Definitions of research, business research and scientific research, Hallmarks of scientific research, Hypothetico-deductive method, Review of the hypothetico-deductive method, Obstacles to conducting research in management area

1. APPROACHES TO SCIENTIFIC
INVESTIGATION
www.slideshare.net/AhmadHassan244

2. BY:
AHMAD HASSAN
MBA FINANCE
IB&M, UET

3. TOPICS DISCUSSED
 Definitions of research, business research and scientific research
 Hallmarks of scientific research
 Hypothetico-deductive method
 Review of the hypothetico-deductive method
 Obstacles to conducting research in management area

4. RESEARCH
 Research is an inquiry or investigation.
 Process that is organized, systematic, data-based
critical and objective.
 Its purpose is finding solution to a specific problem.
Business Research
 A systematic inquiry that provides information to guide business decisions to make
well informed and timely decisions.

5. SCIENTIFIC RESEARCH
 Scientific research focuses on solving problems.
 It pursues a step-by-step logical and rigorous method.
 scientific research is more objective than subjective.
 It analyzing situational factors surrounding any problem.
 It control phenomena through prediction and explanation.
Identify
Gather
Analyze
Conclusion

6. SCIENTIFIC RESEARCH AND BUSINESS
 Effect of Scientific investigation and managerial decision making.
 It applies to both basic and applied research.
 It enables managers to deal with problem.
 It help managers to state findings with accuracy and confidence.
 Every organization have their R&D department.
Sense Spot Deal

7. HALLMARKS OF SCIENTIFIC
RESEARCH
On next slide

8. HALLMARKS OF SCIENTIFIC RESEARCH
1- Purposiveness
2- Rigor
3- Testability
4- Replicability
5- Precision and
Confidence
6- Objectivity
7- Generalizability
8- Parsimony
We will explain each of these characteristics in the context of the following example: Consider
the case of a manager of P&G who is interested in investigating how employees` commitment
to the organization can be increased.

9. PURPOSIVENESS
 Research must be started with a definite, clear aim, objective and purpose.
 Research findings must be beneficial for organization.
 For example an increase in employee commitment will be beneficial for
organization.
 It will translate into less turnover, less absenteeism, and increased performance
levels.
 Thus it has a purposive focus.

10. RIGOR
 Rigor connotes carefulness during research.
 It also refers to degree of exactitude in research investigations.
 Chosen sample should be true representative of whole organization.
 Method adopted for collecting data should be appropriate.
 Research process should be free from personal and emotional biases.

11. RIGOR
EXAMPLE:
In the case of our example, let us say the manager of an organization asks 10 to 12
of its employees to indicate what would increase their level of commitment to it. If,
solely on the basis of their responses, the manager reaches several conclusions on
how employee commitment can be increased, the whole approach to the
investigation would be unscientific.

12. RIGOR
EXAMPLE (CONTINUED):
It lacks rigor for the following reasons:
 Based on few employees.
 Bias and incorrectness.
 Ignored influences on commitment.

13. TESTABILITY
 Testability refers that hypothesis must be testable.
 Hypotheses are tentative yet testable statements.
 They are derived from theory or theory based.
 It must be able to testify by applying certain statistical tests
experimentally.

14. TESTABILITY
EXAMPLE:
If, after talking to a random selection of employees of the organization and study of
the previous research done in the area of organizational commitment, the manager
or researcher develops certain hypotheses on how employee commitment can be
enhanced. For instance, the researcher might hypothesize that those employees
who perceive greater opportunities for participation in decision making would have
a higher level of commitment. This is a hypothesis that can be tested when the data
are collected.

15. REPLICABILITY
 Results should be supported again and again when the same type of
research is repeated in other similar circumstances.
 Replicability will gain confidence in the scientific nature of our research.
 Replicability brings exactitude and accuracy in research findings.

16. REPLICABILITY
EXAMPLE:
Let us suppose that the manager/researcher, based on the results of the study,
concludes that participation in decision making is one of the most important factors
that influences the commitment of employees to the organization. We will place
more faith and credence in these findings and conclusion if similar findings emerge
on the basis of data collected by other organizations employing the same methods.

17. PRECISION AND CONFIDENCE
PRECISION:
 Precision refers to the closeness of the findings to reality.
 Precision reflects the degree of accuracy of the results .
 We ensures that our findings are close to reality.
CONFIDENCE:
 Confidence refers to probability that our estimations are correct.
 In social sciences, confidence level is 95%.

18. PRECISION AND CONFIDENCE
EXAMPLE:
If a manager estimated the number of production days lost during the year due
to absenteeism at between 30 and 40, as against the actual of 35, the precision of
his estimation compares more favorably than if he had indicated that the loss of
production days was somewhere between 20 and 50.

19. OBJECTIVITY
 The conclusions drawn from information should be objective.
 The findings should be based on the facts and not on subjective or
emotional values.
 The more objective the interpretation of the data, the more scientific the
research investigation becomes.

20. OBJECTIVITY
EXAMPLE:
For instance, if the manager/researcher had a hypothesis that stated that greater
participation in decision making will increase organizational commitment, and this
was not supported by the results, it makes no sense if the manager/researcher
continues to argue that increased opportunities for employee participation would
still help!

21. GENERALIZABILITY
 It refers to the scope of applicability of the research findings in one
organizational setting to other settings.
 The more generalizable the research, the greater its usefulness and value.
 A more elaborate sampling design also doubtlessly increase the generalizability
of the results.

22. GENERALIZABILITY
EXAMPLE:
For instance, if a researcher’s findings that participation in decision making
enhances organizational commitment are found to be true in a variety of
manufacturing, industrial, and service organizations, and not merely in the
particular organization studied by the researcher, then the generalizability of the
findings to other organizational settings is enhanced.

23. PARSIMONY
 Parsimony refers to simplicity in explaining the phenomena or problems that
occur.
 It is Level of understanding in generating solutions for the problems.
 Economy in research models is achieved when we can build a lesser number of
variables.
 Those variables would explain the variance far more efficiently than a complex
set of variables.
 Parsimony can be introduced with a good understanding of the problem and the
important factors that influence it.

24. PARSIMONY
EXAMPLE:
For instance, if two or three specific variables in the work situation are identified,
which when changed would raise the organizational commitment of the
employees by 45%, that would be more useful and valuable to the manager
than if it were recommended that he should change 10 different variables to
increase organizational commitment by 48%. Such an unmanageable number
of variables might well be totally beyond the manager’s control to change.

25. HYPOTHETICO-DEDUCTIVE METHOD
► This typical version of scientific investigation was popularized by the Austrian philosopher
Karl Popper.
► It provides a useful, systematic approach for generating knowledge to solve basic and
managerial problems.

26. SEVEN-STEP PROCESS
 Identify a broad problem area
 Define the problem statement
 Develop hypothesis
 Determine measures
 Data collection
 Data analysis
 Interpretation of data

27. IDENTIFY A BROAD PROBLEM AREA
Following matters could attract the attention of manager to conduct a research
project:
 Drop in sales
 Frequent production interruptions
 Incorrect accounting results
 Low-yielding investments
 Disinterestedness of employees
 Customer switching

28. DEFINE THE PROBLEM STATEMENT
 Scientific research starts with a definite aim or purpose.
 A problem statement stating the general objective and research question of the
research should be developed.
 Information about factors causing problem could also help to narrow down broad
problem area and define problem statement.
 This could also be done a literature review.

29. DEVELOP HYPOTHESIS
 The theoretical framework formulated is often guided by experience and intuition.
 The network of associations between the problem and the variables that affect it
is identified.
 A scientific hypothesis must meet two requirements:
▪ The hypothesis must be testable.
▪ The hypothesis must be falsifiable.

30. DETERMINE MEASURES
 The variables in the theoretical framework should be measurable in some way.
 Some variables cannot be measured quantitatively, such as unresponsive
employees and customer switching, so we need to operationalize these variables.
 Different measurement scales are used to measure variables like likert scale,
nominal scale, ordinal scale etc.

31. DATA COLLECTION
 Data with respect to each variable in the hypothesis need to be obtained.
 Data for each variable form basis for data analysis.
 There are two types of data:
▪ Quantitative data
▪ Qualitative data

32. DATA ANALYSIS
 In this step, the data gathered are statistically analyzed to see if the hypotheses
that were generated have been supported.
 Analyses of both quantitative and qualitative data can be done to determine if
certain relations are important.
EXAMPLE:
For instance, to see if responsiveness of employees affects customers switching, we
might want to do a correlational analysis to determine the relationship between
these variables.

33. INTERPRETATION OF DATA
 Now we must decide whether our hypotheses are supported or not by
interpreting the meaning of the results or the data analysis.
 Based on these results, the researcher would make recommendations in
order to solve the problem in hand.

34. REVIEW OF THE HYPOYHETICO-
DEDUCTIVE METHOD
► Deductive reasoning
► Inductive reasoning

35. DEDUCTION AND INDUCTION
DEDUCTIVE REASONING:
 Deductive reasoning is a process of arriving at a conclusion by applying
known facts or principles to a specific situation.
 It works from the more general to the more specific.
 Sometimes this is informally called a “top down” approach.
 Conclusion follows logically from premises (facts available).

36. DEDUCTION AND INDUCTION
INDUCTIVE REASONING:
 Inductive reasoning is a process in which certain observations are used to
logically establish a general proposition from which we draw a
conclusion.
 It works the other way, moving from specific observations to broader
generalizations and theories.
 Sometimes this is informally called a “bottom up” approach.
 Conclusion is likely based on premises.
 Involves a degree of uncertainty.

37. OBSTACLES TO CONDUCTING
RESEARCH IN MANAGEMENT AREA
On next slide

38. OBSTACLES
 In the management and behavioral areas, it is not always possible to conduct
investigations that are 100 % scientific
 It is due to human behaviour being studied.
 Unlike in the physical sciences, collection of data in the subjective areas of feelings,
emotions, attitudes, and perceptions may not be exact and error-free.
 Sometimes, the obstacles are due to lack of a representative sample, which restricts
the generalizability of the findings

39. QUESTION AND ANSWER SESSION

40. THANK YOU
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