Business research methods & publishing
RESEARCH DESIGN
Chapter 4
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Elements of Research Design
Refers to the outline, plan, or strategy specifying the procedure to be used in answering research questions
It encompasses many issues.
We need to decide on the different choices.
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To decide for any given situation
the type of investigation needed
the study setting,
the extent of researcher interference
the unit of analysis,
the time horizon of the study
to identify whether a causal or a correlation study would be more appropriate in a given situation
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The Research Design
Types of
Investigation
Establishing:
-Casual
relationship
– Correlation's
– Group
difference
ranks, etc.
Purpose of the
study
Exploratory
Description
Hypotheses
Testing
Extent of
Researcher
interference
Minimal: studying
events as they
normally occur
Manipulation
Study setting
contrived
non-contrived
1. Feel for
data
2.Goofiness
of data
3. Hypothesis
Testing
Units of analysis
(population to be
studied)
individuals
dyads
groups
organizations
machines
etc
Sampling
design
Probability/
Non-probability
Sample size (n)
Time horizon
One-shot
(cross-sectional)
Longitudinal
Data collection
method
Observation
Interview
Questionnaire
Physical
measurement
Un-obstructive
Measurement
& Measures
Operational Definition
scaling
categorizing
coding
Problem Statement
THE PURPOSE OF THE STUDY
Studies can be either exploratory in nature, or descriptive, or they can be conducted to test the hypotheses.
The nature of the study – whether it is exploratory, descriptive or hypothesis testing – depends on the stage to which knowledge about the research topic has advanced.
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The Case Studies, which is an examination of studies done in similar organizational situations, is also a method of solving problems, or for understanding phenomena of interest and generating additional knowledge in that area.
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Exploratory StudyExploratory studies are undertaken to better comprehend the nature of the problem, since very few studies might have been conducted in that area.
Extensive interviews with many people might have to be undertaken to get handle on the situation and to understand the phenomena.
After obtaining a better understanding, more rigorous research proceeds.
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Some qualitative studies (as opposed to quantitative data gathered through questionnaire, etc.) where data are collected through observation or interviews, are exploratory studies in nature.
When the data reveals some pattern regarding the phenomena of interest, theories are developed, and hypotheses formulated for subsequent testing.
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Example: The manager of a firm wants to explore the nature of managerial work (Mintzberg in 1970)
Based on the analysis of his interview data, he formulated theories of managerial roles, the nature and types of managerial activities, and so on.
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Example : What is the role of virtual markets for e – commerce? (in 2005)
The recent development of the internet and the busy lifestyle of the people in the west, lots of the individuals are showing interest in accessing internet.
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Descriptive Study:A descriptive study is undertaken in order to ascertain and be able to describe the characteristics of the variables of interest in a situation.
For instance a study of class in terms of the percentage of members who are in their senior and junior years, gender composition, age groupings, number of semesters until graduation, and number of business courses taken, can only be considered as descriptive in nature.
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Descriptive studies that present data in a meaningful form help:
1. to understand the characteristics of a group in a given situation.
2. to think systematically about aspects in a given situation.
3. offer ideas for further probe and research
4. make certain simple decisions, (such as how many and what type of individuals should be transferred from one department to another).
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Example:
A bank manager wants to have a profile of the individuals who have loan payments outstanding for six months or more. It would include details of their average age, earnings, type of occupation they are in, full time/part time employment status, and the like.
This information might help to ask for further information or make an immediate decision on the types of individuals to whom he would not extend loans in future.
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Example:
The ministry of science and technology wants to know how many projects have failed, what were the reasons. Out of the triple constraints (cost, time, scope) how many failed due to scope constraint.
The information received can help tighten the scope definition process at MOST technology projects.
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Hypotheses Testing:Hypothesis testing is undertaken to explain the variance in the dependent variable or to predict organizational outcomes.
Similar to the kind of examples we had discussed in the theoretical framework chapter.
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Example:
A Marketing manager would like to know whether the sales of the company will increase if he doubles the advertising dollars.
Here, the manager wants to know the nature of the relationship between advertising and sales that can be established by testing the hypothesis.
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H0: There is no relationship between sales and advertisement
Ha: If advertising is increased, then sales will also increase
H0 :ρ = 0
Ha : ρ > 0
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Example: The manager of a manufacturing firm believes that the voluntary turn over is more with its female employees. The manager would like to test the difference between the turnover rates of males and females.
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Ho: There is no difference between the turn over rates of men and women.
Ha: There is a difference between the turn over rates of men and women.
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So exploratory studies are focused on understanding the characteristics of a phenomenon of interest.
A pilot study on small scale interviewing individuals is done (what is an internet club?)
A Descriptive study is when characteristics of the phenomenon are known, and we want to describe it better (How many internet clubs are in the city; how many are open for 24 hours etc.)
A hypothesis testing is when we try to test certain theories (Internet clubs have caused a decline in the social values).
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Types of Investigation: Causal versus Correlation
When the researcher wants to define the cause of one or more problems, then the study is called a Causal Study.
When the researcher is interested to outline the important variables that are associated with the problem, it is called a Correlational Study.
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Example:
A causal study question:
Does smoking cause cancer?
A correlational question:
Is smoking related to cancer?
A causal study hypothesis:
Smoking causes cancer.
A correlational hypothesis:
Smoking and cancer are related.
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Extent of Researcher Interference with the Study
The extent to which the researcher interferes with the normal flow of work at the workplace has direct bearing on whether the study undertaken is causal or correlational.
A correlational study is conducted in the natural environment of the organization, with the researcher interfering minimally with the normal flow of work.
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For example,
if a researcher wants to study the factors influencing training effectiveness
(a correlational study),
the individual simply has to develop a theoretical framework, collect the relevant data, and analyze them to come up with the findings.
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Although there is some disruption to the normal flow of work in the system as the researcher interviews employees and administers questionnaire at the workplace, the researcher’s interference in the system is minimal compared with that in causal studies.
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In case of causal study, the researcher would try to manipulate certain variables so as to study the effect on the dependent variable
Example: Effect of lighting on employee performance.
Here, the researcher's interference is high.
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Study Setting: Contrived and Non-contrived
Organizational research can be done in the natural environment where work proceeds normally (i.e., in non-contrived setting) or in artificial, contrived settings.
Correlational studies are invariably conducted in non-contrived settings, whereas rigorous causal studies are done in contrived lab setting.
Correlational studies done in organizations are called field studies.
(factors influencing a call center’s employees’ turn over).
Studies to establish cause and effect relationships using the same natural environment in which employees normally function are called field experiments.
Example:
employees who have been given recognition and employee who have not been given recognition.
Cause effect studies in contrived environment in which the environment extraneous factors are controlled are termed as lab experiments.
Example:
Select all new employees with the same scores in the entry test and provide one group training and the other no training and controlling that they are not exposed to any senior employee who could guide them.
Unit of Analysis: Individuals, Dyads, Groups, Organizations, Cultures
The unit of analysis refers to the level of aggregation of the data collected during the subsequent data analysis stages.
Individuals: If the problem statement focuses on how to raise the motivational levels of employees in general, then we are interested in individual employees in the organization and would like to find out what we can do to raise their motivation.
Here the unit of analysis is the individual (managers’ perception on the factors which influence the success of the project).
Dyads: If the researcher is interested in studying two-person interactions, then several two-person groups are known as dyads and will become unit of analysis.
For example, analysis of husband-wife(are they satisfied with the education provided by the school) in families.
Groups: If the problem statement is related to group effectiveness, however, then obviously the unit of analysis would be at group level.
For example, if we wish to study group decision-making patterns, we would probably examine such aspects as group size, group structure, cohesiveness, and the like, in trying to explain the variance in group decision making.
In such cases the unit of analysis will be groups (e.g. use of IT by different departments).
Organizations: If we compare different departments in the organization, then the data analysis will be done at the departmental level – that is, the individuals in the department will be treated as one unit and comparison made treating the department as the unit of analysis.
(Conservation of energy initiatives by public and private organizations).
Cultures: If we want to study cultural differences among nations, we will have to collect data from different countries and study the underlying patterns of culture in each country. Here the unit of analysis used will be cultures.
(Moral values of Eastern vs Western cultures)
Time Horizon: Cross-sectional versus Longitudinal
Cross-Sectional Studies
A study can be done in which data are gathered just once, perhaps over a period of days or weeks or months, in order to answer a research question. Such studies are called one-shot or cross-sectional studies.
(data collected from project managers and their psychological well being between October till December)
Longitudinal Studies
In some cases, the researcher might want to study people or phenomena at more than one point in time in order to answer the research question. For example, the researcher might want to study employees behavior before and after a change in the top management, to learn the effects of change.
Or when data on the dependent variable are gathered at two or more points in time to answer the research question, are called longitudinal studies. (use of electricity by a city in summers and then in winters).
Scenarios
Following are some scenarios , for each indicate how researcher should proceed, giving the following reasons:
Purpose of the study
Type of investigation
Researcher Interference
Study setting
Time Horizon
Unit of analysis
