Executive Doctor of Business Administration (EDBA) Program Case Study

Abstract

Begin writing here…

Checklist:

1. Briefly introduce the study topic, state the research problem, and describe who or what is impacted by this problem.
2. Clearly articulate the study purpose and guiding conceptual framework of the case study.
3. Provide details about the research method, design, procedures, and analysis.
4. Clearly present the results in relation to the research question(s).
5. State the conclusions to include both the potential implications of the results and the recommendations for future research and practice.
6. Do not include citations and abbreviations or acronyms, except those that are noted as exceptions by the American Psychological Association (APA).

General Literature Review Guidelines for EDBA Students

1. A Literature Review has depth and presents a critical analysis and synthesis of the literature that provides a context for your study. Discussion is comprehensive, organized, and flows logically. 
2. Everything that is said in this paper needs to be supported by research and must be shown through in-text citations. The actual Literature Review section needs to tackle the specific problem/purpose with depth and present a critical analysis and synthesis of the literature that provides the context of the study (Torraco, 2005). The discussion must be comprehensive, organized, and flow logically. Please use themes and/or subtopics as headings. 
3. Please watch this Webinar on “Writing the Lit Review”. It’s an excellent lecture on the topic. Save the link so you can reload whenever you wish.
4. Please watch these Webinars on “Referencing APA Style”. These are very useful lectures on the topic. Save the links so you can reload whenever you wish.
5. Please watch this Webinar on “Writing Structured Paragraphs”. It’s an excellent lecture on the topic. Save the link so you can reload whenever you wish.

Further Embedded Case Study Guidelines: 

Case studies enable a rich and in-depth description of data that, besides providing evidence, can enable the discovery of theory. Research design should offset the intrinsic limits of case studies and respond to the needs of using them to inform extrapolations. Solid evidence from case studies is the cornerstone to go beyond earlier extrapolations by embedding them into empirical realities. Therefore, a careful research design is crucial particularly for what concerns the more in-depth case-level evidence and corresponding case studies. In this regard, it should be underlined in fact that, first of all, generalization from case studies may be of dubious credibility if the cases are not selected according to a reasoned research design and especially when the cases are exemplary (best practices) rather than representative of the average situation in a given field. 

The purpose of case-level evidence is not only that of building a case study per se, rather they must provide evidence to be used to generate the scenarios and coefficients for eventual quantitative extrapolations. As such, they cannot be only best practices, otherwise the generated case-level evidence will bias the extrapolations. Second, case studies should be context-embedded in the sense of reflecting on the peculiarities of the industry sectors discussed within the case study . This requires a careful selection of cases to reflect sectoral and size difference and, thus, enable more granular and credible extrapolations. Third, case study selection should be transparent (to allow others to replicate it in the future) and used systematically. This reasoned approach to case study research design that will be applied to your paper will produce a limited set of case-level evidence to start building the fundamental basis for further qualitative and quantitative research. So, by following this template you ensure a high-quality output for your specific embedded case study while achieving the outcome, research basis and agenda for future research and studies in your chosen field. 

Embedded Case Study Writing Guidelines: 

1. Please use reliable and methodologically rigorous studies that are related to your paper’s topic and problem (once they are specified). Additionally, present works that provide alternate and opposing perspectives on your topic area in order to demonstrate unbiased research (balanced approach), focusing particularly on those works that address the main ideas in your field or practice and describe areas of controversy, including historical, seminal, and current works.
2. The problem, purpose, and research question(s) must remain aligned among them. If work deviates among these foundational elements of your paper it will change the alignment and it will be difficult to determine the direction of the research. More information on the critical role of alignment among the elements of a study is given within this template.
3. The topic must be very focused and specific. Do not try to cover too many issues in one scholarly paper. If your topic is too broad, then it cannot be considered doctoral-level research work, and you will not be able to create a proper literature search strategy.
4. Do not begin too many sentences with the author name. State ideas and then place the citation after the presentation of the literature/ideas.
5. You cannot just use the same citation continuously in one paragraph—you must demonstrate synthesis of knowledge—you need at least three citations in each paragraph—even if you are simply describing a study—to show that other researchers support your position (not just one author—and not just support form one source). 
6. Always place citations after the first sentence of the paragraph. Always end the paragraph with a citation (This does not include the citations within the paragraph). 
7. To fulfill the partial requirements of your EDBA degree, your case study must be approximately 10,000 words and considered “of publishable quality”. It is strongly recommended that before your final submission you have your manuscript reviewed and edited by a professional APA Editor.
8. Your supervisor will evaluate your case study and the EDBA Committee will use the classic five-stage integrative review process (Russel, 2005), which covers: (1) problem formulation, (2) data collection or literature search, (3) evaluation of data, (4) data analysis, and (5) interpretation and presentation of results. The integrative review methodology must involve detailed and thoughtful work, the outcome of which can be a significant contribution to a particular body of knowledge and, consequently, to practice and research.

Data Analysis Guidelines: 

1. Qualitative data analysis deals with turning written data such as interview, field notes, and archival documents into findings and conclusions. Case study data analysis is the process of examining, categorizing, tabulating, testing, and converging case study evidences to produce empirically based findings (Yin, 2017). The most common problem researchers encounter in qualitative studies is being confronted with a huge amount of data that has piled up unanalyzed during the data collection period (Maxwell, 2013). The interweaving of the data collection and data analysis process increases research rigor (Miles, Huberman, & Saldana, 2014). 
2. The process of data analysis begins with reviewing and examining the data to determine what is worth investigating by reading through the interview-transcribed data and other documents that are to be analyzed (Maxwell, 2013), determining and following a specific analytical technique appropriate for the data, coding the interview data, and interpreting the findings (Miles et al., 2014). The analysis of data will allow you to identify emerging themes and patterns that help offer explanation and answers to the central research question. When the emerging themes are categorized, findings will emerge that will help achieve a deep understanding of the gap in the literature you’ve identified.  
3. A documentation and understanding of the conditions under which a study takes place will also boost the repeatability or replication of the study if the study is to be conducted by another researcher under similar settings. As the researcher, your focus will be to develop the codes to be applied to the data, analyze the data, and connect the result of the data analysis with the central research question and draw conclusions in such a way that anyone can check with clarity the entire research process leading to the conclusions. This is called establishing an audit trail.
4. Data analysis needs to be approached with rigor when applying any of the five analytical techniques: pattern matching, explanation building, time series analysis, logic models, and cross case synthesis for multiple-case study research. For detailed explanations of the techniques and which are appropriate for use for specific case study designs, please see Yin (2017).  
5. In qualitative inquiry, a code is a researcher’s generated construct that is symbolically assigned to capture the summative, or the essence, of every statement in the transcript. Code could be a word or summative short phrase assigned to individual datum in the data to initiate the analytic process of a qualitative research (Miles et al., 2014; Saldaña, 2015). In an interview-based case study and after each of the participants has been served with a copy of their transcript for validation, you begin the initial review of data and begin the coding. There will be two cycles of coding: the pre-codes and the actual code. The pre-coding provides the basis for coding and allows comparison of the pre-code with the code, and once the codes have been determined, the next step is to roll the codes into categories for thematic analysis. Saldaña (2015) mentioned that coding is a cyclical act and it is rarely possible to arrive at perfect codes during the first cycle. You may carry out the coding activities using a Microsoft Excel template. Hence, coding is necessary before the adoption of computer-assisted qualitative data analysis (CAQDAS) to aid the efficient analysis of the qualitative data. Manual coding is also an action if you do not wish to use CAQDAS. NVivo is a comprehensive data management and analysis software with capacity to organize and automate coding, and analyze varieties of data such as interview, field notes, video files, and images from multiple sources. 
6. The next step is the interpretation of the data analysis. This involves comparing various themes that emerge from the analysis of the data generated through multiple sources (interview, field notes, and archival data) and comparing the findings with the theoretical proposition generated from the literature review. Yin (2017) noted that the strength of a case study’s findings rests in its ability to be generalized to the theoretical propositions established from the literature. To this end, and since this study is framed by a conceptual framework, the alignment of these conceptual categories to the overall findings from the case study research is essential in interpreting the result to arrive at a deep understating of your identified purpose. 
7. The final step in the data analysis process with both primary and secondary data collection is comparing the findings with the findings from similar studies, which will help in validating the findings of the study. If needed, identify discrepant cases (data that are out of congruence with the patterns or explanations that are emerging from the data analysis). Analyzing, interpreting, and reporting discrepant cases is necessary as it may help you broaden, revise, or confirm the patterns emerging from the data analysis and further enhance the study’s credibility. 

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