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The Research Process: Elements of Research Design

CHAPTER 5

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Chapter Objectives Understand the different aspects relevant

to designing a research study. Identify the scope of any given study and

the end use of the results. Describe the type of investigation needed,

the study setting, the extent of researcher interference, the unit of analysis, and the time horizon of the study.

Identify which of the two, a causal or a correlational study, would be more appropriate in a given situation.

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The Research Design In this step we need to design

the research in a way that the requisite data can be gathered and analyzed to arrive at a solution.

The research design was originally presented in a simple manner in the next Figure.

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Research Design

©2009 John Wiley & Sons Ltd.

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Purpose of the Study

Exploration Description Hypothesis Testing

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Purpose of the Study

Exploratory study: is undertaken when not much is

known about the situation at hand, or no information is available on how similar problems or research issues have been solved in the past.

Example: A service provider wants to know why

his customers are switching to other service providers?.

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Purpose of the Study Descriptive study:

is undertaken in order to ascertain and be able to describe the characteristics of the variables of interest in a situation.

Example: A bank manager wants to have a profile of the

individuals who have loan payments outstanding for 6 months and more. It would include details of their average age, earnings, nature of occupation, full-time/part-time employment status, and the like. This might help him to elicit further information or decide right away on the types of individuals who should be made ineligible for loans in the future.

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Purpose of the Study

Hypothesis testing: Studies that engage in hypotheses

testing usually explain the nature of certain relationships, or establish the differences among groups or the independence of two or more factors in a situation.

Example: A marketing manager wants to know

if the sales of the company will increase if he doubles the advertising dollars.

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Type of Investigation

Causal Study it is necessary to establish a definitive

cause-and-effect relationship. Correlational study

identification of the important factors “associated with” the problem.

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Study Setting

Contrived: artificial setting

Non-contrived: the natural environment where work proceeds normally

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Examples A causal study question: Does smoking cause cancer? A correlational study question: Are smoking and cancer related? Or Are smoking, drinking, and chewing

tobacco associated with cancer? If so, which of these contributes most to

the variance in the dependent variable?

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Example: causal relationship Fears of an earthquake predicted

recently in an area were a causal of a number of crashes of some houses in the area in order to be eligible of insurance policy.

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Example: correlational relationship Increases in interest rates and

property taxes, the recession, and the predicted earthquake considerably slowed down the business of real state agents in the country.

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Extent of Researcher InterferenceWith the Study

The extent of interference by the researcher with the normal flow of work at the workplace has a direct bearing on whether the study undertaken is causal or correlational.

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Extent of Researcher InterferenceWith the Study

A correlational study is conducted in the natural environment of the organization with minimum interference by the researcher with the normal flow of work.

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Extent of Researcher InterferenceWith the Study In studies conducted to establish cause-

and-effect relationships, the researcher tries to manipulate certain variables so as to study the effects of such manipulation on the dependent variable of interest.

In other words, the researcher deliberately changes certain variables in the setting and interferes with the events as they normally occur in the organization.

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Minimal Interference Example A hospital administrator wants to

examine the relationship between the perceived emotional support in the system and the stress experienced by the nursing staff. In other words, she wants to do a correlational study.

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Example (Cont.) The researcher will collect data from the

nurses ( through a questionnaire) to indicate how much emotional support they get in the hospital and to what extent they experience stress. By correlating the two variables, the answer is found.

In this case, beyond administering a questionnaire to the nurses, the researcher has not interfered with the normal activities in the hospital.

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Moderate Interference If the researcher wants to establish

a causal connection between the emotional support in the hospital and stress, or, wants to demonstrate that if the nurses had emotional support, this indeed would cause them to experience less stress.

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Moderate Interference To test the cause-and-effect

relationship, the researcher will measure the stress currently experienced by the nurses in three wards in the hospital, and then deliberately manipulate the extent of emotional support given to the three groups of nurses in the three wards for perhaps a week, and measure the amount of stress at the end of that period.

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Moderate Interference For one group, the researcher will

ensure that a number of lab technicians and doctors help and comfort the nurses when they face stressful events.

For a second group of nurses in another ward, the researcher might arrange for them only a moderate amount of emotional support and employing only the lab technicians and excluding doctors.

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Moderate Interference The third ward might operate without

any emotional support. If the experimenter’s theory is

correct, then the reduction in the stress levels before and after the 1-week period should be greater for the nurses in the first ward, moderate for those in the second ward, and nil for the nurses in the third ward.

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Moderate Interference We find that not only does the researcher

collect data from nurses on their experienced stress at two different points in time, but also manipulated the normal course of events by deliberately changing the amount of emotional support received by the nurses in two wards, while leaving things in the third ward unchanged.

Here, the researcher has interfered more than minimally.

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Excessive Interference Example IF the researcher feels, after conducting the

previous experiments, that the results may not be valid since other external factors might have influenced the stress levels experience by the nurses.

For example, during that particular experimental week, the nurses in one or more wards may not have experienced high levels of stress because there were no serious illnesses or deaths in the ward. Hence the emotional support received might not be related to the level of stresses experienced.

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Excessive Interference The researcher want to make sure

that such external factors that might affect the cause-and-effect relationship are controlled.

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Controlling the External factors The researcher might take three groups of

medical students, put them in different rooms, and confront all of them with the same stressful task.

For example, he might ask them to describe in detail, the surgical procedures in performing surgery on a patient who has not responded to chemotherapy and keep asking them with more and more questions.

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Controlling the External factors Although all are exposed to the same

intensive questioning, one group might get help from a doctor who voluntarily offers clarifications and help when students stumble.

In the second group, a doctor might be nearby, but might offer clarifications and help only if the group seeks it.

In the third group, there is no doctor present and no help is available.

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Controlling the External factors In the above example, not only is the

support manipulated, but even the setting in which this experiment is conducted is artificial inasmuch as the researcher has taken the subject away from their normal environment and put them in a totally different setting.

The researcher has intervened maximally with the normal setting, the participants, and their duties.

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Excessive Interference The extent of researcher interference

would depend on whether the study is correlational or causal and also the importance of establishing causal relationship beyond any doubt.

Most organizational problems seldom call for a causal study, except in some market research areas.

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Study Setting: Contrived and Noncontrived Correlational studies are

conducted in noncontrived settings (normal settings), whereas most causal studies are done in contrived settings.

Correlational studies done in organizations are called field studies.

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Study Setting: Contrived and Noncontrived Studies conducted to establish cause-

and-effect relationship using the same natural environment in which employees normally function are called field experiments.

Experiments done to establish cause-and- effect relationship in a contrived environment and strictly controlled are called lab experiments.

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Example: Field Study A bank manager wants to analyze the

relationship between interest rates and bank deposit patterns of clients.

The researcher tries to correlate the two by looking at deposits into different kinds of accounts (such as savings, certificates of deposit, and interest-bearing checking accounts) as interest rates changed.

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Example: Field Study This is a field study where the bank

manager has taken the balances in various types of accounts and correlated them to the changes in interest rates.

Research here is done in a noncontrived setting with no interference with the normal work routine.

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Example: Field Experiment The bank manager now wants to

determine the cause-and-effect relationship between interest rate and the inducements it offers to clients to save and deposit money in the bank. The researcher selects four branches within 60/km radius for the experiment.

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Example: Field Experiment For 1 week only, he advertises the annual

rate for new certificates of deposit received during that week. The interest rate would be 9% in one branch, 8% in another, and 10% in the third. In the fourth branch, the interest rate remains unchanged at 5%. Within the week, the researcher would be able to determine the effects, if any, of interest rates on deposit mobilization.

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Example: Field Experiment This example would be a field experiment

since nothing but the interest rate is manipulated, with all activities occurring in the normal and natural work environment.

Hopefully, all four branches chosen would be compatible in size, number of depositors, deposit patterns, and the like, so that the interest-savings relationships are influenced by some third factor.

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Example: Lab Experiment To be sure about the true relationship

between the interest rate and deposits, the researcher could create an artificial environment by choosing, for instance, 40 students who are all business majors in their final year of study and in the same age. The researcher splits the students into four groups and give each one of them $1000, which they are told they might buy their needs or save for the future, or both.

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Example: Lab Experiment The researcher offers them interest on what

they save as followings: 6% on savings for group 1. 8% for group 2. 9% for group 3. 1% for group 4 ( the old rate of interest). Here, the researcher has created an artificial

laboratory environment and has manipulated the interest rates for savings. He also chosen subjects with similar backgrounds.

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Population to be Studied

Unit of analysis: Individuals Dyads Groups Organizations Cultures

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Unit of Analysis: Individual If the researcher focuses on how

to raise the motivational levels of employees, then we are interested in individual employees in the organization. Here the unit of analysis is the individual (the data will be gathered from each individual).

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Unit of Analysis: Dyads If the researcher is interested in

studying two-person interaction, then several two-person groups also known as dyads, will become the unit of analysis ( analysis of husband-wife, and supervisor-subordinate relationships at the work place.

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Unit of Analysis Groups as a unit of analysis Organizations as a unit of analysis

Cultures as a unit of analysis

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Example: Individuals as The Unit of Analysis The Chief Financial Officer of a

manufacturing company wants to know how many of the staff would be interested in attending a 3-day seminar on making appropriate investment decisions.

Data will have to be collected from each individual staff member and the unit of analysis is individual.

The unit of analysis is the individual.

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Example: Dyads as the Unit of Analysis A human resources manager wants

to first identify the number of employees in three departments of the organization who are in mentoring relationships, and then find out what the jointly perceived benefits of such a relationship are.

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Example: Dyads as the Unit of Analysis Once the mentor and the mentored pairs

are identified, their joint perceptions can be obtained by treating each pair as one unit.

If the manager wants data from a sample of 10 pairs, he will have to deal with 20 individuals, a pair at a time. The information obtained from each pair will be a data point for subsequent analysis.

Thus, the unit of analysis is the dyad.

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Example: Groups as Unit of Analysis A manager wants to see the patterns of

usage of the newly installed Information System (IS) by the production, sales, and operations personnel.

Here three groups of personnel are involved and information on the number of times the IS is used by each member in each of the three groups as well as other relevant issues will be collected and analyzed.

Here the unit of analysis is the group.

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Example: Divisions as the Unit of Analysis Johnson & Johnson company wants to see

which of its various divisions (soap, shampoo, body oil, etc.) have made profits of over 12% during the current year.

Here, the profits of each of the divisions will be examined and the information aggregated across the various geographical units of the division.

The unit of analysis will be the division, at which level the data will be aggregated.

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Example: Industry as the Unit of Analysis An employment survey specialist wants to

see the proportion of the workforce employed by the health care, transportation, and manufacturing industries.

The researcher has to aggregate the data relating to each of the subunits comprised in each of the industries and report the proportions of the workforce employed at the industry level.

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Example: Industry as the Unit of Analysis The health care industry, for instance,

includes hospitals, nursing homes, small and large clinics, and other health care providing facilities.

The data from these subunits will have to be aggregated to see how many employees are employed by the heath care industry.

This will need to be done for each of the other industries.

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Example: Countries as the Unit of Analysis The Chief Financial Officer (CFO) of

a multinational corporation wants to know the profits made during the past 5 years by each of the subsidiaries in England, Germany, and France. It is possible that there are many regional offices of these subsidiaries in each of these countries.

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Example: Countries as the Unit of Analysis The profits of the various regional

centers for each country have to be aggregated and the profits for each country for the past 5 years provided to the CFO.

The data will now have to be aggregated at the country level.

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Time Horizon

Cross-sectional studies Snapshot of constructs at a single point in time Use of representative sample

Multiple cross-sectional studies Constructs measured at multiple points in time Use of different sample

Longitudinal studies Constructs measured at multiple points in time Use of same sample = a true panel

.

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Time Horizon: Cross-Sectional Versus Longitudinal Studies Example Data were collected from stock

brokers between April and June of last year to study their concerns in a turbulent stock market.

Data has to be collected at one point in time. It is a cross-sectional design.

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Time Horizon: Cross-Sectional Versus Longitudinal Studies Example A drug company desirous of investing

in research for a new headache pill conducted a survey among headachy people to see how many of them would be interested in trying the new pill.

This is a one-shot or cross-sectional study to assess the likely demand for the new product.

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Time Horizon: Cross-Sectional Versus Longitudinal Studies Longitudinal Studies Studying people or phenomena at

more than one point in time in order to answer the research question.

Because data are gathered at two different points in time, the study is not cross-sectional kind, but is carried longitudinally across a period of time.

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Example A marketing manager is interested in

tracing the pattern of sales of a particular product in four different regions of the country on a quarterly basis for the next 2 years.

Since the data are collected several times to answer the same issue, the study falls under the longitudinal category.

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Time Horizon: Cross-Sectional Versus Longitudinal Studies Longitudinal studies take more time and

effort and cost more than cross-sectional studies. However, well-planned longitudinal studies could help to identify cause-and-effect relationships.

For example, one could study the sales volume of a product before and after an advertisement, and provided other environmental changes have not impacted on the results, one could attribute the increase in the sales volume, if any, to the advertisement.

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Exercise A supervisor thinks that the low

efficiency of the machine tool operators is directly linked to the high level of fumes emitted in the workshop. He would like to prove this to his supervisor through a research study.

1. Would this be a causal or a correlational study? Why?

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Exercise 2. Is this an exploratory, descriptive, or

hypothesis-testing (analytical or predictive) study? Why?

3. What kind of study would this be: field study, lab experiment, or field experiment? Why?

4. What would be the unit of analysis? Why?

5. Would this be a cross-section or a longitudinal study? Why?

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Answers to the Exercise1. This would be a causal study because the

operator wants to prove to the supervisor that the fumes are causing operators to be low in their efficiency. In other words, the machine tool operator is trying to establish the fact that fumes cause low efficiency in workers.

2. This is an analytical study because the machine tool operator wants to establish that fumes cause low efficiency and convince his workshop supervisor through such analysis (i.e. establish cause and effect relationship).

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Answers to the Exercise3. This would be a field experiment. Though the

study would be set up in the natural environment of the workers where the work is normally done, the amount of fumes will have to be manipulated while other factors such as atmospheric pressure may have to be controlled. Because of the location of the study, it will be a field experiment.

4. The unit of analysis would be the individual operators. The data will be collected with respect to each operator and then the conclusions will be made as to whether the operators are less efficient because of the fumes emitted in the workshop.

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Answers to the Exercise5. This would be a longitudinal study

because data will be gathered at more than one point in time. First, the efficiency of the operators would be assessed at a given rate of fume emission. Then the fumes emitted would be manipulated to varying degrees, and at each manipulation, the efficiency of the workers would again be assessed to confirm that the high rate of fume emission causes a drop in operators’ efficiency.

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Answers to the Exercise6. This would be a longitudinal study

because data will be gathered at more than one point in time. First, the efficiency of the operators would be assessed at a given rate of fume emission. Then the fumes emitted would be manipulated to varying degrees, and at each manipulation, the efficiency of the workers would again be assessed to confirm that the high rate of fume emission causes a drop in operators’ efficiency.