Research Methodology

Research Methodology

Lecture No :15(Sampling Design / Probability vs Non probility)

Recap

Sampling is the process of selecting the right individuals

Sample is used to represent the whole data or population

Sampling process include defining population, sample frame, sampling design, sample size and sampling process

Lecture Objectives

Differentiate between probability and non probability samplingLearn about the types of probability sampling, its advantages and disadvantagesLearn about the types of non probability sampling, its advantages and disadvantagesIssues relevant to sample design and collection

Probability Sampling Unrestricted or simple random sampling

Technique which ensures that each element in the population has an equal chance of being selected for the sample.

The simple random sampling is the least bias and offer the most generalizability.

Probability Sampling

The major advantage of simple random sampling is its simplicity.

The sampling process could become cumbersome and expensive.

Example: Choosing raffle tickets from a drum, computer-generated selections, random-digit telephone dialing.

Simple random sampling


Restricted or complex probability sampling:

It is an alternate to simple random sampling design, several complex probability sampling designs can be used.

Efficiency is improved in that more information can be obtained for a given sample size using the complex probability sampling procedures.


The most common complex probability sampling design 1.Systematic sampling 2.Stratified sampling3.Cluster sampling

1. Area sampling 4.Double sampling

Probability Sampling Systematic Sampling:Technique in which an initial starting point is selected by a random process, after which every nth number on the list is selected to constitute part of the sample.

Sampling interval (SI) = population list size (N) divided by a pre-determined sample size (n)

How to draw: 1) calculate SI, say (200/20)=10 2) select a number between 1 and SI randomly, i.e. 1-10 3) go to this number as the starting point and the item on the list

here is the first in the sample, e.g 3 4) add SI to the position number of this item and the new

position will be the second sampled item, e.g 3+10=13 5) continue this process until desired sample size is reached.

For systematic sampling to work best, the list should be random in nature and not have some underlying systematic pattern.

E.g: Office directory with the Senior Manager, Middle manager .names are listed in each department. This can create as systematic problem

Probability Sampling Stratified Sampling:Technique in which simple random subsamples are drawn from within different strata that share some common characteristic. Within the group they are homogenous and among the group they are heterogeneous.


Stratified SamplingExample: The student body of CIIT is divided into two groups (management science, engineering) and from each group, students are selected for a sample using simple random sampling in each of the two groups, whereby the size of the sample for each group is determined by that groups overall strength.


Cluster SamplingTechnique in which the target population is first divided into clusters. Then, a random sample of clusters is drawn and for each selected cluster either all the elements or a sample of elements are included in the sample.Cluster samples offer more heterogeneity within groups and more homogeneity among groups


Area samplingSpecific type of cluster sampling in which clusters consist of geographic areas such as counties, city blocks, or particular boundaries within a locality. Area sampling is less expensive than most other sampling designs and it is not dependent on sampling frame.Key motivation in cluster sampling is cost reduction.


Area samplingExample: A city map showing the blocks of the city is adequate information to allow the researcher to take a sample of the blocks and obtain data from the resident therein.Example: If you wanted to survey the residents of the city, you would get a city map, take a sample of city blocks and select respondents within each city block.


Single stage and multistage cluster samplingSingle stage cluster sampling involves the division of population into convenient clusters, randomly choosing the required number of clusters as sample subjects, and investigating all the elements in each of the randomly chosen clusters Cluster sampling can also be done in several stages and is then known as multistage cluster sampling.


Example: If we were to do a national survey of the average monthly bank deposits, cluster sampling would be used to select the urban, semi urban and rural geographical location for study. At the next stage particular areas in each of these locations would be chosen. At the third stage, banks within each area would be chosen.Example:


Double sampling:A sampling design where initially a sample is used in a study to collect some preliminary information of interest, and later a subsample of this primary sample is use to examine the matter in more detail.


Double samplingExample: A structured interview might indicate that a subgroup of respondents has more insight into the problems of the organization. These respondents might be interviewed again and again and asked additional questions.

Non-Probability Sampling

Convenience Sampling:Sampling technique which selects those sampling units most conveniently available at a certain point in, or over a period, of time.


Convenience Sampling:Major advantages of convenience sampling is that is quick, convenient and economical; a major disadvantage is that the sample may not be representative.Convenience sampling is best used for the purpose of exploratory research and supplemented subsequently with probability sampling.


Judgment (purposive) Sampling: Sampling technique in which the business researcher selects the sample based on judgment about some appropriate characteristic of the sample members.Example: Selection of certain students who are active in the university activities to inquire about the sports and recreation facilities at the university.

Recap Simple random sampling and restricted

sampling are two basic types of probability sampling.

Probability ( Simple Random, Systematic, Cluster, Single stage/multistage, Double sampling)

Non Probability (Convenience, judgment)


Lecture No : 22 Introduction to SPSS

Recap

Questionnaire checking involves eliminating unacceptable questionnaires.

Editing looks to correct illegible, incomplete, inconsistent and ambiguous answers.

Coding typically assigns numeric codes to answers that do not already have them so that statistical techniques can be applied.

Some times we need to treat the missing values.

Recap Cont.

Cleaning reviews data for consistencies. Inconsistencies may arise from faulty logic, out of range or extreme values.

Statistical adjustments applies to data that requires weighting and scale transformations.

objective

How to use SPSS for Data entry Defining variables Assigning them values Assigning sizes and constraints Data entry using data from coded Questionnaires

How to generate simple descriptive summaries

Job Satisfaction

Intention to Leave


Lecture No :27(Sample Research Project Using SPSS Part -A)

Recap

Hypothesis testing the relationship/Association

Correlations Regression

Objective

Develop a research project from the start Problem definition Importance of research Gap Research objective/ questions Introduction and Literature review Theoretical framework Methodology

Apply SPSS for Data Analysis

Research Area and Problem

Knowledge Projects Knowledge Senior Project Manager do not share their

knowledge

Importance of the issue

Experienced project managers can pass on their knowledge to their juniors which allow them to become better project managers.

Training costs in millions and yet the area focused is seldom achieved but with senior project managers can deliver knowledge which is very pertinent to your customer and your organization.

Organization can gain efficiency and have higher success rate , etc..

Gap

A number of researcher have conducted research to find the antecedents to knowledge sharing (ref ref ..ref..)

Among them some also have explored the knowledge sharing from the cognitive level (ref ., ref ..)

But just one has studied knowledge sharing from the project management aspect and recommends that more research is needed (ref .)

Introduction

What is knowledge What is a project Role of Project manager Specifics of project experience Behavior and Intentions Intentions formation Theory of Reasoned Action

Theory of Reasoned Action

Subjective Norm for sharing PROJECT

knowledge

(Normative Belief & Motivation to Comply)

Intention to share PROJECT knowledge

Attitude towards sharing PROJECT knowledge

Intentions are influenced by attitude and subjective norms

The subjective norms concept is operationalized to have 2 sub dimensions Norms Belief Motivation to Comply

Literature Review Knowledge sharing can be defined as a process of

conveying knowledge from a person to another and also to collect shared knowledge through information and technology (Hwie Seo et al., 2003)..

Riege (2005) lists three dozen of these barriers which need to be addressed in order to implement a knowledge management strategy. One way to understand the effect of these barriers is through the Theory of Reasoned Action (TRA). TRA helps us understand the cognitive process of formation of intentions and it has been successfully used in numerous studies to understand intentions and predict behavior (Sheppard et al., 1998)

One study by tried to study the .knowledge sharing of projects .. and recommended more to be conducted..

Objectives of Research/ Research Questions

To develop a better understanding as to how knowledge sharing behavior is formed IN THE PROJECT MANGERS. Through the cognitive (mental)process of intentions formation Through studying intention difference between different

demographic variables To what extent does attitude influence intentions for

sharing of project knowledge ? To what extent does subjective norms influence intentions

for sharing of project knowledge ? Does attitude for project knowledge mediates the

relationship between subjective norm and intentions ? Is there a difference between the intentions to share

project knowledge and the gender?

Theoretical Framework The attitude towards a specific action will lead to formation

of intentions , which will lead to the behavior .. Knowledge sharing is one such act , if you have attitude

towards sharing then you would also show intent to share. The norms influences the behavior, individual get

influenced by the people around them specially the people who they consider important. If the norms of the important people is to share then and then individuals are influenced by that but it also important that to note that individuals motivation to comply with the norm is also important ins determining the effect norms in an organization

So we theorize that the attitude for sharing ones knowledge on certain ( types )projects would lead to formation intentions to share that knowledge and ultimately it would lead to actual sharing.

So we theorize that the norms for sharing ones knowledge on certain (types) projects in an organization by the important people would lead to formation of intentions to share provided the individual also have motivation to comply to the norms.

Norms have direct impact on intentions and also indirect impact through attitude as well

Schematic Diagram

Subjective Norm for

sharing projects knowledge

Intention to share project

knowledge

Attitude towards sharing project

knowledge

position Nature

Normative Belief Motivation to Comply

Hypotheses H1: The higher the attitude towards projects knowledge sharing the

higher the intentions to share PROJECT knowledge. H2: The higher the subjective norm of projects knowledge sharing the

higher the intentions to share projects knowledge. H3: The higher the subjective norm the higher the attitude to share

projects knowledge H4: The attitude mediates the relationship between subjective norm and

intentions

H5: The women have higher level of sharing their knowledge about projects then men

H6: The project managers permanent /temporary positions at the company would moderate the relationship between attitude and intentions

Methods Population : Senior I.T project managers in the 150

software house of Islamabad. Sample: Randomly select 50 companies and approach

around 150 senior managers to be part of the study. A 5-point Likert scale anchored by strongly disagree (1) to

strongly agree (5) is used. It is ensured that not more than 3 responses per firms are obtained.

Data collection: Adapted Questionnaire from (ref ) personally administered or Mailed

Feel of data ( Descriptive Analysis- Mean, Percentage) Goodness of Data (Reliability and Validity-Cron Bach,

Factor Analysis) Group Difference ( Independent sample T test) Inferential Statistics : Correlations and Regression Analysis

Instrument Attitude Towards PROJECT Knowledge Sharing [Adapted from Bock et al(2005)] To me, sharing PROJECT knowledge with my co-workers is harmful.. To me, sharing PROJECT knowledge with my co-workers is good... To me, sharing PROJECT knowledge with my co-workers is pleasant. To me, sharing PROJECT knowledge with my co-workers is worthless... To me, sharing PROJECT knowledge with my co-workers is wise Affect of Subjective Norm Towards PROJECT Knowledge sharing [Adapted from Bock et al(2005)] My CEO/Head of organization thinks I should share PROJECT knowledge with my coworkers My Boss thinks I should share PROJECT knowledge with my co-worker My colleagues thinks I should share PROJECT knowledge with my co-workers. Generally Speaking, I accept and carry out my CEOs policy and intentions Generally Speaking, I accept and carry out my Boss decision even though it is different form mine ..................................... Generally Speaking, I respect and put in practice my colleagues decisions

Intentions to Share PROJECT Knowledge [Adapted from Bock et al (2005)] If given opportunity, I would share PROJECT knowledge with my co-workers If given opportunity, I would share my work experience with my co-

workers.. If given opportunity, I would share know-how or ticks of the trade with my co-workers. If given opportunity, I would share expertise from education Or training with my co-

workers.. If given opportunity, I would share know-why knowledge from work with my

coworkers...

Demographic: Please provide some personal Information 1. Your gender: Male Female 2. Your age? ____ (in years) 3. Your level of your education? FA/FSc Diploma Bachelor Masters PhD 4-Nature of your Job : Software Development/Support Networking Other( Specify)____________ 5- Your Name: ______________________(* optional) 6- Your Organization:__________________(*optional) 7- Your e-mail : ____________________ ( Interested in receiving the results of this study) Yes No 8- How long have you been working in Information Technology Industry? less than 1 year 1-3 years 4-6 years over 6 years 9-. How long have you been working with this organization? less than 1 year 1-3 years 4-6 years over 6 years 10- Your Position at the company is permanent of contractual Permanent Contractual THANK YOU


Lecture No :30(Research Output Discussions and Report Format)

Objectives

Findings and Discussion section of the research Research Report Layout

Two research articles and their findings would be discussed.

These article have already been partially covered

Now the focus is on the Results/Findings section, conclusion and recommendation sections.

Research Report Layout

Title Introduction A brief literature review Research Questions Theoretical Framework Hypothesis Method section

Study Design (cross sectional , ) Population and Sample

Variables and measures Their reliability and Validity

Data Collection Data Analysis Discussion of Results Recommendations

Research Methodology

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