RCH 5301 VI PP

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Course Learning Outcomes for Unit I At the end of this unit, you should be able to:

1. Integrate philosophical assumptions and worldviews held by researchers. 1.1 Appraise philosophical assumptions, research worldviews, research methodologies, research

traditions, and research designs.

2. Discriminate among the characteristics of qualitative and quantitative research methods. 2.1 Deduce differences between a quantitative methodological research strategy and a qualitative

research strategy.

3. Evaluate research designs. 3.1 Differentiate between descriptive, explanatory, and exploratory research designs based on their

unique characteristics. Required Unit Resources Chapter 1: The Selection of a Research Approach (ULO 1.1, 2.1, and 3.1) Article: Complex Problems and Dealing with Them on a Research Methods Course in a Business School (ULO 1.1, 2.1, and 3.1) This study reflects the relative importance of research problem formulation in comparison to solution development. (22 pages) Unit Lesson Lesson: Reflecting Your Worldview Through Research Design (ULOs 1.1 and 3.1)

Introduction Research Design and Methods is a course that extends its relevance to many professional disciplines, including health and safety, education, psychology, sociology, law, business and entrepreneurism, not-for- profit ventures, and arguably any organization that is working to achieve goals. To see the value of this course, it is important to understand that the primary purpose of research design and methods is to enhance decision-making in order to reduce risk and improve organizational performance. When thinking about research from this perspective, you can probably recall many difficult decisions that you have had to make in the absence of perfect information. Since perfect information is rarely available to assist in making difficult decisions, research methods can help improve the odds of achieving favorable outcomes. This course will provide the foundational knowledge for you to design your own research projects, whether they be career- related or in pursuit of terminal degrees.

Applied Research, Evidence-based Management, and the Scientific Method The type of research that is the focus of this course is called applied research. Applied research is normally used to answer questions, solve problems, and address dilemmas. This contrasts with pure research, such as academic studies, which may be used to solve problems but are predominately used to expand humanity’s knowledge on a variety of topics. Two defining features of applied research are a dependence on evidence and a systematic approach. Bell et al. (2022) refer to applied research as evidence-based management

UNIT I STUDY GUIDE Understanding the Nature and Language of Research Design and Methods

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(EBM), where a systematic process is applied to the best available information for enhancing professional practice. While this course will introduce qualitative and mixed methodological approaches to research, it will be predominately focused on the quantitative research methodology. This is not because the quantitative methodology is superior to the qualitative methodology but, rather, because it is better suited to today’s data- driven world. Data is ubiquitous, inexpensive, and frequently used for strategic decision-making, which makes quantitative methods a great fit to address many issues. Using empirical evidence for decision-making replaces unreliable use of intuition, historical events, conventional wisdom, group think, and anecdotal information (Pfeffer & Sutton, 2006b). Decision-makers frequently use only one criterion when making decisions, when multiple criteria increase the probability of success. Similarly, decision-makers often consider only one alternative when evaluating several alternatives improves the odds of selecting an optimal solution to problems. Organizational politics sometimes inhibit subordinates from challenging superiors’ flawed and evidence-deficient decisions. The interests of small groups of stakeholders commonly dominate organizational decision-making, when the input of more and varied stakeholders increases the quality of information for decision-making. Decision-makers routinely base decisions on easily available information rather than spending time, effort, and money on higher quality but less accessible information (Rousseau, 2018). Shifting to an EBM approach to decision-making helps avoid these pitfalls and is appropriate for many disciplines. Notwithstanding the high stakes in many professions, many have been historically measured in the adoption of academic recommendations for best practices. Resistance to EBM is not unique. It may be shocking and concerning to learn that the medical community has also been slow to integrate EBM into medical practice. Pfeffer and Sutton (2006a) found that while there are thousands of academic articles published each year on medical advances and best practices, only about 15% of medical decisions are evidence-based. As is often seen in decision-making, physicians predominately rely on historical outdated information, untested traditions, personal experience, and medical vendor advice. In other words, 85% of medical decisions are not based on scientifically derived evidence. If a great percentage of physicians, who are responsible for the health of patients and bear liability, are hesitant to embrace EBM, how many more managers and organizational leaders also ignore the value of scientific evidence for decision-making? Fortunately, the medical and other professional communities have seen the emergence of an EBM movement in this century. Professions across many sectors have embraced EBM to fortify their organizational strategies. All industries’ participants are under increasing pressure from investors and other stakeholders (e.g., communities), competition, climate change, inflation, social unrest, pandemics, supply chain constraints, labor constraints, and many other uncontrollable factors. Access to large repositories of information provides an advantage for those interested in adopting EBM. While many managers lack professional training in research methods, there is a growing respect for and acceptance of data as the basis for strategic decision-making (Charlier et al., 2011; Mohrman et al., 2001; Rousseau, 2006; Rousseau, 2020; Van Aken & Romme, 2009). For more information on this topic, watch Evidence-based Management [Video]. California Management Review. (2018, February 8). Evidence-based management [Video]. cielo24.

https://c24.page/4we52qyqag2tn693eu2psmkt85 A transcript and closed-captioning are available once you access the video. While dependence on evidence is one of the defining features of applied research, the other defining feature is a systematic approach. EBM is facilitated through the systematic process better known as the scientific method. The scientific method is a process that is associated with the quantitative research methodology. It is a linear process for using data to solve problems. The scientific method is comprised of the steps shown in Figure 1.

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Figure 1: The Scientific Method While each step involves its own level of complexity, the scientific method provides an intuitive and easy path to follow when designing a research project. Adopting scientific inquiry to aid in decision-making results in EBM’s effectiveness (Charlier et al., 2011). EBM and the scientific method can transform practicing managers into experts who utilize disciplines like social science, psychology, and organizational research to make informed decisions rather than relying on untested gut feelings or unreliable experiences (Rousseau, 2006; Rousseau, 2018). While some managers may experience trepidation at the idea of using research methods, employing a systematic process, like the scientific method, can demystify research as a means to EBM. Using applied research, the scientific method and EBM can improve organizational performance and create competitive advantage since this approach to decision-making is not universally practiced among competitors (Pfeffer & Sutton, 2006b). Take some time to watch the two videos below. Scientific method [Video]. The scientific method [Video]. A transcript and closed-captioning are available once you access the videos.

The Terminology and Hierarchy of Research Terminology within research can be confusing and is often used incorrectly. The remainder of this lesson will explain the differences between the concepts of philosophical assumptions, worldviews, research traditions, research methodologies, research designs, and research methods. These can be thought of as elements of a research hierarchy, with everything flowing from philosophical assumptions down to more granular levels of the hierarchy. Watch this video to learn more: Ontology epistemology methodology and methods I Ontology and epistemology in research examples [Video]

A transcript and closed-captioning are available once you access the video.

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Philosophical Assumptions and Worldviews Like all humans, researchers hold their own personal views of the universe, the world, society, and their place within these domains. An individual’s worldview is shaped by the intersection of their philosophical assumptions about the nature of reality and truth (ontology), the nature of knowledge (epistemology), and the nature of values (axiology).

Depending on the researcher’s philosophical beliefs, they will adhere to either a realism or relativism worldview. Realists believe that reality and truth are fixed, objective, and independent of experience. There is one reality and one truth for the phenomena under study, which they observe externally with an etic approach, or a view from the outside. Realists believe that knowledge is created through empirically derived evidence. To this end, realists use collection and measurement of data, statistical analysis, logic, reason, and deduction to test hypotheses. Realists believe that research should be as value-free and absent—as humanly possible—of researcher bias and subjectivity. Consistent with the etic approach, realists insist research should be conducted externally and objectively. The relativism worldview is at odds with the realism worldview. Relativists believe that reality and truth are fluid, subjective, and dependent on experience. They believe there are multiple realities and multiple truths for the phenomena under study, which they observe internally with an emic approach, or a view from the inside. Relativists believe that knowledge is constructed through the interpretation of beliefs, perceptions, shared experiences and realities, memories, stories, culture, and self-reflection. Relativists rely on non-measurable observation using methods such as case studies, unstructured interviews, focus groups, phenomenology, and ethnographies. Relativists find acceptable value-laden research results obtained through researcher immersion with research participants. This is consistent with the emic approach of research that is conducted internally and subjectively.

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Research Traditions There are two primary research traditions: positivism and interpretivism (i.e., constructivism). The research tradition signals the researcher’s philosophical assumptions about ontology, epistemology, and axiology, which, as discussed above, define their worldview as either realist or relativist. The research tradition also defines the methodological lens, quantitative or qualitative, through which the researcher will view their research studies. Researchers who have a realist worldview will follow a positivist research tradition and use a quantitative lens, while researchers with a relativist worldview will follow an interpretivist (constructivist) research tradition and use a qualitative lens.

Positivism was the dominant quantitative research paradigm throughout much of the 20th century. Post- positivism evolved from positivism as critics argued that no researcher can remain completely unbiased or observe and measure reality as it truly exists. Post-positivists are more accepting of the influence of subjectivity in research and reject the rigid objectivity that logical positivists profess. They have a valid argument for sociology and social science studies since variables related to human phenomena and behavior can be difficult to measure. For physical sciences, positivism is still the dominant research paradigm. For the purposes of this course, positivism and interpretivism will be the two primary research paradigms discussed.

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Research Methodologies Research methodologies refer to the strategies that guide a study’s research design and research methods. Research methodologies are either quantitative, qualitative, or mixed (i.e., research that involves both quantitative and qualitative methodologies). As discussed above, positivist researchers use a quantitative methodological lens, while interpretivist researchers use a qualitative methodological lens through which to study phenomena. A quantitative research methodology approaches a research dilemma with the assumption that it can be solved by collecting relatively large amounts of numerical data that can be described and statistically analyzed. Quantitative research results produced using inferential statistics can be generalized to populations. For example, results from sample data can be used to make statistical inferences about populations of interest. A qualitative research methodology explores issues, but the information collected is non-numerical, such as ideas, thoughts, feelings, attitudes, and behaviors. Qualitative information is sometimes coded but can still be difficult, if not impossible, to measure numerically. Results of qualitative research are not generalizable to a population of interest. A mixed-methods strategy includes aspects of both quantitative and qualitative research. The idea is to leverage the best of both methodologies; however, these strategies have opposing philosophical assumptions leading to criticism from many in the research community. In some instances, a researcher may choose to use both a quantitative and qualitative research strategy for their study. This is called a mixed-methodological approach, and it can be extremely insightful since it includes the best of both worlds. However, this strategy also increases the time, cost, and complexity of research projects. Mixed methods research is also criticized by many researchers for the impossibility of gleaning valid and reliable information by using two methodological strategies that are at philosophical odds. In a perfect world, the dilemma should dictate the choice of research methodological strategy, whether that is quantitative, qualitative, or mixed. In reality, it is the researcher’s worldview and research tradition that normally determines the methodology used, which is usually either quantitative or qualitative rather than mixed.

Research Designs Research design refers to the research study blueprint. One's choice of research methodology, quantitative or qualitative, dictates the choices of research design. There are three primary design types: exploratory, explanatory, and descriptive. Exploratory designs are aligned with the qualitative methodology. Exploratory designs are subjective in nature versus explanatory and descriptive designs, which are quantitative. Inferential statistics and sampling are not used with exploratory studies, and results cannot be generalized to populations. Although results are not generalizable, they normally provide a much deeper and richer understanding of the groups or phenomena under study. Explanatory designs are also aligned with the quantitative methodology; however, their advantage lies in the ability to determine causation, unlike descriptive designs that cannot. Explanatory designs test hypotheses to determine if independent variables cause a change in dependent variables or if independent variables cause differences between group means or percentages. Explanatory designs use extraordinarily controlled experiments and are not typically conducted in general research given the required investment of time, money, and expertise; however, since explanatory designs control variables, claims of causality can be made. Like descriptive designs, the use of inferential statistics enables results from explanatory studies to be generalized to populations of interest. Descriptive designs are aligned with the quantitative methodological strategy. Descriptive designs are highly structured using statistical analysis to test hypotheses to determine if relationships or differences exist between variables. Descriptive designs are non-experimental and do not use control groups; therefore, descriptive designs cannot make any claims about causality. Although claims of causality cannot be made, the use of inferential statistics enables results from descriptive studies to be generalized to populations of interest. Descriptive designs should not be confused with descriptive statistics, which is an analytical approach to research. Descriptive statistics is depicted in the charts below and will be explained in more detail in a later unit.

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Explanatory Design (Experimental) Quantitative

Analytical Approach

Data Collection Methods

Sampling Design

Data Analysis

Procedures

Methodology

Research Methods

• Population • Cross-Sectional • Longitudinal • Sampling Frame

• Sample Size • Sample Type (random, stratified, systematic, quota, convenience, etc.)

• Correlation • Causal-Comparative

• Laboratory Experiment • Field Experiment

• Chi-Square (X2) • Pearson’s r • Regression • Factor Analysis • SEM

• t test • ANOVA • Factorial ANOVA • ANCOVA • MANOVA

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Research Methods Research methods refer to specific procedures and tools that are used to collect and analyze data and are selected based on the chosen methodology and design. Elements that fall under research methods are voluminous and may include data collection procedures (e.g., surveys, interviews, case studies, ethnographies, focus groups, etc.), descriptive statistics, causal-comparative statistical procedures (e.g., t- test, ANOVA, MANOVA, etc.), correlation statistical procedures (e.g., Pearson’s r, simple regression, multiple regression, discriminate analysis, etc.), and sampling design. Take some time to watch Differences between research methods and research methodology [Video]. A transcript and closed-captioning are available once you access the video.

Conclusion At this point, you may feel like you have just taken a drink from a fire hose. What has been presented is admittedly a lot of information to absorb, especially since research is a new domain for many of you. It can be helpful to keep visual aids handy for the terminology and hierarchy of research that can be quickly and easily referenced. The table below is a snapshot of worldviews, research traditions, methodologies, and designs discussed above. It is also important to recognize that the terminology that you are introduced to in this unit is often used interchangeably, synonymously, and sometimes incorrectly depending on the source. A quick internet search for “research methods” will reveal that it is described in many different ways depending on the source. The important takeaway is that you have a framework to follow for your own organizational studies, even though the labels may vary. A research framework will also be helpful if you decide to pursue a terminal degree, where you will be expected to design and implement your own research project.

Descriptive Design (Non-experimental) Quantitative

Analytical Approach

Data Collection Methods

Sampling Design

Data Analysis

Procedures

Methodology

Research Methods

• Population • Cross-Sectional • Longitudinal • Sampling Frame

• Sample Size • Sample Type (random, stratified, systematic, quota, convenience, etc.)

• Correlation • Causal-Comparative

• Survey (telephone, mail, electronic) • Structured Interview • Non-Participant Observation • Document Analysis

• Chi-Square (X2) • Pearson’s r • Regression • Factor Analysis • SEM

• t test • ANOVA • Factorial ANOVA • ANCOVA • MANOVA

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References Bell, E., Bryman, A., & Harley, B. (2022). Business research methods (6th ed.). Oxford University Press.

https://online.vitalsource.com/#/books/9780192640505 California Management Review. (2018, February 8). Evidence-based management [Video]. cielo24.

https://c24.page/4we52qyqag2tn693eu2psmkt85 Centers for Disease Control Prevention. (2022, June 28). The scientific method [Video]. cielo24.

https://c24.page/pqrdbhuvh65rh7yu7zx54g2xsv Charlier, S. D., Brown, K. G., & Rynes, S. L. (2011). Teaching evidence-based management in MBA

programs: What evidence is there? Academy of Management Learning & Education, 10(2), 222–236. https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc t=true&db=bth&AN=62798931&site=ehost-live&scope=site

Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods

approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964 GarryKillian. (n.d.). Abstract big data graphic [Image]. Freepik. https://www.freepik.com/free-vector/abstract-

big-data-graphic_10559761.htm#fromView=image_search&page=1&position=3&uuid=1beadf48- 7749-43c0-b98c-08aaa0ebd77e

Harwood, S. (2022, November 7). Complex problems and dealing with them on a research methods course in

a business school. Systemic Practice and Action Research, 2023(36), 587-607. https://research- ebsco-com.libraryresources.columbiasouthern.edu/linkprocessor/plink?id=82eefbef-264f-3a19-8499- ae67714f07c3

IfD_Qualitative Research Specialists. (2020, August 30). Ontology epistemology methodology and methods I

Ontology and epistemology in research examples [Video]. cielo24. https://c24.page/wb7t6w42t7ah9pyj499ff4xsc5

Joebite. (n.d.). ID 291589842 [Image]. Dreamstime. https://www.dreamstime.com/difference-quantitative-

data-numerical-measurements-statistical-analysis-qualitative-observations-subjective- image291589842

Lancelotlachartre. (n.d.). ID 110228264 [Photograph]. Dreamstime. https://www.dreamstime.com/business-

illustration-showing-concept-evidence-based-management-image110228264

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Mohrman, S. A., Gibson, C. B., & Mohrman, A. M., Jr. (2001). Doing research that is useful to practice: A model and empirical exploration. Academy of Management Journal, 44(2), 357–375. https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc t=true&db=bth&AN=4377989&site=ehost-live&scope=site

Pfeffer, J., & Sutton, R. I. (2006a). Evidence-based management. Harvard Business Review, 84(1), 62–74.

https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire ct=true&db=bth&AN=19117732&site=ehost-live&scope=site

Pfeffer, J., & Sutton, R. I. (2006b). Hard facts, dangerous half-truths, and total nonsense: Profiting from

evidence-based management (2nd ed.). Harvard Business School Press. Rousseau, D. M. (2006). Is there such a thing as evidence-based management? Academy of Management

Review, 31(2), 256–269. https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire ct=true&db=bsu&AN=20208679&site=eds-live&scope=site

Rousseau, D. M. (2018). Making evidence-based organizational decisions in an uncertain world.

Organizational Dynamics, 47(3), 135–146. https://doi.org/10.1016/j.orgdyn.2018.05.001 Rousseau, D. M. (2020). The realist rationality of evidence-based management. Academy of Management

Learning & Education, 19(3), 415–424. https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire ct=true&db=bsu&AN=146635032&site=eds-live&scope=site

Sociology Live! (2015, November 24). Scientific method [Video]. cielo24. https://c24.page/c74hcrtnk7jgduza263rbtqt79

Thesis Helper. (2021, December 29). Differences between research methods and research methodology [Video]. cielo24. https://c24.page/4hc4y9y7zf7pesqf6nudhhwec2

Van Aken, J. E., & Romme, G. (2009). Reinventing the future: Adding design science to the repertoire of organization and management studies. Organization Management Journal, 6(1), 2–12. https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc t=true&db=bth&AN=48971122&site=ehost-live&scope=site