1. Research Methodology Dr. Lotfalla Imam École Supérieure Libre des Science Commerciales Appliquées Research Methods for Business A Skill Building Approach By UmaSekaran and Roger Bougie By, Osama Mosad Antoine Andrawos Shady Taymour Youssef Ishak 1

2. 2 Chapter one Introduction to research

3. What is Research? Research, a somewhat intimidating term for some, is simply the process of finding solutions to a problem after a thorough study and analysis of the situation factors. 3

4. Business Research Business research can be described as a systematic and organized effort to investigate a specific problem encountered in the work setting, which needs a solution. 4

5. Definition of Business Research We can define business research as an organized, systematic, data-based, critical, objective, scientific inquiry or investigation into a specific problem, undertaken with purpose of finding answers or solutions to it. 5

6. Some commonly researched areas in business Employee behaviors such as performance, absenteeism, and turnover Employee attitudes such as job satisfaction, loyalty, and organizational commitment Supervisory performance, managerial leadership style, and performance appraisal systems. 6

7. Types of business research: applied and basic Applied research Research done with the intention of applying the results of the findings to solve specific problems currently being experienced in an organization Basic research “ fundamental – pure” Research done chiefly to make a contribution to existing knowledge 7

8. Managers and research Managers with knowledge of research have an advantage over those without Knowledgeable about research and research methods helps professional managers to: Identify and effectively solve minor problems in the work setting Know how to discriminate good from bad research Appreciate and be constantly aware of the multiple influences and multiple effects of factors impinging on a situation Take calculated risks in decision making, knowing full well the probabilities associated with the different possible outcomes. Prevent possible vested interests from exercising their influence in a situation. Related to hire researchers and consultants more effectively. Combine experience with scientific knowledge while making decision. 8

9. The Manager and the consultant- researcher Managers often need to engage a consultant to study some of the more complex, time consuming problems that they encounter 9

10. The Managers – researcher relationship During their careers, it often becomes necessary for managers to deal with consultants, so while hiring researchers or consultants the manager should make sure that: The roles and expectations of both parties are made explicit. Related philosophies and value systems of organization are clearly stated and constraints, if any, are communicated. A good rapport is established with the researchers, and between the researchers and the employees in the organization, enabling the full cooperation of the latter. 10

11. Internal consultants / researchers 1-2 Some organizations have their own consulting or research department, which might be called the management services department, the organization and methods department, R & D 11

12. Internal consultants / researchers2-2 12

13. External consultants / researchers 13

14. Knowledge about research and managerial effectiveness Managers are responsible for the final outcome by making the right decisions at work. This is greatly facilitated by research knowledge 14

15. Ethics and business research Ethics in business research refers to a code of conduct or expected societal norm of behavior while conducting research. 15

16. Chapter two Scientific investigation 16

17. The hallmarks of scientific research 1-3 1. Purposiveness Started the research with a definite aim or purpose 2. Rigor Rigor connotes carefulness, scrupulousness, and the degree of exactitude in research investigations 3. Testability The manager or researcher develops certain hypotheses on how employee commitment can be enhanced, then these can be tested by applying certain statistical tests to the data collected for the purpose. 17

18. The hallmarks of scientific research 2-3 4. 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. 5. Precision and confidence Design the research in a manner the ensures that our findings are as close to reality 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: refer to the probability that our estimations are correct, it is important that we can confidently claim that 95% of the time our results will be true and there is only a 5 % chance of our being wrong. 18

19. The hallmarks of scientific research 3-3 6. Objectivity The conclusion drawn through the interpretation of the results of data analysis should be based on facts of the findings derived from actual data, and not on our own subjective or emotional values. 7. Generalizability Refers to the scope of applicability of the research findings in one organizational setting to other settings 8. Parsimony Simplicity in explaining the phenomena or problems that occur, and in generating solutions for the problem, And it can be introduced with a good understanding of the problem and the important factors that influence it. 19

20. Some obstacles to conducting scientific research in the management area In the management and behavioral areas, it is not always possible to conduct investigations that are 100 % scientific, in the sense that, unlike in the physical sciences, the results obtained will not be exact and error-free. This is primarily because of difficulties likely to be encountered in the measurement and collection of data in the subjective areas of feelings, emotions, attitudes, and perceptions. 20

21. The hypothetico-deductive method Scientific research pursues a step –by- step, logical, organized, and rigorous method to find a solution to a problem 21

22. The seven-step process in the hypothetico-deductive method 1-2 1. Identify a broad problem area A drop in sales, frequent production interruptions,… and the like, could attract the attention of manager and catalyze the research project 2. Define the problem statement Problem statement that stats the general objective of the research should be developed 3. Develop hypotheses In this step variable are examined as to their contribution or influence in explaining why the problem occurs and how it can be solved. 4. Determine measures Unless the variables in the theoretical framework are measured in some way, we will not be able to test our hypotheses. 22

23. The seven-step process in the hypothetico-deductive method 2-2 5. Data collection Data with respect to each variable in the hypothesis need to be obtained. 6. Data analysis In the data analysis step, the data gathered are statistically analyzed to see if the hypotheses that were generated have been supported 7. Interpretation of data Now we must decide whether our hypotheses are supported or not by interpreting the meaning of the results of the data analysis. 23

24. Review of the hypothetco-deductive method Deductive reasoning is a key element in the hypothetico—deductive methods. Deductive reasoning: start with a general theory and then apply this theory to a specific case. Inductive reasoning: works in the opposite direction it is a process where we observe specific phenomena and on this basis arrive at general conclusions. 24

25. Other types of research Case studies and action research are sometimes used to study certain types of issues. Case studies Involve in depth, contextual analyses of similar situations in other organizations. Case study, as a problem solving technique, is not often undertaken in organizations Action research Is sometimes undertaken by consultants who want to initiate change processes in organizations. Thus, action research is a constantly evolving project with interplay among problem, solution, effects or consequences, and new solution. 25

26. Chapter Three The research process The broad problem area and defining the problem statement 26

27. The definition of problem is any situation where a gap exists between the actual and the desired ideal states. Example: training program is not as effective as anticipated 27

28. Broad problem area : After identification of the broad problem area through the process of observation and focusing on the situation we need to be narrowed down to a specific problem statement after some preliminary information (interviews and literature research) is gathered by the researcher. 28

29. 2. Preliminary information gathering : a) Data sources : Primary data sources ( it is that information’s that the researcher obtain it by himself by , talking , observing, and administrating questionnaires ) Secondary data sources ( it is that information’s that already existed and the researcher has no role in obtaining it but he read it and take what he need from it ) 29

30. b) Data nature : Unstructured interviews, structured interviews, and a review through existing sources of information will help us to narrow the broad problem area and to define a specific problem statement. 30

31. Collection of information’s about the following factors to stand on the real issues instead of working only on the surface symptoms Contextual factors ( background information of the organization ) Structural factors ( philosophy, policies, goals, system structure, reward system ) Attitudinal factors ( information’s about believes and reactions the members of organization about certain subjects like , nature of the work, reward system , opportunities ) Behavioral factors (actual work habits ) 31

32. In some cases there are variables that are not identified during the interviews but influence the problem critically, then research done without considering them is an exercise in futility, in such case the true reason for the problem will remain unidentified even at the end of the research, to avoid such possibilities the researcher needs to delve into all the important research relating to the particular problem area. 32

33. 3. Literature review : The literature review helps the researcher to develop a good problem statement; it ensures that no important variable is overlooked in the process of defining the problem Sometimes the investigator might spend considerable time and effort in “discovering” something that has already been thoroughly researched. A Literature review would prevent such a waste of resources in reinventing the wheel. 33

34. Conducting the literature review 1- Data sources ( you will need to use a combination of information resources the precise combination of resources depend on the nature and the objectives of your research project ) this combination come from information’s from text books, journals, theses, conference proceedings, unpublished manuscripts, reports, newspapers, the internet. 34

35. 2- Searching for literature In past go through several bibliographical indexes but now by computer online systems (locating sources to locate and printout the published information) Internet online searching directories (subject, title, geographical location, trade opportunities, industrial plants, foreign traders, data bases) 35

36. 3- Evaluating the literature Accessing the online system and searching for literature in the area of interest will provide a comprehensive bibliography on the subject. 36

37. 4- Documenting the literature review Is important to convince the reader that The researcher is knowledgeable about the problem area and has done the preliminary homework that is necessary to conduct the research The theoretical framework will be structured on work already done and will add to the solid foundation of existing knowledge. 37

38. Defining the problem statement There are three key criteria to assess the quality of the problem statement: it should be relevant, feasible, and interesting. It is very important that symptoms of problems are not defined as the real problem When you have defined the problem statement you are ready to start your research first however you need to communicate the problem statement and a number of other important frame and the budget 38

39. Chapter Four The research process Theoretical framework and hypothesis development 39

40. 40

41. The need for a theoretical framework A theoretical framework is the foundation of hypothetico-deductive research. Represents your believes on how certain phenomena are related to each other. 41

42. The process of building a theoretical framework includes: Introducing definitions of the concept or variable in your model. Developing a conceptual model that provides a descriptive representation of your theory Coming up with a theory that provides an explanation for relationships between the variable in your model. 42

43. Variables: A variable is anything that can take on differing or vareing values. Examples of variables are: production units, absentiesm and motivation. 43

44. Types of variables : 1- Dependent variable The dependent variable is the variable of primary interest to the researcher. Through the analysis of the dependent variable is possible to find answers or solutions to the problem 44

45. 2- Independent variable The independent variable is generally conjectured that an independent variable is one that influences the independent variable in either a positive or negative way. That is, when the independent variable is present, the dependent variable is also present, and with each unit of increase in the independent variable, there is an increase or decrease in the dependent variable. 45

46. 3- Moderating variable The moderating variable is the presence of a third variable that modifies the relationship between the independent and the dependent variables. 46

47. 4- Mediating variable The mediating variable is one that surfaces between the time the independent variable start operating to influence the dependent variable and the time their impact is felt on it. The Mediating variable surfaces as a function of the independent variable operating in any situation, and helps to conceptualize and explain the influence of the independent variable on the dependent variable. 47

48. Theoretical framework The theoretical framework is the foundation on which the entire research project is based. Variables are relevant to the problem situation and identified through; interviews, observations and leterature review. Experience and intuition also guide the development of theoretical framework after identifying the appropriate variable, the next step is to elaborate the network of associations among the variables, so that relevant hypotheses can be developed and subsequently tested. Based on the results of hypothesis testing the extend to which the problem can be solved becomes evident. 48

50. Explains the theory underlying these relations.

51. Describes the nature and direction of the relationships. Just as the literature review sets the stage for a good theoretical framework, this in turn provides the logical base for developing testable hypothesis. 49

53. A conceptual model that describes the relationships between the variables in the model should be given.

54. There should be a clear explanation of why we expect these relationships to exist. Both a schematic diagram of the conceptual model and a description of the relationships between the variables in words should be given, so that the reader can see and easily comprehend the theorized relationships. 50

55. Hypothesis development Hypothesis can be defined as logically conjectured relationships between two or more variables expressed in the form of testable statement. By testing the hypothesis and confirming the conjectured relationships, it is expected that solutions can be found to correct the problem incountered. 51

56. Statement of hypothesis : Formats 1- If-Then statement To examine whether or not the conjectured relationship or differences exist, this hypothesis can be set either propositions or in the form of If-Then statement. Example: IF the employees are more healthy, THEN they will take sick leave less frequently. 52

57. 2- Directional and non directional hypothesis If, instating the relationship between two variables or comparing two groups, terms such as positive, negative, more then, less then, and the like are used, then these are: Directional hypothesis because the direction of the relationship between the variables ( positive – negative) is indicated. Example: The greater the stress experienced in the job, the lower the job satisfaction of employees. Non directional hypothesis there is a significant relationship between two variables, we may not be able to say whether the relationship is positive or negative. Example: There is a relationship between age and job satisfaction. 53

58. 3- Null and alternate hypothesis Null hypothesis may state that the correlation between two variables is equal to zero. The null statement is expressed in terms of there being no relationship between two variables. The alternate hypothesis, whish is the opposite of the null, is a statement expressing a relationship between two variables. 54

59. The steps to be followed in hypothesis testing are: State the null and the alternate hypothesis. Choose the appropriate statistical test depending on whether the data collected are parametric or non parametric. 55

60. 56 Chapter Seven Measurement Scaling, Reliability, Validity

61. Scales: Is tool or mechanism by which individuals are distinguished as to how they differ from one to another on the variables of interest to our study 57

63. Ordinal scale

64. Interval scale

65. Ratio scale58

66. 1- Nominal scale : Allows the researcher to assign subjects to certain categories or groups it categorize individuals or objects into mutually exclusive and collectively exhaustive groups, thus such scaling tells us nothing more about the two groups and gives some basic, categorical, gross information, personal data such gender or department in which one works , 59

67. There are two types : a) Dichotomous scale : Used to … elicit a yes or no answer ex. Do you own a car? Yes no b) Category scale : Used to … elicit a single response ex. Where in London do you reside? - east London - south London - west London - north London -outskirts 60

68. 2- Ordinal scale: 61 In this scale the respondents might be asked to indicate their preferences by ranking the importance they attach to five distinct characteristics in a job that the researcher might be interested in studying

69. The ordinal scale helps researcher to determine the percentage of respondents who consider interaction with others as most important, those who consider using a number of different skills as most important and so on, such knowledge might help in designing jobs that are seen as most enriched by the majority of the employees. 62

72. 3- Interval scale: In nominal scale we can make qualitatively distinguish groups by categorizing them into mutually exclusive and collectively exhaustive and in ordinal scale allow us to rank order the preferences the interval scale indicate whether once preference is the same extent, or a greater extent than the second. 65

73. 66 This can be done by changing the scale from the ranking type to make it appear as if there are several points on a scale that represent the extent or magnitude. So it used when responses to various items that measure a variable can be tapped on a five points or more Strongly disagree disagree neither agree nor disagree agree strongly agree 1 2 3 4 5

74. There are five types: 1) Semantic differential scale: لفظي It is used to assess respondent’s attitudes toward a particular brand, advertisement, object, or individual. Several bipolar attributes: respondents are asked to indicate their attitudes toward a particular individual, object Several bipolar adjectives: used might employ such terms as good-bad, strong-weak, hot-cold Responsive -----unresponsive Beautiful --------ugly Courageous ------- timid 67

75. 2) Numerical scale : عددي Similar to the semantic scale but with numbers on five-point or seven-point scale are provided Extremely pleased 7 6 5 4 3 2 1 extremely displeased 68

76. 69 3) Itemized rating scale : يفصل المفردات أو يضع جدولا لها It provides the flexibility to use as point in the scale as considered necessary (4,5,7,9 or whatever) and its possible to use different anchors e.g. very unimportant to very important and extremely low to extremely high )when a neutral point is provided it is a balanced rating scale, and when it is not it is an unbalanced rating scale. It is balanced rating scale with a neutral point It is unbalanced rating scale which does not have a neutral point.

77. 4) Likertscale: 70 Used in it the summated approach High score in items I and 3 reflects a favorable attitude to work this will lead to high total scores for respondents who have a favorable attitude toward work and low total scores for respondents who have an unfavorable attitude towards work.

78. 71 5) Staple scale: This scale measures both the direction and intensity of the attitude toward the items under study Rate your supervisor abilities:

79. 4- Ratio scale: Usually used in organizational research when exact numbers on objective (as opposed to subjective) factors are called: 1. How many other organizations did you work for before joining this system? 2. Please indicate the number of children you in each of the following categories: --- Below 3 years of age --- Between 3 and 6 --- Over 6 years but under 12 --- 12 years and over 3. How many retail outlets do you operate? The responses to the questions could range from 0 to any reasonable figure. 72

80. 73 Chapter Ten Sampling

82. The sampling process: 1- Defining the population: Sampling begin with precisely defining the target population, the researcher objective and the scope of the study play a crucial role in defining the target population. 2- Determining the sample frame: The sampling frame is a representation of all the elements in the population from whish the sample is drawn. 3- Determining the sampling design: ( Two types ) Probability sampling, the elements in the population have some known probability of being selected as sample subject. Non probability sampling, the elements do not have a known chance of being selected as sample subject. 75

83. 4- Determining the sample size: Factors affecting decisions on sample size are: Researcher objective. Extent of precision desired. Acceptable risk in predicting that level of precision. Amount of variability in the population itself. Cost and time constraints. Size of the population. 76

84. Probability sampling: When elements in the population have a known chance of being chosen as subjects in the sample. Types of Probability sampling: 1- Unrestricted or simple random sampling: Every element in the population has a known and equal chance of being selected. 77

85. 78 2 - Restricted or complex probability sampling:

86. Non probability sampling: When elements in the population do not have any probabilities attached to their being chosen as sample subjects. Convenient Sampling: Refers to the collection of information from members of the population who are conveniently available to provide it. It is used during the exploratory phase of a research project and is perhaps the best way of getting some basic information quickly and efficiently. 79

87. 80 Purposive sampling: Confined to a specific type of people who can provide the desired information Types of purposive sampling:

88. 81 SPSS

90. managing, analyzing, and presenting data 82

91. Some Definitions Population(universe) is the collection of things under consideration Sample is a portion of the population selected for analysis Statisticis a summary measure computed to describe a characteristic of the sample 83

92. Mean (average) is the sum of the values divided by the number of values Median is the midpoint of the values (50% above; 50% below) after they have been ordered from the smallest to the largest, or the largest to the smallest Modeis the value among all the values observed that appears most frequently Rangeis the difference between the smallest and largest observation in the sample 84

93. Type of data Categorical data: There are basically two kinds of data in this groups: Nominal data(named categories), e.g. gender (male/female), ethnicity (Malay, Chinese, Indian), outcome (dead/alive), etc. The nominal data are summarised by percentages. Ordinal data(ordered categories), e.g. there is an order to the values high, medium, and low, but the distance between values cannot be calculated. Likert scale (5-point scale, 1-5), etc. The ordinal data are summarised by median value. 85

94. “Scale” Continuous data: Continuous data is sometime referred to as interval data. These data take the form of a range of number, and may or may not have decimals, e.g. age, weight, height, salary, etc. The continuous data are summarized by mean and standard deviation (SD). 86

95. Variance and Standard Deviation Variance(deviations) is a measure of the dispersion of a sample (or how closely the observations cluster around the mean [average]) Standard Deviation, the square root of the variance, is the measure of variation in the observed values (or variation in the clustering around the mean), it helps detect tampering of data. 87

96. Thank You 88