Chapter 1 - Introduction to Research.ppt
- 1. CHAPTER 1 : INTRODUCTON TO RESEARCH MGT 648 – RESEARCH METHODS
- 2. CHAPTER 1 • INTRODUCTON TO RESEARCH • 1.1 Definition and importance of research • 1.2 Qualitative and quantitative research • 1.3 Types of Research – Basic and Applied • 1.4 Characteristics of a good research • 1.5 Overview of the research process 1–2
- 3. 1. Describe what research is and how it is defined. 2. Understand the difference between basic and applied business research 3. Understand the characteristics of a good research 1–3 After studying this chapter, you should: LEARNING OUTCOMES:
- 4. SOME COMMONLY RESEARCHED AREAS IN BUSINESS • Employee behaviors – performance, absenteeism, and turnover • Employee attitudes – job satisfaction, loyalty, and organizational commitment • Supervisory performance, managerial leadership style, and performance appraisal systems • Employee selection, recruitment, training and retention • Validation of performance appraisal systems • Brand loyalty, product life cycle, and product innovation 1–4
- 5. CONTINUE.. • Risk assessment, exchange rate fluctuations and foreign investment • Development of effective cost accounting procedures • Organizational outcomes – increased sales, market share, profits, growth and effectiveness • Consumer complaints • Cost of capital, valuation of firms, divided profits, and investment decisions • Cultural differences and the dynamics of managing a multinational firm 1–5
- 6. DEFINITION OF RESEARCH • An organized, systematic, data-based, critical, objective, scientific inquiry or investigation into a specific problem, undertaken with the purpose of finding answers or solution to it (Sekaran, 2003) • Research provides the needed information that guides managers to make informed decision to successfully deal with problems (Sekaran, 2003) • The process of thoroughly studying and analysing the situational factors surrounding a problem in order to seek solutions to it (Cavana, Delahaye, & Sekaran, 2001) • One of the ways to find answers to your questions (Kumar, 2005) 1–6
- 7. QUANTITATIVE RESEARCH • An organized method for conducting deductive logic with precise empirical observations of individual behaviour in order to discover and confirm a set of probabilistic causal laws that can be used to predict general patterns of human activity (Neuman, 1997)
- 8. QUALITATIVE RESEARCH • The systematic analysis of socially meaningful action through the direct detailed observation of people in natural settings in order to arrive at understandings and interpretations of how people create and maintain their social worlds (Newman, 1997)
- 10. DEDUCTION • Deduction is the process by which the researcher begins with a theoretical proposition and then moves towards concrete empirical evidence • For example: We may theorise that all high performers are highly efficient in their job • We would gather data on the two concepts (for example a psychological questionnaire measuring efficiency in specific tasks, and a measure of performance based on the number of items produced) and then conduct a correlational analysis
- 12. INDUCTION • Induction is a process by which we observe certain phenomena and arrive a certain conclusion • The researcher begins with detailed observations of the world and moves towards more theoretical generalizations and ideas • In induction, we establish a general proposition logically based on observed facts
- 13. APPLIED AND BASIC RESEARCH • Applied research • conducted to address a specific business decision for a specific firm or organization. • Solve a current problem faced by the manager in the work setting • Research done with the intention of applying the results of the findings to solve specific problems currently being experienced in the organization 1–13
- 14. APPLIED RESEARCH • Example: • Should McDonald’s add Italian pasta dinners to its menu? • Which health insurance plan should a business provide for its employees? 1–14
- 15. APPLIED AND BASIC RESEARCH • Basic research (also called pure research) • conducted without a specific decision in mind that usually does not address the needs of a specific organization. • Attempts to expand the limits of knowledge in general. • Not aimed at solving a pragmatic problem. • To generate a body of knowledge by trying to comprehend how certain problems that occur in organization can be solved • Research done chiefly to enhance the understanding of certain problems that commonly occur in organizational settings, and seek methods of solving them 1–15
- 16. BASIC RESEARCH (ALSO CALLED PURE RESEARCH) • Example: • Do consumers experience cognitive dissonance in low- involvement situations? • Does employee tenure with a company influence productivity? 1–16
- 17. CHARACTERISTICS OF A GOOD RESEARCH • Purposiveness • Rigor • Testability • Replicability • Precision and Confidence • Objectivity • Generalizability • Parsimony 1–17
- 18. PURPOSIVENESS • A definite aim or purpose • For instance • Increasing the commitment of employees to the organization • Benefits • Less turnover • Less absenteeism • Increased performance levels 1–18
- 19. RIGOR (RIGID, STRICT) • Rigor connotes – carefulness in research investigation • Rigorous research – involves a good theoretical base and a carefully thought-out methodology • Rigor in research design makes possible the achievement of the other six characteristics of a good research 1–19
- 20. CONTINUE • Poor research • The conclusions would be incorrectly drawn – findings may not be representative of those of entire population • The manner of framing and addressing the questions could have introduced bias or incorrectness in the responses • There might be many other important variables would have failed to include them 1–20
- 21. TESTABILITY • Hypotheses can be tested by applying certain statistical rests to the data collected • Results – accepted or rejected 1–21
- 22. REPLICABILITY • The results of the tests of hypotheses should be supported again and yet again when the same type of research is repeated in other similar circumstances. • The hypotheses would not have been supported by chance, but are reflective of the true state of affairs in the population 1–22
- 23. PRECISION & CONFIDENCE • Precision – the closeness of the findings to “reality” based on a sample • Precision reflects the degree of accuracy or exactitude of the results on the basis of the sample, to what really exists in the universe • Confidence – the probability that our estimations are correct • Confident level of 95% - claims that 95% of the time the results would be true and there is only 5% chance of being wrong 1–23
- 24. OBJECTIVITY • The conclusions drawn through the interpretation of the results of data analysis should be objective • Should be based on the facts of the findings derived from actual data, and not on our own subjective or emotional values • For example – if we 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 researcher continues to argue that increased opportunities for employee participation would still help 1–24
- 25. PARSIMONY (VERY CAREFUL IN USING RESOURCES) • Simplicity in explaining the phenomena or problems that occur, and in generating solutions for the problems, is always preferred to complex research frameworks that consider an unmanageable number of factors • Parsimony can be introduced with a good understanding of the problem and the important factors that influence it 1–25
- 26. GENERALIZABILITY • Generalizability – 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 • The more generalizable the research, the greater its usefulness and value • For wider generalizability, the research sampling design has to be logically developed and a number of other details in the data-collection methods need to be meticulously followed 1–26
- 27. OVERVIEW OF A RESEARCH PROCESS • The Seven-Step Process in the Hypothetico- Deductive Method • Identify a broad problem area • Define the problem statement • Develop hypotheses • Determine measures • Data collection • Data analysis • Interpretation of data © 2012 John Wiley & Sons Ltd. www.wiley.com/college/sekaran
- 28. IDENTIFY A BROAD PROBLEM AREA • A drop in sales, frequent production interruptions, incorrect accounting results, low-yielding investments, disinterestedness of employees in their work, customer switching, and the like, could attract the attention of the manager and catalyze the research project 1–28
- 29. DEFINE THE PROBLEM STATEMENT • Scientific research starts with a definite aim or purpose • Gathering initial information about the factors that are possibly related to the problem will help the researcher to narrow the broad problem area and to define the problem statement • Preliminary information gathering involves the seeking of information in depth, of what is observed (for instance, the observation that the company is losing customers). • This could be done by a literature review (literature on customer switching) or by talking to several people in the work setting, to clients (why do they switch?), or to other relevant sources, thereby gathering information on what is happening and why. • This allow the researcher to develop a specific problem statement. 1–29
- 30. DEVELOP HYPOTHESES • Varibales are examined to ascertain their contribution or influence in explaining why the problem occurs and how it can be solved • The network of association identified among the variables is then theoretically woven, together with justification as to why they might influence the problem • From a theorized network of associations among the variables, certain hypotheses can be generated • A scientific hypothesis must meet two requirement • Testable • Falsifiable (possible to disprove the hypothesis) 1–30
- 31. DETERMINE MEASURES • Unless the variables in the theoretical framework are measured in some way, the researcher will not able to test the hypotheses 1–31
- 32. DATA COLLECTION • Data with respect to each variable in the hypotheses need to be obtained • Further scientific data collection is needed to test the hypotheses that are generated in the study • Data on every variable in the theoretical framework from which hypotheses are generated should also be collected 1–32
- 33. DATA ANALYSIS • 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 conjectures are substantiated • Qualitative data – information gathered in a narrative form through interviews and observation 1–33
- 34. INTERPRETATION OF DATA • Deciding whether the hypotheses are supported or not by interpreting the meaning of the results of the data analysis • The process of arriving at conclusions by interpreting the meaning of the results of the data analysis 1–34