

research information on the decision. If the decision is highly significant in

terms of the investment required or in terms of its effect on the long- run

success of the organisation, then information may have a high value.

However, uncertainty that is meaningful to the decision also must exist if the

information is to have value. If the outcomes are already known with

certainty, or if the decision will not be affected by the research information,

the information will have no value.

2.3 Research Design

A research design is a logical and systematic plan prepared for directing a

research study. It specifies the objectives of the study, the methodology and

techniques to be adopted for achieving the objectives. It constitutes the blue

print for the collection, measurement and analysis of data. It is the plan,

structure and strategy of investigation conceived so as to obtain answers to

research questions. The plan is the overall scheme or program of research.

A research design is the program that guides the investigator in the process

of collecting, analyzing and interpreting observations. It provides a

systematic plan of procedure for the researcher to follow.



Selltiz, Jahoda and Destsch and Cook describe, “A research design is the

arrangement of conditions for collection and analysis of data in a manner

that aims to combine relevance to the research purpose of with economy in

procedure.”

2.3.1 Needs of Research Design

1) In many a research inquiry, the researcher has no idea as to how

accurate the results of his study ought to be in order to be useful. Where

such is the case, the researcher has to determine how much inaccuracy

may be tolerated. In a quite few cases he may be in a position to know

how much inaccuracy his method of research will produce. In either

case he should design his research if he wants to assure himself of

useful results.

2) In many research projects, the time consumed in trying to ascertain what

the data mean after they have been collected is much greater than the

time taken to design a research which yields data whose meaning is

known as they are collected.

3) The idealized design is concerned with specifying the optimum research

procedure that could be followed where there are no practical

restrictions.

2.3.2 Characteristics of a Good Research Design

1) It is a series of guide posts to keep one going in the right direction.

2) It reduces wastage of time and cost.

3) It encourages coordination and effective organization.

4) It is a tentative plan which undergoes modifications, as

circumstances demand, when the study progresses, new aspects,

new conditions and new relationships come to light and insight into

the study deepens.



5) It has to be geared to the availability of data and the cooperation of

the informants.

6) It has also to be kept within the manageable limits

2.3.3 Important Concepts relating to Research Design

It is important to be familiar with the important concepts relating to research

design. They are:

1. Dependent and Independent variables: A magnitude that varies is

known as a variable. The concept may assume different quantitative

values, like height, weight, income, etc. Qualitative variables are not

quantifiable in the strictest sense of objectivity. However, the

qualitative phenomena may also be quantified in terms of the presence

or absence of the attribute considered. Phenomena that assume

different values quantitatively even in decimal points are known as

‘continuous variables’. But, all variables need not be continuous.

Values that can be expressed only in integer values are called ‘non-

continuous variables’. In statistical term, they are also known as

‘discrete variable’. For example, age is a continuous variable; where

as the number of children is a non-continuous variable. When changes

in one variable depends upon the changes in one or more other

variables, it is known as a dependent or endogenous variable, and the

variables that cause the changes in the dependent variable are known

as the independent or explanatory or exogenous variables. For

example, if demand depends upon price, then demand is a dependent

variable, while price is the independent variable. And if, more variables

determine demand, like income and prices of substitute commodity,

then demand also depends upon them in addition to the own price.

Then, demand is a dependent variable which is determined by the

independent variables like own price, income and price of substitute.



2. Extraneous variable: The independent variables which are not

directly related to the purpose of the study but affect the dependent

variable are known as extraneous variables. For instance, assume that

a researcher wants to test the hypothesis that there is relationship

between children’s school performance and their self-concepts, in

which case the latter is an independent variable and the former the

dependent variable. In this context, intelligence may also influence the

school performance. However, since it is not directly related to the

purpose of the study undertaken by the researcher, it would be known

as an extraneous variable. The influence caused by the extraneous

variable on the dependent variable is technically called as an

‘experimental error’. Therefore, a research study should always be

framed in such a manner that the dependent variable that completely

influence the change in the independent variable and any other

extraneous variable or variables.

3. Control: One of the most important features of a good research

design is to minimize the effect of extraneous variable. Technically, the

term control is used when a researcher designs the study in such a

manner that it minimizes the effects of extraneous independent

variables. The term control is used in experimental research to reflect

the restrain in experimental conditions.

4. Confounded relationship: The relationship between dependent and

independent variables is said to be confounded by an extraneous

variable, when the dependent variable is not free from its effects.

5. Research hypotheses: When a prediction or a hypothesized

relationship is tested by adopting scientific methods, it is known as

research hypothesis. The research hypothesis is a predictive

statement which relates a dependent variable and an independent

variable. Generally, a research hypothesis must consist of at least one



dependent variable and one dependent variable. Whereas, the

relationships that are assumed but not be tested are predictive

statements that are not to be objectively verified are not classified as

research hypotheses.

6. Experimental and non-experimental hypothesis testing research:

when the objective of a research is to test a research hypothesis, it is

known as a hypothesis-testing research. Such research may be in the

nature of experimental design or non-experimental design. A research

in which the independent variable is manipulated is known as

‘experimental hypothesis-testing research’, where as a research in

which the independent variable is no manipulated is termed as ‘non-

experimental hypothesis-testing research’. E.g., assume that a

researcher wants to examine whether family income influences the

social attendance of a group of students, by calculating the coefficient

of correlation between the two variables. Such an example is known

as a non-experimental hypothesis-testing research, because the

independent variable family income is not manipulated. Again assume

that the researcher randomly selects 150 students from a group of

students who pay their school fees regularly and them classifies them

into two sub-groups by randomly including 75 n Group A, whose

parents have regular earning, and 75 in group B, whose parents do not

have regular earning. And that at the end of the study, the researcher

conducts a test on each group in order to examine the effects of

regular earnings of the parents on the school attendance of the

student. Such a study is an example of experimental hypothesis-

testing research, because in this particular study the independent

variable regular earnings of the parents have been manipulated.

7. Experimental and control groups: When a group is exposed to

usual conditions in an experimental hypothesis-testing research, it is



known as ‘control group’. On the other hand, when the group is

exposed to certain new or special condition, it is known as an

‘experimental group’. In the afore-mentioned example, the Group A

can be called a control group and the Group B an experimental group.

If both the groups A and B are exposed to some special feature, then

both the groups may be called as ‘experimental groups’. A research

design may include only the experimental group or the both

experimental and control groups together.

8. Treatments: Treatments are referred to the different conditions to

which the experimental and control groups are subject to. In the

example considered, the two treatments are the parents with regular

earnings and those with no regular earnings. Likewise, if a research

study attempts to examine through an experiment the comparative

impacts of three different types of fertilizers on the yield of rice crop,

then the three types of fertilizers would be treated as the three

treatments.

9. Experiment: An experiment refers to the process of verifying the truth

of a statistical hypothesis relating to a given research problem. For

instance, experiment may be conducted to examine the yield of a

certain new variety of rice crop developed. Further, Experiments may

be categorized into two types namely, absolute experiment and

comparative experiment. If a researcher wishes to determine the

impact of a chemical fertilizer on the yield of a particular variety of rice

crop, then it is known as absolute experiment. Meanwhile, if the

researcher wishes to determine the impact of chemical fertilizer as

compared to the impact of bio-fertilizer, then the experiment is known

as a comparative experiment.

10. Experiment unit: Experimental units refer to the predetermined plots,

characteristics or the blocks, to which the different treatments are



applied. It is worth mentioning here that such experimental units must

be selected with great caution.

2.3.4 Types of Research Designs

There are a number of crucial research choices and various writers advance

different classification schemes, some of which are:

1. Experimental, historical and inferential designs (American Marketing

Association).

2. Exploratory, descriptive and causal designs (Selltiz, Jahoda, Deutsch

and Cook).

3. Experimental, and expost facto (Kerlinger)

4. Historical method, and case and clinical studies (Goode and scates)

5. Sample surveys, field studies, experiments in field settings, and

laboratory experiments (Festinger and Katz)

6. Exploratory, descriptive and experimental studies (Body and Westfall)

7. Exploratory, descriptive and casual (Green and Tull)

8. Experimental, ‘quasi-experimental designs’ (Nachmias and Nachmias)

9. True experimental, quasi-experimental and non-experimental designs

(Smith).

10. Experimental, pre-experimental, quasi-experimental designs and

Survey Research (Kidder and Judd).

These different categorizations exist, because ‘research design’ is a

complex concept. In fact, there are different perspectives from which any

given study can be viewed. They are:

1) The degree of formulation of the problem (the study may be

exploratory or formalized)

2) The topical scope-breadth and depth-of the study (a case or a

statistical study)



3) The research environment: field setting or laboratory (survey,

laboratory experiment)

4) The time dimension (one-time or longitudinal)

5) The mode of data collection (observational or survey)

6) The manipulation of the variables under study (experimental or expost

facto)

7) The nature of the relationship among variables (descriptive or causal)

1. Research design in case of exploratory research studies:

Exploratory research studies are also termed as formulative research

studies. The main purpose of such studies is that of formulating a

problem for more precise investigation or of developing the working

hypotheses from an operational point of view. The major emphasis in

such studies is on the discovery of ideas and insights. As such, the

research design appropriate for such studies must be flexible enough to

provide opportunity for considering different aspects of a problem under

study. Inbuilt flexibility in research design is needed because the

research problem, broadly defined initially, is transformed into one with

more precise meaning in exploratory studies, which in fact may

necessitate changes in the research procedure for gathering relevant

data. Generally, the following three methods in the context of research

design for such studies are talked about:

a. The survey of concerning literature happens to be the most

simple and fruitful method of formulating precisely the research

problem or developing hypotheses. Hypotheses stated by earlier

workers may be reviewed and their usefulness be evaluated as a

basis for further research. It may also be considered whether the

already stated hypotheses suggest new hypotheses. In this way, the

researcher should review and build upon the work already done by

others, but in cases where hypotheses have not yet been



formulated, his task is to review the available material for deriving

the relevant hypotheses from it.

b. Besides, the bibliographical survey of studies, already made in

one’s area of interest may as well as made by the researcher for

precisely formulating the problem. He should also make an attempt

to apply concepts and theories developed in different research

contexts to the area in which he himself is working. Sometimes, the

works of creative writers also provide a fertile ground for hypotheses

formulation as such may be looked into by the researcher.

c. Experience survey means the survey of people who have had

practical experience with the problem to be studied. The object of

such a survey is to obtain insight into the relationships between

variables and new ideas relating to the research problem. For such a

survey, people who are competent and can contribute new ideas

may be carefully selected as respondents to ensure a representation

of different types of experience. The respondents so selected may

then be interviewed by the investigator. The researcher must

prepare an interview schedule for the systematic questioning of

informants. But, the interview must ensure flexibility in the sense that

the respondents should be allowed to raise issues and questions

which the investigator has not previously considered. Generally, the

experience collecting interview is likely to be long and may last for

few hours. Hence, it is often considered desirable to send a copy of

the questions to be discussed to the respondents well in advance.

This will also give an opportunity to the respondents for doing some

advance thinking over the various issues involved, so that, at the

time of interview, they may be able to contribute effectively. Thus, an

experience survey may enable the researcher to define the problem

more concisely and help in the formulation of the research



hypotheses. This survey may as well provide information about the

practical possibilities for doing different types of research.

d. Analysis of ‘insight-stimulating’ examples is also a fruitful method

for suggesting hypotheses for research. It is particularly suitable in

areas where there is little experience to serve as a guide. This

method consists of the intensive study of selected instance of the

phenomenon in which one is interested. For this purpose the existing

records may be examined, the unstructured interviewing may take

place, or some other approach may be adopted. Attitude of the

investigator, the intensity of the study and the ability of the

researcher to draw together diverse information into a unified

interpretation are the main features which make this method an

appropriate procedure for evoking insights.

Now, what sorts of examples are to be selected and studied? There

is no clear cut answer to it. Experience indicates that for particular

problems certain types of instances are more appropriate than

others. One can mention few examples of ‘insight-stimulating’ cases

such as the reactions of strangers, the reactions of marginal

individuals, the study of individuals who are in transition from one

stage to another, the reactions of individuals from different social

strata and the like. In general, cases that provide sharp contrasts or

have striking features are considered relatively more useful while

adopting this method of hypotheses formulation.

Thus, in an exploratory or formulative research study, which merely

leads to insights or hypotheses, whatever method or research design

outlined above is adopted, the only thing essential is that it must

continue to remain flexible so that many different facets of a problem

may be considered as and when they arise and come to the notice of

the researcher.



2. Research design in case of descriptive and diagnostic research

studies: Descriptive research studies are those studies which are

concerned with describing the characteristics of a particular individual, or

of a group, where as diagnostic research studies determine the

frequency with which something occurs or its association with something

else. The studies concerning whether certain variables are associated

are the example of diagnostic research studies. As against this, studies

concerned with specific predictions, with narration of facts and

characteristics concerning individual, group of situation are all examples

of descriptive research studies. Most of the social research comes under

this category. From the point of view of the research design, the

descriptive as well as diagnostic studies share common requirements

and as such we may group together these two types of research studies.

In descriptive as well as in diagnostic studies, the researcher must be

able to define clearly, what he wants to measure and must find adequate

methods for measuring it along with a clear cut definition of population

he wants to study. Since the aim is to obtain complete and accurate

information in the said studies, the procedure to be used must be

carefully planned. The research design must make enough provision for

protection against bias and must maximize reliability. With due concern

for the economical completion of the research study. The design in such

studies must be rigid and not flexible and must focus attention on the

following:

Formulating the objective of the study

Designing the methods of data collection

Selecting the sample

Collecting the data

Processing and analyzing the data

Reporting the findings.



In a descriptive/diagnostic study, the first step is to specify the objectives

with sufficient precision to ensure that the data collected are relevant. If

this is not done carefully, the study may not provide the desired

information. Then crops up the question of selecting the methods by

which the data are to be obtained. While designing data-collection

procedure, adequate safeguards against bias and unreliability must be

ensured. Which ever method is selected, questions must be well

examined and be made unambiguous; interviewers must be instructed

not to express their own opinion; observers must be trained so that they

uniformly record a given item of behaviour.

More often than not, sample has to be designed. Usually, one or more

forms of probability sampling or what is often described as random

sampling are used. To obtain data free from errors introduced by those

responsible for collecting them, it is necessary to supervise closely the

staff of field workers as they collect and record information. Checks may

be set up to ensure that the data collecting staffs perform their duty

honestly and without prejudice. The data collected must be processed

and analyzed. This includes steps like coding the interview replies,

observations, etc., tabulating the data; and performing several statistical

computations.

Last of all is the question of reporting the findings. This is the task of

communicating the findings to others and the researcher must do it in an

efficient manner.

3. Research design in case of hypothesis-testing research studies:

Hypotheses-testing research studies (generally known as experimental

studies) are those where the researcher tests the hypotheses of causal

relationships between variables. Such studies require procedures that

will not only reduce bias and increase reliability, but will permit drawing



inferences about causality. Usually experiments meet this requirement.

Hence, when we talk of research design in such studies, we often mean

the design of experiments.

2.3.5 Principles of Experimental Designs

Professor Fisher has enumerated three principles of experimental designs:

1) The principle of replication: The experiment should be repeated. Thus,

each treatment is applied in many experimental units instead of one.

By doing so the statistical accuracy of the experiments is increased.

For example, suppose we are to examine the effect of two varieties of

rice. For this purpose we may divide the field into two parts and grow

one variety in one part and the other variety in the other part. We can

compare the yield of the two parts and draw conclusion on that basis.

But if we are to apply the principle of replication to this experiment,

then we first divide the field into several parts, grow one variety in half

of these parts and the other variety in the remaining parts. We can

collect the data yield of the two varieties and draw conclusion by

comparing the same. The result so obtained will be more reliable in

comparison to the conclusion we draw without applying the principle of

replication. The entire experiment can even be repeated several times

for better results. Consequently replication does not present any

difficulty, but computationally it does. However, it should be

remembered that replication is introduced in order to increase the

precision of a study; that is to say, to increase the accuracy with which

the main effects and interactions can be estimated.

2) The principle of randomization: It provides protection, when we

conduct an experiment, against the effect of extraneous factors by

randomization. In other words, this principle indicates that we should

design or plan the experiment in such a way that the variations caused

by extraneous factors can all be combined under the general heading



of “chance”. For instance, if we grow one variety of rice, say, in the first

half of the field and the other variety is grown in the other half, then it is

just possible that the soil fertility may be different in the first half in

comparison to the other half. If this is so, our results would not be

realistic. In such a situation, we may assign the variety of rice to be

grown in different parts of the field on the basis of some random

sampling technique i.e., we may apply randomization principle and

protect ourselves against the effects of extraneous factors. As such,

through the application of the principle of randomization, we can have

a better estimate of the experimental error.

3) Principle of local control: It is another important principle of

experimental designs. Under it, the extraneous factors, the known

source of variability, is made to vary deliberately over as wide a range

as necessary and this needs to be done in such a way that the

variability it causes can be measured and hence eliminated from the

experimental error. This means that we should plan the experiment in

a manner that we can perform a two-way analysis of variance, in which

the total variability of the data is divided into three components

attributed to treatments, the extraneous factor and experimental error.

In other words, according to the principle of local control, we first divide

the field into several homogeneous parts, known as blocks, and then

each such block is divided into parts equal to the number of

treatments. Then, the treatments are randomly assigned to these parts

of a block. In general, blocks are the levels at which we hold an

extraneous factors fixed, so that we can measure its contribution to the

variability of the data by means of a two-way analysis of variance. In

brief, through the principle of local control we can eliminate the

variability due to extraneous factors from the experimental error.



2.3.6 Important Experimental Designs:

Experimental design refers to the framework or structure of an experiment

and as such there are several experimental designs. We can classify

experimental designs into two broad categories, viz., informal experimental

designs and formal experimental designs. Informal experimental designs are

those designs that normally use a less sophisticated form of analysis based

on differences in magnitudes, whereas formal experimental designs offer

relatively more control and use precise statistical procedures for analysis.

Informal experimental designs:

1. Before and after without control design: In such a design, single test

group or area is selected and the dependent variable is measured

before the introduction of the treatment. The treatment is then

introduced and the dependent variable is measured again after the

treatment has been introduced. The effect of the treatment would be

equal to the level of the phenomenon after the treatment minus the level

of the phenomenon before the treatment.

2. After only with control design: In this design two groups or areas (test

and control area) are selected and the treatment is introduced into the

test area only. The dependent variable is then measured in both the

areas at the same time. Treatment impact is assessed by subtracting the

value of the dependent variable in the control area from its value in the

test area.

3. Before and after with control design: In this design two areas are

selected and the dependent variable is measured in both the area for an

identical time-period before the treatment. The treatment is then

introduced into the test area only, and the dependent variable is

measured in both for an identical time-period after the introduction of the

treatment. The treatment effect is determined by subtracting the change



in the dependent variable in the control area from the change in the

dependent variable in test area.

2.3.7 Formal Experimental Designs

Completely randomized design (CR design): It involves only two

principles viz., the principle of replication and randomization. It is

generally used when experimental areas happen to be homogenous.

Technically, when all the variations due to uncontrolled extraneous

factors are included under the heading of chance variation, we refer to

the design of experiment as CR Design.

Randomized block design (RB design): It is an improvement over the CR

design. In the RB design the principle of local control can be applied

along with the other two principles.

Latin square design (LS design): It is used in agricultural research. The

treatments in a LS design are so allocated among the plots that no

treatment occurs more than once in any one row or column.

Factorial design: It is used in experiments where the effects of varying

more than one factor are to be determined. They are especially

important in several economic and social phenomena where usually a

large number of factors affect a particular problem.

2.4 Potential Errors affecting research design

The usefulness of a research project depends on the overall quality of the

research design and on the data collected and analysed based on the

design. Several potential sources of error can affect the quality of a research

process. The errors can influence the various stages of the research

process and result in inaccurate or useless research findings.



2.4.1 Sampling Error

Sampling error is the difference between a measure obtained from a sample

representing the population and the true measure that can be obtained only

from the entire population. This error occurs because no sample is a perfect

representation of a given population, unless the sample size equals the

population.

2.4.2 Non-Sampling Error

Non-sampling error includes all other errors associated with a research

project. There may be several different reasons for these errors, which can

be broadly classified into four groups: i) Design errors ii) Administering

errors iii) Response errors and iv) Non-response errors.

2.4.3 Design Error

Design errors, also called researcher-induced errors, are mainly due to

flaws in the research design. There are several different types of design

errors.

2.4.4 Selection Errors

Selection error occurs when a sample obtained through a non-probability

sampling method is not representative of population. For example, if a mail

interviewer interested in shopping habits of the visitors to the mall avoids

interviewing people with children, he or she is inducing a selection error into

the research study.

2.4.5 Population Specific Errors

Population specific error occurs when an inappropriate population is chosen

to obtain data for the research study. For example, if the objective of the

study is to determine what brands of dog food people buy for their pets, and

research draws a sample from a population that consists predominantly of

cat owners, a population specification error is induced into the study.



2.4.6 Sampling Frame Errors

A sampling frame is directory of population members from which a sample is

selected. A sampling frame error occurs when the sample is drawn from an

inaccurate sampling frame.

2.4.7 Surrogate Information Errors

Surrogate information error is the difference or variation between the

information required for a marketing research study and the information

being sought by the researcher.

2.4.8 Measurement Errors

Measurement error is the difference between the information sought by a

researcher for a study and the information generated by a particular

measurement procedure employed by the researcher. Measurement error

can occur at any state of the measurement process, from the development

of an instrument to the data analysis and interpretation stage.

2.4.9 Experimental Errors

An experiment is designed to determine the existence of any causal

relationship between two variables. Any error caused by the improper

design of the experiment induces an experimental error into the study.

2.4.10 Data Analysis Errors

Data analysis error can occur when data from the questionnaire are coded,

edited, analyzed or interpreted. For example, incorrect coding of data or a

wrong use of a statistical analysis procedure can induce a data analysis

error into the study.

2.4.11 Administering Errors

All errors that occur during administration of a survey instrument to the

respondents are classified as administering errors. They are caused by



mistakes committed by the person administering the questionnaire. They

may be caused by various factors.

2.4.12 Questioning Errors

This error arises while addressing questions to the respondents. If the

interviewer does not word the question exactly as designed by the

researcher, a questioning error is induced.

2.4.13 Recording Error

This error arises from improperly recording the respondent’s answer. If the

interviewer misinterprets the response or hears it inaccurately, this induces

a recording error into the study.

2.4.14 Interference Error

This error occurs when an interviewer interferes with or fails to follow the

exact procedure while collecting data. For example, if the interviewer

fabricates the responses to a survey, it induces an inference error.

2.4.15 Response Errors

Response errors also called data errors which occur when the respondent –

intentionally or unintentionally – provides inaccurate answers to the survey

questions. This might be due top the respondent’s failing to comprehend the

questions or it may be due to fatigue, boredom, or misinterpretation of the

question.

2.4.16 Non-Response Errors

Non-response errors occur if (i) some members of a sample were not

contacted, and hence their responses were not included in the study; or ii)

some of the members contacted provide an incomplete or no response to

the survey instrument. The primary reason for this error occurring include

the unwillingness of respondents to participate in the study and the inability

of the interviewer to contact the respondents.





1. The research process consists of stages or steps that guide the project

form its conception through the final analysis, recommendation, and

ultimate action.

2. Research studies evolve through a series of steps, each representing

the answer to a key question.

3. Selection error occurs when a sample obtained through a non-

probability sampling method is not representative of population.

4. Population specific error occurs when an inappropriate population is

chosen from which to obtain data for the research study.

5. A sampling frame is directory of population members from which a

sample is selected.

2.5 Summary

The research process consists of stages or steps that guide the project from


action. Research studies evolve through a series of steps, each

representing the answer to a key question. The research objective is a

statement, in as precise terminology as possible, of what information is

needed. The research objective should be framed so that, obtaining the

information will ensure that the research purpose is satisfied. Before a

research approach can be selected, it is necessary to have an estimate of

the value of information that is, the value of obtaining answers to the

research questions. Such an estimate will help determine how much, if

anything, should be spent on the research.

A research design is a logical and systematic plan prepared for directing a

research study.



In many a research inquiry, the researcher has no idea as to how accurate

the results of his study ought to be in order to be useful. It is important to be

familiar with the important concepts relating to research design. There are

number of crucial research choices, various writers advance different

classification schemes.

Experimental design refers to the framework or structure of an experiment

and as such there are several experimental designs. The usefulness of a

research project depends on the overall quality of the research design and

on the data collected and analysed based on the design.

Sampling error is the difference between a measure obtained from a sample

representing the population and the true measure that can be obtained only

from the entire population. Non-sampling error includes all other errors

associated with a research project. There may be several deferent reasons

for these errors, which can be broadly classified into four groups: i) Design

errors ii) Administering errors iii) Response errors and iv) Non-response

errors.


1. Explain the nature of Research Process

2. What are the steps in Marketing Research Design Process?

3. What is meant by Research Design?

4. What is the need of Research Design?

5. What the potential errors affecting research design?




SAQs

1. True

2. True

3. True

4. True

5. True

TQs

1. Section 2.1

2. Section 2.2.

3. Section 2. 5

4. Section 2.2.2

5. Section 2.6



Unit 3 Sources of Research Data

Structure

3.1 Introduction: Meaning of Data

Objectives

3.2 Types of Data

3.3 Importance of Data

3.4 Sources of Data

3.4.1 Primary Sources of Data

3.4.2 Secondary Sources of Data

3.4.3 Features of Secondary Sources

3.5 Uses of Secondary Data

3.6 Advantages of Secondary Data

3.7 Disadvantages of Secondary Data

3.8 Evaluation of Secondary Data

3.8.1 Data Pertinence

3.8.2 Data Quality

3.9 Commercial Surveys, Audits and Panels

3.9.1 Personal Interview

3.9.2 Advantages of Personal Interview

3.9.3 Limitations of Personal Interview

3.9.4 Characteristics of Personal Interview

3.9.5 Telephone Interviewing

3.9.6 Advantages of Telephone Interviews

3.9.7 Disadvantages of Telephone Interviews

3.9.8 Group Interview

3.9.9 Advantages of Group Interview

3.9.10 Disadvantages of Group Interview

3.9.11 Mail Survey

3.9.12 Procedures of Mail Survey



3.9.13 Alternative Mode of Sending Questionnaire

3.9.14 Improving Response Rate in Mail Survey

3.9.15 Advantages of Mail Survey

3.9.16 Disadvantages of Mail Survey

3.9.17 Panel Method

3.9.18 Characteristics of Panel Method

3.9.19 Needs of Panel

3.9.20 Types of Panel

3.9.21 Advantages of Panel

3.9.22 Disadvantages of Panel Study

3.10 Survey Research

3.10.1 Steps Involved in Survey

3.11 Experimentation and Experiment Environment

3.11.1 Planning and Conducting Experiments

3.11.2 Advantages of Experiments

3.11.3 Disadvantages of Experiments

3.11.4 Laboratory Experiments

3.11.5 Field Experiments

3.11.6 Advantages of Field Experiments

3.11.7 Limitations of Field Experiments


3.12 Summary



3.1 Introduction: Meaning of Data

The search for answers to research questions is called collection of data.

Data are facts, and other relevant materials, past and present, serving as

bases for study and analyses. Some examples of data are:



The types of loans secured by borrowers (for a credit survey)

The items if raw materials required for a product line (Materials

management)

The quantity of each material required for a unit of output.

The sex, age, social class, religion, income level of respondents in a

consumer behaviour study.

The opinions of eligible couples on birth control devices (Family

Planning survey)

The capital expenditure proposals considered by a firm during a year

(Financial Management)

The marks obtained by students of a class in a test on a particulars

subject (performances of students)

The opinions of people on voting in a general election (Opinion poll)

The types of news read by newspaper readers (Readership survey)

The aspirations of management trainees (The emerging Managers in

Indian Enterprises)

The types and frequency of breakdowns occurred in particular brand of

scooter (post purchases Behaviour survey) and so on.

Objectives:

After studying this unit, the students should be able to:

understand the Types of data

discuss the importance of Data

explain the sources of data

explain Commercial surveys, audits and panels

explain Personal Interview, telephone interview, group interview etc

explain Advantages and limitations of the different types of interviews

discuss the Mail survey and procedure of mail survey



explain Panel method, its characteristics, types, advantages and

disadvantages of panel method

explain Survey research, steps involved in survey

discuss experimentation and experiment environment, planning and

conducting experiments, advantages and disadvantages of experiments

discuss the Laboratory experiments, Field experiments, advantages and

disadvantages of the same

3.2 Types of Data

The data needed for a social science research may be broadly classified

into

a) Data pertaining to human beings,

b) Data relating to organization and

c) Data pertaining to territorial areas.

Personal data or data related to human beings consists of:

1. Demographic and socio-economic characteristics of individuals: Age,

sex, race, social class, religion, martial status, education, occupation

income, family size, location of the household life style etc.

2. Behavioural variables: Attitudes, opinions, awareness, knowledge,

practice, intentions, etc

3. Organizational data consist of data relating to an organizations origin,

ownership, objectives, resources, functions, performance and growth.

4. Territorial data are related to geophysical characteristics, resource

endowment, population, occupational pattern infrastructure degree of

development, etc. of spatial divisions like villages, cities, talluks,

districts, state and the nation.



3.3 Importance of Data

The data serve as the bases or raw materials for analysis. Without an

analysis of factual data, no specific inferences can be drawn on the

questions under study. Inferences based on imagination or guess work

cannot provide correct answers to research questions. The relevance,

adequacy and reliability of data determine the quality of the findings of a

study.

Data form the basis for testing the hypotheses formulated in a study. Data

also provide the facts and figures required for constructing measurement

scales and tables which are analyzed with statistical techniques? Inferences

on the results of statistical analysis and tests of significance provide the

answers to research questions. Thus, the scientific process of

measurements, analysis, testing and inferences depends on the availability

of relevant data and their accuracy. Hence, the importance of data for any

research studies.

3.4 Sources of Data

The sources of data may be classified into (a) primary sources and (b)

secondary sources.

3.4.1 Primary Sources of Data

Primary sources are original sources from which the researcher directly

collects data that have not been previously collected e.g.., collection of data

directly by the researcher on brand awareness, brand preference, brand

loyalty and other aspects of consumer behaviour from sample of consumers

by interviewing them. Primary data are first hand information collected

through various methods such as observation, interviewing, mailing etc.



3.4.2 Secondary Sources of Data

These are sources containing data which have been collected and compiled

for another purpose. The secondary sources consists of already compiled

statistical statements and reports whose data may be used by researches

for their studies e.g., Census reports , Annual reports and Financial

statements of companies, Statistical statement, Reports of Government

Departments, Annual reports of currency and finance published by the

Reserve Bank of India, Statistical statements relating to Co-operatives and

Regional Banks published by the NABARD, Reports of the National sample

survey Organization, Reports of trade associations, Publications of

international organizations such as UNO, IMF, World Bank, ILO, WHO, etc.,

Trade and Financial journals newspapers etc.,

Secondary sources consist of not only published records and reports, but

also unpublished records. The latter category includes various records and

registers maintained by the firms and organizations, e.g., accounting and

financial records, personnel records, register of members, minutes of

meetings, inventory records etc.

3.4.3 Features of Secondary Sources

Though secondary sources are diverse and consist of all sorts of materials,

they have certain common characteristics.

First, they are readymade and readily available, and do not require the

trouble of constructing tools and administering them.

Second, they consist of data over which a researcher has no original

control over collection and classification. Both the form and the content

of secondary sources are shaped by others. Clearly, this is a feature

which can limit the research value of secondary sources.



Finally, secondary sources are not limited in time and space. That is, the

researcher using them need not be present when and where they were

gathered.

3.5 Use of Secondary Data

The secondary data may be used in three ways by a researcher.

First, some specific information from secondary sources may be used for

reference purpose. For example, the general statistical information in the

number of co-operative credit societies in the country, their coverage of

villages, their capital structure, volume of business, etc. may be taken

from published reports and quoted as background information in a study

on the evaluation of performance of cooperative credit societies in a

selected district/state.

Second, secondary data may be used as bench marks against which the

findings of research may be tested, e.g., the findings of a local or

regional survey may be compared with the national averages; the

performance indicators of a particular bank may be tested against the

corresponding indicators of the banking industry as a whole; and so on.

Finally, secondary data may be used as the sole source of information

for a research project studies such as securities Market Behaviour,

Financial Analysis of companies, Trade in credit allocation in commercial

banks, Sociological studies on crimes, Historical studies etc. Year

books, statistical reports of government departments, report of public

organizations of Bureau of Public Enterprises, Censes Reports etc,

serve as major data sources for such research studies.



3.6 Advantages of Secondary Data

Secondary sources have some advantages:

1. Secondary data, if available, can be secured quickly and cheaply. Once

their source of documents and reports are located, collection of data is

just matter of desk work. Even the tediousness of copying the data from

the source can now be avoided, thanks to Xeroxing facilities.

2. Wider geographical area and longer reference period may be covered

without much cost. Thus, the use of secondary data extends the

researcher’s space and time reach.

3. The use of secondary data broadens the data base from which scientific

generalizations can be made. This is especially so when data from

several Environmental and cultural settings are required for the study.

4. The use of secondary data enables a researcher to verify the findings

based on primary data. It readily meets the need for additional empirical

support. The researcher need not wait for the time when additional

primary data can be collected.

3.7 Disadvantages of Secondary Data

The use of a secondary data has its own limitations.

1. The most important limitation is that the available data may not meet our

specific needs. The definitions adopted by those who collected those

data may be different; units of measure may not match; and time

periods may also be different.

2. The available data may not be as accurate as desired. To assess their

accuracy, we need to know how the data were collected

3. The secondary data are not up-to-date and become obsolete when they

appear in print, because of the time lag in producing them. For example,



population census data are published two or three years later after

compilation and no new figures will be available for another ten years.

4. Finally, information about the whereabouts of sources may not be

available to all social scientists. Even if the location of the source is

known, the accessibility depends primarily on proximity. For example,

most of the unpublished official records and compilations are located in

the capital city, and they are not within the easy reach of researchers

based in far off places.

3.8 Evaluation of Secondary Data

When a researcher wants to use secondary data for his research, he should

evaluate them before deciding to use them.

3.8.1 Data Pertinence

The first consideration in evaluation is to examine the pertinence of the

available secondary data to the research problem under study. The

following questions should be considered.

1. What are the definitions and classifications employed? Are they

consistent with our own?

2. What are the measurements of variables used? What is the degree to

which they conform to the requirements of our research?

3. What is the coverage of the secondary data in terms of topic and time?

Does this coverage fit the needs of our research?

On the basis of above consideration, the pertinence of the secondary data

to the research on hand should be determined. A researcher who is

imaginative and flexible may be able to redefine his research problem so as

to make use of otherwise unusable available data.



3.8.2 Data Quality

If the researcher is convinced about the available secondary data for his

needs, the next step is to examine the quality of the data. The quality of data

refers to their accuracy, reliability and completeness.

The assurance and reliability of the available secondary data depends on

the organization which collected them and the purpose for which they were

collected. What is the authority and prestige of the organization? Is it well

recognized? Is it noted for reliability? It is capable of collecting reliable data?

Does it use trained and well qualified investigators? The answers to these

questions determine the degree of confidence we can have in the data and

their accuracy.

It is important to go to the original source of the secondary data rather than

to use an immediate source which has quoted from the original. Then only,

the researcher can review the cautionary and other comments that were

made in the original source.

The completeness refers to the actual coverage of the published data. This

depends on the methodology and sampling design adopted by the original

organization. Is the methodology sound? Is the sample size small or large?

Is the sampling method appropriate? Answers to these questions may

indicate the appropriateness and adequacy of the data for the problem

under study.

The question of possible bias should also be examined. Whether the

purpose for which the original organization collected the data had a

particular orientation? Has the study been made to promote the

organization’s own interest? How the study was conducted? These are

important clues.



The researcher must be on guard when the source does not report the

methodology and sampling design. Then it is not possible to determine the

adequacy of the secondary data for the researcher’s study.

3. 9 Commercial Surveys, Audits and Panels

Primary data are directly collected by the researcher from their original

sources. In this case, the researcher can collect the required data precisely

according to his research needs, he can collect them when he wants them

and in the form he needs them. But the collection of primary data is costly

and time consuming. Yet, for several types of social science research,

required data are not available from secondary sources and they have to be

directly gathered from the primary sources.

Primary data have to be gathered in cases where the available data are

inappropriate, inadequate or obsolete. They include: socio economic

surveys, social anthropological studies of rural communities and tribal

communities, sociological studies of social problems and social institutions,

marketing research, leadership studies, opinion polls, attitudinal surveys,

radio listening and T.V. viewing surveys, knowledge-awareness practice

(KAP) studies, farm managements studies, business management studies

etc.,

There are various methods of data collection. There are four basic survey

methods which include:

Personal interview

Telephone interview

Mail survey and

Fax survey



3.9.1 Personal interview

Personal interviewing is one of the prominent methods of data collection. It

may be defined as a two way systematic conversation between an

investigator and an informant, initiated for obtaining information relevant to a

specific study. It involves not only conversation, but also learning from the

respondent’s gesture, facial expressions and pauses, and his environment.

Interviewing may be used either as a main method or as a supplementary

one in studies of persons. Interviewing is the only suitable method for

gathering information from illiterate or less educated respondents. It is

useful for collecting a wide range of data from factual demographic data to

highly personal and intimate information relating to a person’s opinions,

attitudes, values, beliefs, experiences and future intentions. Interviewing is

appropriate when qualitative information is required or probing is necessary

to draw out fully. Where the area covered for the survey has a compact or

when a sufficient number of qualified interviewers are available, personal

interview is feasible.

Interview is often superior to other data-gathering methods. People are

usually more willing to talk than to write. Once report is established, even

confidential information may be obtained. It permits probing into the context

and reasons for answers to questions.

Interview can add flesh to statistical information. It enables the investigator

to grasp the behavioural context of the data furnished by the respondents. It

permits the investigator to seek clarifications and brings to the forefront

those questions which for some reason or the others the respondents do not

want to answer.



3.9.2 Advantages of Personal Interview

There are several real advantages to personal interviewing.

First, the greatest value of this method is the depth and detail of

information that can be secured. When used with well conceived

schedules, an interview can obtain a great deal of information. It far

exceeds mail survey in amount and quality of data that can be secured.

Second, the interviewer can do more to improve the percentage of

responses and the quality of information received than other method. He

can note the conditions of the interview situation, and adopt appropriate

approaches to overcome such problems as the respondent’s

unwillingness, incorrect understanding of question, suspicion, etc.

Third, the interviewer can gather other supplemental information like

economic level, living conditions etc through observation of the

respondent’s environment.

Fourth, the interviewer can use special scoring devices, visual materials

and like in order to improve the quality of interviewing.

Fifth, the accuracy and dependability of the answers given by the

respondent can be checked by observation and probing.

Last, interview is flexible and adaptable to individual situations. Even

more control can be exercised over the interview situation.

3.9.3 Limitations of Personal Interview

Interviewing is not free of limitations.

Its greatest drawback is that it is costly both in terms of money and time.

Second, the interview results are often adversely affected by

interviewer’s mode of asking questions and interactions, incorrect

recording and also by the respondent’s faulty perception, faulty memory,

inability to articulate etc.



Third, certain types of personal and financial information may be refused

in face-to face interviews. Such information might be supplied more

willingly on mail questionnaires, especially if they are to be unsigned.

Fourth, interview poses the problem of recording information obtained

from the respondents. No full proof system is available. Note taking is

invariably distracting to both the respondent and the interviewer and

affects the thread of the conversation.

Last, interview calls for highly competent interviewers. The availability of

such persons is limited and the training of interviewers is often a long

and costly process.

3.9.4 Characteristics of Personal Interview

Interviewing as a method of data collection has certain characteristics. They

are:

1. The participants – the interviewer and the respondent – are strangers;

hence, the investigator has to get him introduced to the respondent in

an appropriate manner.

2. The relationship between the participants is a transitory one. It has a

fixed beginning and termination points. The interview proper is a

fleeting, momentary experience for them.

3. Interview is not a mere casual conversational exchange, but a

conversation with a specific purpose, viz., obtaining information

relevant to a study.

4. Interview is a mode of obtaining verbal answers to questions put

verbally.

5. The interaction between the interviewer and the respondent need not

necessarily be on a face-to-face basis, because interview can be

conducted over the telephone also.



6. Although interview is usually a conversation between two persons, it

need not be limited to a single respondent. It can also be conducted

with a group of persons, such as family members, or a group of

children or a group of customers, depending on the requirements of

the study.

7. Interview is an interacting process. The interaction between the

interviewer and the respondent depends upon how they perceive each

other.

8. The respondent reacts to the interviewer’s appearance, behaviour,

gestures, facial expression and intonation. His perception of the thrust

of the questions and his own personal needs. As far as possible, the

interviewer should try to be closer to the social-economic level of the

respondents.

9. Information furnished by the respondent in the interview is recorded by

the investigator. This poses a problem of seeing that recording does

not interfere with the tempo of conversation.

10. Interviewing is not a standardized process like that of a chemical

technician; it is rather a flexible psychological process.

3.9.5 Telephone Interviewing

Telephone interviewing is a non-personal method of data collection. It may

be used as a major method or supplementary method. It will be useful in the

following situations:

1. When the universe is composed of those persons whose names are

listed in telephone directories, e.g. business houses, business

executives, doctors and other professionals.

2. When the study required responses to five or six simple questions. E.g.

Radio or Television programme survey.



3. When the survey must be conducted in a very short period of time,

provided the units of study are listed in telephone directory.

4. When the subject is interesting or important to respondents, e.g. a

survey relating to trade conducted by a trade association or a chamber

of commerce, a survey relating to a profession conducted by the

concerned professional association.

5. When the respondents are widely scattered and when there are may

call backs to make.

3.9.6 Advantages of Telephone Interviewing

The advantages of telephone interview are:

1. The survey can be completed at very low cost, because telephone

survey does not involve travel time and cost and all calls can be made

from a single location.

2. Information can be collected in a short period of time. 5 to 10 interviews

can be conducted per hours.

3. Quality of response is good, because interviewer bias is reduced as

there is no face-to-face contact between the interviewer and the

respondent.

4. This method of interviewing is less demanding upon the interviewer.

5. It does not involve fieldwork.

6. Individuals who could not be reached or who might not care to be

interviewed personally can be contacted easily.

3.9.7 Disadvantages of Telephone Interviewing

Telephone interview has several limitations:

1. It is limited to persons with listed telephones. The sample will be

distorted if the universe includes persons not on phone. In several

counties like India only a few persons have phone facility and that too in



urban areas only. Telephone facility is very rare in rural areas. Hence,

the method is not useful for studying the general population.

2. There is a limit to the length of interview. Usually, a call cannot last over

five minutes. Only five or six simple questions can be asked. Hence,

telephone cannot be used for a longer questionnaire.

3. The type of information to be collected is limited to what can be given in

simple, short answers or a few words. Hence telephone is not suitable

for complex surveys, and there is no possibility of obtaining detailed

information.

4. If the questions cover personal matters, most respondents will not

cooperate with the interviewer.

5. The respondent’s characteristics and environment cannot be observed.

6. It is not possible to use visual aids like charts, maps, illustrations or

complex scales.

7. It is rather difficult to establish rapport between the respondent and the

interviewer.

8. There is no possibility to ensure the identity of the interviewer and to

overcome suspicion.

3.9.8 Group Interviews

A group interview may be defined as a method of collecting primary data in

which a number of individuals with a common interest interact with each

other. In a personal interview, the flow of information is multi dimensional.

The group may consist of about six to eight individuals with a common

interest. The interviewer acts as the discussion leader. Free discussion is

encouraged on some aspect of the subject under study. The discussion

leader stimulates the group members to interact with each other.



The desired information may be obtained through self-administered

questionnaire or interview, with the discussion serving as a guide to ensure

consideration of the areas of concern. In particular, the interviewers look for

evidence of common elements of attitudes, beliefs, intentions and opinions

among individuals in the group. At the same time, he must be aware that a

single comment by a member can provide important insight.

Samples for group interview can be obtained through schools, clubs and

other organized groups.

3.9.9 Advantages of Group Interview

The advantages of this technique are:

1. The respondents comment freely and in detail.

2. The method is highly flexible. The flexibility helps the research work with

new concepts or topics which have not been previously investigated.

3. Visual aids can be used.

4. A group can be interviewed in the time required for one personal

interview.

5. The client can watch the interview unobserved.

6. Respondents are more articulated in a group than in the individual

interviews.

7. The technique eliminates the physical limitations inherent in individual

interviews.

3.9.10 Disadvantages of Group Interview

This method is not free from drawbacks.

1. It is difficult to get a representative sample.

2. There is the possibility of the group being dominated by one individual.

3. The respondents may answer to please the interviewer or the other

members in the group.



3.9.11 Mail Survey

The mail survey is another method of collecting primary data. This method

involves sending questionnaires to the respondents with a request to

complete them and return them by post. This can be used in the case of

educated respondents only. The mail questionnaires should be simple so

that the respondents can easily understand the questions and answer them.

It should preferably contain mostly closed-end and multiple choice questions

so that it could be completed within a few minutes.

The distinctive feature of the mail survey is that the questionnaire is self-

administered by the respondents themselves and the responses are

recorded by them, and not by the investigator as in the case of personal

interview method. It does not involve face-to-face conversation between the

investigator and the respondent. Communication is carried out only in

writing and this requires more cooperation from the respondents than verbal

communication.

3.9.12 Procedures of Mail Survey

The researcher should prepare a mailing list of the selected respondents by

collecting the addresses from the telephone directory of the association or

organization to which they belong.

A covering letter should accompany a copy of the questionnaire. It must

explain to the respondent the purpose of the study and the importance

of his cooperation to the success of the project.

Anonymity may be assured.

The sponsor’s identity may be revealed. However, when such

information may bias the result, it is not desirable to reveal it. In the later

case, a disguised organization name may be used.

A self-addressed stamped envelope should be enclosed in the covering

letter.



After a few days from the date of mailing the questionnaires to the

respondents, the researcher can expect the return of completed ones

from them. The progress in return may be watched and at the

appropriate stage follow-up efforts can be made.

3.9.13 Alternative Modes of Sending Questionnaires

There are some alternative methods of distributing questionnaires to the

respondents. They are: (1) personal delivery, (2) attaching questionnaire to

a product (3) advertising questionnaire in a newspaper of magazine, and (4)

news-stand insets.

Personal delivery: The researcher or his assistant may deliver the

questionnaires to the potential respondents with a request to complete them

at their convenience. After a day or two, he can collect the completed

questionnaires from them. Often referred to as the self-administered

questionnaire method, it combines the advantages of the personal interview

and the mail survey. Alternatively, the questionnaires may be delivered in

person and the completed questionnaires may be returned through mail by

the respondents.

Attaching questionnaire to a product: A firm test marketing a product

may attach a questionnaire to a product and request the buyer to complete it

and mail it back to the firm. The respondent usually is rewarded by a gift or

a discount coupon.

Advertising the questionnaire: The questionnaire with the instructions for

completion may be advertised on a page of magazine or in section of

newspapers. The potential respondent completes it, tears it out and mails it

to the advertiser. For example, the committee of Banks customer services

used this method of Management Studies for collecting information from the

customers of commercial banks in India. This method may be useful for

large-scale on topics of common interest.



News-stand inserts: This method involves inserting the covering letter,

questionnaire and self addressed reply-paid envelope into a random sample

of news-stand copies of a newspaper or magazine.

3.9.14 Improving the Response Rate in a Mail Survey

The response rate in mail surveys is generally very low in developing

countries like India. Certain techniques have to be adopted to increase the

response rate. They are:

1. Quality printing: The questionnaire may be neatly printed in quality

light coloured paper, so as to attract the attention of the respondent.

2. Covering letter: The covering letter should be couched in a pleasant

style so as to attract and hold the interest of the respondent. It must

anticipate objections and answer them briefly. It is desirable to address

the respondent by name.

3. Advance information: Advance information can be provided to

potential respondents by a telephone calls or advance notice in the

newsletter of the concerned organization or by a letter. Such preliminary

contact with potential respondents is more successful than follow-up

efforts.

4. Incentives: Money, stamps for collection and other incentives are also

used to induce respondents to complete and return mail questionnaire.

5. Follow-up-contacts: In the case of respondents belonging to an

organization, they may be approached through some one in that

organization known as the researcher.

6. Larger sample size: A larger sample may be drawn than the estimated

sample size. For example, if the required sample size is 1000, a sample

of 1500 may be drawn. This may help the researcher to secure an

effective sample size closer to the required size.



3.9.15 Advantages of Mail Survey

They are less costly than personal interviews, as cost of mailing is the

same throughout the country irrespective of distances.

They can cover extensive geographical areas.

Mailing is useful in contacting persons such as senior business

executives who are difficult to reach in any other way.

The respondents can complete the questionnaires at their

conveniences.

Mail surveys, being more impersonal, provide more anonymity than

personal interviews.

Mail surveys are totally free from the interviewer’s bias, as there is no

personal contact between the respondents and the investigator.

Certain personal and economic data may be given accurately in an

unsigned mail questionnaire.

3.9.16. Disadvantages of Mail Survey

The scope for mail surveys is very limited in a country like India where

the percentage of literacy is very low.

The response rate of mail surveys is low. Hence, the resulting sample

will not be a representative one.

It is also difficult to determine the degree of representativeness of a

sample obtained by mail.

The causes for inadequate and non-responses cannot be known and no

probing is possible.

Information on the personal characteristics of the respondent and his

environment cannot be secured.



Respondents may not be cooperative if the mail questionnaire is long or

complex.

Several returned questionnaire might contain unanswered questions and

incomplete responses.

3.9.17 Panel Method

The panel method is a method of data collection, by which data is collected

from the same sample respondents at intervals either by mail or by personal

interview. This is used for longitudinal studies on economic conditions,

expenditure pattern, consumer behaviour, recreational pattern, effectiveness

of advertising, voting behaviour, and so on. The period over which the panel

members are contacted for information may spread over several months or

years. The time interval at which they are contacted repeatedly may be 10

or 15 days or one or two months depending on the nature of the study and

the memory span of the respondents.

3.9.18 Characteristics of Panel Method

A basic characteristic of the panel method is successive collection of

data on the same items from the same persons over a period of time.

The type of information to be collected should be such facts that can be

accurately and completely furnished by the respondent without any

reservation.

The number of item should be as few as possible so that they could be

furnished within a few minutes, especially when mail survey is adopted.

The average amount of time that a panel method has to spend each

time for reporting can be determined in a pilot study.

The panel method requires carefully selected and well-trained field

workers and effective supervision over their work.



3.9.19 Need for Panel Study

When sample respondents – particularly household or individuals are

contacted only once, they may not be able to recall exactly what have

occurred during a long period, say a year, because of the short memory

span. Therefore, they will not be able to give correct information on such

facts as cash inflow, source wise income, expenditure pattern, purchases,

savings, and recreation pattern and so on. But when they are contacted

successively at short intervals of 10 or 15 days, they would to able to give

accurate information on happenings between two successive contacts, as

the time span is short and well within the memory span. In this way, data are

collected repeatedly at intervals, and computations for the required period

like a year can be easily made and the data so collected will be more

reliable.

3.9.20 Tpes of Panel

The panel may be static or dynamic. A static or continuous panel is one in

which the membership remains the same throughout the life of panel,

except for members who drop out. The dropouts are not replaced. The static

panel is appropriate when the purpose is to study changes in a given group

of persons over a period of time. The main drawbacks of the static panel

are:

Due to dropouts, it ceases to be representative of the original universe

after a time.

The size of the reporting panel may become too small for satisfactory

results.

In a dynamic panel, to keep the panel representative of the current

population in the area covered by the universe, replacements are found for

the members who drop out. A dynamic panel may also be a rotating one, in

which members are systematically replaced at specified time intervals.



The dynamic panel is most useful when it is important to keep the panel

representative of the population at all times. The main problem connected

with its use is the cost and difficultly of recruiting new members to replace

the dropouts.

3.9.21 Advantages of Panel Method

The advantages of panel method are:

This method facilities collection of more accurate data for longitudinal

studies than any other method, because under this method event or

action is reported soon after its occurrence.

This method makes it possible to have before and after designs are

made for field based studies. For example, the effect of public relations

or advertising campaigns or welfare measures can be measured by

collecting data before, during and after the campaign.

The panel method offers a good way of studying trends in events,

behaviour or attitudes. For example, a panel enables a market

researcher to study how brand preferences change from month to

month; it enables an economics researcher to study how employment,

income and expenditure of agricultural labourers change from month to

month; a political scientist can study the shifts in inclinations of voters

and the causative influential factors during an election, it is possible to

find out how the constituency of the various economy and social strata

of society changes through time; and so on.

A panel study also provides evidence on the casual relationship

between variables. For example, a cross sectional study of employees

may show an association between their attitude to their jobs and their

positions in the organization, but it does not indicate as to which comes

first-favourable attitude or promotion. A panel study can provide data for

finding an answer to this question.



It facilities depth interviewing, because panel members become well

acquainted with the field workers and will be willing to allow probing

interviews.

3.9.22 Disadvantages of Panel Method

The major limitations or problems of the panel method are:

This method is very expensive. The selection of panel members, the

payment of premiums, periodic of investigators and supervisors, and the

costs involved in replacing drop-outs, all add to the expenditure.

It is often difficult to set up a representative’s panel and to keep it

representative. Many persons may be unwilling to participate in a panel

study. In the course of the study, there may be frequent drop-outs.

Persons with similar characteristics may replace the drop-outs. But there

is no guarantee that the emerging panel would be a representative.

A real danger with the panel method is “panel conditioning” i.e., the risk

that repeated interviews may sensitize the panel members and they

become untypical as a result of being on the panel. For example, the

members of a panel study of political opinions may try to appear

consistent in the views they express on consecutive occasions. In such

cases the panel becomes untypical of the population it was selected to

represent. One possible safeguard to panel conditioning is to give

members of a panel only a limited panel life and then to replace them

with persons taken randomly from a reserve list.

The quality of reporting may tend to decline due to decreasing interest

after a panel has been in operations for some time. Cheating by panel

members or investigators may be a problem in some cases.



3.10 Survey Research

Survey is a fact finding study. It is method of research involving collection of

data directly from a population or a sample at a particular time. Data might

be collected by observation or interviewing or mailing questionnaires.

Survey has certain characteristics:

It is always conducted in a natural setting. It is a field study.

It seeks responses directly form the respondents.

It can cover a very large population.

A survey may include extensive study or intensive study.

A survey covers a definite geographical area.

3.10.1 Steps Involved in a Survey

Selection of a problem and its formulation

Preparation of the research design

Operation concepts and construction of measuring indexes and scales

Sampling

Construction of tools for data collection

Field work and collection of data

Processing of data and tabulation

Analysis of data

Reporting

3.11 Experimentation and Experiment Environment

Experimentation is a research process used to study the causal

relationships between variables. 1t aims at studying the effect of an

independent variable on a dependent variable by keeping the other

independent variable constant through some type of control. For example, a



social scientist may use experimentation for studying the effect of a method

of family planning publicity on people’s awareness of family planning

techniques. Various kinds of designs such as “after-only-design” etc, are

used for experimentation

Experimentation required special effort. It is often extremely difficult to

design, and it is also a time consuming process. Why should then one take

such trouble? Why not simply observe/survey the phenomenon? The

fundamental weakness of any non-experimental study is its inability to

specify causes and effect. It can show only correlations between variables,

but correlations alone never prove causation. The experiment is the only

method which can show the effect of an independent variable on dependent

variable. In experimentation, the researcher can manipulate the independent

variable and measure its effect on the dependent variable. For example, the

effect of various types of promotional strategies on the sale of a given

product can be studied by using different advertising media such as TV’s,

radio and Newspaper.

Moreover, experiment provides “the opportunity to vary the treatment

(experimental variable) in a systematic manner, thus allowing for the

isolation and precise specification of important difference”.

3.11.1 Planning and Conducting Experiments

It is easy to conceive ideas, but difficult to translate the ideas into a

workable, credible, meaningful set of experimental operations. This to a

great extent depends upon the researcher’s knowledge, imagination and

intelligence. Yet the general procedure in experimentation may be outlined

First, determine the hypothesis to be tested and the independent and

dependent variables involved in it.

Second, operate the variables by identifying their measurable

dimensions.



Third, select the type of experimental plan. The type of experimental

design based on types of control may be classified into: (i) one group

plan, using the same group as experimental and control group and

measuring it before and after experimental treatment; (ii) matched

groups plan, consisting of two identical groups, one to be used as

control group and another as experimental group, with (a) Post-test only

measurement or (b) pre-test post test measurements.

Fourth, choose the setting. The setting may be field or laboratory (See

subsequent paragraphs for detailed discussion on these two types of

experiments)

Fifth, make the experimental conditions as nearly the same as the

expected read life conditions.

Sixth, make a record of pre-experimental conditions.

Seventh, introduce appropriate methods for controlling extraneous

variables that are not manipulated in the experiment. These methods

are:

1. Removing the Variable: An extraneous variable may be eliminated

completely. For example, observer distraction may be removed by

separating the observer by a one-way glass partition. Some

variables may be eliminated by selecting cases with uniform

characteristics, e.g., using only male subjects removing sex as a

variable.

2. Matching Cases: Selecting control and experimental groups with

identical characteristics. But all the variables are kept constant.

3. Balancing Cases: This means assigning subjects to experimental

and control groups in such as way that the means and the variances

of the groups are as nearly equal as possible.



4. Randomization: This involves pure chance selection and

assignment of subjects to experimental and control groups. This

method eliminates systematic bias and minimizes the effect of

extraneous variable.

5. Analysis of co-variance: This is a statistical method of eliminating

initial difference on several variables between the experimental and

control groups. Pre-test means scores are used as co-variants.

Eighth, apply the experimental treatment and record

observations and measurements using appropriate measurement

devices. If feasible, repeat the tests several times in order to

unsure the accuracy of results.

Ninth, analyse the results, using appropriate statistical devices.

Last, interpret the results, giving consideration to all possible

extraneous conditions. No possible cause should be overlooked,

as unforeseen conditions might influence the results.

3. 11.2. Advantages of Experimentation

Experimentation has some specific advantages and disadvantages:

1. Its power to determine causal relationships between variables

surpasses that of all other methods. The influence of extraneous

variables can be more effectively controlled in this method.

2. The element of human errors is reduced to the minimum.

3. In this method better conditions for conducting experiments may be

created, than is possible in other methods.

4. Experimentation yields generally exact measurements and can be

repeated for verifying results.



3. 11.3 The Disadvantages of Experimentation

It is difficult to establish comparable control and experimental groups.

Second, the scope for experimentation with human beings is extremely

limited.

Thirdly, experiment is often difficult to design, tends to be expensive and

time-consuming.

Fourthly, it is artificial to some extent and may lack realism.

Fifthly, experimentation can be used only in studies of the present but

not in studies relating to past or future.

Sixthly, it is of no use in determining opinions, motives and intentions of

persons.

Finally, the results observed may not be the true effects of the

experimental treatment, but may be artificial, e.g, effects of some

extraneous variable. For instance, an experimenter may unwillingly

influence his subjects to behave in ways that confirm the hypothesis,

particularly if the subjects want to please the experimenter. Laboratory

experiments are especially vulnerable to such artificialities when

subjects know they are being studied and want to create a good

impression.

3.11.4 Laboratory Experiment

An experiment can be conducted either in a laboratory or in a real life

setting.

A laboratory experiment is an investigation conducted in a setting created

specifically for the purpose. The researcher manipulated an independent

variable and studies its effect on a dependent variable keeping other

variables constant.



Purpose: The purpose of laboratory experiments are (1) to discover causal

relations under uncontaminated conditions, reduce the discovered relations

to functional from y= f(x) and make predictions on the basis of the functions;

(2) to test the predictions derived from theory and other researches; and (3)

to refine theories.

Applications or Uses: This method is useful not only in physical sciences

research, but also in social sciences research. Even though experimentation

on a social science problem has special difficulties, it can be used for a

variety of studies such as voting behaviour, leadership style, learning

process, effectiveness of advertising media, and effect of package on sales,

influence of incentive schemes on labour productivity and so on.

Advantages

This method has several merits, they are:

The chief merit of experiment method is the possibility of securing

relatively complete control over extraneous factors.

The experimenter can manipulate one or more variables and study its or

their impact on dependent variables.

The experimenter is most cases can achieve a high degree of specificity

on operating the variables.

An experiment yields precise results and it is replicable.

Demerits:

The experimental method is not free from drawbacks:

The greatest weakness of this method is probably the lack of strength of

independent variables. As the laboratory situation is artificial, the effects

of experimental manipulations are usually weak.

This method is highly structured, thus limiting flexibility.



The result cannot be simply generalized to real life situations, because

in the latter, various extraneous forces operate. Thus, an experimental

method lacks external validity

Nevertheless, the contributions of experimental method to theory

building are so great that this method is one of man’s greatest

achievements.

3.11.5 Field Experiments

This is an experiment conducted in a real life situation in which the

experimenter manipulates an independent variable in order to test a

hypothesis. Compared with laboratory experiment, a filed experiment

incorporates less control. As it is difficult to foresee and control extraneous

factors in a filed experiment, its result is subject to large uncontrolled

variation.

Application or uses: This method is well suited to both testing of theory and

finding solutions to practical social problems, It has been used for studying a

variety of social action programmes such as, improving the quality of work

life in assembly lines, post offices and insurance companies and banks; the

learning process in educational institutions and training centres; changing

group productivity; changing organization culture; changing superior-

subordinate relationship in organization overcoming resistance to change

through participative approach; changing attitude through social contract;

changing food habits; improving the effectiveness of mass education; testing

new products in markets; determining best procedures or techniques for

tasks; and so on.

“Anyone who wishes to take effective social action in any setting can

improve upon the uncontrolled, by out of new methods by the applications of

more scientific, experimental procedures. Through careful measurements,

better theorizing, the use of control groups, and other aspects of improved



experimental design, the practical problems of social action can be solved

with greater certainty, with greater accuracy and sometimes with greater

efficiency than through common sense trial-and-error methods.

The field experiment will be more successful if preceded by a field study

which gives a more thorough knowledge of the setting and thus enables the

experimenter to manipulate and control his variables more effectively.

3.11.6 Advantages of the Field Experiments

This method has some unique virtues.

The variables in a field experiment usually have a stronger effect than

those of a laboratory experiment, as the field situation is real. Realism

increased with strength of the variables.

The field experiment permits a more unequivocal determination of

causal relations, while processes and social changes, in real life

settings.

As the field experiment deals with the total life situation, it is well suited

for studying complex syndromes and social processes where the inter-

relationships among many analytical variables are involved.

3.11.7 Limitations of Field Experimentations

The experimental method is not free from limitations:

The major limitation of this method is the practical difficulty involved in

the manipulation of independent variables and randomization in many

field situations.

Another weakness inherent in this method is lack of precision. Precise

measurement in realistic situation is not as possible as in a laboratory

setting.

A field experiment is a very difficult process, as it calls for social skills

and good contacts on the part of the experiments and also it is a time



consuming process. Unless the organization where it has to be

conducted and the subject cooperate, it is not possible to conduct it.



1. The search for answers to research questions is called collection of

data.

2. Data are facts, and other relevant materials, past and present, serving

as bases for study and analyses.

3. The data needed for a social science research may be broadly classified

into (a) Data pertaining to human beings, (b) Data relating to

organization and (c) Data pertaining to territorial areas.

4. The sources of data may be classified into (a) primary sources and (b)

secondary sources.

3.12 Summary

The sources of data may be classified into (a) primary sources and (b)

secondary sources. Secondary sources consist of not only published

records and reports, but also unpublished records. The latter category

includes various records and registers maintained by the firms and

organizations, e.g., accounting and financial records, personnel records,

register of members, minutes of meetings, inventory records etc. When a

researcher wants to use secondary data for his research, he should

evaluate them before deciding to use them.

There are various methods of data collection. There are four basic survey

methods

Personal interview

Telephone interview

Mail survey



And fax survey

Telephone interviewing is a non-personal method of data collection. It may

be used as a major method or supplementary method. A group interview

may be defined as a method of collecting primary data in which a number of

individuals with common interest interact with each other. The mail survey

is another method of collecting primary data. This method involves sending

questionnaires to the respondents with a request to complete them and

return them by post. The panel method is a method of data collection, by

which data is collected from the same sample respondents at intervals

either by mail or by personal interview. Experimentation is a research

process used to study the causal relationships between variables. 1t aims at

studying the effect of an independent variable on a dependent variable by

keeping the other independent variable constant through some type of

control.


1. What are the sources of data for research?

2. Distinguish between primary and secondary data.

3. What are commercial surveys?

4. What is the advantage of panel study?

5. What are field experiments?


SAQs

1. True

2. True

3. True

4. True



TQs

1. Section 3.4.

2. Section 3.4.1 and 2

3. Section 3.9.

4. Section 3.9.2

5. Section 3.11.5



Unit 4 Measurement Techniques in

Marketing Research

Structure

4.1 Introduction: The Concept of Measurement

Objectives

4.2 Scales of Measurement

4.3 Components of Measurement

4.3.1 Nominal Scale

4.3.2 Ordinal Scale

4.3.3 Interval Scale

4.3.4 Ratio Scale

4.4 Components of Measurement Accuracy

4.4.1 Validity

4.4.2 Reliability

4.4.3 Sensitivity

4.4.4 Generalization

4.4.5 Relevancy

4.5 Measurement Accuracy and Measurement Development

4.5.1 Questionnaire Designing

4.5.2 Plan What to Measure

4.5.3 Format the Questions

4.5.4 Question Wording

4.5.5 Sequence and Layout Design

4.5.6 Pre-test Design

4.6 Direct Response Attitude Scales

4.6.1 Single Item Scales

4.6.2 Itemized Scale

4.6.3 Comparative Scales



4.6.4 Rank Order Scale

4.6.5 Q-Sort Scale

4.6.6 Constant Sum Scales

4.6.7 Pictorial Scales

4.6.8 Paired Comparison Scales

4.6.9 Derived Attitude Scales

4.6.10 Likert Scales

4.6.11 Thurstone Scales

4.6.12 Semantic Differential Scales

4.7 Types of Observation

4.7.1 Participant Observation

4.7.2 Non-Participant Observation

4.7.3 Direct Observation

4.7.4 Indirect Observation

4.7.5 Controlled Observation

4.7.6 Uncontrolled Observation

4.7.7 Planning Observation

4.7.8 Prerequisite of Observation

4.7.9 Observation Tools and Research Devices

4.7.10 Suitability and Application

4.7.11 Advantages of Observation

4.7.12 Limitations of Observation


4.8 Summary


4.10 Answers to SAQ’s and TQ’s



4.1 Introduction: Concept of Measurement

Measurement can be defined as a standardized process of assigning

numbers or other symbols to certain characteristics of the objects of interest,

according to some pre-specified rules. Measurement often deals with

numbers, because mathematical and statistical analysis can be performed

only on numbers, and they can be communicated throughout the world in

the same form without any translation problems. For a measurement

process to be standardized process assignment, two characteristics are

necessary. First, there must be one-to-one correspondence between the

symbol and the characteristic in the object that is being measured. Second,

the rules for assignment must be invariant over time and the objects being

measured.

Objectives:

After learning this unit, the students should be able to:

discuss the scales and components of measurement

explain the components of measurement accuracy and measurement

development

understand the concept of Questionnaire design, observation, response

attitude scales etc.

discuss the types of observation

explain the observation tools and research devices

4.2 Scales of Measurement

Scaling is the process of creating a continuum on which objects are located

according to the amount of the measured characteristics they possess. An

illustration of a scale that is often used in research is the dichotomous scale

for sex. The object with male (or female) characteristics is assigned the

number 1 and the object with the opposite characteristics is assigned the



number 0. This scale meets the requirements of the measurement process

in that the assignment is one to one and it is invariant with respect to top

time and object. Measurement and scaling are basic tools used in the

scientific method and are used in almost every marketing research situation.

4.3 Components of Measurement

The assignment of numbers is made according to rules that should

correspond to the properties of whatever is being measured. The rule may

be very simple, as when a bus route is given a number to distinguish it from

other routes. Here, the only property is identity, and any comparisons of

numbers are meaningless. This is a nominal scale. At other extreme is the

ratio scale, which has very rigorous properties. In between the extremes are

ordinal scales and interval scales.

4.3.1 Nominal Scale

In a nominal scale, objects are assigned to mutually exclusive, labelled

categories, but there are no necessary relationships among the categories;

that is , no ordering or spacing is implied. If one entity is assigned the same

number as another, they are identical with respect to a nominal variable.

Otherwise, they are just different. Sex, geographic location, and marital

status are nominally scaled variables. The only arithmetic operation that can

be performed on such a scale is a count of each category. Thus we can

count the number of automobiles dealers in the state of Karnataka or the

number of buses seen on a given route in the past hour.

4.3.2 Ordinal Scale

An ordinal scale is obtained by ranking objects or by arranging them in order

with regard to some common variable. The question is simply whether each

object has more or less of this variable than some other object. The scale

provides information as to how much difference there is between the



objects. Because we do not know the amount of difference between objects,

the permissible arithmetic operations are limited to statistics such as the

median or mode but not median). For example, suppose a sample of 1,000

consumers ranked five brands of frozen mixed vegetables according to

quality. The results for Birds-eye brand were as follows:

Quality brands Number of respondents giving

Rankings to Bird-Eye

Highest 150

Second 300

Third 250

Fourth 200

Lowest 100

Total 1,000

The second quality category is mode; the third category is the median;

however it is not possible to compute a mean ranking, because the

differences between ordinal scaled values are not necessarily the same.

The finishing order in a horse race per class standing illustrates this type of

scale. Similarly, brands of frozen vegetables can be ranked according to

quality, from highest to lowest.

4.3.3 Interval Scale

In an interval scale the numbers used to rank the objects also represent

equal increments of the attribute being measured. This means that

differences can be compared. The difference between 1 and 2 is the same

as between 2 and 3, but is only half the difference between 2 and 4. The

location of the zero point is not fixed, since zero does not denote the

absence of the attribute. Fahrenheit and Celsius temperatures are

measured with different interval scales and have different zero points.

Interval scales have very desirable properties, because virtually the entire



range of statistical operations can be employed to analyze the resulting

number, including addition and subtraction. Consequently, it is possible to

compute an arithmetic mean from interval-scale measures.

4.3.4 Ratio Scale

A ratio scale is a special kind of interval scale that has a meaningful zero

point. With such a scale – of weight, market share, or dollars in savings

accounts, for example, it is possible to say how many times greater or

smaller one object is than another. This is the only type of scale that permits

us to make comparisons of absolute magnitude. For example, we can say

that an annual income of Rs.80, 000/- is two times as large as an income of

Rs.40, 000/-.

There have been some contemporary efforts to adapt ratio scales to the

measurement of social opinion. Some researchers have attempted to use

magnitude estimation scales to overcome the loss of information that results

when categories arbitrarily constrain the range of opinion. Magnitude scaling

of attitudes has been calibrated through numeric estimation.

4.4 Components of Measurement Accuracy

Attitude measures, used in marketing, must be both accurate and useful.

Aspects that contribute accuracy are validity, reliability and sensitivity.

4.4.1 Validity

An attitude measure has validity if it measures what it is supposed to

measure. If this is the case, then differences in attitude scores will reflect

differences among the objects or individuals on the characteristic being

measured. How a researcher is to know whether measured differences in

the attitudes of managers, consumer activist, and consumers toward

marketing practices, regulation, and the contribution of the consumer



movement are true. There have been three basic approaches to this

question of validity assessment.

Face, or consensus, validity is invoked when the argument is made that the

measurement so self-evidently reflects or represents the various aspects of

the phenomenon that there can be little quarrels with it. For instance,

buyer’s recognition of advertisements is usually accepted at face value as

an indication of past ad exposure.

Criterion validity is more defensible, for it is based on empirical evidence

that the attitude measure correlate with other criterion variables. If the two

variables are measured at the same time concurrent validity is established.

Better yet, if the attitude measures can predict some future event, then

predictive validity is established.

4.4.2 Reliability

The total error of a measurement consists of systematic error component

and a random error component. Random error is manifested by lack of

consistency (unreliability) in repeated or equivalent measures of the same

object or person. As a result, any measurement can be expressed as a

function of several components:

Observed Score = True Score + Systematic Error + Random Error

If the measure is to be valid, it has to be reliable. A measure is highly

reliable if random error is zero and still has a substantial systematic error

that distorts the validity. In brief, reliability is a necessary but not a sufficient

condition for validity. The basic methods for establishing reliability can be

classified according to whether they measure stability of results over time or

internal consistency of items in an attitude. Stability over time is assessed

by repeating the measurement with the same instrument and the same

respondents at two points of time and correlating the results.



4.4.3 Sensitivity

The third characteristic of a good attitude measure is sensitivity, or the

ability to discriminate among meaningful differences in attitudes. Sensitivity

is achieved by increasing the number of scale categories; however, the

more categories there are, the lower the reliability will be

4.4.4 Generalization

Generalization refers to the ease of scale administration and interpretation

in different research settings and situations. Thus the Generalization of a

multiple- item scale is determined by whether it can be applied in a wide

variety of data collection modes, whether it can be used to obtain data from

a wide variety of individuals, and under what conditions it can be interpreted.

4.4.5 Relevancy

Relevancy of a scale refers to how meaningful it is to apply the scale to

measure a construct. Mathematically, it is represented as the product of

reliability and validity.

Relevance = reliability + validity.

If reliability and validity are evaluated by means of correlated coefficients,

the implications are:

The relevance of a scale can vary form 0 (no relevance) to 1 (complete

relevance).

If either reliability or validity is low, the scale will possess little relevance.

Both reliability and validity are necessary for scale relevance.

4.5 Measurement Accuracy and Measurement Development

4.5.1 Questionnaire Designing

Questionnaire construction is properly regarded as a very imperfect art.

There are no established procedures that will lead consistently to a good



questionnaire. A good questionnaire accomplishes the research’s

objectives. Surveys should be custom built to the specification of given

research purposes, and they are much more than a collection of

unambiguous questions. A number of constraints are imposed on the

development of an appropriate questionnaire. For example, the number,

form, and ordering of the specific questions are partly determined by the

data collection method.

There is a sequence of logical steps that every researcher must follow to

develop a good questionnaire.

Plan what to measure

Formulate questions to obtain the needed answers

Decide on the order and wording of questions and on the layout of the

questionnaire.

Using a small sample, test the questionnaire for omissions and

ambiguity.

Correct the problems and pre-test again.

4.5.2 Plan What to Measure

The most difficult step is specifying exactly what information is to be

collected from each respondent. Poor judgment and lack of thought at this

stage may mean that the results are not relevant to the research purpose or

that they are incomplete. When a questionnaire is sent into the field that is

incomplete in important aspects, the error is irreversible. To avoid this awful

situation, careful thought is required; this is facilitated by:

1. Clear research objectives, which describe as fully as possible the kind of

information the decision maker needs, the hypotheses, and the scope of

the research



2. Exploratory research, which will suggest further relevant variables and

help the researcher absorb the vocabulary and point of view of the

typical respondent.

3. Experience with similar studies

4. Pre-testing of preliminary versions of the questionnaire.

4.5.3 Formatting the Questions

Before specific questions are phrased, a decision has to be made as to the

degree of freedom to be given to respondents in answering the question.

The alternatives are:

i) Open-ended questions with no classification, where the interviewer

tries to record the response verbatim.

ii) Open-ended, where the interviewer uses preceded classifications to

record the response; or

iii) The closed, or structured, format, in which a question or supplementary

card presents the responses that the respondent may consider.

4.5.4 Question Wording

The wording of particular questions can have a large impact on how a

respondent interprets them. Even small changes in wording can shift

respondent’s answers, but it is difficult to know in advance whether or not a

wording change will have such an effect. The following guidelines are of

greatest value in critically evaluating and improving an existing question.

1. Is the vocabulary simple, direct and familiar to all respondents?

2. Do any words have vague or ambiguous meaning?

3. Are any questions double-barrelled?

4. Are any questions leading or loaded?

5. Are the instructions potentially confusing?

6. Is the question applicable to all respondents?



7. Split-ballot technique: whenever there is doubt as to the appropriate

wording it is desirable to test several alternatives.

8. Are the questions of an appropriate length?

4.5.5 Sequence and Layout Design

The order or sequence of questions will be determined initially by the need

to gain and maintain the respondent’s cooperation and make the

questionnaire as easy as possible for the interviewer to administer. Once

these considerations are satisfied, attention must be given to the problem of

order bias – the possibility that prior questions will influence answers to

subsequent questions. The basic guidelines for sequencing a questionnaire

are straight forward:

i) Open the interview with an easy and non threatening question.

ii) The questionnaire should flow smoothly and logically from one topic to

the next.

iii) For most topics it is better to proceed from broad, general questions to

the more specific.

iv) Sensitive or difficult questions dealing with income status, ability and so

forth should not be placed at the beginning of the questionnaire.

4.5.6 Pre-test Design

Effective Pre-testing demands that the researcher be open to criticism and

willing to pursue the deficiencies. There are some very specific reasons for

pre-test questions. Four common tests for specific questions are as follows:

Variation: testing items for an acceptable level of variation in the target

population is one of the most common goals of pre-testing.

Meaning: the intended meaning of the question for the investigators may

not be the meaning the respondents interpret it to be.



Task difficulty: A meaningful and clear question can still be difficult to

answer if the question requires that a respondent makes connections or

puts together information in unfamiliar ways.

Respondent interest and attention: Excessive repletion within a question

or use of the same format within a question can reduce the amount of

attention paid to questions by respondents.

4.6 Direct Response Attitude Scales

There are many ways to present a respondent with a continuum of

numbered categories that represent the range of possible attitude

judgments. They can be generally classified as single item scales and

multiple item scales.

4.6.1 Single Item Scales

Single item scales are those that have only one item to measure a

construct. Under the single item scales, the itemized category scale is the

most widely used by marketing researchers. In some situations,

comparative scales, rank order scales, or constant-sum scales have

advantages.

4.6.2 Itemized Scales

There are four categories from which respondents can choose to indicate

their overall level of satisfaction with their present health insurance plan.

– Very satisfied

– Quite satisfied

– Somewhat satisfied

– Not at all satisfied.

This satisfaction scale has the following characteristics.

All categories are labelled.



The respondent is forced to make a choice; there is no provision for

neutral opinion or ‘don’t know’ response.

There are more favourable than unfavourable categories, so the scale is

unbalanced.

There is no explicit comparison of respondents’ present plan with other

health insurance plan.

4.6.3 Comparative Scale

Another version of the preceding scale would label the categories

“excellent”, “Very good”, “fair” and “poor” thereby eliminating the implicit

comparisons. The problem with a comparative scale is that the reference

point is unclear and different respondents may use different reference point

or standards.

4.6.4 Rank Order Scale

Rank order scale requires the respondent to arrange a set of objects with

regard to a common criterion: advertisements in terms of interest, product

features in terms of importance, or new-product concepts with regard to

willingness to buy in the future. The result is an ordinal scale with the

inherent limitations of weak scale properties. Ranking is widely used in

surveys, however, because it corresponds to the choice process occurring

in shopping environment where a buyer makes direct comparison among

competing alternatives (brands, flavours, product variations, and so on).

4.6.5 Q-Sort Scaling

When the number of objects or characteristics that are to be rated or ranked

is very large, it becomes rather tedious for the respondents to rank order or

to do pair-wise comparisons. If the respondent is forced to rank ordering or

a pair-wise comparison, a number of problems and biases creep into the

study. To deal with such situations the Q-sort scaling process is used. In

Q-sort scale the respondents are asked to sort the various characteristics or



objects that are being compared into various groups, such that the

distribution of the number of objects or characteristics in each groups follow

a normal distribution. For example, let us take the case of a toy

manufacturing company such as Toys ‘R’ developing a new product. After a

marathon brain storming session, the new product team has come up with a

hundred different products; each with minor variations in features, and

wants to test and find out from consumers which feature combination is

most preferred and will generate maximum sales. The best scaling

procedure that can be used in this context is Q-sort scaling.

4.6.6 Constant Sum Scales

Constant sum scales require respondents to allocate a fixed number of

rating points (usually hundred) among several objects to reflect the relative

preference of each object. It is widely used to measure the relative

importance of attributes.

4.6.7 Pictorial Scales

In the pictorial scales, the various categories of the scale are depicted

pictorially. The respondents are shown a concept or read an attitudinal

statement and are asked to indicate their degree of agreement or interest by

indicating the corresponding position on the pictorial scale.

4.6.8 Paired Comparison Scale

The brands to be rated were presented two at a time, so each brand in the

category was compared once to every other brand. In each pair the

respondent is asked to divide ten points among the brands on the basis of

how much they like once compared to the other. A score was then totalled

for each brand. Although, this scale performs well on the criteria it is

cumbersome to administrate. Another possible limitation is that the frame of

reference is always the other brands in the set being tested. These brands

may change over time.



4.6.9 Derived Attitude Scales

Attitudes towards complex objects such as health plans, automobiles, credit

instruments, or transportation modes have many facets. Thus, it is often

unrealistic to attempt to capture the full picture with one overall attitude-

scale questions. For example, the public appears to support the general

idea of income tax reforms but opposes the elimination of the most popular

tax loopholes. The most frequent employed of these methods are Likert,

Thurstone and semantic-differential scales.

4.6.10 Likert Scales

Likert scale requires a respondent to indicate a degree of agreement or

disagreement with a variety of statement related to the attitudes or objects.

They are also called summated scales, because the scores on the individual

term are summed to produce a total score for the respondent. A Likert scale

usually consists of two parts, the item part and evaluative part. The item part

is essentially a statement about a certain product, event, or attitude. The

evaluative part is a list of response categories ranking form “strongly agree

to strongly disagree” an important assumption of this scaling method is that

each of the items (statements) measures some aspects of a single common

factor: otherwise, the items cannot be legitimately summed. In other words,

the resulting scale is one-dimensional.

4.6.11 Thurstone Scale

The procedure of Thurstone scale is also known as the method of equal

appearing intervals, since the objective is to obtain a one-dimensional scale

with interval properties. The first step is to develop a large number of

statements or adjectives reflecting all degrees of favourableness toward the

attitude objects then a group of judges is given this set of items and asked

to classify them according to their favourableness or unfavourableness.



4.6.12 Semantic – Differential Scales

Semantic differential scales are used widely to describe the set of beliefs

that comprise a person’s image of an organisation or brand. The procedure

is also an insightful procedure for comparing the images of competing

brands, stores, or services. Respondents are asked to rate each attitude

object in turn on a number of five- or seven point rating scales, bounded at

each end by polar adjectives or phrases.

Observation and Psychological Measures

Observation methods are limited to providing information on current

behaviour. Too often, this limitation becomes an excuse for not considering

observational methods; because many researchers do not use these

methods, they may not appreciate their considerable benefits. Nevertheless

there are strong arguments for considering the observation of ongoing

behaviour as an integral part of the research design.

4.7 Types of Observation

Observations may be classified in different ways. With reference to

investigator’s role, it may be classified into (a) participant observation and

(b) non-participant observation. In terms of mode of observation, it may be

classified into (c) direct observation. With reference to the rigor of the

system adopted. Observation is classified into (e) controlled observation,

and (f) uncontrolled observation

4.7.1 Participant observation: In this observation the observer is a part of

the phenomenon or group which is observed and he acts as both an

observer and a participant. For example, a study of tribal customs by an

anthropologist by taking part in tribal activities like folk dance. The persons

who are observed should not be aware of the researcher’s purpose. Then

only their behaviour will be ‘natural’. The concealment of research objective



and researcher’s identity is justified on the ground that it makes it possible to

study certain aspects of the group’s culture which are not revealed to

outsiders.

Advantages of Participatory observation

The advantages of participant observation are

1 The observer can understand the emotional reactions of the observed

group, and get a deeper insight of their experiences.

2 The observer will be able to record context which gives meaning to the

observed behaviour and heard statements.

Disadvantages of Participatory Observation

Participant observation suffers from some demerits.

1 The participant observer narrows his range of observation. For example,

if there is a hierarchy of power in the group/community under study, he

comes to occupy one position within and thus other avenues of

information are closed to him.

2 To the extent that the participant observer participates emotionally, the

objectivity is lost.

3 Another limitation of this method is the dual demand made on the

observer. Recording can interfere with participation, and participation

can interfere with observation. Recording on the spot is not possible and

it has to be postponed until the observer is alone. Such time lag results

in some inaccuracy in recording

Because of the above limitations, participant observation is generally

restricted to those cases where non-participant observation is not practical,

e.g. study of the functioning of a mobile library or mobile bank or tribal

community etc.



4.7.2 Non-participant observations

In this method, the observer stands apart and does not participate in the

phenomenon observed. Naturally there is no emotional involvement on the

part of the observer. This method calls for skill in recording observations in

an unnoticed manner.

4.7.3 Direct observation

This means observation of an event personally by the observer when it

takes place. This method is flexible and allows the observer to see and

record subtle aspects of events and behaviour as they occur. He is also free

to shift places, change the focus of the observation. A limitation of this

method is that the observer’s perception circuit may not be able to cover all

relevant events when the latter move quickly, resulting in the

incompleteness of the observation.

4.7.4 Indirect observation

This does not involve the physical presence of the observer, and the

recording is done by mechanical, photographic or electronic devices, e.g.

recording customer and employee movements by a special motion picture

camera mounted in a department of a large store. This method is less

flexible than direct observations, but it is less biasing and less erratic in

recording accuracy. It also provides a permanent record for an analysis of

different aspects of the event.

4.7.5 Controlled Observation

This involves standardization of observational techniques and exercises of

maximum control over extrinsic and intrinsic variables by adopting

experimental design and systematically recording observations. Controlled

observation is carried out either in the laboratory or in the field. It is typified

by clear and explicit decisions on what, how and when to observe.



4.7.6 Uncontrolled observation

This does not involve control over extrinsic and intrinsic variables. It is

primarily used for descriptive research. Participant observation is a typical

uncontrolled one.

4.7.7 Planning Observations

The use of observation method requires proper planning.

First, the researcher should carefully examine the relevance of

observation method to the data needs of the selected study.

Second, he must identify the specific investigative questions which call

for use of observation method. These determine the data to be

collected.

Third, he must decide the observation content, viz., specific conditions,

events and activities that have to be observed for the required data. The

observation content should include the relevant variables.

Fourth, for each variable chosen, the operational definition should be

specified.

Fifth, the observation setting, the subjects to be observed, the timing

and mode of observation, recording, procedure, recording instruments to

be used, and other details of the task should be determined.

Last, observers should be selected and trained. The persons to be

selected must have sufficient concentration powers, strong memory

power and unobtrusive nature. Selected persons should be imparted

both theoretical and practical training

4.7.8 Prerequisites of Effective Observation

The pre-requisites of observation consist of:

1. Observations must be done under conditions which will permit accurate

results. The observer must be in vantage point to see clearly the objects

to be observed. The distance and the light must be satisfactory. The



mechanical devices used must be in good working conditions and

operated by skilled persons.

2. Observation must cover a sufficient number of representative samples of

the cases.

3. Recording should be accurate and complete.

4. The accuracy and completeness of recorded results must be checked. A

certain number of cases can be observed again by another

observer/another set of mechanical devices, as the case may be. If it is

feasible, two separate observers and sets of instruments may be used in

all or some of the original observations. The results could then be

compared to determine their accuracy and completeness.

4.7.9 Observations Tools and Recording Devices

Systematic observation require the use of observation schedule , objectives

of the study, the investigative questions, hypothesis and the operational

definition of concepts and out of the data requirements, items of data to be

collected through observation are identified. A schedule is then constructed,

covering those items of data. It should be constructed in such a manner as

to make it possible to record the necessary information easily and correctly.

Enough space should be provided for recording observations for each item.

The item should appear in logical groupings and in the order in which the

observer would observe him

Field Observation Log: This may take the form of a diary or cards. Each

item of observations is recorded under appropriate sub-heading. At the time

of observation, rough noting may be made, and at the end of the day, full log

may be made. The card system is flexible and facilitates arrangement and

re-arrangement of items in any desired order.

Mechanical Devices: These may include cameras, tape recorders,

videotape and electronic devices, still, motion, sound and colour and time-



lapse cameras give a permanent record of events. Microscopic and

telescopic lens may be used in cameras. Eye cameras are common in

advertising and package research. They record eye movements while a

consumer is looking at advertisements or packages. Other recording

instruments are: tape, disc, and wire recorders, barometer, hygrometers,

speedometers, one-way screens and mirrors, closed circuit television, light

meters, pocket calculators.

4.7.10 Suitability and Application

Observation is suitable for a variety of research purposes. It may be used

for studying (a) the behaviour of human beings and social groups, life styles

customs and manner, interpersonal relations, group dynamics, crowd

behaviour, leadership styles, managerial style, other behaviours and

actions; (b) the behaviour of other living creatures like birds, animals etc., (c)

physical characteristic of inanimate things like stores, factories residence

etc., (d) flow of traffic and parking problems; (e) movement of

materials/products through a plant.

It may be used in exploratory research to gain insights that will be

subsequently tested as hypothesis. It may be used to collect supplementary

data that may interpret or qualify findings obtained by other methods.

Observation may be used as the primary method, e.g. anthropological

studies of communities, behavioural studies of small groups

Observation may be used in studying behaviour in ‘natural’ setting or in the

laboratory, e.g. group formation may be studied as it occurs in a real life

situation or in the laboratory room.

4.7.11 Advantages of Observation

Observation has certain advantages:

1. The main virtue of observation is its directness: it makes it possible to

study behaviour as it occurs. The researcher need not ask people about



their behaviour and interactions; he can simply watch what they do and

say.

2. Data collected by observation may describe the observed phenomena

as they occur in their natural settings. Other methods introduce

elements or artificiality into the researched situation for instance, in

interview; the respondent may not behave in a natural way. There is no

such artificiality in observational studies, especially when the observed

persons are not aware of their being observed.

3. Observations is more suitable for studying subjects who are unable to

articulate meaningfully, e.g. studies of children, tribal, animals, birds etc.

4. Observations improve the opportunities for analyzing the contextual

back ground of behaviour. Further more, verbal resorts can be validated

and compared with behaviour through observation. The validity of what

men of position and authority say can be verified by observing what they

actually do.

5. Observations make it possible to capture the whole event as it occurs.

For example, only observation can provide an insight into all the aspects

of the process of negotiation between union and management

representatives.

6. Observation is less demanding of the subjects and has less biasing

effect on their conduct than questioning.

7. It is easier to conduct disguised observation studies than disguised

questioning.

8. Mechanical devices may be used for recording data in order to secure

more accurate data and also of making continuous observations over

longer periods.



4.7.12 Limitations of Observation

Observation cannot be used indiscriminately for all purposes. It has its own

limitations:

1. Observation is of no use, studying past events or activities. One has to

depend upon documents or narrations and people for studying such

things.

2. Observation is not suitable for studying and attitudes. However, an

observation of related behaviour affords a good clue to the attitudes.

E.g. and observations of the seating pattern of high caste and class

persons in a general meeting in a village may be useful for forming an

index of attitude.

3. Observation poses difficulties in obtaining a representative sample. For

interviewing and mailing methods, the selection of a random sampling

can be rapidly ensured. But observing people of all types does not make

the sample a random one.

4. Observation cannot be used as and when the researcher finds it

convenient to use. He has to wait for the event to occur. For example,

an observation of folk dance of a tribal community is possible, only when

it is performed.

5. A major limitation of this method is that the observer normally must be at

the scene of the event when it takes place. Yet it may not be possible to

predict where and when the event will occur, e.g., road accident,

communal clash.

6. Observation is slow and expensive process, requiring human observers

and/or costly surveillance equipments





1. Measurement can be defined as a standardized process of assigning

numbers or other symbols to certain characteristics of the objects of

interest, according to some pre-specified rules.

2. Scaling is the process of creating a continuum on which objects are

located according to the amount of the measured characteristics they

possess.

3. The assignment of numbers is made according to rules that should

correspond to the properties of whatever is being measured.

4. In a nominal scale, objects are assigned to mutually exclusive, labelled

categories, but there are no necessary relationships among the

categories; that is , no ordering or spacing is implied

4.8 Summary

Measurement can be defined as a standardized process of assigning

numbers or other symbols to certain characteristics of the objects of interest,

according to some pre-specified rules. Scaling is the process of creating a

continuum on which objects are located according to the amount of the

measured characteristics they possess. The assignment of numbers is

made according to rules that should correspond to the properties of

whatever is being measured. In a nominal scale, objects are assigned to

mutually exclusive, labelled categories, but there are no necessary

relationships among the categories; that is, no ordering or spacing is

implied. An ordinal scale is obtained by ranking objects or by arranging them

in order with regard to some common variable. In an interval scale the

numbers used to rank the objects also represent equal increments of the

attribute being measured. A ratio scale is a special kind of interval scale that



has a meaningful zero point. Attitude measures, used in marketing, must be

both accurate and useful. Aspects that contribute accuracy are validity,

reliability and sensitivity. An attitude measure has validity if it measures what

it is supposed to measure. The total error of a measurement consists of

systematic error component and a random error component. The third

characteristic of a good attitude measure is sensitivity, or the ability to

discriminate among meaningful differences in attitudes. Sensitivity is

achieved by increasing the number of scale categories; however, the more

categories there are, the lower the reliability will be. Generalization refers to

the ease of scale administration and interpretation in different research

settings and situations. Relevancy of a scale refers to how meaningful it is to

apply the scale to measure a construct. Questionnaire construction is

properly regarded as a very imperfect art. There are no established

procedures that will lead consistently to a good questionnaire.

There are many ways to present a respondent with a continuum of

numbered categories that represent the range of possible attitude

judgments. They can be generally classified as single item scales and

multiple item scales. Single item scales are those that have only one item to

measure a construct. Under the single item scales, the itemized category

scale is the most widely used by marketing researchers. In some situations,

comparative scales, rank order scales, or constant-sum scales have

advantages. There are four categories from which respondents can choose

to indicate their overall level of satisfaction with their present health

insurance plan. Rank order scale requires the respondent to arrange a set

of objects with regard to a common criterion: advertisements in terms of

interest, product features in terms of importance, or new-product concepts

with regard to willingness to buy in the future. Constant sum scales require

respondents to allocate a fixed number of rating points (usually hundred)



among several objects to reflect the relative preference of each object. It is

widely used to measure the relative importance of attributes.

Attitudes towards complex objects such as health plans, automobiles, credit

instruments, or transportation modes have many facets. Likert scale

requires a respondent to indicate a degree of agreement or disagreement

with a variety of statement related to the attitudes or objects. They are also

called summated scales, because the scores on the individual term are

summed to produce a total score for the respondent. Semantic differential

scales are used widely to describe the set of beliefs that comprise a

person’s image of an organisation or brand. Observation methods are

limited to providing information on current behaviour. Observations may be

classified in different ways. With reference to investigator’s role, it may be

classified into (a) participant observation and (b) non-participant

observation. In terms of mode of observation, it may be classified into (c)

direct observation. With reference to the rigor of the system adopted.

Observation is classified into (e) controlled observation, and (f) uncontrolled

observation


1. What are the concepts of measurement techniques used in marketing

research?

2. Explain different scales of measurement.

3. How is a questionnaire designed?

4. What are derived attitude scales?

5. What are the types of observation?




SAQs

1. True

2. True

3. True

4. True

TQs

1. Section 4.1

2. Section 4. 5

3. Section 4. 4.5.1

4. Section 4.6.9

5. Section 4.6.7



Unit 5 Sampling and Data Analysis

Structure

5.1 Introduction: Meaning of sampling

Objectives

5.1.1 Census and sample

5.2 The sampling process

5.2.1 Criteria for sampling procedure

5.3 Different types of sampling techniques

5.3.1 Probability or random sampling

5.3.2 Non-probability or Non-random sampling

5.4 Random sampling

Self assessment questions

5.5 Summary

5.6 Terminal questions


5.1 Introduction: Meaning of Sampling

A part of the population is known as sample. The method consisting of the

selecting for study, a portion of the ‘universe’ with a view to drawing

conclusions about the ‘universe’ or ‘population’ is known as sampling. A

statistical sample ideally purports to be a miniature model or replica of the

population constituted of all the items that the study should principally

encompass, that is, the items which potentially hold promise of affording

information relevant to the purpose of a given research.

Sampling helps in time and cost saving. It also helps in checking their

accuracy. But on the other hand it demands exercise of great care and

caution; otherwise the results obtained may be incorrect or misleading.



Objectives:

After studying this unit, the students should be able to:

explain the census and sample

discuss the sampling process and criteria for sampling procedure

explain the different types of sampling techniques

5.1.1 Census and Sample Survey

The process of designing a field study, among other things, involves a

decision to use sampling or not. The researcher must decide whether he

should cover all the units. When all the units are studied, such a complete

coverage is called a census survey. When only a sample of the universe is

studied, the study is called a sample survey.

In making this decision of census or sampling, the following factors are

considered:

1) The size of the population: If the population to be studied is relatively

small, say 50 institutions or 200 employees or 150 households, the

investigator may decide to study the entire population. The task is easily

manageable and the sampling may not be required. But, if the

population to be studied is quite large, sampling is warranted.

However, the size is a relative matter. Whether a population is large or

small depends upon the nature of the study, the purpose for which it is

undertaken, and the time and other resources available for it.

2) Amount of funds budgeted for the study: The decision regarding

census or sampling depends upon the budget of the study. Sampling is

opted when the amount of money budgeted is smaller than the

anticipated cost of census survey.

3) Facilities: The extent of facilities available – staff, access to computer

facility and accessibility to population elements - in another factor to be

considered in deciding to sample or not. When the availability of these



facilities is extensive, census survey may be manageable. Otherwise,

sampling is preferable.

4) Time: The time limit within which the study should be completed is

another important factor to be considered in deciding the question of

census or sample survey. This, in fact, is a primary reason for using

sampling by academic and marketing researchers.

5.2 Sampling Process

5.2.1 Criteria of Sampling Procedure

The decision process is complicated one. The researcher has to first identify

the limiting factor or factors and must judiciously balance the conflicting

factors. The various criteria governing the choice of the sampling technique:

1. Purpose of the Survey: What does the researcher aim at? If he intends

to generalize the findings based on the sample survey to the population,

then an appropriate probability sampling method must be selected. The

choice of a particular type of probability sampling depends on the

geographical area of the survey and the size and the nature of the

population under study.

2. Measurability: The application of statistical inference theory requires

computation of the sampling error from the sample itself. Probability

samples only allow such computation. Hence, where the research

objective requires statistical inference, the sample should be drawn by

applying simple random sampling method or stratified random sampling

method, depending on whether the population is homogenous or

heterogeneous.

3. Degree of Precision: Should the results of the survey be very precise,

or even rough results could serve the purpose? The desired level of

precision as one of the criteria of sampling method selection. Where a

high degree of precision of results is desired, probability sampling



should be used. Where even crude results would serve the purpose

(E.g., marketing surveys, readership surveys etc) any convenient non-

random sampling like quota sampling would be enough.

4. Information about Population: How much information is available

about the population to be studied? Where no list of population and no

information about its nature are available, it is difficult to apply a

probability sampling method. Then exploratory study with non-probability

sampling may be made to gain a better idea of population. After gaining

sufficient knowledge about the populations through the exploratory

study, appropriate probability sampling design may be adopted.

5. The Nature of the Population: In terms of the variables to be studied, is

the population homogenous or heterogeneous? In the case of a

homogenous population, even a simple random sampling will give a

representative sample. If the population is heterogeneous, stratified

random sampling is appropriate.

6. Geographical Area of the Study ad the Size of the Population: If the

area covered by a survey is very large and the size of the population is

quite large, multi-stage cluster sampling would be appropriate. But if the

area and the size of the population are small, single stage probability

sampling methods could be used.

7. Financial resources: If the available finance is limited, it may become

necessary to choose a less costly sampling plan like multistage cluster

sampling or even quota sampling as a compromise. However, if the

objectives of the study and the desired level of precision cannot be

attained within the stipulated budget, there is no alternative than to give

up the proposed survey. Where the finance is not a constraint, a

researcher can choose the most appropriate method of sampling that fits

the research objective and the nature of population.



8. Time Limitation: The time limit, within which the research project should

be completed, restricts the choice of a sampling method. Then, as a

compromise, it may become necessary to choose less time consuming

methods like simple random sampling instead of stratified

sampling/sampling with probability proportional to size; multi-stage

cluster sampling instead of single-stage sampling of elements. Of

course, the precision has to be sacrificed to some extent.

9. Economy: It should be another criterion in choosing the sampling

method. It means achieving the desired level of precision at minimum

cost. A sample is economical if the precision per unit cost is high or the

cost per unit of variance is low. The above criteria frequently conflicts

and the researcher must balance and blend them to obtain a good

sampling plan. The chosen plan thus represents an adaptation of the

sampling theory to the available facilities and resources. That is, it

represents a compromise between idealism and feasibility. One should

use simple workable methods instead of unduly elaborate and

complicated techniques.

5.3 Different Types of Sample Techniques

Sampling techniques or methods may be classified into two generic types:

5.3.1 Probability or Random Sampling

Probability sampling is based on the theory of probability. It is also known as

random sampling. It provides a known non-zero chance of selection for each

population element. It is used when generalization is the objective of study,

and a greater degree of accuracy of estimation of population parameters is

required. The cost and time required is high and thus the benefit derived

from it should justify the costs. The following are the types of probability

sampling.



Simple random sampling: This sampling technique gives each element an

equal and independent chance of being selected. An equal chance means

equal probability of selection. An independent chance means that the draw

of one element will not affect the chances of other elements being selected.

The procedure of drawing a simple random sample consists of:

Enumeration of all elements in the population,

Preparation of a List of all elements, giving them numbers in serial order

1, 2, 3, and so on, and

Drawing sample numbers by using (a) lottery method, (b) a table of

random numbers or (c) a computer.

Suitability: This type of sampling is suited for a small homogeneous

population.

Advantages: The advantage of this is that it is one of the easiest methods,

all the elements in the population have an equal chance of being selected,

simple to understand, does not require prior knowledge of the true

composition of the population.

Disadvantages: It is often impractical because of non-availability of

population list or of difficulty in enumerating the population, does not ensure

proportionate representation and it may be expensive in time and money.

The amount of sampling error associated with any sample drawn can easily

be computed but it is greater than that in other probability samples of the

same size, because it is less precise than other methods.

Stratified random sampling: This is an improved type of random or

probability sampling. In this method, the population is sub-divided into

homogenous groups or strata, and from each stratum, random sample is

drawn. E.g., university students may be divided on the basis of discipline,

and each discipline group may again be divided into juniors and seniors.

Stratification is necessary for increasing a sample’s statistical efficiency,



providing adequate data for analyzing the various sub-populations and

applying different methods to different strata. The stratified random sampling

is appropriate for a large heterogeneous population. Stratification process

involves three major decisions. They are stratification base or bases,

number of strata and strata sample sizes. Stratified random sampling may

be classified into:

Proportionate stratified sampling: This sampling involves drawing a

sample from each stratum in proportion to the latter’s share in the total

population. It gives proper representation to each stratum and its statistical

efficiency is generally higher. This method is therefore very popular. E.g., if

the final year MBA students of the Management Faculty of a University

consist of the following specialization groups:

Specialization stream

No. of students Proportion of each stream

ProductionFinance MarketingRural development

40203010

0.40.20.30.1

100 1.0

The research wants to draw an overall sample of 30. Then the strata sample

sizes would be:

Strata Sample size

ProductionFinance MarketingRural development

30 x 0.430 x 0.230 x 0.330 x 0.1

12 6 9 3

30

Advantages: Stratified random sampling enhances the representative ness

to each sample, gives higher statistical efficiency, easy to carry out, and

gives a self-weighing sample.



Disadvantages: A prior knowledge of the composition of the population and

the distribution of the population, it is very expensive in time and money and

identification of the strata may lead to classification of errors.

Disproportionate stratified random sampling: This method does not give

proportionate representation to strata. It necessarily involves giving over-

representation to some strata and under-representation to others. The

desirability of disproportionate sampling is usually determined by three

factors, viz, (a) the sizes of strata, (b) internal variances among strata, and

(c) sampling costs.

Suitability: This method is used when the population contains some small

but important subgroups, when certain groups are quite heterogeneous,

while others are homogeneous and when it is expected that there will be

appreciable differences in the response rates of the subgroups in the

population.

Advantages: The advantages of this type are that it is less time consuming

and facilitates giving appropriate weighing to particular groups which are

small but more important.

Disadvantages: The disadvantage is that it does not give each stratum

proportionate representation, requires prior knowledge of composition of the

population, is subject to classification errors and its practical feasibility is

doubtful.

Systematic random sampling: This method of sampling is an alternative to

random selection. It consists of taking kth item in the population after a

random start with an item form 1 to k. It is also known as fixed interval

method. E.g., 1st, 11th, 21st ……… Strictly speaking, this method of sampling

is not a probability sampling. It possesses characteristics of randomness

and some non-probability traits.



Suitability: Systematic selection can be applied to various populations such

as students in a class, houses in a street, telephone directory etc.

Advantages: The advantages are that it is simpler than random sampling,

easy to use, easy to instruct, requires less time, it’s cheaper, easier to

check, sample is spread evenly over the population, and it is statistically

more efficient.

Disadvantages: The disadvantages are that it ignores all elements between

two kth elements selected, each element does not have equal chance of

being selected, and this method sometimes gives a biased sample.

Cluster sampling: It means random selection of sampling units consisting

of population elements. Each such sampling unit is a cluster of population

elements. Then from each selected sampling unit, a sample of population

elements is drawn by either simple random selection or stratified random

selection. Where the population elements are scattered over a wide area

and a list of population elements is not readily available, the use of simple or

stratified random sampling method would be too expensive and time-

consuming. In such cases, cluster sampling is usually adopted. The cluster

sampling process involves: identify clusters, examine the nature of clusters,

and determine the number of stages.

Suitability: The application of cluster sampling is extensive in farm

management surveys, socio-economic surveys, rural credit surveys,

demographic studies, ecological studies, public opinion polls, and large

scale surveys of political and social behaviour, attitude surveys and so on.

Advantages: The advantages of this method are that it is easier and more

convenient, cost of this is much less, promotes the convenience of field

work as it could be done in compact places, it does not require more time,

units of study can be readily substituted for other units and it is more

flexible.



Disadvantages: The cluster sizes may vary and this variation could

increase the bias of the resulting sample. The sampling error in this method

of sampling is greater and the adjacent units of study tend to have similar

characteristics than do units distantly apart.

Area sampling: This is an important form of cluster sampling. In larger field

surveys cluster consisting of specific geographical areas like districts, taluks,

villages or blocks in a city are randomly drawn. As the geographical areas

are selected as sampling units in such cases, their sampling is called area

sampling. It is not a separate method of sampling, but forms part of cluster

sampling.

Multi-stage and sub-sampling: In multi-stage sampling method, sampling

is carried out in two or more stages. The population is regarded as being

composed of a number of second stage units and so forth. That is, at each

stage, a sampling unit is a cluster of the sampling units of the subsequent

stage. First, a sample of the first stage sampling units is drawn, then from

each of the selected first stage sampling unit, a sample of the second stage

sampling units is drawn. The procedure continues down to the final

sampling units or population elements. Appropriate random sampling

method is adopted at each stage. It is appropriate where the population is

scattered over a wider geographical area and no frame or list is available for

sampling. It is also useful when a survey has to be made within a limited

time and cost budget. The major disadvantage is that the procedure of

estimating sampling error and cost advantage is complicated.

Sub-sampling is a part of multi-stage sampling process. In a multi-stage

sampling, the sampling in second and subsequent stage frames is called

sub-sampling. Sub-sampling balances the two conflicting effects of

clustering i.e., cost and sampling errors.



Random sampling with probability proportional to size: The procedure

of selecting clusters with probability Proportional to size (PPS) is widely

used. If one primary cluster is twice as large a population as another, it has

twice the chance of being selected. If the same number of persons is then

selected from each of the selected clusters, the overall probability of any

person will be the same. Thus PPS is a better method for securing a

representative sample of population elements in multi-stage cluster

sampling.

Advantages: The advantages are that the clusters of various sizes get

proportionate representation, PPS leads to greater precision than would a

simple random sample of clusters and a constant sampling fraction at the

second stage, equal-sized samples from each selected primary cluster are

convenient for field work.

Disadvantages: PPS cannot be used if the sizes of the primary sampling

clusters are not known.

Double sampling and multiphase sampling: Double sampling refers to

the subsection of the final sample form a pre-selected larger sample that

provided information for improving the final selection. When the procedure is

extended to more than two phases of selection, it is then, called multi-phase

sampling. This is also known as sequential sampling, as sub-sampling is

done from a main sample in phases. Double sampling or multiphase

sampling is a compromise solution for a dilemma posed by undesirable

extremes. “The statistics based on the sample of ‘n’ can be improved by

using ancillary information from a wide base: but this is too costly to obtain

from the entire population of N elements. Instead, information is obtained

from a larger preliminary sample nL which includes the final sample n.

Replicated or interpenetrating sampling: It involves selection of a certain

number of sub-samples rather than one full sample from a population. All



the sub-samples should be drawn using the same sampling technique and

each is a self-contained and adequate sample of the population. Replicated

sampling can be used with any basic sampling technique: simple or

stratified, single or multi-stage or single or multiphase sampling. It provides

a simple means of calculating the sampling error. It is practical. The

replicated samples can throw light on variable non-sampling errors. But

disadvantage is that it limits the amount of stratification that can be

employed.

5.3.2 Non-Probability or Non Random Sampling

Non-probability sampling or non-random sampling is not based on the

theory of probability. This sampling does not provide a chance of selection

to each population element.

Advantages: The only merits of this type of sampling are simplicity,

convenience and low cost.

Disadvantages: The demerits are that it does not ensure a selection

chance to each population unit. The selection probability sample may not be

a representative one. The selection probability is unknown. It suffers from

sampling bias which will distort results.

The reasons for usage of this sampling are when there is no other feasible

alternative due to non-availability of a list of population, when the study does

not aim at generalizing the findings to the population, when the costs

required for probability sampling may be too large, when probability

sampling required more time, but the time constraints and the time limit for

completing the study do not permit it. It may be classified into:

1. Convenience or accidental sampling: It means selecting sample units

in a just ‘hit and miss’ fashion E.g., interviewing people whom we happen to

meet. This sampling also means selecting whatever sampling units are

conveniently available, e.g., a teacher may select students in his class. This



method is also known as accidental sampling because the respondents

whom the researcher meets accidentally are included in the sample.

Suitability: Though this type of sampling has no status, it may be used for

simple purposes such as testing ideas or gaining ideas or rough impression

about a subject of interest.

Advantage: It is the cheapest and simplest, it does not require a list of

population and it does not require any statistical expertise.

Disadvantage: The disadvantage is that it is highly biased because of

researcher’s subjectivity, it is the least reliable sampling method and the

findings cannot be generalized.

2. Purposive (or judgment) sampling: This method means deliberate

selection of sample units that conform to some pre-determined criteria. This

is also known as judgment sampling. This involves selection of cases which

we judge as the most appropriate ones for the given study. It is based on

the judgement of the researcher or some expert. It does not aim at securing

a cross section of a population. The chance that a particular case be

selected for the sample depends on the subjective judgement of the

researcher.

Suitability: This is used when what is important is the typicality and specific

relevance of the sampling units to the study and not their overall

representative ness to the population.

Advantage: It is less costly and more convenient and guarantees inclusion

of relevant elements in the sample.

Disadvantage: It is less efficient for generalizing, does not ensure the

representative ness, requires prior extensive information and does not lend

itself for using inferential statistics.



3. Quota sampling: This is a form of convenient sampling involving

selection of quota groups of accessible sampling units by traits such as sex,

age, social class, etc. It is a method of stratified sampling in which the

selection within strata is non-random. It is this ‘Non-random’ element that

constitutes its greatest weakness.

Suitability: It is used in studies like marketing surveys, opinion polls, and

readership surveys which do not aim at precision, but to get quickly some

crude results.

Advantage: It is less costly, takes less time, no need for a list of population,

and field work can easily be organized.

Disadvantage: It is impossible to estimate sampling error, strict control if

field work is difficult, and subject to a higher degree of classification.

4. Snow-ball sampling: This is the colourful name for a technique of

building up a list or a sample of a special population by using an initial set of

its members as informants. This sampling technique may also be used in

socio-metric studies.

Suitability: It is very useful in studying social groups, informal groups in a

formal organization, and diffusion of information among professional of

various kinds.

Advantage: It is useful for smaller populations for which no frames are

readily available.

Disadvantage: The disadvantage is that it does not allow the use of

probability statistical methods. It is difficult to apply when the population is

large. It does not ensure the inclusion of all the elements in the list.

5.4 Random Sampling

The importance of randomness is that sampling needs no emphasis. It is a

means for securing a representative sample. Experience shows that the



human being is an extremely poor instrument for the conduct of a random

selection. To ensure true randomness, the method of selection must be

independent of human judgment. There are three basic procedures:

The Lottery Method: This is the simplest and most familiar procedure of

random sampling. In a sampling procedure, there are two alternatives. After

a number is selected by draw, it may be replaced, and consequently it has a

chance of being selected again. Such a method is known as sampling with

replacement. This is usually referred to as unrestricted random sampling.

Alternatively, the selected number is set aside, and so in the subsequent

draw, it does not get a chance of being selected again. This type of

sampling is known as sampling without replacement. This is a form of

restricted sampling. Lottery Method is used for drawing a small form a small

population. But it would be time consuming and tedious if the population is

very large.

The use of Table of Random Numbers: This is a less cumbersome but

equally valid procedure of sample selection. Tables of random numbers

have been developed by Kendall and Smith (1939), Fisher and Yates (1963)

and Tippett (1927). One of them is usually found in a standard book on

Statistics or Methodology of Research. To select a random sample out of a

given frame, one should simply start to read numbers form a Table of

Random Numbers at any randomly selected point and pick out numbers

within the range of the frame.

Use of computer: If the population is very large and if computer facilities are

available, a computer may be used for drawing a random sample. The

computer can be programmed to print out a series of random numbers, as

many as the researcher desires.



Self Assessment Questions – I


1. Sampling helps in time and cost saving.

2. The decision regarding census or sampling depends upon the budget of

the study.

3. Simple random sampling technique gives each element an equal and

independent chance of being selected.

5.5 Summary

A statistical sample ideally purports to be a miniature model or replica of the

population constituted of all the items that the study should principally

encompass, that is, the items which potentially hold promise of affording

information relevant to the purpose of a given research. Sampling helps in

time and cost saving. It also helps in checking their accuracy. But on the

other hand it demands exercise of great care and caution; otherwise the

results obtained may be incorrect or misleading. The process of designing a

field study, among other things, involves a decision to use sampling or not.

The researcher must decide whether he should cover all the units. When all

the units are studied, such a complete coverage is called a census survey.

When only a sample of the universe is studied, the study is called a sample

survey. If the population to be studied is quite large, sampling is warranted.

However, the size is a relative matter. Whether a population is large or small

depends upon the nature of the study, the purpose for which it is

undertaken, and the time and other resources available for it.

The decision regarding census or sampling depends upon the budget of the

study. Sampling is opted when the amount of money budgeted is smaller

than the anticipated cost of census survey. The extent of facilities available

– staff, access to computer facility and accessibility to population elements -



is another factor to be considered in deciding to sample or not. When the

availability of these facilities is extensive, census survey may be

manageable. Otherwise, sampling is preferable. The time limit within the

study should be completed is another important factor to be considered in

deciding the question of census or sample survey. This, in fact, is a primary

reason for using sampling by academic and marketing researchers. The

application of statistical inference theory requires computation of the

sampling error from the sample itself. Probability samples only allow such

computation. Hence, where the research objective requires statistical

inference, the sample should be drawn by applying simple random sampling

method or stratified random sampling method, depending on whether the

population is homogenous or heterogeneous.

Probability sampling is based on the theory of probability. It is also known as

random sampling. It provides a known non-zero chance of selection for each

population element. Simple random sampling technique gives each

element an equal and independent chance of being selected. An equal

chance means equal probability of selection. Stratified random sampling

is an improved type of random or probability sampling. In this method, the

population is sub-divided into homogenous groups or strata, and from each

stratum, random sample is drawn. Proportionate stratified sampling

involves drawing a sample from each stratum in proportion to the latter’s

share in the total population. It gives proper representation to each stratum

and its statistical efficiency is generally higher. Disproportionate stratified

random sampling does not give proportionate representation to strata. It

necessarily involves giving over-representation to some strata and under-

representation to others. The desirability of disproportionate sampling is

usually determined by three factors, viz, (a) the sizes of strata, (b) internal

variances among strata, and (c) sampling costs. Systematic random

sampling method is an alternative to random selection. It consists of taking



kth item in the population after a random start with an item from 1 to k. It is

also known as fixed interval method. Cluster sampling means random

selection of sampling units consisting of population elements. Each such

sampling unit is a cluster of population elements. Then from each selected

sampling unit, a sample of population elements is drawn by either simple

random selection or stratified random selection. In Area sampling larger

field surveys cluster consisting of specific geographical areas like districts,

taluks, villages or blocks in a city are randomly drawn. As the geographical

areas are selected as sampling units in such cases, their sampling is called

area sampling. It is not a separate method of sampling, but forms part of

cluster sampling. Double sampling and multiphase sampling refers to the

subsection of the final sample from a pre-selected larger sample that

provided information for improving the final selection. When the procedure is

extended to more than two phases of selection, it is then, called multi-phase

sampling. This is also known as sequential sampling, as sub-sampling is

done from a main sample in phases. Replicated or interpenetrating

sampling involves selection of a certain number of sub-samples rather than

one full sample from a population. All the sub-samples should be drawn

using the same sampling technique and each is a self-contained and

adequate sample of the population. Non-probability or non random

sampling is not based on the theory of probability. This sampling does not

provide a chance of selection to each population element. Purposive (or

judgment) sampling method means deliberate selection of sample units

that conform to some pre-determined criteria. This is also known as

judgment sampling. This involves selection of cases which we judge as the

most appropriate ones for the given study. It is based on the judgment of the

researcher or some expert. Quota sampling is a form of convenient

sampling involving selection of quota groups of accessible sampling units by

traits such as sex, age, social class, etc. it is a method of stratified sampling



in which the selection within strata is non-random. Snow-ball sampling is

the colourful name for a technique of building up a list or a sample of a

special population by using an initial set of its members as informants. This

sampling technique may also be used in socio-metric studies.


1. Distinguish between Census and sample survey

2. Explain the Sampling process

3. What are the types of Probability or random sampling?

4. Explain Multi-stage and sub-sampling?

5. What is Random sampling with probability proportional to size?

6. Distinguish between Double sampling and multiphase sampling:

7. What is replicated or interpenetrating sampling?

8. What is Non-probability or non random sampling?

9. What is Purposive (or judgment) sampling?

10. What is Quota sampling?

11. What is Snow-ball sampling?

12. What is Random sample?


SAQs

1. True

2. True

3. True



TQs

1. Section 5.11

2. Section 5.2

3. Section 5.3.1.

4. Section 5.3.1.

5. Section 5.3.1

6. Section 5.3.1

7. Section 5.3.1

8. Section 5.3.2

9. Section 5.3.2.

10. Section 5.3.2

11. Section 5.3.2.

12. Section 5.6.



Unit 6 Hypothesis Formation and Testing

Structure

6.1 Introduction: Meaning of hypothesis

Objectives:

6.2 Criteria for hypothesis construction

6.3 Nature of hypothesis

6.4 Features of hypothesis

6.5 Characteristics of hypothesis

6.6 Concept of testing hypothesis

6.7 Procedure and flow diagram for testing hypothesis

6.8 Test of hypothesis

6.9 Important parametric tests

Self assessment questions

6.10 Summary



6.1 Introduction: Meaning of Hypotheses

A hypothesis is an assumption about relations between variables. It is a

tentative explanation of the research problem or a guess about the research

outcome. Before starting the research, the researcher has a rather general,

diffused, even confused notion of the problem. It may take long time for the

researcher to say what questions he had been seeking answers to. Hence,

an adequate statement about the research problem is very important. What

is a good problem statement? It is an interrogative statement that asks: what

relationship exists between two or more variables? It then further asks

questions like: If A related to B or not? How are A and B related to C? Is A



related to B under conditions X and Y? Proposing a statement pertaining to

relationship between A and B is called a hypothesis.

According to Theodorson and Theodorson, “a hypothesis is a tentative

statement asserting a relationship between certain facts. Kerlinger describes

it as “a conjectural statement of the relationship between two or more

variables”. Black and Champion have described it as “a tentative statement

about something, the validity of which is usually unknown”. This statement is

intended to be tested empirically and is either verified or rejected. If the

statement is not sufficiently established, it is not considered a scientific law.

In other words, a hypotheses carries clear implications for testing the stated

relationship, i.e., it contains variables that are measurable and specifying

how they are related. A statement that lacks variables or that does not

explain how the variables are related to each other is no hypotheses in

scientific sense.

Objectives:


explain the criteria for hypothesis construction

discuss the nature of hypothesis, features of hypothesis, characteristics

of hypothesis and testing hypothesis

discuss the important parametric tests

6.2. Criteria for Hypotheses Construction

Hypothesis is never formulated in the form of a question. The standards to

be met in formulating a hypothesis:

1. It should be empirically testable, whether it is right or wrong.

2. It should be specific and precise.

3. The statements in the hypotheses should not be contradictory.



4. It should specify variables between which the relationship is to be

established.

5. It should describe one issue only.

6. 3 Nature of Hypotheses

A scientific and justified hypothesis must meet the following criteria:

It must accurately reflect the relevant sociological fact.

It must not be in contradiction with approved relevant statements of

other scientific disciplines.

It must consider the experience of other researchers.

6.4 The Functions of Hypotheses

1. A hypothesis gives a definite point to the investigation, and it guides the

direction on the study.

2. A hypothesis specifies the sources of data, which shall be studied, and

in what context they shall be studied.

3. It determines the data needs.

4. A hypothesis suggests which type of research is likely to be most

appropriate.

5. It determines the most appropriate technique of analysis.

6. A hypothesis contributes to the development of theory

6.5 Characteristics of Good Hypotheses

Conceptual Clarity

Specificity

Testability

Availability of Techniques



Theoretical relevance

Consistency

Objectivity

Simplicity

6.6 Concept of Testing Hypotheses

Basic concepts in the context of testing of hypotheses need to be explained

1) Null hypotheses and alternative hypotheses: In the context of

statistical analysis, we often talk null and alternative hypotheses. If we

are to compare method A with method B about its superiority and if we

proceed on the assumption that both methods are equally good, then

this assumption is termed as null hypotheses. As against this, we may

think that the method A is superior, it is alternative hypotheses.

Symbolically presented as:

Null hypotheses = H0 and Alternative hypotheses = Ha

Suppose we want to test the hypotheses that the population mean is

equal to the hypotheses mean (µ H0) = 100. Then we would say that the

null hypotheses are that the population mean is equal to the

hypothesized mean 100 and symbolical we can express as: H0: µ= µ

H0=100

If our sample results do not support this null hypothesis, we should

conclude that something else is true. What we conclude rejecting the

null hypotheses is known as alternative hypotheses. If we accept H0,

then we are rejecting Ha and if we reject H0, then we are accepting Ha.

For H0: µ= µ H0=100, we may consider three possible alternative

hypotheses as follows:



Alternative Hypotheses To be read as follows

Ha: µ≠µ H0 (The alternative hypotheses is that the population mean is not equal to 100 i.e., it may be more or less 100)

Ha: µ>µ H0 (The alternative hypotheses is that the population mean is greater than 100)

Ha: µ< µ H0 (The alternative hypotheses is that the population mean is less than 100)

The null hypotheses and the alternative hypotheses are chosen before

the sample is drawn (the researcher must avoid the error of deriving

hypotheses from the data he collects and testing the hypotheses from

the same data). In the choice of null hypotheses, the following

considerations are usually kept in view:

a. Alternative Hypotheses is usually the one which wishes to prove and

the null hypotheses are one that wishes to disprove. Thus a null

hypotheses represent the hypotheses we are trying to reject, the

alternative hypotheses represents all other possibilities.

b. If the rejection of a certain hypotheses when it is actually true

involves great risk, it is taken as null hypotheses because then the

probability of rejecting it when it is true is α (the level of significance)

which is chosen very small.

c. Null hypotheses should always be specific hypotheses i.e., it should

not state about or approximately a certain value.

Generally, in hypotheses testing we proceed on the basis of null

hypotheses, keeping the alternative hypotheses in view. Why so? The

answer is that on assumption that null hypotheses is true, one can

assign the probabilities to different possible sample results, but this

cannot be done if we proceed with alternative hypotheses. Hence the



use of null hypotheses (at times also known as statistical hypotheses) is

quite frequent.

2) The Level of Significance: This is a very important concept in the

context of hypotheses testing. It is always some percentage (usually

5%) which should be chosen with great care, thought and reason. In

case we take the significance level at 5%, then this implies that H0 will

be rejected when the sampling result (i.e., observed evidence) has a

less than 0.05 probability of occurring if H0 is true. In other words, the 5%

level of significance means that researcher is willing to take as much as

5% risk rejecting the null hypotheses when it (H0) happens to be true.

Thus the significance level is the maximum value of the probability of

rejecting H0 when it is true and is usually determined in advance before

testing the hypotheses.

3) Decision rule or test of hypotheses: Given a hypotheses H0 and an

alternative hypothesis H0 we make rule which is known as decision rule

according to which we accept H0 (i.e., reject Ha) or reject H0 (i.e., accept

Ha). For instance, if (H0 is that a certain lot is good (there are very few

defective items in it) against Ha that the lot is not good (there are many

defective items in it), that we must decide the number of items to be

tested and the criterion for accepting or rejecting the hypotheses. We

might test 10 items in the lot and plan our decision saying that if there

are none or only 1 defective item among the 10, we will accept H0

otherwise we will reject H0 (or accept Ha). This sort of basis is known as

decision rule.

4) Type I & Type II errors: In the context of testing of hypotheses, there

are basically two types of errors that we can make. We may reject H0

when H0 is true & we may accept H0 when it is not true. The former is

known as Type I & the later is known as Type II. In other words, Type I



error mean rejection of hypotheses which should have been accepted &

Type II error means accepting of hypotheses which should have been

rejected. Type I error is donated by α (alpha), also called as level of

significance of test; and Type II error is donated by β(beta).

Decision

Accept H0 Reject H0

H0 (true) Correct decision Type I error (α error)

Ho (false) Type II error (β error) Correct decision

The probability of Type I error is usually determined in advance and is

understood as the level of significance of testing the hypotheses. If type

I error is fixed at 5%, it means there are about chances in 100 that we

will reject H0 when H0 is true. We can control type I error just by fixing it

at a lower level. For instance, if we fix it at 1%, we will say that the

maximum probability of committing type I error would only be 0.01.

But with a fixed sample size, n when we try to reduce type I error, the

probability of committing type II error increases. Both types of errors can

not be reduced simultaneously. There is a trade-off in business

situations, decision-makers decide the appropriate level of type I error

by examining the costs of penalties attached to both types of errors. If

type I error involves time & trouble of reworking a batch of chemicals

that should have been accepted, where as type II error means taking a

chance that an entire group of users of this chemicals compound will be

poisoned, then in such a situation one should prefer a type I error to a

type II error means taking a chance that an entire group of users of this

chemicals compound will be poisoned, then in such a situation one

should prefer a type II error. As a result, one must set very high level for

type I error in one’s testing techniques of a given hypotheses. Hence, in



testing of hypotheses, one must make all possible effort to strike an

adequate balance between Type I & Type II error.

5) Two Tailed test & One Tailed test: In the context of hypotheses testing

these two terms are quite important and must be clearly understood. A

two-tailed test rejects the null hypotheses if, say, the sample mean is

significantly higher or lower than the hypnotized value of the mean of the

population. Such a test is inappropriate when we haveH0: µ= µ H0 and

Ha: µ≠µ H0 which may µ>µ H0 or µ<µ H0. If significance level is % and

the two-tailed test to be applied, the probability of the rejection area will

be 0.05 (equally split on both tails of curve as 0.025) and that of the

acceptance region will be 0.95. If we take µ = 100 and if our sample

mean deviates significantly from µ, in that case we shall accept the null

hypotheses. But there are situations when only one-tailed test is

considered appropriate. A one-tailed test would be used when we are to

test, say, whether the population mean in either lower than or higher

than some hypothesized value.

6.7 Procedure and Flow Diagram for Testing Hypotheses

To test a hypotheses means to tell (on the basis of the data researcher has

collected) whether or not the hypothesis seems to be valid. In hypothesis

testing, the main question is: whether or not to accept the null hypothesis?

Procedure for hypothesis testing refers to all those steps that we undertake

for making a choice between the two actions i.e., rejection and acceptance

of a null hypothesis. The various steps involved in hypothesis testing are

stated below:

i. Making a formal statement: The step consists in making a formal

statement of the null hypothesis (Ho) and also of the alternative

hypothesis (Ha). This means that hypothesis should be clearly stated,



considering the nature of the research problem. For instance, Mr. Mohan

of the Civil Engineering Department wants to test the load bearing

capacity of an old bridge which must be more than 10 tons, in that case

he can state his hypothesis as under:

Null hypotheses HO: µ =10 tons

Alternative hypotheses Ha: µ >10 tons

Take another example. The average score in an aptitude test

administered at the national level is 80. To evaluate a state’s education

system, the average score of 100 of the state’s students selected on the

random basis was 75. The state wants to know if there is a significance

difference between the local scores and the national scores. In such a

situation the hypothesis may be stated as under:

Null hypotheses HO: µ =80

Alternative hypotheses Ha: µ ≠ 80

The formulation of hypothesis is an important step which must be

accomplished with due care in accordance with the object and nature of

the problem under consideration. It also indicates whether we should

use a tailed test or a two tailed test. If Ha is of the type greater than, we

use alone tailed test, but when Ha is of the type “whether greater or

smaller” then we use a two-tailed test.

ii. Selecting a significant level: The hypotheses are tested on a pre-

determined level of significance and such the same should have

specified. Generally, in practice, either 5% level or 1% level is adopted

for the purpose. The factors that affect the level of significance are:

a) The magnitude of the difference between sample ;

b) The size of the sample;



c) The variability of measurements within samples;

d) Whether the hypotheses is directional or non – directional (A

directional hypotheses is one which predicts the direction of the

difference between, say, means). In brief, the level of significance

must be adequate in the context of the purpose and nature of

enquiry.

iii. Deciding the distribution to use: After deciding the level of

significance, the next step in hypothesis testing is to determine the

appropriate sampling distribution.. The rules for selecting the correct

distribution are similar to those which we have stated earlier in the

context of estimation.

iv. Selecting a random sample & computing an appropriate value:

Another step is to select a random sample(S) and compute an

appropriate value from the sample data concerning the test statistic

utilizing the relevant distribution. In other words, draw a sample to

furnish empirical data.

v. Calculation of the probability: one has then to calculate the probability

that the sample result would diverge as widely as it has from

expectations, if the null hypothesis were in fact true.

vi. Comparing the probability: Yet another step consists in comparing the

probability thus calculated with the specified value for α, the significance

level. If the calculated probability is equal to smaller than the value in

case of one tailed test (and α/2 in case of two-tailed test), then reject the

null hypothesis (i.e. accept the alternative hypothesis), but if the

probability is greater, then accept the null hypothesis. In case we reject

H0 we run a risk of (at most level of significance) committing an error of

type I, but if we accept H0, then we run some risk of committing error

type II.



Flow diagram for testing hypotheses

Specify the level of significance

Decide the correct sampling distribution

Sample a random sample and workout an appropriate value

Calculate the probability that sample result would diverge as widely as

it has form expectations, if H0 were true

Is this probability equal to or smaller than α value in case of one-tailed

test and α/2 in case of two-tailed test

Run the risk of Committing type I error committing type II error

6.8 Test of Hypotheses

The hypotheses testing determine the validity of the assumption (technically

described as null hypotheses) with a view to choose between the conflicting

hypotheses about the value of the population hypotheses and about the

value of the population parameter. Hypotheses testing helps to succeed on

the basis of a sample data, whether a hypotheses about the population is

State H0 as well as Ha

Reject H0 Accept H0



likely to be true or false. Statisticians have developed several tests of

hypotheses (also known as tests of significance) for the purpose of testing

of hypotheses which can be classified as:

a) Parametric tests or standard tests of hypotheses ;

b) Non Parametric test or distribution – free test of the hypotheses.

Parametric tests usually assume certain properties of the parent population

from which we draw samples. Assumption like observations come from a

normal population, sample size is large, assumptions about the population

parameters like mean, variants etc must hold good before parametric test

can be used. But there are situation when the researcher cannot or does not

want to make assumptions. In such situations we use statistical methods for

testing hypotheses which are called non- parametric tests because such test

do not depend on any assumption about the parameters of parent

population. Besides, most non-parametric test assumes only nominal or

original data, where as parametric test require measurement equivalent to at

least an interval scale. As a result non-parametric test needs more

observation than a parametric test to achieve the same size of Type I &

Type II error.

6. 9 Important parametric tests

The important parametric tests are:

1) z-test

2) t-test

3) x2-test

4) f-test

All these test are based on the assumption of normality i.e., the source of

data is considered to be normally distributed. In some cases the population

may not be normally distributed, yet the test will be applicable on account of



the fact that we mostly deal with samples and the sampling distributions

closely approach normal distributions.

z-test is based on the normal probability distribution and is used for judging

the significance of several statistical measures, particularly the mean. The

relevant test statistic is worked out and compared with its probable value (to

be read from the table showing area under normal curve) at a specified level

of significance for judging the significance of the measure concerned. This is

a most frequently used test in research studies. This test is used even when

binomial distribution or t-distribution is applicable on the presumption that

such a distribution tends to approximate normal distribution as ‘n’ becomes

larger. Z-test is generally used for comparing the mean of a sample to some

hypotheses mean for the population in case of large sample, or when

population variance is known as z-test is also used for judging the

significance of difference between means to of two independent samples in

case of large samples or when population variance is known z-test is

generally used for comparing the sample proportion to a theoretical value of

population proportion or for judging the difference in proportions of two

independent samples when happens to be large. Besides, this test may be

used for judging the significance of median, mode, co-efficient of correlation

and several other measures.

t-test is based on t-distribution and is considered an appropriate test for

judging the significance of sample mean or for judging significance of

difference between the two means of the two samples in case of samples

when population variance is not known (in which case we use variance of

the sample as an estimate the population variance). In case two samples

are related, we use paired t-test (difference test) for judging the significance

of them mean of difference between the two related samples. It can also be

sued for judging the significance of co-efficient of simple and partial

correlations. The relevant test statistic, t, is calculated from the sample data



and then compared with its probable value based on t-distribution at a

specified level of significance for concerning degrees of freedom for

accepting or rejecting the null hypotheses it may be noted that t-test applies

only in case of small sample when population variance is unknown.

x2-test is based on chi-square distribution and as a parametric test is used

for comparing a sample variance to a theoretical population variance is

unknown.

f-test is based on f-distribution and is used to compare the variance of the

two-independent samples. This test is also used in the context of variance

(ANOVA) for judging the significance of more than two sample means at

one and the same time. It is also used for judging the significance of multiple

correlation coefficients. Test statistic, f, is calculated and compared with its

probable value for accepting or rejecting the H0.



1. A hypothesis is an assumption about relations between variables.

2. A hypothesis gives a definite point to the investigation, and it guides the

direction on the study.

3. A hypothesis specifies the sources of data, which shall be studied, and

in what context they shall be studied.

4. A two-tailed test rejects the null hypotheses if, say, the sample mean is

significantly higher or lower than the hypnotized value of the mean of the

population.



6.10 Summary

A hypothesis is an assumption about relations between variables. It is a

tentative explanation of the research problem or a guess about the research

outcome. Before starting the research, the researcher has a rather general,

diffused, even confused notion of the problem. A hypothesis gives a definite

point to the investigation, and it guides the direction on the study. A

hypothesis specifies the sources of data, which shall be studied, and in what

context they shall be studied. In the context of hypotheses testing, these two

terms are quite important and must be clearly understood. A two-tailed test

rejects the null hypotheses if, say, the sample mean is significantly higher or

lower than the hypnotized value of the mean of the population.

Z-test is based on the normal probability distribution and is used for judging

the significance of several statistical measures, particularly the mean. The

relevant test statistic is worked out and compared with its probable value (to

be read from the table showing area under normal curve) at a specified level

of significance for judging the significance of the measure concerned. This is

a most frequently used test in research studies.

T-test is based on t-distribution and is considered an appropriate test for

judging the significance of sample mean or for judging significance of

difference between the two means of the two samples in case of samples

when population variance is not known (in which case we use variance of

the sample as an estimate of the population variance).

X2-test is based on chi-square distribution and as a parametric test is used

for comparing a sample variance to a theoretical population variance is

unknown.

F-test is based on f-distribution and is used to compare the variance of the

two-independent samples.



6.11 Test Questions

1. What is the meaning of Hypothesis?

2. What are the criteria for Hypotheses Construction?

3. What are the characteristics of Good Hypotheses?

4. What are the types of Hypotheses?

5. What is Type I & Type II Errors?

6. What is Two Tailed Test & One Tailed Test?

7. What are the procedure and Flow Diagram for Testing Hypotheses?

8. Which are the important Parametric Tests?


SAQs

1. True

2. True

3. True

4. True

TQs

1. Section 6.1

2. Section 6.2

3. Section 6.5

4. Section 6.6

5. Section 6.6

6. Section 6.6

7. Section 6.7

8. Section 6.9



Unit 7 Techniques of Quantitative Data Analysis

Structure

7.1 Introduction: Cross tabulation

Objectives

7.1.1 Setting up of cross tabulation

7.1.2 Choosing for variable for cross tabulation

7.1.3 Two-way cross tabulation

7.2 Multiple regressions

7.3 Perceptual mapping

7.4 Conjoint analysis


7.5 Summary

7.6 Test Questions


7.1 Introduction: Cross Tabulation

It is true, that if all sets of marketing data are viewed only in terms of

frequency distribution and measures of central tendency, only a fraction of

the possible significant findings will be revealed. Cross tabulation, is the

most frequently used analytical technique in marketing research, which

involves examination of one variable crossed by one or more other

variables.

Objectives


discuss the setting up of cross tabulation

understand the choosing for variable for cross tabulation

explain two-way cross tabulation, multiple regressions, perceptual

mapping and conjoint analysis.



7.1.1 Setting up Cross Tabulation

We usually think of a cross-tabulation table as looking at two or possibly

three variables simultaneously. This is most often the case when a firm

conducts the research project itself, including processing the data and using

some software program such as SPSS to run each cross-tabbed table. If the

researcher has contracted with an independent marketing research firm to

do the survey, the firm will likely b3e doing the data processing, including

setting up the cross-tabs per the researcher’s instructions. If the firm is

responsible for the data collection and processing, then it will probably

include as part of the contracted price what will be referred to as an

eighteen points or twenty point “banner”. This means the firm will provide a

set of computer printout pages that are eighteen or twenty columns wide for

every question in the survey. Each question in the survey would appear

down the side of a page, called the stub.

The appeal of banners is obvious – they provide a simple way to look at

survey questions crossed by the most important variables the researcher is

interested in exploring.

An eighteen-point banner means any combination of column headings that

total eighteen can be used. It is usual practice to devote the left-most

column to grand total which in effect gives the frequency distribution for

each question. The remaining seventeen columns may be divided in any

combination of columns desired.

It is customary to have the banner headings consist of independent

variables that the research purpose, questions, and hypotheses suggest are

most likely to be influencing the dependent measures of interest (such as

attitudes, consumption rate, likelihood of purchase, membership or non-

membership, etc.)



Another common practice in setting up a banner heading or single cross-

tabbed table is to consistently move from low to high, moving from left to

right in the banner; and from high to low, moving down the stub.

7.1.2 Choosing Variables for Cross- tabulations

It is tempting to ask the data processors to “cross everything by everything”

so that a cross-tabbed table for every combination of two questions in the

survey is available. That way, one or more tables are available to look at, to

help the researcher determine the relationship between the variables of

interest.

A cross-tabbed table is merely inserting data into a dummy table, so the

plan of analysis primarily consists of determining which variables should be

simultaneously examined for possible relationships to get answers to

questions, test hypothesis, or fill in dummy tables. Although the researcher

will think of relationships, he or she wishes to examine during the analysis

and not before, there is also a point at which the researcher must get on

with the implications and alternative decision suggestions, which is the

purpose of the research and its analysis. Ts are easy to become distracted

by the almost infinite number of possible relationships so that one avoids

drawing the conclusions necessary to move through the process.

7.1.3 Two-Way Cross Tabulation

I will pay extra Re. 1 for my favourite brand

Substitute Consumption Rate

Low Medium High

# % # % # %

Strongly agree or agree 113 34 239 54 308 67

Neither agree or disagree 107 33 108 24 101 22

Strongly disagree or disagree 108 33 98 22 54 11

Total 328 100 445 100 463 100



7.2 Multiple Regressions

The error term includes the effects on the dependent variable of variables

other than the independent variable. It may be desirable to include explicitly

some of these variables in the model. As predictions, their inclusion will

improve the model’s ability to predict and will decrease the unexplained

variation; in terms of understanding, they will introduce the effect of other

variables and therefore elaborate and clarify the relationships.

7.3 Perceptual Mapping

Multidimensional scaling addresses the problem of identifying the

dimensions upon which customers perceive or evaluate phenomena

(products, brands, or companies) in a perceptual map. Multidimensional

scaling techniques result in perceptual maps that describe the positioning of

companies or brands that are compared relative to the position they occupy

in the minds of customers according to key attributes. These maps allow the

decision maker to examine underlying criteria or dimensions that people

utilize to form perceptions about similarities between and preferences

among various products, services, or companies. The question of

positioning by multidimensional scaling ( MDS) and perceptual mapping,

deals with how a firm compares to its competitors on key attributes, what the

ideal set of attributes sought by the customers might be, or what positioning

or repositioning strategy should be developed for a specific sector of the

marketplace. A medium sized bank might learn for example, that the most

effective way to compete for commercial loan business with larger, more

prestigious banks with a wider range of services, is by focusing on the

genuine concern communicated by loan supervisors as well as the expertise

they develop in their knowledge of their client’s sub-sector of industry.



7.4 Conjoint Analysis

Conjoint analysis is also known as trade-off analysis, is used for evaluating

judgmental data where choices between attributes are involved. It is more

commonly used for measuring the trade-off values of purchases selection

factor attributes. Specifically, conjoint analysis is concerned with the joint

effect of two or more independent variables on the ordering of a dependent

variable. In essence, this method allows a determination of how consumers

value various levels of purchase criteria and the extent to which they might

tend to forego a high level of one attribute in order to obtain a high level of

another. Fro example, the trade-off values of holding power, scent, non-

stickiness, brand name, and price for hair spray might be cause for a

conjoint evaluation.



1. A cross-tabbed table is merely inserting data into a dummy table, so the

plan of analysis primarily consists of determining which variables should

be simultaneously examined for possible relationships to get answers to

questions, test hypothesis, or fill in dummy tables.

2. Multidimensional scaling techniques result in perceptual maps that

describe the positioning of companies or brands that are compared

relative to the position they occupy in the minds of customers according

to key attributes.

3. Perceptual maps allow the decision maker to examine underlying criteria

or dimensions that people utilize to form perceptions about similarities

between and preferences among various products, services, or

companies.



4. Conjoint analysis is also known as trade-off analysis, is used for

evaluating judgmental data where choices between attributes are

involved

7.5 Summary

Cross tabulation, is the most frequently used analytical technique in

marketing research, which involves examination of one variable crossed by

one or more other variables. A cross-tabbed table is merely inserting data

into a dummy table, so the plan of analysis primarily consists of determining

which variables should be simultaneously examined for possible

relationships to get answers to questions, test hypothesis, or fill in dummy

tables. Multidimensional scaling techniques result in perceptual maps that

describe the positioning of companies or brands that are compared relative

to the position they occupy in the minds of customers according to key

attributes. These maps allow the decision maker to examine underlying

criteria or dimensions that people utilize to form perceptions about

similarities between and preferences among various products, services, or

companies. Conjoint analysis is also known as trade-off analysis, is used for

evaluating judgmental data where choices between attributes are involved.

It is more commonly used for measuring the trade-off values of purchases

selection factor attributes


1. What is cross tabulation?

2. What are multiple regressions?

3. What are perceptual maps?

4. Explain the use of conjoint analysis.




SAQs

1. True

2. True

3. True

4. True

TQs

1. Section 7.1

2. Section 7.2

3. Section 7.3

4. Section 7.4



Unit 8 Writing a Research Report

Structure

8.1 Introduction: Meaning of Research Report

Objectives

8.2 Purpose of Research Report

8.3 Characteristics of Research Report

8.4 Functions of Research Report

8.5 Types of Research Report

8.5.1 Technical Reports

8.5.2 Popular Reports

8.5.3 Interim Reports

8.5.4 Summary Reports

8.5.5 Research Abstract

8.5.6 Research Article

8.6 Preparing the Research Report and Approaches to Research Report

8.6.1 Communicate To Specific Audience

8.6.2 Structure the Presentation

8.6.3 Create Audience Interest

8.6.4 Be Specific and Visual

8.6.5 Address Validity and Reliability Issues

8.7 Written Presentations

8.8 Organization of a Research Report

8.9 Reading Research Reports

8.9.1 Don’t Read

8.9.2 Use Visual Aids

8.9.3 Make Sure the Start Is Positive

8.9.4 Avoid Distracting the Audience

8.9.5 Involve the Audience




8.10 Summary


8.12 Answers To SAQs And TQs

8.1 Introduction: Meaning of Research Report

Research report is a means for communicating research experience to

others. A research report is a formal statement of the research process and

it results. It narrates the problem studied, methods used for studying it and

the findings and conclusions of the study.

Objectives:


explain the purpose, characteristics and functions of research report

discuss the types of research report

explain the preparation of the research report and approaches to

research report

discuss the written presentations

understand the organization of a research report and reading research

reports

8.2 Purpose of the Research Report

The purpose of the research report is to communicate to interested persons

the methodology and the results of the study in such a manner so as to

enable them to understand the research process and to determine its

validity. The aim is not to convince but to convey what was done, why and

what was its outcome.



8.3 Characteristics of Research Report

Research report is a narrative and authoritative document on the outcome of

a research effort. It represents highly specific information for a clearly

designated audience. It is simple, readable and accurate form of

communication.

8.4 Functions of Research Report

It serves as a means for presenting the problem studied, methods and

techniques used for collecting and analyzing data, findings and conclusions

and recommendations. It serves as a basic reference material for future use.

It is a means for judging the quality of research project.

It is a means for evaluating researcher’s competency.

It provides a systematic knowledge on problems and issues analyzed.

8.5 Types of Research Report

Research reports can be classified as:

Technical reports

Popular reports

Summary reports

Research abstract

Research article

These differ in terms of the degree of formality, physical form, scope, style

and size.

8.5.1 Technical Reports

In a technical, comprehensive full report of the research process and its

outcome. It covers all the aspects of the research process. A description of

the problem studied, the objectives of the study, method and techniques

used, a detailed account of sampling filed and other research procedures,



sources of data, tools for data collection, methods of data processing and

analysis, detailed findings and conclusions and suggestion.

8.5.2 Popular Reports

In popular report the reader is less interested in the methodological details,

but more interested in the findings of the study. Complicated statistics are

avoided and pictorial devices are used. After a brief introduction to the

problem and the objectives of the study, an abstract of the findings of the

study, conclusion and recommendations are presented. More headline,

underlining pictures and graphs may be used. Sentences and paragraphs

should be short.

8.5.3 Interim Report

When there is a time lag between data collection and presentation of the

result, the study may lose significance and usefulness. An interim report in

such case can narrate what has been done so far and what was its

outcome. It presents a summary of the findings of that part of analysis which

has been completed.

8.5.4 Summary Reports

Summary report is meant for lay audience i.e., the general pubic. It is written

in non-technical, simple language with pictorial charts, objectives, findings

and its implications. It is a short report of two to three pages.

8.5.5 Research Abstract

Research abstract is a short summary of technical report. It is prepared by a

doctoral student on the eve of submitting his thesis. It contains a brief

presentation of the statement of the problem, the objectives of the study,

methods and techniques used and an overview of the report. A brief

summary of the results of the study may also be used.



8.5.6 Research Article

Research article is designed for publication in a professional journal. A

research article must be clearly written in concise unambiguous language. It

must be logically organised. Progression from a statement of a problem and

purpose of the study, through analysis of evidence to the conclusions and

implications are given in the report.

8.6 Preparing the Research Report and Approaches to Research

Report

Along with the related skill of working with and motivating people, the ability

to communicate effectively is undoubtedly the most important attribute a

manager can have. Effective communication between research users and

research professional is extremely important to the research process. The

formal presentation usually plays a key role in the communication effort.

Generally presentations are made twice during the research process. First,

there is the research proposal presentation. Second there is the

presentation of the research results.

Guidelines for successful presentations

In general, a presenter should –

Communicate to a specific audience.

Structure the presentation.

Create audience interest

Be specific and visual

Address validity and reliability issues

8.6.1 Communicate to a Specific Audience

The first step is to know the audience, its background, and its objectives.

Most effective presentations seem live conversations or memos to a

particular person as opposed to an amorphous group. Audience



identification affects presentation decisions such as selecting the material to

be included and the level of presentation. Excessive detail or material

presented at too low a level can be boring. The audience can become

irritated when material perceived as relevant is excluded or the material is

presented at too high level. In an oral presentation, the presenter can ask

audience whether they already know some of the material.

Frequently, a presentation must be addressed to two or more different

audiences. There are ways to deal with such a problem. In a written

presentation, an executive summary at the outset can provide an overview

of the conclusions for the benefit of those in the audience who are not

interested in details. The presentation must respect the audience’s time

constraints. An appendix can be used to reach some people selectively,

without distracting the others. Sometimes, introduction to a chapter or a

section can convey the nature of the contents, which certain audiences may

bypass. In an oral presentation, the presence of multiple audiences should

be recognized

8.6.2 Structure the Presentation

Each piece of presentation should fit into the whole, just as individual pieces

fit into a jigsaw puzzle. The audience should not be muttering. The solution

to this is to provide a well-defined structure. The structure should include an

introduction, a body, and a summary. Further, each of the major sections

should be structured similarly. The precept is to tell the audience what you

are going to say, say it and then tell them what you said. Sometimes you

want to withhold the conclusion to create interest.

Introduction should play several roles. First, it should provide audience

interest. The second function is to identify the presentation’s central idea or

objective. Third, it should provide a road map to the rest of the presentation

so that the audience can picture is organisation and flow.



It is better to divide the body of the presentation into two and five parts. The

audience will be able to absorb only so much information. If that information

can be aggregated into chunks, it will be easier to assimilate. Sometimes

the points to be made cannot be combined easily or naturally. In that case, it

is sometimes necessary to use a longer list.

One way to structure the presentation is by the research questions. Another

method that is often useful when presenting the research proposal is to

base it on the research process. The most useful presentations will include

a statement of implications and recommendations relevant to the research

purpose. However, when researcher lacks information about the total

situation because of the research study addressing only a limited aspect of

it, the ability to generate recommendations may be limited.

The purpose of the presentation summary is to identify and underline the

important points of the presentations and to provide some repetition of their

content. The summary should support the presentation communication

objectives by helping the audience to retain the key parts of the content. The

audience should feel that there is a natural flow from one section to another

8.6.3 Create Audience Interest

The audience should be motivated to read or listen to the presentation’s

major parts and the individual elements of each section the audience should

know as to why the presentation is relevant to them and why each section

was included. A section that cannot hold interest should be excluded or

relegated to appendix.

The research purpose and objectives are good vehicles to provide

motivation. The research purpose should specify decisions to be made and

should relate to the research questions. A presentation that focuses on

those research questions and their associated hypothesis will naturally be

tied to relevant decisions and hold audience interest. In contrast, a



presentation that attempts to report on all the questions that were included

in the survey and in the cross-tabulations often will be long, uninteresting

and of little value.

As the analysis proceeds and presentation is being prepared, the

researcher should be on the lookout for results that are exceptionally

persuasive, relevant, interesting, and unusual. Sometimes the deviant

respondent with strange answers can provide the most insight in his or her

responses are pursued and not discarded.

8.6.4 Be Specific and Visual

Avoid taking or writing in the abstract. If different members of the audience

have different or vague understandings of important concepts, there is a

potential problem. Terms that are ambiguous or not well known should be

defined and illustrated or else omitted.

The most interesting presentations usually use specific stories, anecdotes,

studies, or incidents to make points. They will be much more interesting and

graphic that generalization, however accurate and scientific.

8.6.5 Address Validity and Reliability Issues

The presentation should help the audience avoid misinterpreting the results.

The wording of the questions, the order in which they are asked, and the

sampling design are among the design dimensions that can lead to biased

results and misinterpretations. The presentation should not include an

exhaustive description of all the design considerations. Nobody is interested

in a textbook discussion of the advantages of telephone over mail surveys,

or how you located homes in an area sampling design.

The presentation should include some indication of the reliability of the

results. At a minimum, it always should be clear what sample size was

involved. The key results should be supported by more precise information

in the form of interval estimates or a hypothesis test. The hypothesis test



basically indicates, given the sample size, what probability exists that the

results were merely an accident of sampling. If the probability of the latter is

not low, then the results probably would not be repeated. Do not imply more

precision than is warranted.

8.7 Written presentation

The general guidelines discussed so far are applicable to both written and

oral presentations. However, it is important to generate a research report

that will be interesting to read. Most researchers are not trained in effective

report writing. In their enthusiasm for research, they often overlook the need

for a good writing style. In writing a report, long sentences should be

reconsidered and the critical main points should stand out.

Here are some hints for effective report writing.

Use main heading and subheadings to communicate the content of the

material discussed.

Use the present tense as much as possible to communicate information.

Whether the presentation is written or oral, use active voice construction

to make it lively and interesting, passive voice is wordy and dull.

Use computer-generated tables and graphs for effective presentations.

Use informative headings.

Use variations to communicate respondent’s comments.

Use double-sided presentation as possible. For example, tables or

graphs could be presented on the left side of an open report and their

descriptions on the right side.



8.8 Organisation of the Research Report

The outline of a research report is given below:

I. Prefatory Items

Title page

Declaration

Certificates

Preface/ acknowledgements

Table of content

List of tables

List of graphs/ figures/ charts

Abstract or synopsis

II. Body of the Report

Introduction

Theoretical background of the topic

Statement of the problem

Review of literature

The scope of the study

The objectives o the study

Hypothesis to be tested

Definition of the concepts

Models if any

Design of the study

Methodology

Method of data collection

Sources of data

Sampling plan

Data collection instruments

Field work



Data processing and analysis plan

Overview of the report

Limitation of the study

Results: findings and discussions

Summary, conclusions and recommendations

III. Reference Material

Bibliography

Appendix

Copies of data collection instruments

Technical details on sampling plan

Complex tables

Glossary of new terms used.

8.9 Reading Research Reports

Preparing Oral Presentation

The ability to communicate orally is extremely important to effective

management in general and to the marketing research function in particular.

Five suggestions are discussed in this regard:

Don’t read

Use visual aids

Make sure the start is positive

Avoid distracting the audience

Involve the audience

8.9.1 Don’t Read

The biggest problem with reading is that it is boring for the reader and the

audience. Very few can make a script sound interesting and those few do

even better without a script. It is necessary to develop the ability to

communicate orally in front of a group without a script, to prepare for those



occasions when there is no time to prepare a script or when the presenter

must adapt to new developments in the middle of a presentation. If you rely

too heavily on a script and use it in what may be limited opportunities to give

presentations, you will not develop this important capability.

8.9.2 Use Visual Aids

Visual aids perform several functions. First, they give impact to the

information and focus attention on important points. Second, ideas that are

extremely difficult to express in words often can be communicated easily

with visual aids. Finally, they help to give the presentation variety. Visual

aids include computer-assisted presentations, transparencies, charts, hand-

outs, slides, video-tapes, films, samples, demonstrations, and role-playing.

Transparencies, charts, slides, and hand-outs are probably the most widely

used.

8.9.3 Make Sure the Start is Positive

The start should be positive in tone, confident, and involving. Sometimes the

silence can be used effectively to get attention. It is useful to stimulate and

involve the audience immediately, perhaps by a provocative question or

statement. Absolutely never apologize at the outset, even in jest.

8.9.4 Avoid Distracting the Audience

The presenter needs to be aware that the audience is easily distracted. The

following do’s and don’ts address some common causes of distraction.

Take everything out of your pockets and make sure there is nothing on

the lectern other than your notes. Remove pens, pointers, keys, clips –

everything. If often happens, without your being aware of it, that you will

pick up objects and manipulates them until the audience is severely

distracted.

Try to avoid the extremes of either obvious pacing or hiding behind a

lectern. It can be distracting to see a speaker clutch a lectern for support



as to see someone pace back and forth. The speaker’s movement

should be purposeful and natural, such as stepping aside to point to a

chart, standing or sitting beside the lectern, or moving closer to the

audience for a short portion of the presentation.

Maintain good eye contact. This allows audience feedback, stimulates

trust and confidence in what you are saying, and involves the audience.

A speaker who avoids eye contact by looking up or down or somewhere

else risks distracting the audience.

Be concerned about the sound of your voice. Listen to a tape of your

presentation if possible. A presentation can be distracting if it is too soft,

loud, fast, slow or monotonous. Be sure to use pauses to break up the

presentation and to allow the audience to digest the material.

8.9.5 Involve the Audience

An involved audience will be more interested. An effective technique is to

intersperse questions throughout. If time does not permit a discussion, a

pause at least gives the audience a chance to reflect.

The question – and-answer part of the presentation is particularly important.

This often concludes the talk, but it can be permitted to occur during the

presentation. Pause and make sure the question is understood. Then if

possible give a short positive or negative response and as compact an

explanation as possible. A good technique is to write the question down so

you do not forget it. Anticipate questions before hand and rehearse the

answers. Sometimes it is even effective to leave things out of the

presentation if they can be covered more effectively during the question-

and-answer period.




State whether following statements are true or false:

1. Research report is a means for communicating research experience to

others.

2. The purpose of the research report is to communicate to interested

persons the methodology and the results of the study in such a manner

as to enable them to understand the research process and to determine

its validity.

3. Research report is a narrative and authoritative document on the

outcome of a research effort. It represents highly specific information for

a clearly designated audience.

8.10 Summary

Research report is a means for communicating research experience to

others. The purpose of the research report is to communicate to interested

persons the methodology and the results of the study in such a manner as

to enable them to understand the research process and to determine its

validity. Research report is a narrative and authoritative document on the

outcome of a research effort. It represents highly specific information for a

clearly designated audience. It serves as a means for presenting the

problem studied, methods and techniques used for collecting and analyzing

data, findings and conclusions and recommendations. It serves as a basic

reference material for future use. It is a means for judging the quality of

research project. It is a means for evaluating researcher’s competency. It

provides a systematic knowledge on problems and issues analyzed. In a

technical report a comprehensive full report of the research process and its

outcome. It covers all the aspects of the research process. In popular report,

the reader is less interested in the methodological details, but more

interested in the findings of the study. An interim report in such case can



narrate what has been done so far and what was its outcome. It presents a

summary of the findings of that part of analysis which has been completed.

Summary report is meant for lay audience i.e., the general pubic. It is written

in non-technical, simple language with pictorial charts it just contains

objectives, findings and its implications. It is a short report of two to three

pages. Research abstract is a short summary of technical report. It is

prepared by a doctoral student on the eve of submitting his thesis. Research

article is designed for publication in a professional journal. A research article

must be clearly written in concise unambiguous language.


1. What is a research report?

2. What are the contents of research report?

3. What are the types of research reports?


SAQs

1. True

2. True

3. True

TQs

1. Section 8.1

2. Section 8.8

3. Section 8.5



Unit 9 Ethical Issues in Marketing Research

Structure

9.1 Introduction: Nature of Ethical Issues in Marketing Research

Objectives

9.2 Overt and Covert Purposes

9.3 Dishonesty in Dealing with Suppliers

9.4 Misuse of Research Information

9.5 The Supplier’s Ethics

9.6 Abuse of Respondents

9.7 Respondent’s Ethics and Rights

9.8 Corporate Espionage


9.9 Summary


9.11 Answers to SAQ’s and TQ’s

9.1 Introduction: Nature of Ethical Issues in Marketing Research


of the individual or group. Researchers have responsibilities to their

profession. Clients and respondents must adhere to high ethical standards

to ensure that both the function and the information are not brought into

disrepute. The Marketing Research Association, Inc. (Chicago, Illinois) has

instituted a code of ethics that serves as a guideline for marketing ethical

decisions. The Council of American Research Organisation (CASRO) has

also established a detailed code of marketing research ethics to which its

members adhere.



Normally, three parties are involved in a marketing project:

1. The client who sponsors the project

2. The supplier who designs and executes the research

3. The respondent who provides the information.

Below given is the Code of Professional Ethics and Practices instituted by

the Marketing Research Association.

1. To maintain high standards of competence and integrity in marketing

and survey research.

2. To maintain the highest level of business and professional conduct

and to comply with the Federal State and local laws, regulations and

ordinances applicable to business practices and those of the company.

3. To exercise all reasonable care and to observe the best standards of

objectivity and accuracy in the development, collection, processing

and reporting of marketing and survey research information.

4. To protect the anonymity of respondents and hold all information

concerning an individual respondent privileged, such that this

information is used only within the context of the particular study.

5. To thoroughly instruct and supervise all persons for whose work I am

responsible in accordance with study specifications and general

research techniques.,

6. To observe the rights of ownership of all materials received from and /

or for clients and to keep in confidence all research techniques, data

and other information considered confidential by the owners.

7. To make available to clients such details on the research methods and

techniques of an assignment as may be reasonable required for

proper interpretation of the data, providing this reporting does not

violate the confidence of respondents or clients.



8. To promote the trust of the public for marketing and survey research

activities and to avoid any procedures which misrepresents the

activities of the respondents, the rewards of cooperation or the uses of

data

9. To refrain from referring to membership in this organisation as proof of

competence, since the organisation does not certify any person or

organisation.

10. To encourage the observance of principles of this code among all

people engaged in marketing and survey research.

Source: Marketing Research Association, Inc., Chicago, Illinois

Objectives:


explain the Overt and Covert Purposes

discuss dishonesty in dealing with suppliers

understand the supplier’s ethics

explain the abuse of respondents, respondent’s ethics and rights

explain the corporate espionage

9.2 Overt and Covert Purposes

Most researchers have encountered situations where the main purpose of

their efforts was to serve someone’s organisational goals. Thus research

can be used to postpone an awkward decision or to lend respectability to a

decision that has been made already. A related purpose is to avoid

responsibility. When there are competing factions, the manager who must

make a difficult choice looks to research to guide the decision. This has the

further advantage that if the decision is later proven wrong, the manager can

find someone else to blame.



Sometimes a covert purpose will open the way to ethical abuses that

present difficult dilemmas to researchers. The most serious abuses are

created when there is subtle (or not so subtle) pressure to design research

to support a particular decision or enhance a legal position.

9. 3 Dishonesty in Dealing with Suppliers

A few client companies have been known to indulge in “picking the brains”

of research suppliers by asking them to submit elaborate bids that detail the

research design and methodology the supplier would adopt in conducting

the research. Later, the client-firm uses these ideas and conducts the

research itself. Another technique that client firms sometimes use is to make

a false promise of future contracts in an effort to obtain low price for the

current project

9.4 Misuse of Research Information

The client firm should not misuse information gathered through marketing

research projects. For example, data base about consumer preference are

used in target marketing to identify the people who are most likely to buy or

use a product.

The common form of misuse comes from comparative advertisement or

product performance claims that stem from data that are statically not

significant, though puffery in advertisements is a normal practice; gross

misuse of research data is ethically unacceptable.

Too often researchers find themselves dealing with demands by sales and

other professional for access to result and the names and telephone

numbers of respondents. The intention of course is to use the research

study for the entirely different – and usually unethical – purpose of

generating sales leads. The only time this is acceptable is when the

interviewer asks specifically whether the respondent will accept a follow up



sales call or would like more information, and acts precisely on respondents

answer, sadly there are a number of situation where the research study is

simply a disguise or a selling pitch. Many people have received phone calls

ostensibly to ask some research questions that lead only to a canned sales

message for life insurance, an encyclopaedia for a mutual fund. This is not

only unethical behaviour because it has no merits on its own; it is also a

serious abuse of respondent rights. Not surprisingly, respondents are more

suspicious after a few of these encounters and may refuse to participate in

any research study.

9.5 Supplier’s Ethics

The more common ethical issues for the research supplier are:-

Violating client confidentiality: disclosing any information about the client

that the supplier has gathered from the research project amounts to a

violation of client confidentiality.

Improper execution of research: suppliers are required to conduct

marketing research project in an objective manner, free from personal

biases and motives. Improper execution also includes using biased

samplings, ignoring relevant data or misusing statistics all of which lead to

erroneous and misleading results

9.6 Abuse of Respondents

Abuse of respondents is perhaps the most frequent and controversial

problem that crops up regarding ethics in conducting research. Any form of

violation of a respondents rights amounts to unethical treatment or abuse of

the respondent.



9.7 Respondent’s Ethics and Rights

A respondent who of his or her own free will agrees to participate in a

marketing research project has the ethical obligation to provide the supplier,

and hence the client with honest and truthful answers. The respondent can

abstain from answering a sensitive question, but falsifying the answers is

ethically improper.

Any respondent who participates in a research project has the following

rights:-

The right to privacy.

The right to safety

The right to know the true purpose of the research

The right to the research results

The right to decide which questions to answer.

9.8 Corporate Espionage

Over the past few years, there has been increasing concern for protecting

the rights of subjects used in research projects. This is a potential problem

in all studies involving human subjects. The researcher should give careful

consideration to the potential negative effects on those participating in an

experiment to avoid violating the subjects’ rights and deflect potential

lawsuits.



1. Ethics refer to moral principles or values that generally govern the

conduct of the individual or group. Researchers have responsibilities to

their profession.



2. Clients and respondents must adhere to high ethical standards to

ensure that both the function and the information are not brought into

disrepute.

3. Most researchers have encountered situations where the main purpose

of their efforts was to serve someone’s organisational goals. The client

firm should not misuse information gathered through marketing research

projects

4. Disclosing any information about the client that the supplier has

gathered from the research project amounts to a violation of client

confidentiality

9.9 Summary


of the individual or group. Researchers have responsibilities to their

profession. Clients and respondents and must adhere to high ethical

standards to ensure that both the function and the information are not

brought into disrepute. Most researchers have encountered situations where

the main purpose of their efforts was to serve someone’s organisation goals.

Thus research can be used to postpone an awkward decision or to lend

respectability to a decision that has been made already. A related purpose

is to avoid responsibility. The client firm should not misuse information

gathered through marketing research projects. Disclosing any information

about the client that the supplier has gathered from the research project,

amounts to a violation of client confidentiality. Suppliers are required to

conduct marketing research project in an objective manner, free from

personal biases and motives. Any form of violation of a respondents rights

amounts to unethical treatment or abuse of the respondent. A respondent

who of his or her own fee will agrees to participate in a marketing research



project has the ethical obligation to provide the supplier, and hence the

client with honest and truthful answers


1. What are some ethical problems that marketing researchers face in

designing and conducting field studies?

2. What is sponsor’s ethics?

3. How research information is misused?

4. What is dishonesty in dealing with suppliers?

5. What is supplier’s ethics?

6. What is abuse of respondents?

7. What are the rights of respondents in marketing research?


SAQs

1. True

2. True

3. True

4. True

TQs

1. Section 9.1

2. Section 9.1.

3. Section 9.4

4. Section 9.3

5. Section 9.5

6. Section 9.6

7. Section 9.7

MK 0004 Marketing Research Contents

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