RESEARCHINTRODUCIONResearch is a part of any systematic knowledge. It has occupied the realm of human understanding in some form or the other from times immemorial. The thirst for new areas of knowledge and the human urge for solutions to the problems have developed a faculty for search and research and re-research in him/her. Research has now become an integral part of all the areas of human activity.Broadly defined the purpose of research is to answer questions and acquire new knowledge. This process of asking and answering question which in turn assists us in acquiring new knowledge (or in simple terms the process of research) is often viewed as a pillar of scientific progress in any field. Research is a primary tool used in virtually all areas of science to expand the frontiers of knowledge. By conducting research, researchers attempt to reduce the complexity of problems, discover the relationship between seemingly unrelated events and ultimately improve the way we live.

The research can be used for the purpose of description, explanation, and prediction all of which make valuable and important contributions to the expansion of what we know and how we live our lives.

It is an endeavor to discover answers to problems (of intellectual and practical nature) through the application of scientific methods. Research, thus, is essentially a systematic inquiry seeking facts (truths) through objective, verifiable methods in order to discover the relationship among them and to deduce from them broad conclusions. It is thus a method of critical thinking. It is imperative that any type of organization in the globalised environment needs systematic supply of information coupled with tools of analysis for making sound decisions which involve minimum risk.

1.9 SCOPE OF SOCIAL RESEARCH

Social work profession has a scientific base which consists of a special body of knowledge; tested knowledge, hypothetical knowledge and assumptive knowledge. Assumptive knowledge requires transformation into hypothetical knowledge, which in turn needs transformation into tested knowledge. Social work research has significant role in transforming the hypothetical and assumptive knowledge to tested knowledge.

Not all concepts or theories that are used by professional social workers have been tested and validated. Concerted efforts through social work research are very much required to conceptually articulate and validate the concepts and theories, which will in turn strengthen the scientific base of professional social work. Identification of social work needs and resources, evaluation of programmes and services of social work agencies are some of the areas in which social work researches are undertaken. Social work research may be conducted to know the problems faced

by professional social workers in social work agencies and communities in its concern with social work functions. Thus, social work research embraces the entire gamut of social work profession; concepts, theories, methods, programmes, services and the problems faced by social workers in their practice.

The areas of social work research may be broadly categorized as follows:

1) Studies to establish, identify and measure the need for service.

2) To measure the services offered as they relate to needs.

3) To test, gauge and evaluate results of social work intervention.

4) To list the efficacy of specific techniques of offering services.

5) Studies in methodology of social work.

Social work is a diverse profession, possible broad research areas could be:

i) Community Development and Scope

ii) Community Health (Including Mental Health)

iii) Child Welfare

iv) Women Welfare

v) Youth Welfare

vi) Aged Welfare

vii) Welfare of SC & ST Groups

viii) Poverty Alleviation

ix) Physical and Mental Disabilities

X) Juvenile Delinquency

xi) Crime and Correction etc.

xii) Management of Social Welfare Department and Organization

xiii) Disaster Management

xiv) Industrial Social Work

xv) Issues concerning Advocacy and Networking

The list is not exhaustive; it's only an exemplary list which enlists broad areas which is very frequently studied by social workers. Again, within one or more problem areas research might focus on individuals, families, groups, community organizations or broad social systems.

It might deal with characteristics of a larger population, and the services available to them.

1.10 GOALS AND LIMITATIONS OF SOCIAL RESEARCH

Social research offers an opportunity for all social workers to make differences in their practice. There is no doubt about the fact that social worker will be more effective practitioner guided by the findings of social work research. Thus, social research seeks to accomplish the same- humanistic goals, as does a social work method. Social work research deals with those methods and issues, which are useful in evaluating social work programmes and practices. It explains the methodology of social research and illustrates its applications in social work settings.

A substantive part of social work practice is concerned with the micro-level practice, such as working with individuals, groups, or a community. Social work research has to take into consideration the limitations of micro level design of study and techniques.

Social research is basically a practice based research in which mostly draws its inferences through inductive reasoning. That is, inferring something about a whole group or a class of objects from the facts or knowledge of one or few members of that group/class. Thus, in practice based research inductive reasoning carries us from observation to theory through intervention/ assessment. Practitioners, for example, may observe that delinquents tend to come from family with low socio-economic status. Based on the assumption that the parent-child bond is weaker in low socio-economic families and that such parents, therefore, have less control over their children, the practitioners may inductively conclude that a weak parent-child bond leads to delinquency.

1.11 SIGNIFICANCE OF RESEARCH IN MANAGEMENT

Management Research can be broadly defined "as a form of systematic inquiry that contributes to knowledge in the field of management". It is also about searching systematically for solutions to management problems

Research is the process of systematic and in depth study or search for a solution to a problem or an answer to a question backed by collection, compilation, presentation, analysis and interpretation of relevant details, data and information. It is also a systematic endeavor to discover valuable facts or relationships. Research may involve careful enquiry or experimentation and result in discovery or invention. There cannot be any research which does not increase knowledge which may be useful to different people in different ways.

Let us see the need for research to business organizations and their managers and how it is useful to them.i) Industrial and economic activities have assumed huge dimensions. The size of modern business organizations indicates that managerial and administrative decisions can affect vast quantities of capital and a large number of people. Trial and error methods are not appreciated, as mistakes can be tremendously costly. Decisions must be quick but accurate and timely and should be objective i.e. based on facts and realities. In this back drop business decisions now days are mostly influenced by research and research findings. Thus, research helps in quick and objective decisions.ii) Research, being a fact-finding process, significantly influences business decisions. The business management is interested in choosing that course of action which is most effective in attaining the goals of the organization. Research not only provides facts and figures to support business decisions but also enables the business to choose one which is best.

iii) A considerable number of business problems are now given quantitative treatment with some degree of success with the help of operations research. Research into management problems may result in certain conclusions by means of logical analysis which the decision maker may use for his action or solution.iv) Research plays a significant role in the identification of a new project, project feasibility and project implementation.v) Research helps the management to discharge its managerial functions of planning, forecasting, coordinating, motivating, controlling and evaluation effectively.vi) Research facilitates the process of thinking, analyzing, evaluating and interpreting of the business environment and of various business situations and business alternatives. So as to be helpful in the formulation of business policy and strategy.vii) Research and Development (R & D) helps discovery and invention. Developing new products or modifying the existing products, discovering new uses, new markets etc., is a continuous process in business.viii) The role of research in functional areas like production, finance, human resource management, and marketing need not be over emphasized. Research not only establishes relationships between different variables in each of these functional areas, but also between these various functional areas.ix) Research is a must in the production area. Product development, new and better ways of producing goods, invention of new technologies, cost reduction, improving product quality, work simplification, performance improvement, process improvement etc., are some of the prominent areas of research in the production area.x) The purchase/material department uses research to frame alternative suitable policies regarding where to buy, when to buy, how much to buy, and at what price to buy.xi) Closely linked with production function is marketing function. Market research and marketing research provide a major part of marketing information which influences the inventory

level and production level. Marketing research studies include problems and opportunities in the market, product preference, sales forecasting, advertising effectiveness, product distribution, after sales service etc.,xii) In the area of financial management, maintaining liquidity, profitability through proper funds management and assets management is essential. Optimum capital mix, matching of funds inflows and outflows, cash flow forecasting, cost control, pricing etc., require some sort of research and analysis. Financial institutions also (banking and non-banking) have found it essential to set up research division for the purpose of collecting and analyzing data both for their internal purpose and for making in depth studies on economic conditions of business and people.xiii) In the area of human resource management personnel policies have to be guided by research. An individual’s motivation to work is associated with his needs and their satisfaction. An effective Human Resource Manager is one who can identify the needs of his work force and formulate personnel policies to satisfy the same so that they can be motivated to contribute their best to the attainment of organizational goals. Job design, job analysis, job assignment, scheduling work breaks etc., have to be based on investigation and analysis.xiv) Finally, research in business is a must to continuously update its attitudes, approaches, products goals, methods, and machinery in accordance with the changing environment in which it operates.

QUALITATIVE VS QUANTITATIVE

1.1 INTRODUCTION

A starting point in trying to understand the collection of information for research purposes is that there are broadly two approaches: quantitative research and qualitative research. Early forms of research originated in the natural sciences such as biology, chemistry, physics, geology etc. and were concerned with investigating things which we could observe and measure in some way. Such observations and measurements can be made objectively and repeated by other researchers. This process is referred to as “quantitative” research.

Much later, along came researchers working in the social sciences: psychology, sociology, anthropology etc. They were interested in studying human behaviour and the social world inhabited by human beings. They found increasing difficulty in trying to explain human behaviour in simply measurable terms. Measurements tell us how often or how many people behave in a certain way but they do not adequately answer the question “why?” Research which attempts to increase our understanding of why things are the way they are in our social world and why people act the ways they do is “qualitative” research.

The unit begins with a general introduction into the nature of qualitative research and quantitative research. This includes identification of the strengths of qualitative research in a brief comparison with quantitative research.

1.2 MEANING OF QUANTITATIVE RESEARCH

Quantitative research is based on the measurement of quantity or amount. It is applicable to phenomena that can be expressed in terms of quantity. In quantitative research your aim is to determine the relationship between one thing (an independent variable) and another (a dependent or outcome variable) in a population. Quantitative research designs are either descriptive (subjects usually measured once) or experimental (subjects measured before and after a treatment). A descriptive study establishes only associations between variables. An experiment establishes causality.

For an accurate estimate of the relationship between variables, a descriptive study usually needs a sample of hundreds or even thousands of subjects; an experiment, especially a crossover, may need only tens of subjects. The estimate of the relationship is less likely to be biased if you have a high participation rate in a sample selected randomly from a population.

In all studies, subject characteristics can affect the relationship you are investigating. Limit their effect either by using a less heterogeneous sample of subjects or preferably by measuring the characteristics and including them in the analysis. In an experiment, try to measure variables that might explain the mechanism of the treatment. In an unblended experiment, such variables can help define the magnitude of any placebo effect.

1.3 DEFINITIONS OF QUANTITATIVE RESEARCH.

Different researchers and educators give different definitions to “quantitative research.” Here are some of them:

Quantitative research is the numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect. It is used in a wide variety of natural and social sciences, including physics, biology, psychology, sociology and geology. (Wikipedia Encyclopedia, 2005).

In addition, according to Cohen (1980), quantitative research is defined as social research that employs empirical methods and empirical statements.. He states that an empirical statement is defined as a descriptive statement about what “is” the case in the “real world” rather than what “ought” to be the case. Typically, empirical statements are expressed in numerical terms; another factor in quantitative research is that empirical evaluations are applied. Empirical evaluations are

defined as a form that seeks to determine the degree to which a specific program or policy empirically fulfils or does not fulfil a particular standard or norm.

Moreover, Creswell (1994) has given a very concise definition of quantitative research as a type of research that is `explaining phenomena by collecting numerical data that are analyzed using mathematically based methods (in particular statistics).'

1.4 ELEMENTS OF QUANTITATIVE RESEARCH

The first element is explaining phenomena. This is a key element of all research, be it quantitative or qualitative. When we set out to do some research, we are always looking to explain something. In education this could be questions, for example, `Does constructivism work for teaching English in a Thai context?', or `What factors influence student achievement in learning English as a foreign language?'

The specificity of quantitative research lies in the next part of the definition. In quantitative research we collect numerical data. This is closely connected to the final part of the definition: analysis using mathematically-based methods. In order to be able to use mathematically based methods our data have to be in numerical form. This is not the case for qualitative research. Qualitative data are not necessarily or usually numerical, and therefore cannot be analyzed using statistics. The last part of the definition refers to the use of mathematically based methods, in particular statistics, to analyze the data. This is what people usually think about when they think of quantitative research, and is often seen as the most important part of quantitative studies. This is a bit of a misconception. While it is important to use the right data analysis tools, it is even more important to use the right research design and data collection instruments. However, the use of statistics to analyze the data is the element that puts a lot of people off doing quantitative research, because the mathematics underlying the methods seem complicated and frightening.

Therefore, because quantitative research is essentially about collecting numerical data to explain a particular phenomenon, particular questions seem immediately suited to being answered using quantitative methods. For example,

• How many students learning Experiential English I get A’s in the first semester?

• What percentage of the students learning Experiential English I has negative attitudes towards the course?

• On average, is there any significant difference between the general English proficiency of the students learning Foundation English and Experiential English courses?

These are all questions we can look at quantitatively, as the data we need to collect are already available to us in numerical form. However, there are many phenomena we might want to look at, but which don't seem to produce any quantitative data. In fact, relatively few phenomena in education actually occur in the form of `naturally' quantitative data.

Luckily, we are far less limited than what might appear above. Many data that do not naturally appear in quantitative form can be collected in a quantitative way. We do this by designing research instruments aimed specifically at converting phenomena that don't naturally exist in quantitative form into quantitative data, which we can analyze statistically. Examples of this are attitudes and beliefs. We might want to collect data on students' attitudes to their school and their teachers. These attitudes obviously do not naturally exist in quantitative form. However, we can develop a questionnaire that asks pupils to rate a number of statements (for example, `I think school is boring') as either agree strongly, agree, disagree or disagree strongly, and give the answers a number (e.g. 1 for disagree strongly, 4 for agree strongly). Now we have quantitative data on pupil attitudes to school. In the same way, we can collect data on a wide number of phenomena, and make them quantitative through data collection instruments like questionnaires or tests.

In short, quantitative research generally focuses on measuring social reality. Quantitative research and/or questions are searching for quantities in something and to establish research numerically. Quantitative researchers view the world as reality that can be objectively determined so rigid guides in the process of data collection and analysis are very important.

1.5 QUANTITATIVE RESEARCH METHODS

The basic building blocks of quantitative research are variables. Variables (something that takes on different values or categories) are the opposite of constants (something that cannot vary, such as a single value or category of a variable).

When we speak of measurement, the simplest classification is between categorical and quantitative variables. Quantitative variables vary in degree or amount (e.g., annual income) and categorical variables vary in type or kind (e.g., gender).

The other set of variables are the kinds of variables we talk about when explaining how the world operates and when we design a quantitative research study. Independent variables (symbolized by "IV") are the presumed cause of another variable. Dependent variables (symbolized by "DV") are the presumed effect or outcome. Dependent variables are influenced by one or more independent variables. What are the IV and DV in the relationship between smoking and lung cancer? (Smoking is the IV and lung cancer is the DV.)

Sometimes we want to understand the process or variables through which one variable affects another variable. This brings us to the idea of intervening variables (also called mediator or mediating variables). Intervening variables are variables that occur between two other variables. For example, tissue damage is an intervening variable in the smoking and lung cancer relationship. We can use arrows (which mean causes or affects) and draw the relationship that includes an intervening variable like this:

Smoking---->Tissue Damage---->Lung Cancer.

Sometimes a relationship does not generalize to everyone; therefore, researchers often use moderator variables to show how the relationship changes across the levels of an additional variable. For example, perhaps behavioral therapy works better for males and cognitive therapy works better for females. In this case, gender is the moderator variable. The relationship be type of therapy (behavioral versus cognitive) and psychological relief is moderated by gender.

1.6 DIFFERENT TYPES OF QUANTITATIVE RESEARCH

1.6.1 EXPERIMENTAL RESEARCH

The purpose of experimental research is to study cause and effect relationships. Its defining characteristic is active manipulation of an independent variable (i.e., it is only in experimental research that “manipulation” is present). Also, random assignment (which creates "equivalent" groups) is used in the strongest experimental research designs.

Here is an example of an experiment.

Pretest Treatment Posttest

O1 XE O2 O1 XC O2Where: • E stands for the experimental group (e.g., new teaching approach) • C stands for the control or comparison group (e.g., the old or standard teaching approach)

Because the best way to make the two groups similar in the above research design is to randomly assign the participants to the experimental and control groups, let’s assume that we have a convenience sample of 50 people and that we randomly assign them to the two groups in our experiment. Here is the logic of this experiment. First, we made our groups approximately the same at the start of the study by using random assignment (i.e., the groups are “equated”). You pretest the participants to see how much they know. Next, you manipulate the independent variable by using the new teaching approach with the experimental group and using the old teaching approach for the control group. Now (after the manipulation) you measure the participants’ knowledge to see how much they know after having participated in our experiment. Let’s say that the people in the experimental group show more knowledge improvement than those in the control group. What would you conclude? In this case, we can conclude that there is a causal relationship between the IV, teaching method, and the DV, knowledge, and specifically we can conclude that the new teaching approach is better than the old teaching approach. Make sense? Now, let’s say that in the above experiment we could not use random assignment to equate our groups. Let’s say that, instead, we had our best teacher (Mrs. Smith) use the new teaching

approach with her students in her 5th

period class and we had a newer and less experienced

teacher (Mr. Turner) use the old teaching approach with his 5th

period class. Let’s again say that the experimental group did better than the control group. Do you see any problems with claiming that the reason for the difference between the two groups is because of the teaching method? The problem is that there are alternative explanations. First, perhaps the difference is because Mrs. Smith is the better teacher. Second, perhaps Mrs. Smith had the smarter students (remember the students were not randomly assignment to the two groups; instead, we used two intact classrooms). We have a name for the problems just mentioned. It is the problem of alternative explanations. In particular, it is very possible that the difference we saw between the two groups was due to variables other than the IV. In particular, the difference might have been due to the teacher (Mrs. Smith vs Mr. Turner) or to the IQ levels of the groups (perhaps Mrs. Smith’s students had higher IQs than Mr. Smith’s students) We have a special name for these kinds of variables. They are called extraneous variable.

It is important to remember the definition of an extraneous variable because they can destroy the integrity of a research study that claims to show a cause and effect relationship. An extraneous variable is a variable that may compete with the independent variable in explaining the outcome. Remember this, if you are ever interested in identifying cause and effect relationships you must

always determine whether there are any extraneous variables you need to worry about. If an extraneous variable really is the reason for an outcome (rather than the IV) then we sometimes like to call it a confounding variable because it has confused or confounded the relationship we are interested in.

1.6.2 NONEXPERIMENTAL RESEARCH

Non-experimental approach is represented by two methods, which are causal-comparative research and correlational research. Both methods of non-experimental approach in quantitative research use attribute variables, which cannot be manipulated. Such attribute variables include “gender, parenting style, learning style, ethnic group, college major, party identification, type of school, marital status of parents, retention in grade, type of disability, presence or absence of an illness, drug or tobacco use, and any personality trait that is operationalized as a categorical variable” (Johnson, 2001). It is necessary to underline the fact that non-experimental methods are more widely used by the researchers because “many important variables of interest are not manipulable”.

In the "basic case" of causal-comparative research, there is one categorical Independent Variable (IV) and one quantitative dependent variable (DV).

• Example: Gender (IV) and class performance (DV). • You would look for the relationship by comparing the male and female average

performance levels.

In the simple case of correlational research, there is one quantitative IV and one quantitative DV.

• Example: Self-esteem (IV) and class performance (DV). • You would look for the relationship by calculating the correlation coefficient. • The correlation coefficient is a number that varies between –1 and +1, and 0 stands for no

relationship. The farther the number is from 0, the stronger the relationship. • If the sign of the correlation coefficient is positive (e.g., +.65) then you have a positive

correlation, which means the two variables move in the same direction (as one variable increases, so does the other variable). Education level and annual income are positively correlated (i.e., the higher the education, the higher the annual income).

• If the sign of the correlation coefficient is negative (e.g., -.71) then you have a negative correlation, which means the two variables move in opposite directions (as one variable increases, the other decreases). Smoking and life expectancy are negatively correlated (i.e., the higher the smoking, the lower the life expectancy).

1.7 ADVANTAGES OF QUANTITATIVE RESEARCH

There are several advantages of quantitative research. They are as follows:

1. Provides estimates of populations at large.

2. Indicates the extensiveness of attitudes held by people.

3. Provides results which can be condensed to statistics.

4. Allows for statistical comparison between various groups.

5. Has precision, is definitive and standardized.

6. Measures level of occurrence, actions, trends, etc.

7. Can answer such questions as "How many?" and "How often?"

1.8 USE OF QUANTITATIVE METHODS

There are four main type of research question that quantitative research is particularly suited to finding an answer to:

1. The first type of research question is that demanding a quantitative answer. Examples are’ how many students choose to study education?’Or How many math’s teachers do we need and how many we got in our school district?’ that we need to use quantitative research to answer this type of question.

2. Numerical changes likewise accurately be studied only be studied only by using quantitative methods. Are the numbers of students in our university re falling or rising? Is achievement going up or down? We need to do a quantitative study to find out.

3. As well as wanting to find out about the state of something or other, we often want to explain phenomena. What factors predict the recruitment of math’s teacher? What factors related to change in student’s achievement over time?

4. The final activity for which quantitative research is especially suited is the testing of hypotheses. We might want to explain something- for example, whether there is a relationship between pupil’s achievement and their self esteem and social background. We could look at the theory and come up with the hypothesis that lower social class background leads to low self esteem, which would in turn be related to low achievement. Using quantitative research, we can try to test this model.

1.9 QUALITATIVE RESEARCH1.9.1 MEANING AND NATURE OF QUALITATIVE RESEARCH

Qualitative research has its roots in social science and is more concerned with understanding why people behave as they do: their knowledge, attitudes, beliefs, fears, etc. (e.g., why do patients prefer to be involved in decision-making about their treatment?).

Qualitative research seeks out the ‘why’, not the ‘how’ of its topic through the analysis of unstructured information – things like interview transcripts, open ended survey responses, emails, notes, feedback forms, photos and videos. It doesn’t just rely on statistics or numbers, which are the domain of quantitative researchers.

Qualitative research is used to gain insight into people's attitudes, behaviors, value systems, concerns, motivations, aspirations, culture or lifestyles. It’s used to inform business decisions, policy formation, communication and research. Focus groups, in-depth interviews, content analysis, ethnography, evaluation and semiotics are among the many formal approaches that are used, but qualitative research also involves the analysis of any unstructured material, including customer feedback forms, reports or media clips.

Collecting and analyzing this unstructured information can be messy and time consuming using manual methods. When faced with volumes of materials, finding themes and extracting meaning can be a daunting task.

Qualitative research is designed to reveal a target audience’s range of behavior and the perceptions that drive it with reference to specific topics or issues. It uses in-depth studies of small groups of people to guide and support the construction of hypotheses. The results of qualitative research are descriptive rather than predictive.

Qualitative research methods originated in the social and behavioral sciences: sociology, anthropology and psychology. Today, qualitative methods in the field of marketing research include in-depth interviews with individuals, group discussions (from two to ten participants is typical); diary and journal exercises; and in-context observations. Sessions may be conducted in person, by telephone, via videoconferencing and via the Internet.

Several unique aspects of qualitative research contribute to rich, insightful results:

Synergy among respondents, as they build on each other’s comments and ideas. The dynamic nature of the interview or group discussion process, which engages respondents

more actively than is possible in more structured survey.

The opportunity to probe ("Help me understand why you feel that way") enabling the researcher to reach beyond initial responses and rationales.

The opportunity to observe, record and interpret non-verbal communication (i.e., body language, voice intonation) as part of a respondent’s feedback, which is valuable during interviews or discussions, and during analysis.

The opportunity to engage respondents in "play" such as projective techniques and exercises, overcoming the self-consciousness that can inhibit spontaneous reactions and comments.

The strength of qualitative research is its ability to provide complex textual descriptions of how people experience a given research issue. It provides information about the “human” side of an issue – that is, the often contradictory behaviors, beliefs, opinions, emotions, and relationships of individuals. Qualitative methods are also effective in identifying intangible factors, such as social norms, socioeconomic status, gender roles, ethnicity, and religion, whose role in the research issue may not be readily apparent. When used along with quantitative methods, qualitative research can help us to interpret and better understand the complex reality of a given situation and the implications of quantitative data.

Although findings from qualitative data can often be extended to people with characteristics similar to those in the study population, gaining a rich and complex understanding of a specific social context or phenomenon typically takes precedence over eliciting data that can be generalized to other geographical areas or populations. In this sense, qualitative research differs slightly from scientific research in general.

1.10 USES OF QUALITATIVE RESEARCH

Qualitative research is only widely used where small segments of the population (or groups of people who have a common characteristic) are of specific interest to a researcher. Below is a list of some of the main reasons for carrying out qualitative research:

• To evaluate a market, product or consumer where no information exists• To identify and explore concepts• To take researchers rapidly up the learning curve when they know very little about a group of consumers• To identify behaviour patterns, beliefs, attitudes, opinions and motives• To establish priorities amongst categories of behaviour, beliefs, opinions and attitudes• To identify problems in depth and develop models for further research• To put flesh on the bones of points arising from a pilot or major survey• To provide verbatim comments and anecdotes from participants – so that the research findings can be brought alive for the client

• To test how a questionnaire works by going through question by question asking about routing, signposting, understanding and ambiguity• Where direct questioning will not give us personal or hidden details about respondents.

1.11 PROCESS OF QUALITATIVE RESEARCH

1) Deciding who should participate

In addition to demographic, attitudinal, and experience criteria pertaining to the research topic (e.g., first-time mothers of toddlers, men who color their hair, dissatisfied small business customers of a particular bank), experienced consultants may also consider the following issues – especially when recruiting for focus group participants:

Select individuals from households or businesses that truly represent the target market. Seek out persons who are forthcoming about their own experiences and opinions; comfortable

accepting contrasting viewpoints from others in the group; sufficiently articulate to contribute to the discussion.

Discuss the issue of past participation with clients and recruiters, and set limits appropriate to your topic and objectives.

Exclude anyone suspected of not being truthful about his or her qualifications.

2) Choosing the setting

Weigh the relative advantages and limitations offered by each medium or venue.

In person - Maximizes opportunities to observe and interpret non-verbal communication; easiest format for using visual and/or tactile stimuli (e.g., storyboards, prototypes, packaging); preserves the highest degree of control over who actually shows up and participates.

Telephone - Lacks non-verbal component of face-to-face interaction (among respondents as well as with the moderator); reduces or eliminates certain logistical barriers (e.g., respondents are geographically dispersed or homebound); can elicit more candor from respondents if they feel somewhat anonymous.

Online – Offers access to respondents who would not or could not participate in person; offers potential for more candid responses; opportunity for voice or visual contact will vary depending on the method used; excludes respondents without Internet access.

3) Deciding how much qualitative research is enough

When deciding how many group discussions, interviews, or other types of qualitative research to recommend, experienced qualitative research consultants will often advise conducting at least two group sessions and/or a minimum number of interviews with each key market segment (defined geographically or otherwise). Beyond that guideline, the appropriate amount of research will depend on the range of issues to be covered, and the number and nature of respondent segments to be included.

4) Executing the research

Generally, a qualitative research project includes the following steps:

Finalize the project design, schedule, and budget Arrange recruiting and reserve facilities Develop screening questionnaire(s) and field instructions Monitor recruiting progress and check respondent profiles Develop discussion guide(s) and any stimuli to be used in the research Conduct the interviews, group discussions, observational sessions, etc. Debrief with client(s), possibly at intervals during the research Analyze results and prepare deliverables as previously agreed.

1.12 QUALITATIVE RESEARCH METHODS

Qualitative research methods are continually evolving, as patterns and styles of human interaction and communication change. Regardless of venue or medium, qualitative research is always based on open-ended queries; it uses in-depth probing to uncover the thoughts and feelings behind initial responses; and it applies insights and learning to the research process in real time. Typical qualitative methods include:

Participant observation is appropriate for collecting data on naturally occurring behaviors in their usual contexts. One of the most common methods for qualitative data collection, participant observation is also one of the most demanding. It requires that the researcher become a participant in the culture or context being observed. The literature on participant observation discusses how to enter the context, the role of the researcher as a participant, the collection and storage of field notes, and the analysis of field data.

Focus group – A moderator-led discussion among a group of individuals who share a need, habit, or life circumstance relevant to the research issue(s) at hand. Typically one to two hours in length, a focus group discussion often includes from two to ten respondents. While focus groups

have historically been held in person (face-to-face), they can also be conducted remotely by teleconferencing, by videoconferencing, or through the Internet using text chat, online bulletin boards, online collaboration tools, desktop video conferencing, or various forms of tele/web conferencing. Focus groups are effective in eliciting data on the cultural norms of a group and in generating broad overviews of issues of concern to the cultural groups or subgroups represented.

In-depth interview (IDI, one-on-one) – Interview with a single individual, typically lasting from 30 to 90 minutes, depending on the subject matter and context. IDIs may be conducted in person at a research facility, the respondent’s home or workplace or a public location, or by telephone. In-depth interviews are optimal for collecting data on individuals’ personal histories, perspectives, and experiences, particularly when sensitive topics are being explored.

Dyads, triads – In-depth interviews with two or three people who often represent members of the same family or business team, who use a product or service and/or make purchase decisions together.

Paired interviews – Consecutive or interlocking interviews with two people who use and/or decide to purchase a product or service together, e.g., husband and wife, parent and child. Given the objectives of a particular study, the qualitative consultant will advise the client in selecting the most appropriate setting.

Further methods used in qualitative research studies

Diary methods - The researcher or subject keeps a personal account of daily events, feelings, discussions, interactions etc.

Role-play and simulation - Participants may be asked to play a role, or may be asked to observe role-play, after which they are asked to rate behaviour, report feelings, and predict further events.

Case-study - This is an in-depth study of just one person, group or event. This technique is simply a description of individuals.

Case studies are detailed investigations of individuals, groups, institutions or other social units. The researcher conducting a case study attempts to analyze the variables relevant to the subject under study (Polit and Hungler, 1983). The principle difference between case studies and other research studies is that the focus of attention is the individual case and not the whole population of cases. Most studies search for what is common and pervasive. However, in the case study, the focus may not be on generalization but on understanding the particulars of that case in its complexity. A case study focuses on a bounded system, usually under natural conditions, so that the system can be understood in its own habitat (Stake, 1988).

1.13 ADVANTAGES OF QUALITATIVE RESEARCH

One advantage of qualitative methods in exploratory research is that use of open-ended questions and probing gives participants the opportunity to respond in their own words, rather than forcing them to choose from fixed responses, as quantitative methods do. Open-ended questions have the ability to evoke responses that are:

• Meaningful and culturally salient to the participant• Unanticipated by the researcher• Rich and explanatory in nature

Another advantage of qualitative methods is that they allow the researcher the flexibility to probe initial participant responses – that is, to ask why or how. The researcher must listen carefully to what participants say, engage with them according to their individual personalities and styles, and use “probes” to encourage them to elaborate on their answers.

1.14 COMPARING QUANTITATIVE AND QUALITATIVE RESEARCH

Criteria Qualitative Research Quantitative Research

Purpose To understand & interpret social interactions.

To test hypotheses, look at cause & effect, & make predictions.

Group Studied Smaller & not randomly selected.

Larger & randomly selected.

Variables Study of the whole, not variables.

Specific variables studied

Type of Data Collected Words, images, or objects. Numbers and statistics.

Form of Data Collected Qualitative data such as open- ended responses, interviews, participant observations, field notes, & reflections.

Quantitative data based on precise measurements using structured & validated data-collection instruments.

Type of Data Analysis Identify patterns, features, Identify statistical

themes. relationships.

Objectivity and Subjectivity Subjectivity is expected. Objectivity is critical.

Role of Researcher Researcher & their biases may be known to participants in the study, & participant characteristics may be known to the researcher.

Researcher & their biases are not known to participants in the study, & participant characteristics are deliberately hidden from the researcher (double blind studies).

Results Particular or specialized findings that is less generalizable.

Generalizable findings that can be applied to other populations.

Scientific Method Exploratory or bottom–up: the researcher generates a new hypothesis and theory from the data collected.

Confirmatory or top-down: the researcher tests the hypothesis and theory with the data.

View of Human Behavior Dynamic, situational, social, & personal.

Regular & predictable.

Most Common Research Objectives

Explore, discover, & construct Describe, explain, & predict.

Focus Wide-angle lens; examines the breadth & depth of phenomena

Narrow-angle lens; tests a specific hypotheses

Nature of Observation Study behavior in a natural environment.

Study behavior under controlled conditions; isolate causal effects

Nature of Reality Multiple realities; subjective Single reality; objective

Final Reportr Narrative report with contextualdescription & direct quotations from research participants

Statistical report with correlations,comparisons of means, & statistical significance of findings

The key difference between quantitative and qualitative methods is their flexibility. Generally, quantitative methods are fairly inflexible. With quantitative methods such as surveys and questionnaires, for example, researchers ask all participants identical questions in the same order. The response categories from which participants may choose are “closed-ended”

or fixed. The advantage of this inflexibility is that it allows for meaningful comparison of responses across participants and study sites. However, it requires a thorough understanding of the important questions to ask, the best way to ask them, and the range of possible responses.

Qualitative methods are typically more flexible – that is, they allow greater spontaneity and adaptation of the interaction between the researcher and the study participant. For example, qualitative methods ask mostly “open-ended” questions that are not necessarily worded in exactly the same way with each participant. With open-ended questions, participants are free to respond in their own words, and these responses tend to be more complex than simply “yes” or “no.”

In addition, with qualitative methods, the relationship between the researcher and the participant is often less formal than in quantitative research. Participants have the opportunity to respond more elaborately and in greater detail than is typically the case with quantitative methods. In turn, researchers have the opportunity to respond immediately to what participants say by tailoring subsequent questions to information the participant has provided. It is important to note, however, that there is a range of flexibility among methods used in both quantitative and qualitative research and that flexibility is not an indication of how scientifically rigorous a method is. Rather, the degree of flexibility reflects the kind of understanding of the problem that is being pursued using the method.

Both these qualitative and the quantitative approaches to the research can be divergent, contrasting and complimentary. Both of these two types or researches seek to describe and explain phenomena, but have differing epistemological positions. 

Therefore, it is necessary for a researcher to consider whether a qualitative or quantitative approach would be more appropriate whilst devising a research plan.

1.15 SUMMARY

Qualitative research is often depicted as a research strategy whose emphasis on a relatively open-ended approach to the research process frequently produces surprises, changes of direction and new insights. However, quantitative research is by no means a mechanical application of neutral tools that results in no new insights. In quantitative data analysis, the imaginative application of techniques can result in new understandings. Quantitative research generally focuses on

measuring social reality. Quantitative research and/or questions are searching for quantities in something and to establish research numerically. Quantitative researchers view the world as reality that can be objectively determined so rigid guides in the process of data collection and analysis are very important.

1.16 SELF ASSESSMENT EXERCISE

1) What do you mean by quantitative research? Explain its significance.

2) Explain the two types of quantitative research with the help of examples.

3) Write short notes on: (A) Advantages of quantitative research and qualitative research; (B) Elements of quantitative research; (C) Uses of qualitative research;

4) Differentiate quantitative and qualitative research.

METHODS AND TOOLS OF COLLECTING DATA

1.1 INTRODUCTION

The increasingly complex nature of business and government has focused attention on the uses of research methodology in solving managerial problems. The credibility of the results derived from the application of such methodology is dependent upon the up to date information about the various pertinent characters included in the analysis. To illustrate, the demand of disc records has dropped dramatically after cassettes have entered into the market commercially. This information must be taken into consideration for formulating marketing strategy by a dealer selling musical products. Information expressed in appropriate quantitative form is known as data. The necessity and usefulness of information gathering or data collection cannot be overemphasised in government policies. The government must be aware of the actual scenario of the acceptance of family planning before it can formulate any policy in this matter. The components of this scenario are provided by appropriate data to be collected from various families. In industrial disputes regarding wages, cost of living index, a data based indicator of inflation is often accepted as a guideline for arbitration.

In short, neither a business decision nor a governmental decision can be made in a casual manner in the highly involved environment prevailing in this age. It is through appropriate data and their analysis that the decision maker becomes equipped with proper tools of decision making.

1.2 MEANING AND NEED FOR DATA

Data is required to make a decision in any business situation. The researcher is faced with one of the most difficult problems of obtaining suitable, accurate and adequate data. Utmost care must be exercised while collecting data because the quality of the research results depends upon the reliability of the data. Suppose, you are the Director of your company. Your Board of Directors has asked you to find out why the profit of the company has decreased since the last two years. Your Board wants you to present facts and figures. What are you going to do?

The first and foremost task is to collect the relevant information to make an analysis for the above mentioned problem. It is, therefore, the information collected from various sources, which can be expressed in quantitative form, for a specific purpose, which is called data. The rational decision maker seeks to evaluate information in order to select the course of action that maximizes objectives. For decision making, the input data must be appropriate. This depends on the appropriateness of the method chosen for data collection. The application of a statistical technique is possible when the questions are answerable in quantitative nature, for instance; the cost of production and profit of the company measured in rupees, age of the workers in the company measured in years. Therefore, the first step in statistical activities is to gather data. The data may be classified as primary and secondary data. Let us now discuss these two kinds of data in detail.

1.3 PRIMARY AND SECONDARY DATA

The primary data are those which are collected afresh and for the first time, and thus happen to be original in character. Such data are published by authorities who themselves are responsible for their collection.

The Secondary data on the other hand, are those which have already been collected by some other agency and which have already been processed. Secondary data may be available in the form of published or unpublished sources. For instance, population census data collected by the Government in a country is primary data for that Government. But the same data becomes secondary for those researchers who use it later. In case you have decided to collect primary data for your investigation, you have to identify the sources from where you can collect that data. For example, if you wish to study the problems of the workers of X Company Ltd., then the workers who are working in that company are the source. On the other hand, if you have decided to use secondary data, you have to identify the secondary sources that have already collected the related data for their study purpose.

1.4 METHODS OF COLLECTING PRIMARY DATA

The collection of primary data for business research is of paramount importance to assist management in making decisions. Generally, information regarding a large number of characteristics is necessary to analyse any problem pertaining to management. For instance, a study relating to employment in rural areas requires data on income, wages, types of crops and land holdings. The collection of primary data thus requires a great deal of deliberation and expertise. Depending upon the nature of information necessary the following methods of collecting primary data are available.

1) Observation Method

The Concise Oxford Dictionary defines observation as, ‘accurate watching and noting of phenomena as they occur in nature with regard to cause and effect or mutual relations’. Thus observation is not only a systematic watching but it also involves listening and reading, coupled with consideration of the seen phenomena. It involves three processes. They are: sensation, attention or concentration and perception.

Under this method, the researcher collects information directly through observation rather than through the reports of others. It is a process of recording relevant information without asking anyone specific questions and in some cases, even without the knowledge of the respondents. This method of collection is highly effective in behavioural surveys. For instance, a study on behaviour of visitors in trade fairs, observing the attitude of workers on the job, bargaining strategies of customers etc. Observation can be participant observation or non-participant observation. In Participant Observation Method, the researcher joins in the daily life of informants or organisations, and observes how they behave. In the Non-participant Observation Method, the researcher will not join the informants or organisations but will watch from outside.

Merits1) This is the most suitable method when the informants are unable or reluctant to provide information.2) This method provides deeper insights into the problem and generally the data is accurate and quicker to process. Therefore, this is useful for intensive study rather than extensive study.

LimitationsDespite of the above merits, this method suffers from the following limitations:1) In many situations, the researcher cannot predict when the events will occur. So when an event occurs there may not be a ready observer to observe the event.2) Participants may be aware of the observer and as a result may alter their behaviour.3) Observer, because of personal biases and lack of training, may not record specifically what he/she observes.

4) This method cannot be used extensively if the inquiry is large and spread over a wide area.

2) Questionnaire Method

A popular and common method of collection of primary data is by personally interviewing individuals, recording their answers in a structured questionnaire. The complete enumeration of Indian decennial census is performed by this method. The enumerators visit the dwellings of individuals and put questions to them which elicit the relevant information about the subject of enquiry. This information is recorded in the questionnaire. Occasionally a part of the questionnaire is unstructured so that the interviewee can feel free to share information about intimate matters with the interviewer. As the data are collected by the field staff personally it is also known as personal interview method.

Much of the accuracy of the collected data, however, depends on the ability and tactfulness of investigators, who should be subjected to special training as to how they should elicit the correct information through friendly discussions.

If the questionnaire is posted to informants, it is called a Mail Questionnaire. Sometimes questionnaires may also be sent through E-mail depending upon the nature of study and availability of time and resources. After receiving the questionnaires the informants read the questions and record their responses in the space meant for the purpose on the questionnaire. It is desirable to send the questionnaire with self-addressed envelopes for quick and high rate of response.

Merits1) You can use this method in cases where informants are spread over a vast geographical area.2) Respondents can take their own time to answer the questions. So the researcher can obtain original data by this method.3) This is a cheap method because its mailing cost is less than the cost of personal visits.4) This method is free from bias of the investigator as the information is given by the respondents themselves.5) Large samples can be covered and thus the results can be more reliable and dependable.

Limitations1) Respondents may not return filled in questionnaires, or they can delay in replying to the questionnaires.2) This method is useful only when the respondents are educated and co-operative.3) Once the questionnaire has been despatched, the investigator cannot modify the questionnaire.4) It cannot be ensured whether the respondents are truly representative.

Main aspects of a questionnaire: Quite often questionnaire is considered as the heart of a survey operation. Hence it should be very carefully constructed. If it is not properly set up, then the survey is bound to fail. This fact requires us to study the main aspects of a questionnaire viz., the general form, question sequence and question formulation and wording. Researcher should note the following with regard to these three main aspects of a questionnaire:

a) The General Form

The form of a questionnaire will depend partly on the type of data being sought and partly on the data collection method to be used. The choice lies between two extremes. On the one hand, there is the highly structured questionnaire in which all questions and answers are specified and continents in the respondents' own words are held to a minimum. At the other end is the unstructured questionnaire in which the interviewer is provided with a general brief on the sort of information to be obtained but the exact question is largely his own responsibility.

The unstructured questionnaires are useful in carrying out in depth interviews where the aim is to probe for attitudes and reasons. They may also be effectively employed in pretesting, the result of which can be used as a basis for constructing a structured questionnaire at a later stage. Thus, in order to ascertain the expectation of the television viewers about a programme interviews may be conducted with unstructured questionnaires. The resulting range of answers may then be used to prepare a structured questionnaire for use in the main part of the study.

The main disadvantage with any unstructured questionnaire is that it requires personal interview. It cannot be used in the mailed questionnaire method of data collection.

A structured questionnaire usually has fixed alternative answers to each question. They are simple to administer and relatively inexpensive to analyse. The questionnaires have, however, their limitations. It is not possible to record the responses made by the respondent in their own words. They are considered inappropriate in investigations where the aim happens to be to probe for attitudes and feelings.

b) The Question Sequence

The introduction to the questionnaire should be as short and simple as possible. The introductory letter accompanying the mailed questionnaire should also be made very brief. The introduction lays the foundation for establishing the rapport with the respondent in addition to making the interview possible.

Once the rapport is established the questions will generally seek substantive information of ' value to the study. As a general rule, questions that put too great a strain on the memory or the intellect should be reserved till later. Likewise, questions relating to personal wealth and personal character should be avoided in the beginning.

Following the opening phase should come the questions that are really vital to the interview. Even here, substantive questions should be surrounded by more interesting ones in order that the attention does not slip. Awkward questions, which create the risk that the respondent may discontinue the interview, are usually relegated toward the end. By the time the interview has been terminated, some information is already available with the interviewer.

Ideally, the question sequence should conform to the respondents' way of thinking, and this is where unstructured interviews are highly advantageous. The interviewer can rearrange the order of the questions to fit the discussion in each particular case. With structured questionnaire the best that can be done is to determine with pretesting the question sequence which is likely to produce good rapport with most people.

c) The Question Wording

It has been stated that the question wording and formulation are more of an art than a science. Science does enter, however, in testing the stability and the adequacy of replies for business and management decisions. The wording of the questions should be impartial so as not to give a biased picture of the true state of affairs. Colourful adjectives and undue descriptive phrases should be avoided. In general the questions should be worded such that (a) they are easily understood (b) they are simple (c) they are concrete and conform to respondents' way of thinking.

3) Interview Method

Interview is one of the most powerful tools and most widely used method for primary data collection in business research. In our daily routine we see interviews on T.V. channels on various topics related to social, business, sports, budget etc. In the words of C. William Emory, ‘personal interviewing is a two way purposeful conversation initiated by an interviewer to obtain information that is relevant to some research purpose’. Thus an interview is basically, a meeting between two persons to obtain the information related to the proposed study. The person who is interviewing is named as interviewer and the person who is being interviewed is named as informant. It is to be noted that, the research data/information collect through this method is not a simple conversation between the investigator and the informant, but also the glances, gestures, facial expressions, level of speech etc., are all part of the process.

Through this method, the researcher can collect varied types of data intensively and extensively.

Interviews can be classified as direct personal interviews and indirect personal interviews. Under the techniques of direct personal interview, the investigator meets the informants (who come under the study) personally, asks them questions pertaining to enquiry and collects the desired information. Thus if a researcher intends to collect the data on spending habits of Delhi

University (DU) students, he/ she would go to the DU, contact the students, interview them and collect the required information.

Indirect personal interview is another technique of interview method where it is not possible to collect data directly from the informants who come under the study. Under this method, the investigator contacts third parties or witnesses, who are closely associated with the persons/situations under study and are capable of providing necessary information. For example, an investigation regarding bribery pattern in an office. In such a case it is inevitable to get the desired information indirectly from other people who may be knowing them. Similarly, clues about the crimes are gathered by the CBI. Utmost care must be exercised that these persons who are being questioned are fully aware of the facts of the problem under study, and are not motivated to give a twist to the facts.

Another technique for data collection through this method can be structured and unstructured interviewing. In the Structured interview set questions are asked and the responses are recorded in a standardised form. This is useful in large scale interviews where a number of investigators are assigned the job of interviewing. The researcher can minimise the bias of the interviewer. This technique is also named as formal interview. In Un-structured interview, the investigator may not have a set of questions but have only a number of key points around which to build the interview. Normally, such type of interview is conducted in the case of an explorative survey where the researcher is not completely sure about the type of data he/ she collects. It is also named as informal interview. Generally, this method is used as a supplementary method of data collection in conducting research in business areas.

Now-a-days, telephone or cell phone interviews are widely used to obtain the desired information for small surveys. For instance, interviewing credit card holders by banks about the level of services they are receiving. This technique is used in industrial surveys especially in developed regions.

Merits

The major merits of this method are as follows:1) People are more willing to supply information if approached directly. Therefore, personal interviews tend to yield high response rates.2) This method enables the interviewer to clarify any doubt that the interviewee might have while asking him/her questions. Therefore, interviews are helpful in getting reliable and valid responses.3) The informant’s reactions to questions can be properly studied.

4) The researcher can use the language of communication according to the standard of the information, so as to obtain personal information of informants which are helpful in interpreting the results.

LimitationsThe limitations of this method are as follows:1) The chance of the subjective factors or the views of the investigator may come in either consciously or unconsciously.2) The interviewers must be properly trained; otherwise the entire work may be spoiled.3) It is a relatively expensive and time-consuming method of data collection especially when the number of persons to be interviewed is large and they are spread over a wide area.4) It cannot be used when the field of enquiry is large (large sample).

4) Through Local Reporters and Correspondents

Under this method, local investigators/agents or correspondents are appointed in different parts of the area under investigation. This method is generally adopted by government departments in those cases where regular information is to be collected. This method is also useful for newspapers, magazines, radio and TV news channels. This method has been used when regular information is required and a high degree of accuracy is not of much importance.

Merits1) This method is cheap and economical for extensive investigations.2) It gives results easily and promptly.3) It can cover a wide area under investigation.

Limitations1) The data obtained may not be reliable.2) It gives approximate and rough results.3) It is unsuited where a high degree of accuracy is desired.4) As the agent/reporter or correspondent uses his own judgement, his personal bias may affect the accuracy of the information sent.

1.5 SOURCES OF ERROR IN PRIMARY DATA COLLECTION

You are familiar with the sources or error associated with secondary data. The primary data collection methods are also subject to three important types of errors. These are sampling error, non-response error and response error.

Sampling error as the name implies is inherent in the procedure of sample chosen and results in the sample becoming non-representative of the population. For example, in order to study the patterns of cigarette consumption among Indian males if you chose a. sample of college student in a metropolitan city, this sample would not representative of the population of males in India. The study that you conduct on this sample, no matter which tool of data collection you use, would not be valid because it suffers from sampling error. The range of sampling error however can be controlled by changing the characteristics of sample drawn. Moreover, the extent of the sampling error can be measured if we take a. probability sample. More about sampling error has been discussed in the next unit on sampling.

A non-response error occurs when a. unit (unit here may be an individual, a family or an establishment) included in the sample, cannot or has not been reached. For example, in a sample of housewives from a particular city area, if a number of them happen to be away everytime the interviewer chooses to come, non-response is likely to occur. Incidence of non-response error as already noted is very high in mail interviews as respondents simply ignore the questionnaire received by them.

In most direct structured interviews i.e. surveys involving use of questionnaires, non-response bias is a sizeable error. It may affect completeness as well as objectivity in data collection as families who cannot be reached after certain attempts during the day may be significantly different from those which can be easily contacted. The non-response error is a serious matter because the direction of the error is generally unknown. One can assume that the non response respondents would each have responded in a given way and therefore can determine the maximum error due to non-response but it is difficult to measure the magnitude of the error. One simple way of minimising this error would be to fix up an appointment before the interview but especially in a country like ours where a large number of respondents do not have access to the telephone, this may not be very practicable.

Response error occurs when the value of the reported variable differs from the actual value of that variable. We world here include errors of both communication and observation. We have already talked about two reasons for response error i.e. inability of the respondent to give accurate information or their unwillingness to give accurate information because of time factor, prestige factor and invasion of primary factor. Let us now discuss the sources of response error related to the investigator and the tools used by him.

a) Inaccurate information due to the investigator

The most common cause of this type of inaccuracy is cheating by the interviewer. There are a number of way in which interviewers deliberately obtain inaccurate information and supply it. If the questionnaire happens to contain a question that the investigator finds embarrassing to ask, he may decide to supply his own answer or supply an inference on what the respondents answer would have been. In extreme cases reports of interviewees' without ever having contacted the interviews have been discovered to be submitted. Another in between situation that is found to exist is that interviewers get their own friends and associates to fill in the questionnaire or respond to a direct interview amid list the responses in the names of the people listed in the sample, thus vitiating the entire sampling exercise.

Experienced marketing research agencies feel that like other petty forms of cheating, interviewer cheating can only be controlled to lower its incidence, it can never be eliminated completely. Care in selection, training and supervision of interviewers can and does help in controlling the incidence of cheating. In addition, certain control procedures like cross checking of small samples of respondents and use to cheater question which disclose the fabricated answers with a fairly high success rate are employed to minimise the incidence of interviewer generated inaccuracy.

b) Ambiguity

Ambiguity which is defined as errors made in interpreting behaviour or words spoken or written is source of error which occurs in both, communication and observation methods of data collection. All languages are capable of being ambiguous as the person transmitting information and the person receiving them are two different people and the interpretation of the question/behaviour may differ from one person to another.

1.6 COLLECTION OF SECONDARY DATA

Sometimes, it is not possible to collect primary data due to time, cost and human resource constraints. Therefore, researchers have to take the help of secondary data. Now let us discuss, (a) various sources from where, one can get secondary data, (b) precautions while using secondary data, its merits and demerits and some documentary and electronic sources of data in India.

1) Documentary Sources of Data

This category of secondary data source may also be termed as Paper Source. The main sources of documentary data can be broadly classified into two categories:

a) Published sources, andb) Unpublished sources.

Let us discuss these two categories in detail.

a) Published Sources

There are various national and international institutions, semi-official reports of various committees and commissions and private publications which collect and publish statistical data relating to industry, trade, commerce, health etc. These publications of various organisations are useful sources of secondary data.

These are as follows:

1) Government Publications: Central and State Governments publish current information along with statistical data on various subjects, quarterly and annually. For example, Monthly Statistical Abstract, National Income Statistics, Economic Survey, Reports of National Council of Applied Economic Research (NCEAR), Federation of Indian Chambers of Commerce and Industry (FICCI), Indian Council of Agricultural Research (ICAR), Central Statistical Organisation (CSO), etc.

2) International Publications: The United Nations Organisation (UNO), International Labour Organisation (ILO), International Monetary Fund (IMF), World Bank, Asian Development Bank (ADB) etc., also publish relevant data and reports.

3) Semi-official Publications: Semi-official organisations like Corporations, District Boards, Panchayat etc. publish reports.

4) Committees and Commissions: Several committees and commissions appointed by State and Central Governments provide useful secondary data. For example, the report of the 10th Financial Commission or Fifth Pay Commissions etc.

5) Private Publications: Newspapers and journals publish the data on different fields of Economics, Commerce and Trade. For example, Economic Times, Financial Express etc. and Journals like Economist, Economic and Political Weekly, Indian Journal of Commerce, Journal of Industry and Trade, Business Today etc. Some of the research and financial institutions also publish their reports annually like Indian Institute of Finance. In addition to this, reports prepared by research scholars, universities etc. also provide secondary source of information.

b) Unpublished SourcesIt is not necessary that all the information/data maintained by the institutions or individuals are available in published form. Certain research institutions, trade associations, universities, research scholars, private firms, business institutions etc., do collect data but they normally do not publish it. We can get this information from their registers, files etc.

2) Electronic Sources

The secondary data is also available through electronic media (through Internet). You can download data from such sources by entering web sites like google.com; yahoo.com; msn.com; etc., and typing your subject for which the information is needed.

1.7 MERITS AND LIMITATIONS OF SECONDARY DATA

Merits

1) Secondary data is much more economical and quicker to collect than primary data, as we need not spend time and money on designing and printing data collection forms (questionnaire/schedule), appointing enumerators, editing and tabulating data etc.

2) It is impossible to individual or small institutions to collect primary data with regard to some subjects such as population census, imports and exports of different countries, national income data etc. but can obtain from secondary data.

Limitations

1) Secondary data is very risky because it may not be suitable, reliable, adequate and also difficult to find which exactly fit the need of the present investigation.

2) It is difficult to judge whether the secondary data is sufficiently accurate or not for our investigation.

3) Secondary data may not be available for some investigations. For example, bargaining strategies in live products marketing, impact of T.V. advertisements on viewers, opinion polls on a specific subject, etc. In such situations we have to collect primary data.

1.8 SELECTION OF APPROPRIATE METHOD FOR DATA COLLECTION

Thus, there are various methods of data collection. As such the researcher must judiciously select the method/methods for his own study, keeping in view the following factors:

1. Nature, scope and object of enquiry: This constitutes the most important factor affecting the choice of a particular method. The method selected should be such that it suits the type of enquiry that is to be conducted by the researcher. This factor is also important in deciding whether the data already available (secondary data) are to be used or the data not yet available (primary data) are to be collected.

2. Availability of funds: Availability of funds for the research project determines to a large extent the method to be used for the collection of data. When funds at the disposal of the researcher are very limited, he will have to select a comparatively cheaper method which may not be as efficient and effective as some other costly method. Finance, in fact, is a big constraint in practice and the researcher has to act within this limitation.

3. Time factor: Availability of time has also to be taken into account in deciding a particular method of data collection. Some methods take relatively more time, whereas with others the data can be collected in a comparatively shorter duration. The time at the disposal of the researcher, thus, affects the selection of the method by which the data are to be collected.

4. Precision required: Precision required is yet another important factor to be considered at the time of selecting the method of collection of data.

1.9 SUMMARY

The pattern of business and industry in the present day environment has become quite complex and involved due to a variety of reasons. Any meaningful decision to be made in this context must be objective and fact based in nature. This is achieved by collecting and analysing appropriate data. Data may broadly be divided into two categories, namely primary data and secondary data. The primary data are those which are collected for the first time by the organisation which is using them. The secondary data, on the other hand, are those which, have already been collected by some other agency but also can be used by the organisation under consideration. Primary data maybe collected by observation, oral investigation, and questionnaire method or by telephone interviews. Questionnaires may be used for data collection by interviewers. They may also be mailed to prospective respondents. The drafting

of a good questionnaire requires utmost skill. The process of interviewing also requires a great deal of tact, patience and, competence to establish rapport with the respondent. Secondary data

are available in various published and unpublished documents. The suitability, reliability, adequacy and accuracy of the secondary data should, however, be ensured before they are used for research problems.

1.10 SELF ASSESSMENT EXERCISE

1) Discuss the main sources of primary and secondary data.

2) What are the limitations associated with the use of secondary data?

3) Examine the merits and limitations of the observation method in collecting data. Illustrate your answer with suitable examples.

4) What are the guiding considerations in the construction of questionnaire? Explain.

5) Examine the merits and limitations of the observation method in collecting material. Illustrate your answer with suitable examples.

6) Discuss interview as a technique of data collection

7) Construct a suitable questionnaire containing not more than twenty five questions pertaining to the sales promotion of your company’s product.

8) Explain the various methods of collecting primary data pointing out their merits and demerits?

1.11 REFERENCES AND FURTHER READINGS

Festinger L.and Katn D. (1953). Research Methods in Behaviuoral Science, Holt, Rillehart and Winston Inc., New York.

Gupta, C.B., & Vijay Gupta. An Introduction to Statistical Methods, Vikas Publishing House Pvt. Ltd., New Delhi.

Kothari, C.R.(2004) Research Methodology Methods and Techniques, New Age International (P) Ltd., New Delhi.

Kumar, R. (1999). Research Methodology: A Step- By- Step Guide for Beginners. Delhi: Sage.

Levin, R.I. and D.S. Rubin. (1999) Statistics for Management, Prentice-Hall of India, New Delhi

Mustafi, C.K.(1981) Statistical Methods in Managerial Decisions, Macmillan, New Delhi

Rao K.V. 1993. Research Methodology in Commerce and Management, Sterling Publishers Private Limited : New Delhi.

Sadhu, A.N. and A. Singh, 1980. Research Methodology in Social Sciences, Sterling Publishers Private Limited : New Delhi.

1.5 MEASUREMENT SCALES

The most widely used classification of measurement scales are: (a) nominal scale; (b) ordinal scale; (c) interval scale; and (d) ratio scale.

(a) Nominal scale: Nominal scale is simply a system of assigning number symbols to events in order to label them. The usual example of this is the assignment of numbers of basketball players in order to identify them. Such numbers cannot be considered to be associated with an ordered scale for their order is of no consequence; the numbers are just convenient labels for the particular class of events and as such have no quantitative value. Nominal scales provide convenient ways of keeping track of people, objects and events. One cannot do much with the numbers involved. For example, one cannot usefully average the numbers on the back of a group of football players and come up with a meaningful value. Neither can one usefully compare the numbers assigned to one group with the numbers assigned to another. The counting of members in each group is the only possible arithmetic operation when a nominal scale is employed. Accordingly, we are restricted to use mode as the measure of central tendency. There is no generally used measure of dispersion for nominal scales.Chi-square test is the most common test of statistical significance that can be utilized, and for the measures of correlation, the contingency coefficient can be worked out.Nominal scale is the least powerful level of measurement. It indicates no order or distance relationship and has no arithmetic origin. A nominal scale simply describes differences between things by assigning them to categories. Nominal data are, thus, counted data. The scale wastes any information that we may have about varying degrees of attitude, skills, understandings, etc.

In spite of all this, nominal scales are still very useful and are widely used in surveys and other ex-post-facto research when data are being classified by major sub-groups of the population.

(b) Ordinal scale: The lowest level of the ordered scale that is commonly used is the ordinal scale. The ordinal scale places events in order, but there is no attempt to make the intervals of the scale equal in terms of some rule. Rank orders represent ordinal scales and are frequently used in research relating to qualitative phenomena. A student’s rank in his graduation class involves the use of an ordinal scale. One has to be very careful in making statement about scores based on ordinal scales.For instance, if Ram’s position in his class is 10 and Mohan’s position is 40, it cannot be said that Ram’s position is four times as good as that of Mohan. The statement would make no sense at all. Ordinal scales only permit the ranking of items from highest to lowest. Ordinal measures have no absolute values, and the real differences between adjacent ranks may not be equal. All that can be said is that one person is higher or lower on the scale than another, but more precise comparisons cannot be made.Thus, the use of an ordinal scale implies a statement of ‘greater than’ or ‘less than’ (an equality statement is also acceptable) without our being able to state how much greater or less. The real difference between ranks 1 and 2 may be more or less than the difference between ranks 5 and 6.Since the numbers of this scale have only a rank meaning, the appropriate measure of central tendency is the median. A percentile or quartile measure is used for measuring dispersion. Correlations are restricted to various rank order methods. Measures of statistical significance are restricted to the non-parametric methods.

(c) Interval scale: In the case of interval scale, the intervals are adjusted in terms of some rule that has been established as a basis for making the units equal. The units are equal only in so far as one accepts the assumptions on which the rule is based. Interval scales can have an arbitrary zero, but it is not possible to determine for them what may be called an absolute zero or the unique origin. The primary limitation of the interval scale is the lack of a true zero; it does not have the capacity to measure the complete absence of a trait or characteristic. The Fahrenheit scale is an example of an interval scale and shows similarities in what one can and cannot do with it. One can say that an increase in temperature from 30° to 40° involves the same increase in temperature as an increase from 60° to 70°, but one cannot say that the temperature of 60° is twice as warm as the temperature of 30° because both numbers are dependent on the fact that the zero on the scale is set arbitrarily at the temperature of the freezing point of water. The ratio of the two temperatures, 30° and 60°, means nothing because zero is an arbitrary point.Interval scales provide more powerful measurement than ordinal scales for interval scale also incorporates the concept of equality of interval. As such more powerful statistical measures can be used with interval scales. Mean is the appropriate measure of central tendency, while standard deviation is the most widely used measure of dispersion. Product moment correlation techniques are appropriate and the generally used tests for statistical significance are the ‘t’ test and ‘F’ test.

(d) Ratio scale: Ratio scales have an absolute or true zero of measurement. The term ‘absolute zero’ is not as precise as it was once believed to be. We can conceive of an absolute zero of length and similarly we can conceive of an absolute zero of time. For example, the zero point on a centimetre scale indicates the complete absence of length or height. But an absolute zero of temperature is theoretically unobtainable and it remains a concept existing only in the scientist’s mind. The number of minor traffic-rule violations and the number of incorrect letters in a page of type script represent scores on ratio scales. Both these scales have absolute zeros and as such all minor traffic violations and all typing errors can be assumed to be equal in significance. With ratio scales involved one can make statements like “Jyoti’s” typing performance was twice as good as that of “Reetu.” The ratio involved does have significance and facilitates a kind of comparison which is not possible in case of an interval scale.Ratio scale represents the actual amounts of variables. Measures of physical dimensions such as weight, height, distance, etc. are examples. Generally, all statistical techniques are usable with ratio scales and all manipulations that one can carry out with real numbers can also be carried out with ratio scale values. Multiplication and division can be used with this scale but not with other scales mentioned above. Geometric and harmonic means can be used as measures of central tendency and coefficients of variation may also be calculated.

Thus, proceeding from the nominal scale (the least precise type of scale) to ratio scale (the most precise), relevant information is obtained increasingly. If the nature of the variables permits, the researcher should use the scale that provides the most precise description. Researchers in physical sciences have the advantage to describe variables in ratio scale form but the behavioural sciences are generally limited to describe variables in interval scale form, a less precise type of measurement.

Summary of the Four Levels of Measurement: Appropriate Descriptive Statistics and Graphs

Level of Measurement

Properties Examples Descriptive statistics

Graphs

Nominal / Categorical

DiscreteArbitrary (no order)

Dichotomous Yes / No Gender

Types / Categories

colour

Frequencies PercentageMode

BarPie

shape

Ordinal / Rank Ordered categoriesRanks

Ranking of favouritesAcademic grades

FrequenciesModeMedian

BarPieStem & leaf

Interval Equal distances between valuesDiscrete (e.g., Likert scale)Metric (e.g., deg. F)Interval scales >5 can usually be treated as ratio

Discrete- Thoughts, behaviours, feelings, etc. on a Likert scaleMetric- Deg. C or F

Frequencies(if discrete)Mode(if discrete)MedianMeanSDSkewnessKurtosis

Bar(if discrete)Pie(if discrete)Stem & LeafBoxplotHistogram(if metric)

Ratio Continuous / Metric / Meaningful 0 allows ratio statements(e.g., A is twice as large as B)

AgeWeightVO2 maxDeg. Kelvin

MeanSDSkewnessKurtosis

HistogramBoxplotStem&Leaf(may need to round leafs