Lecture-2 (Ch. 2, Uma).pdf....,.........
- 1. 1 The definition of research ◼ Research is an organized, systematic, data-based, critical, objective, scientific inquiry into a specific problem that needs a solution. ◼ Managerial decisions based on the results of scientific research tend to be effective.
- 2. 2 What is Meant by a Scientific Research? ◼ Scientific research focuses on solving problems and pursues a step-by-step logical, organized, and rigorous/exact method to identify the problems, gather data, analyze them, and draw valid conclusions . ◼ Thus, scientific research is not based on guesses, experience, and intuition (though these may play a part in final decision making), but a purposive and rigorous/carefulnes.
- 3. 3 What is Meant by a Scientific Research? ◼ Scientific research helps researchers to state their findings with accuracy and confidence. ◼ This helps various other organizations to apply those solutions when they encounter similar problems.
- 4. 4 The Characteristics of Good Research ◼ The Hallmarks or main distinguishing characteristics of scientific research may be listed as follows: 1. Purposiveness 5. Precision 2. Rigor 6. Objectivity 3. Testability 7. Generalizability 4. Replicability 8. Parsimony
- 5. 5 The Hallmarks of Good Research We will explain each of these characteristics in the context of the following example: Consider the case of a manager who is interested in investigating how employees’ commitment to the organization can be increased.
- 6. 6 1. Purposiveness ◼ The manager has started the research with a definite aim or purpose. ◼ The focus is on increasing the commitment of employees to the organization, as this will be a beneficial in many ways. ◼ An increase in employee commitment will translate into less turnover, less absenteeism, and increased performance levels, all of which would definitely benefit the organization.
- 7. 7 2. Rigor ◼ A good theoretical base and a sound methodological design would add rigor to a purposive study. ◼ Rigor means carefulness, and the degree of exactitude/accuracy in research investigations.
- 8. 8 In the case of our example of increasing the commitment of employees: ◼ Let us say that the manager of an organization asks 10 of its employees to indicate what would increase their level of commitment to the organization. ◼ If the manager depends solely on the basis of their responses reaches to several conclusions on how employee commitment can be increased, the whole approach to the investigation would be unscientific.
- 9. 9 An approach to an investigation would lack rigor for the following reasons: 1. Incorrect conclusions because they are based on the responses of just a few employees (lacks of methodological sophistication). 2. the manner of framing and addressing the questions could have introduced bias in the responses (lacks of methodological sophistication). 3. There might be many other important influences on organizational commitment that this small sample did not verbalize during the interviews, and the researcher would have failed to include them (lacks of a good theoretical framework). Conclusions drawn from an investigation that lacks a good theoretical framework and methodological sophistications would be unscientific.
- 10. 10 3. Testability ◼ After taking random selection of employees of the organization, and the study of previous research done of the area of organizational commitment, the researcher develops certain hypotheses on how employee commitment can be enhanced. Then these hypotheses can be tested by applying certain statistical tests to the data collected for the purpose. ❖ Scientific research tends itself to testing logically developed hypotheses to see whether or not the data support the hypotheses that are developed.
- 11. 11 4. Replicability ◼ The results of the tests of hypotheses should be supported again and again when the same type of research is repeated in other similar circumstances. ◼ If the results are repeated, we will gain confidence in the scientific nature of our research.
- 12. 5. Precision and Confidence ◼ Precision refers to the closeness of the findings to reality based on a sample. ◼ Precision reflects the degree of accuracy of the results on the basis of the sample, to what really exists in the universe. 12
- 13. 13 Precision and Confidence ◼ In business research, we are not able to draw “definitive” conclusions on the basis of the results of data analysis. The reasons are: 1. We have to base our findings on a sample that we draw from the universe. The sample may not reflect the exact characteristics of the phenomenon we try to study. 2. Measurement errors and other problems are bound to introduce an error in our findings.
- 14. 14 Precision and Confidence ◼ We would like to design the research in a manner that ensures that our findings are as close to reality as possible, so that we can place reliance or confidence in the results.
- 15. 15 Precision and Confidence ◼ Confidence refers to the probability that our estimations are correct. ◼ It is not enough to be precise, but it is also important that we can confidently claim that 95% of the time our results would be true and there is only a 5% chance of our being wrong. This is also known as confidence level. ❖ The greater the precision and confidence we aim at in our research, the more scientific is the investigation and the more useful are the results.
- 16. 16 6. objectivity ◼ The conclusions drawn through the interpretation of the results of data analysis should be objective. ◼ The conclusions should be based on the facts of the findings derived from actual data, and not on our own subjective or emotional values. ❖ The more objective the interpretation of the data, the more scientific the research investigation becomes.
- 17. 17 7. Generalizability ◼ Generalizability refers to the scope of applicability of the research findings in one organizational setting to other settings. ❖ The wider the range of applicability of the solutions generated by research, the more useful the research is to the users.
- 18. 18 8. Parsimony ◼ Parsimony refers to simplicity in explaining the phenomena or problems that occur, and in generating solutions for the problems. ◼ Economy in research models is achieved when we can build into our research framework a lesser number of variables that would explain the variance far more efficiently than a complex set of variables that would only marginally add to the variance explained.
- 19. 19 Parsimony/Closeness ◼ Parsimony can be introduced with a good understanding of the problem and the important factors that influence it. ◼ A good conceptual theoretical model can be realized through interviews with the concerned people, and a thorough literature review of the previous research work in the particular problem area.