Research Methods - FoE -24-1 PDF

Research Methodology By: Ashraf Shaarawy  Course Objectives Research and the Research Process Critical Appraisal of Literature Review Research Methods (Quantitative and Qualitative) Research Design Critical Appraisal of different Research Methods Data Analysis...

Research Methodology By: Ashraf Shaarawy  Course Objectives Research and the Research Process Critical Appraisal of Literature Review Research Methods (Quantitative and Qualitative) Research Design Critical Appraisal of different Research Methods Data Analysis and Interpretation Research Ethics and Integrity  Chapter 1 Introduction to Research 3 The Scientific Research Process Hypothesis & Problem Literature Research Definition Review Design Data Data Analysis Conclusion Collection  Definition of Business Research Scientific research: an organized, systematic, data-based, critical, objective, scientific inquiry or investigation into a specific problem, undertaken with the purpose of finding answers or solutions to it.  A process of determining, acquiring, analyzing, synthesizing, and disseminating relevant business data, information, and insights to decision makers in ways that mobilize the organization to take appropriate business actions that, in turn, maximize business performance  Applied versus Basic Research Basic research: generates a body of knowledge by trying to comprehend how certain Phenomena that occur in organizations can be described or analyzed. Applied research: solves a current Problem faced by the manager in the work setting, demanding a timely solution.  Engineering research Engineering research is based on precisely the same scientific method; however, the research is directed toward the practical application of science to products, services and infrastructure. Most research starts with a hypothesis; that is, a statement which can be either proved or disproved.  Why managers should know about research Being knowledgeable about research and research methods helps professional managers to: – Identify and effectively solve problems in the work setting. – Know how to discriminate good from bad research. – Appreciate the multiple influences and effects of factors on a situation. – Take calculated risks in decision making. – Relate to hired researchers and consultants more effectively. – Combine experience with scientific knowledge while making decisions.  Why Engineers should Study research Developing new technologies: Engineers often work on developing new technologies or improving existing ones. Research helps engineers stay up to date with the latest scientific and technological advances in their field, and provides the knowledge and tools needed to design and develop new technologies.  Why Engineers should Study research As an engineer you will be faced with problems that require you to devise innovative and practical solutions. Some problems may be simple and you will solve them drawing on knowledge you acquired through your course of study or using your experiences. On the other hand, there will be cases where your experience and academic training are not sufficient. In these cases, you will need to engage in research. Being able to source valid and credible information in order to formulate viable solutions is an important skill that all engineers need  Examples of Research Areas in Business Absenteeism Communication Motivation Consumer decision making Customer satisfaction Budget allocations Organizational Performance  Internal Researchers Advantages: – Better acceptance from staff – Knowledge about organization – Would be an integral part of implementation and evaluation of the research recommendations. Disadvantages – Less fresh ideas – Power politics could prevail – Possibly not valued as “expert” by staff  External Researchers Advantages – Divergent and convergent thinking – Experience from several situations in different organizations – Better technical training, usually Disadvantages – Takes time to know and understand the organization – Rapport and cooperation from staff not easy – Not available for evaluation and implementation – Costs  Scientific Investigation, Thinking like a Researcher 14  1.Organization Sole/ LLC/ Corporate 5. Geographical 2.Management 4. Business Function Function : Planning 6. Industry Organizing 3. Organizational Sector Leading level Controlling Executives 7. External Environment P.E.S.T Seniors Middle & frontline managers 8. Internal Environment Customers Workers Suppliers Employee Stakeholders 9. Time 9 Element model Developed By Dr. Ashraf Elsafty  Stakeholders of the Organization Source: derived from Figure 5.2, Exploring Strategy, 11th ed., p.135  Language of Research Concepts Constructs Variables Operational Models definitions Terms used in research Theory Propositions/ Hypotheses  Constructs and Concepts Concepts have progressive levels of abstraction. Some concepts such as a person’s weight are precise and objective, while others such as a person’s personality may be more abstract and difficult to visualize. Construct may be a simple concept, such as a person’s weight, or a combination of a set of related concepts such as a person’s communication skill, which may consist of several underlying concepts such as the person’s vocabulary, syntax, and spelling.  Theory and Model A theory is a set of systematically interrelated constructs and propositions intended to explain and predict a phenomenon or behavior of interest, within certain boundary conditions and assumptions. Essentially, a theory is a systemic collection of related theoretical propositions. A model is a representation of all or part of a system that is constructed to study that system (e.g., how the system works or what triggers the system). While a theory tries to explain a phenomenon, a model tries to represent a phenomenon.  Variables Variable is a measurable representation of an abstract construct. constructs are not directly measurable, and we look for proxy measures called variables. intelligence is a construct, and IQ score is a variable that measures the intelligence construct. A Variable Is the Property Being Studied Event Action Variable Characteristic Trait Attribute  Deduction and Induction Deductive reasoning: application of a general theory to a specific case. – Hypothesis testing Inductive reasoning: a process where we observe specific phenomena and on this basis arrive at general conclusions. – Counting white swans Both inductive and deductive processes are often used in research.  Sound Reasoning Argument Deduction Induction Deductive Reasoning Inner-city household interviewing is especially difficult and expensive This survey involves substantial inner-city household interviewing The interviewing in this survey will be especially difficult and expensive © 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin  Inductive Reasoning Why didn’t sales increase during our promotional event? – Our retailers did not have sufficient stock to fill customer requests during the promotional period – A strike by employees prevented stock from arriving in time for promotion to be effective – COVID closed retail outlets in the region for 2 months during the promotion Employee’s Performance  Hypothetico-Deductive Research The Seven-Step Process in the Hypothetico- Deductive Method – Identify a broad problem area – Define the problem statement – Develop hypotheses – Theoretical Framework – Determine measures – Data collection – Data analysis – Interpretation of data  Hypotheses A hypothesis can be defined as a tentative, yet testable, statement, which predicts what you expect to find in your empirical data. hypotheses can be defined as logically conjectured relationships between two or more variables expressed in the form of testable statements. By testing the hypotheses and confirming the conjectured relationships, it is expected that solutions can be found to correct the problem encountered.  The Role of Hypotheses Guide the direction of the study Identify relevant data Suggest most appropriate research design Provide framework for organizing resulting conclusions  Hallmarks of Scientific Research: Hallmarks or main distinguishing characteristics of scientific research: – Purposiveness – Rigor – Testability – Replicability – Precision and Confidence – Objectivity – Generalizability – Parsimony  The Hallmarks of Scientific Research We will explain each of these characteristics in the context of the following example: Consider the case of a researcher who is interested in investigating how employees’ commitment to the organization can be increased.  Purposiveness The researcher 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.  Rigor A good theoretical base and a sound methodological design would add rigor to a purposive study. Rigor means extremely thorough and careful, and the degree of exactness in research investigations.  Rigor In the case of our example of increasing the commitment of employees: Let us say that the researcher of an organization asks 10 of its employees to indicate what would increase their level of commitment to the organization. If the researcher depends solely on the basis of their responses he will have several conclusions on how employee commitment can be increased, the whole approach to the investigation would be unscientific.  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 lends itself to testing the hypotheses to see whether or not the data support the hypotheses that are developed.  Objectivity The conclusions drawn through the interpretation of the results of data analysis should be objective. The conclusions should be based on 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.  Objectivity Example: If we have a hypothesis that stated that greater participation in decision making will increase organizational commitment. However, 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!  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. Replication demonstrates that our hypotheses have not been supported merely by chance, but are reflective of the true state of affairs in the population.  Replicability Example: The study concludes that participation in decision making in manufacturing firms is one of the most important factors that influences the commitment, we will place more faith and credibility in these finding and apply in similar situations. Replication is made possible by a detailed description of the design details of the study, such as the sampling method and the data collection methods that were used.  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.  Generalizability Example: 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 in enhanced. The more generalizable the research, the greater its usefulness and value.  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.  Parsimony Parsimony can be introduced with a good understanding of the problem and the important factors that influence it. A good conceptual or 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.  Parsimony For instance, if 2-3 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%.  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 our world. 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.  Precision and Confidence In 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.  Precision and Confidence Precision Example: If a researcher estimated the average income of Country X people is between 8,000 and 12,000, as against the actual of 10,000. The precision of this estimation is more favorable than if he has indicated that the average income is somewhere between 6,000 and 14,000.  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.  Precision and Confidence Precision and confidence – In social research : 95% confidence level (implies there is only a 5% probability that the findings may not be correct) is accepted as conventional, usually referred as significance level of 0.05 (p = 0.05)  The research document Title page Contents page Acknowledgements - personal thanks to those who have helped you Executive summary or abstract – why, how and what? Introduction Literature review – what others have said about this problem Research method – what considerations were made when choosing a way to conduct this study Data – what have you found from your primary data collection? Discussion – comparing literature to data section Conclusions - answers to your research questions, limitations and future study advice References - cited work - use appropriate referencing – APA 6. Bibliography - sources used but not cited Appendices 50  Title of the research It should be concise, descriptive and informative. Titles should clearly indicate the independent, dependent and /or mediating variables. It is important to specify what population will be investigated. The aim of a title is to capture the reader’s attention to the research problem being investigated 51 52  The Broad Problem Area  Examples of broad problem areas that a manager could observe at the workplace: – Training programs are not as effective as anticipated. – The sales volume of a product is not picking up. – Minority group members are not advancing in their careers. – The newly installed information system is not being used by the managers for whom it was primarily designed. – The introduction of flexible work hours has created more problems than it has solved in many companies. 53  Preliminary Information Gathering  Nature of information to be gathered: – Background information of the organization. – Prevailing knowledge on the topic. 54  The Problem Statement Examples of Well-Defined Problem Statements – To what extent do knowledge-related factors affect the use of MIS by middle managers? – To what extent do the structure of the organization and type of information systems installed account for the variance in the perceived effectiveness of managerial decision making? – To what extent has the new advertising campaign been successful in creating the high-quality, customer-centered corporate image that it was intended to produce? – What are the effects of downsizing on the long-range growth patterns of companies? 55  Literature Review A literature review is “the selection of available documents (both published and unpublished) on the topic, which contain information, ideas, data and evidence written from a particular standpoint to fulfill certain aims or express certain views on the nature of the topic and how it is to be investigated, and the effective evaluation of these documents in relation to the research being proposed” (Sekaran & Bougie, 2016, p. 51). 56  Literature Review A good literature survey: – Ensures that important variables are not left out of the study. – Helps the development of the theoretical framework and hypotheses for testing. – Ensures that the problem statement is precise and clear. – Enhances testability and replicability of the findings. – Reduces the risk of “reinventing the wheel”. – Confirms that the problem is perceived as relevant and significant. 57  Literature Review Searching for literature Evaluating the literature Documenting the literature review 58  Levels of Information Primary Secondary Tertiary Sources: Sources: Sources: Memos Encyclopedias Indexes Letters Textbooks Bibliographies Interviews Handbooks Internet Speeches Magazines search engines Laws Newspapers Internal records Newscasts  6 0 Sources of Data  Primary data: information obtained firsthand by the researcher on the variables of interest for the specific purpose of the study.  Examples: individuals, focus groups, panels  Secondary data: information gathered from sources already existing.  Examples: company records or archives, government publications, industry analyses offered by the media, web sites, the Internet, and so on.  Objectives of Secondary Searches  Gather background information  Identify information that should be gathered  Identify sources for and actual questions that might be used  Identify sources for and actual sample frames that might be used  Searching for Literature Most libraries have the following electronic resources at their disposal: – Electronic journals – Full-text databases – Bibliographic databases – Abstract databases 62  Data sources Textbooks Academic and professional journals Thesis Conference proceedings Unpublished manuscripts Reports of governmental departments and corporations Newspapers The Internet 63  Google Scholar Search on Google Scholar https://scholar.google.com/ Present Samples of Research on Solar Energy – AI - IOT 64 APA Format 65 66  Variable Any concept or construct that varies or changes in value Main types of variables: – Dependent variable – Independent variable – Moderating variable – Mediating variable 67  (In)dependent Variables Dependent variable (DV) – Is of primary interest to the researcher. The goal of the research project is to understand, predict or explain the variability of this variable. Independent variable (IV) – Influences the DV in either positive or negative way. The variance in the DV is accounted for by the IV. © 2009 John Wiley & Sons Ltd.www.wileyeurope.com/college/sekaran 68  Moderators Moderating variable: is a variable that affects the direction and/or strength of relation between independent and dependent variable. ( Motivation, Engagement, etc…) 69  Mediating Variable – It surfaces between the time the independent variables start operating to influence the dependent variable and the time their impact is felt on it. 70 Variables 71  Questions and/or hypotheses A hypothesis can be defined as a tentative prediction or explanation of the relationship between two or more variables. Unambiguous prediction of expected outcomes Null and Alternative Hypothesis Guide/lead the research 72  Example Major Research Question: What are the factors that affect employees turnover? Minor Research Questions : MinQ1: What is the impact of employee engagement on employee turnover? MinQ2: What is the impact of employee satisfaction on employee turnover? MinQ3: What is the role of mangers in employee turnover? 73  Questions and/or hypotheses Example: Ho (Null Hypothesis): There is no relation between employee engagement and employee performance. H_A: Alternative Hypothesis There is a relation between employee engagement and employee performance. There is positive relation between employee engagement and employee performance 74  Questions and/or hypotheses Example: Ha1 (Non-Directional): There is relation between employee engagement and employee performance. Ha2: (Directional) There is positive relation between employee engagement and employee performance 75  Measurement Measurement: the assignment of numbers or other symbols to characteristics (or attributes) of objects according to a pre-specified set of rules. 76  How Variables Are Measured Objects that can be physically measured by some calibrated instruments pose no problem. Data representing several demographic characteristics of the office personnel are also easily obtained by asking employees simple, straight forward questions, for example: – How long have you been working in this organization? – What is your job title? – What is your marital status? 77  Objects and Characteristics Objects include persons, strategic business units, companies, countries, kitchen appliances, restaurants and so on. Examples of characteristics of objects are achievement motivation, organizational effectiveness, shopping enjoyment, length, weight, ethnic diversity, service quality, conditioning effects and taste. 78  Types of Variables Two types of variables: – One lends itself to objective and precise measurement; – The other is more nebulous “Vague” and does not lend itself to accurate measurement because of its abstract and subjective nature. 79  Concepts & Constructs A scientific concept consists of three parts: Concept Labels: facilitates communication. Theoretical definition: the verbal meaning attached to the concept label. Example: “Income”, refers to, the amount of money people receive in return for making labor or knowledge available to another. Operational Definition: translates the verbal meaning provided by the theoretical definition into a prescription for measurement. 80  Operational Definition Operationalizing, or operationally defining a concept so that it becomes measurable, is achieved by looking at the behavioral dimensions, facets, or properties denoted by the concept, and categorizing these into observable and measurable elements. 81  Operationalizing Concepts Operationalizing concepts: reduction of abstract concepts to render them measurable in a tangible way. Operationalizing is done by looking at the behavioural dimensions, facets, or properties denoted by the concept. 82  Operationalization: Dimensions and Elements Example: Aggression has at least two dimensions: Verbal aggression: shouting and swearing at a person Physical aggression: throwing objects, hitting a wall, and physically hurting others A valid measurement scale of aggression would have to include “Elements” that measure verbal aggression and “Elements” that measure physical aggression. A measurement scale that only includes items measuring physical aggression would not be valid if our aim were to measure aggression. 83  Operationalization Scale handbooks, such as the Marketing Scales Handbook or the Handbook of Organizational Measurement, provide an exhaustive overview of measurement scales that have appeared in the academic literature. 84 Achievement Motivation 85  Scale Scale: tool or mechanism by which individuals are distinguished as to how they differ from one another on the variables of interest to our study. 86  Scales and Measurement Scales Nominal scale Rating scale Ordinal scale Likert scale Interval scale Itemized rating scale Ratio scale 87  Nominal Scale A nominal scales categorize individuals or objects into mutually exclusive and collectively exhaustive groups. What is your department? O Marketing O Maintenance O Finance O Production O Servicing O Personnel O Sales O Public Relations O Accounting What is your gender? O Male O Female 88  Ordinal Scale Ordinal scale: not only categorizes variables in such a way as to denote differences among various categories, it also rank- orders categories in some meaningful way. What is the highest level of education you have completed? Job characteristic Rank of importance The job provide interaction with others Use a number of different skills. Complete a whole task from start to end Serve others Work independently. 89  Interval Scale Interval scale: the interval scale lets us measure the distance between any two points on the scale. The difference between any two values on the scale is identical to the difference between any other two neighboring values of the scale. 90  Interval scale Circle the number that represents your feelings at this particular moment best. There are no right or wrong answers. Please answer every question. 1. I invest more in my work than I get out of it I disagree completely 1 2 3 4 5 I agree completely 2. I exert myself too much considering what I get back in return I disagree completely 1 2 3 4 5 I agree completely 3. For the efforts I put into the organization, I get much in return I disagree completely 1 2 3 4 5 I agree completely 91  Interval scale The clinical thermometer is a good example of an interval- scaled instrument; it has an arbitrary origin and the magnitude of the difference between 37 degrees and 38 degrees is the same as the difference between 40 and 41 degrees. 92  Ratio Scale Ratio scale: overcomes the disadvantage of the arbitrary origin point of the interval scale, in that it has an absolute (in contrast to an arbitrary) zero point, which is a meaningful measurement point. What is your age? 93 Ratio Scale 94 95 Properties of the Four Scales 96