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Elements of Research Design

Elements of Research Design. Stage 5. Prepared By : Mukunda Kumar. The Research Design. The research design involves a series of rational decision-making choices. The various issue involved in the research design: Purpose for the study (exploratory, descriptive, hypothesis testing),

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Elements of Research Design

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  1. Elements of Research Design Stage 5 Prepared By : Mukunda Kumar

  2. The Research Design • The research design involves a series of rational decision-making choices. • The various issue involved in the research design: • Purpose for the study (exploratory, descriptive, hypothesis testing), • its location (i.e., the study setting), • the type it should conform to (type of investigation),

  3. The Research Design • The various issue involved in the research design: • the extent to which it is manipulated and controlled by the researcher (extent of researcher interference), • its temporal aspects (time horizon), and • the level at which the data will be analyzed (unit of analysis), are integral to research design.

  4. Purpose Of The Study: Exploratory, Descriptive • Exploratory Study • An 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. • In such cases, extensive preliminary work needs to be done to gain familiarity with the phenomena in the situation, and understand what is occurring, before we develop a model and set up a rigorous design for comprehensive investigation.

  5. Purpose Of The Study: Exploratory, Descriptive • Exploratory Study • Exploratory 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 a handle on the situation and understand the phenomena. • More rigorous research could then proceed.

  6. Purpose Of The Study: Exploratory, Descriptive • Exploratory Study • Some qualitative studies (as opposed to quantitative data gathered through questionnaires, etc.) where data are collected through observation or interviews, are exploratory in nature. • For example, Henry Mintzberg interviewed managers to explore the nature of managerial work. • Based on the analysis of his interview data, he formulated theories of managerial roles, the nature and types of managerial activities.

  7. Purpose Of The Study: Exploratory, Descriptive • Exploratory Study • Exploratory studies are also necessary when some facts are known, but more information is needed for developing a viable theoretical framework. • For instance, when we want to get at the important factors that influence the advancement of women in organizations, previous studies might indicate that women are increasingly taking on qualities such as assertiveness, competitiveness and independence.

  8. Purpose Of The Study: Exploratory, Descriptive • Exploratory Study • There is also a perception that a judicious blend of masculine and feminine traits – such as being strong but not tough, kind but not soft – is conducive to women’s organizational advancement. • These notions apart, there is a need for interviewing women managers who have made it to the top to explore all the relevant variables.

  9. Purpose Of The Study: Exploratory, Descriptive • Exploratory Study • Exploratory studies are important for obtaining a good grasp of the phenomena of interest and advancing knowledge through subsequent theory building and hypothesis testing.

  10. Purpose Of The Study: Exploratory, Descriptive • Descriptive Study • A descriptive study is undertaken in a order to ascertain and be able to describe the characteristics of the variables of interest in a situation. • A study of a class in terms of the percentage of members who are in their senior and junior years, sex composition, age groupings number of semesters left until graduation, and number of business course taken, can be considered as descriptive in nature.

  11. Purpose Of The Study: Exploratory, Descriptive • Descriptive Study • Descriptive studies are undertaken in organizations to learn about and describe the characteristics of a group of employees, as for example, the age, educational level, job status, and length of service of Hispanics or Asian, working in the system. • Descriptive studies are also undertaken to understand the characteristics of organizations that implement flexible manufacturing system (FMS) or that have a certain debt-to-equity ratio.

  12. Purpose of the Study: Exploratory and Descriptive • The goal of a descriptive study is to offer to the researcher a profile or to describe relevant aspects of the phenomena of interest from: • An individual, • Organizational • Industry-oriented or • Other perspectives.

  13. Purpose Of The Study: Exploratory, Descriptive • Descriptive Study • Description studies that present data in a meaningful form thus help to • (1) understand the characteristics of a group in a given situation, • (2), think systematically about aspects in a given situation, • (3) offer ideas for further probe and research, and/or • (4) help make certain simple decisions (such as how many and what kinds of individuals should be transferred from one department to another).

  14. Purpose Of The Study: Exploratory, Descriptive • Examples of situations warranting a descriptive study • Example 1 • A bank manager wants to have a profile of the individual who have loan payments outstanding for six 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 loan in the future.

  15. Purpose Of The Study: Exploratory, Descriptive • Example 2 • A CEO may be interested in having a description of organizations in her industry that follow the LIFO system. • In this case, the report might include the age of the organizations, their locations, their production levels, assets, sales, inventory levels, suppliers, and profits. • Such information might allow comparison later of the performance levels of specific types of companies.

  16. Type Of Investigation: Casual Versus Correlational • A manager should determine whether a casual or a correlational study is needed to find an answer to the issue at hand. • The former is done when it is necessary to establish a definitive cause-and-effect relationship. • If all that the manager wants is a mere identification of the important factors “associated with the problem, then a correlational study is called for. • In the former case, the researcher is keen on delineating one or more factors that are undoubtedly causing the problem.

  17. Type Of Investigation: Casual Versus Correlational • The intention of the researcher conducting a causal study is to be able to state that variable X causes variable Y. So, when variable X is removed or altered in some way, problem Y is solved. • The study in which the researcher wants to delineate that cause of one or more problems is called a causal study.

  18. Type Of Investigation: Casual Versus Correlational • When the researcher is interested in delineating the important variables associated with the problem, the study is called a correlational study. • Whether a study is a causal or a correlational one depends on the type of research questions asked and how the problem is defined.

  19. Type Of Investigation: Casual Versus Correlational Example 1 The following example will illustrate the difference : A causal study question: • Does smoking cause cancer? A correlation 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?

  20. Type Of Investigation: Casual Versus Correlational Example 2 • Fears of an earthquake predicted recently in the New Madrid fault zone were instrumental (i.e., causal) in an unprecedented number of house owners in the Midwest region taking out an earthquake insurance policy.

  21. Type Of Investigation: Casual Versus Correlational • Example 3 • Increase in interest rates and property taxes, the recession, and the predicted earthquake considerably slowed down the business of real estate agents in the Midwest.

  22. Type Of Investigation: Casual Versus Correlational • In example 2, it indicates a causal relationship between the earthquake prediction and earthquake insurance. • Under Example 3, it indicates the several factors, including the predicted earthquake influenced (not caused) the slowdown of real estate agents’ business. • This is a correlational study, which was not intended to establish a cause-and-effect relationship.

  23. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. • The init of analysis refers to the level of aggregation of the data collected during the subsequent data analysis stage. • 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 have to find out what we can do to raise their motivation.

  24. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. • Here the unit of analysis is the individual. We will be looking at the data gathered from each individual and treating each employee’s response as an individual data source. • If the researcher is interested in studying two – person interactions, then several two-person groups, also known as dyads, will become the unit of analysis.

  25. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. • Analysis of husband- wife interaction in families and supervisor-subordinate relationship at the workplace are good examples of dyads as the unit of analysis. • If the problem statement is related to group effectiveness, then the unit of analysis would be at the group level.

  26. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. • Even though we may gather relevant data from all individual comprising, say, six groups, we would aggregate the individual data into group data so as to see the differences among the six groups. • 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 comparisons made treating the department as the unit of analysis.

  27. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. Example 1 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. • For this purpose, data will have to be collected from each individual staff member and the unit of analysis is the individual.

  28. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. Example 2 Dyads As The Unit Of Analysis • Having read about the benefits of mentoring, a human resources manager wants to first identify the number of employees in three departments of the organization who are in mentoring relationship, and then find out what the jointly perceived benefits (i.e., by both the mentor and one mentored) of such a relationship are.

  29. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. Example 2 Dyads As The Unit Of Analysis • Here, once the mentor and the mentored pairs are identified, their joint perceptions can be obtained by the treating each pair as one unit. • Hence, 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 of subsequent analysis. • Thus, the unit of analysis here is the dyad.

  30. Unit Of Analysis: Individuals, Dyads, Groups, Organizations And Cultures. Example 3 Groups As The Unit Of Analysis • A manger wants to see the patterns of usage of the newly installed information system (IS) by the production, sales, and operations personnel. • Here three group of personel are involved and information on the number of times the IS used by member in each of the three groups as well as other relevant issues will be collected and analyzed. • The final result will indicate the mean usage of the system per day or mouth for each group. Here the unit of analysis is the group.

  31. Time horizon; cross-sectional versus longitudinal studies 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 a studies are called one-shot or cross-sectional studies.

  32. Time horizon; cross-sectional versus longitudinal studies Example 1 • Data were collected from stock brokers between April and June of last year to study their concerns in a turbulent stock market. • Data with respect to this particular research had not been collected before, nor will they be collected again from them for this research.

  33. Time horizon; cross-sectional versus longitudinal studies Example 2 • A drug company desirous of investing in research for a new obesity (reduction) pill conducted a survey among obese 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 asses the likely demand for the new product.

  34. Time horizon; cross-sectional versus longitudinal studies • The purpose of both the studies in the two foregoing examples was to collect data that would be pertinent to find the answer to research question. • Data collection at one point in time was sufficient. Both were cross-sectional designs.

  35. Time horizon; cross-sectional versus longitudinal studies 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 reach question. • The researcher might want to study employees’ behavior before and after a change in the top management, so as to know what effects the change accomplished. • Data are gathered at two different points in time, the study is not cross-sectional or of the one-shot kind, but is carried longitudinally across a period of time.

  36. Time horizon; cross-sectional versus longitudinal studies Example 1 • UPS experienced a shutdown for 15 days during the teamsters’ walkout and their clients shifted their business to other carries such as FedEx and the U.S Postal Service. • After the termination of the strike, UPS tried to woo their customers back through several strategies and collected data month after month to see what progress they were making in this regard.

  37. Time horizon; cross-sectional versus longitudinal studies Example 1 • Here, data were collected every month to asses whether UPS had regained the business volume. • Since data were collected at various points in time to answer the same research questions (have we regained lost ground) the study is a longitudinal.

  38. Time horizon; cross-sectional versus longitudinal studies Example 2 • A marketing manager is interested in tracing the pattern of sales of a particular product in four different regions of country on a quarterly basis for the next years. •  Since data are collected several times to answer the same issue (tracing pattern of sales) the study falls under the longitudinal category.

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