Data Collection Techniques Discussion Topic Cond

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Data Collection Techniques Discussion Topic Cond

Consider the readings for this module concerning the analysis of case study data. In your post, address the following:

  1. What three key ideas were most significant from the readings;
  2. Two analytic techniques that you would like to explore or discuss further; and
  3. One element/issue/concept that you found difficult in your understanding or application of case study data analysis.

In your responses to other students, focus on questions 2 and 3.

This assignment is a discussion, so remember to join the conversation early in the module. Remember to cite sources—particularly in your initial post. Finally, respond to several of your classmates.

Background Info

Conducting the Case Study

The following readings are required for Module 2. Optional readings can be found at the end of each section and while not required, may help you understand the material better and be useful to you if you choose to conduct a case study research method for your doctoral study. All readings can be accessed in the Trident Online library, unless linked to another source.

Methods of Data Collection

Data collection in a case study is largely contingent upon the skills of the researcher—as well as the access that the researcher may have to the sources of data. In this method, the researcher is an active participant in the process, so he or she needs to be able to ask good questions, listen impartially, and critically interpret the answers. This process will be framed by the questions and propositions of the study (described in module one) and the ability to process the information collected in an unbiased manner.

To guide the collection of case student data, the researcher relies on a case study protocol. The protocol addresses the following issues (Rowley, 2002, p. 22):

  1. An overview of the case study project.
  2. Field procedures, such as use of different sources of information, and access arrangements to these sources.
  3. Case study questions, or the questions that the case study researcher needs to keep in mind when collecting data. These questions are posed to the researcher, and not to any specific respondents, although they may be used to guide the formulation of questions to interviewees, and members of focus groups. In complex cases studies it is important to differentiate between the questions asked of specific interviewees and used to interrogate documents, questions asked of the individual case, and questions to be asked across multiple cases.

Yin, R.K. (2009). Collecting case study evidence. In Case Study Research: Design and Methods, Fourth Ed.(pp. 99-126). Thousand Oaks, CA: Sage Inc.

Gagnon, Y. (2010). Stage 5: Collecting data. In The Case Study As Research Method : A Practical Handbook (pp. 55-68). Québec [Que.]: Les Presses de l’Université du Québec (EBSCO ebook Collection)

Farquhar, J. D. (2012). Data collection. In Case study research for business (pp. 65-83). London, : SAGE Publications Ltd (SAGE Research Methods Database)

Optional

Beverland, M. & Lindgreen, A. (2010). What makes a good case study? A positivist review of qualitative case research published in Industrial Marketing Management, 1971-2006. Industrial Marketing Management, 39(1), 59-63.

Easton, G. (2005). Critical realism in case study research. Industrial marketing Management, 39(1), 118-128. (Science Direct DataBase)

Johnson, P., Buehring, A., Cassell, C. & Symon, G. (2006). Evaluating qualitative management research: Toward a contingent criteriology. International Journal of Management Review, 8(3), 131-156. (EBSCO: Business Source Complete Database)

Data Analysis

The readings from the section above strongly demonstrate that most case studies rely on multiple sources of evidence. Each source adds a unique perspective on the research question – yielding a more complex and rich view of the problem and greater insight into possible solutions. It is important to note that no matter which sources of information are used, three tenets of data collection are always relevant (Rowley, 2002):

  1. Triangulation – Because case studies collect evidence from two or more sources, findings are corroborated and cross-verified.
  2. Case Study Database – Evidence that is collected in the course of the study must be kept in an evidence database The final report that is the outcome of the study will be strengthened and validated by the availability of well-organized and complete repository of the evidence. This database may consist of interview notes, documents, recordings, and the researcher’s analytical notes. When preparing the final report, your committee can advise you as to whether or not you should include some of this evidence as an appendix.
  3. Chain of Evidence – It is critical to maintain a chain of evidence. This means that it should be clear how and where the report draws on different sections of the database, indicated by accurate citations of interviews and documents.

It should not be understated how difficult it can be to analyze case study evidence! Because there is so much rich data from so many sources, the researcher can become overwhelmed. Therefore, it is necessary for the researcher to be highly organized, categorizing the data as it is collected, relating it to the initial propositions of the study, and making tentative assessments as to whether the evidence supports the propositions or suggests something else. These categorizations and assessments may change as the study progresses (in the light of additional evidence), but the process is always tied to the propositions or the researcher may find himself virtually drowning in the data and losing sight of the objectives of the study.

Exceptions do exist, however. Exploratory cases may not use propositions. Instead, the researcher should develop a “conceptual framework” or “story” for organizing the initial assumptions of the researcher as well as the presentation of the data. This framework comprises the developing themes of the study and new evidence is categorized and organized according to these themes so it can be analyzed and verified from multiple sources.

If this seems vague, it is. Data analysis in case studies does not follow a mechanistic process, but often evolves as directed by the data itself. It is often iterative in nature. The readings below will make this clearer. That said, any good case study analysis follows these principles Rowley, 2001, P. 24):

1. The analysis makes use of all of the relevant evidence.

2. The analysis considers all of the major rival interpretations, and explores each of them in turn.

3. The analysis should address the most significant aspect of the case study.

4. The analysis should draw on the researcher’s prior expert knowledge in the area of the case study, but in an unbiased and objective manner.

Yin, R.K. (2009). Analyzing case study evidence. In Case Study Research: Design and Methods, Fourth Ed. (pp. 126-163). Thousand Oaks, CA: Sage Inc.

Gagnon, Y. (2010). Stage 6: Analyzing data . In The Case Study As Research Method : A Practical Handbook (pp. 69-82). Québec [Que.]: Les Presses de l’Université du Québec (EBSCO ebook Collection)

Gagnon, Y. (2010). Stage 7: Interpreting data. In The Case Study As Research Method : A Practical Handbook (pp.83-92). Québec [Que.]: Les Presses de l’Université du Québec (EBSCO ebook Collection)

Farquhar, J. D. (2012). Managing and analysing data. In Case study research for business (pp. 84-99). London, : SAGE Publications Ltd (SAGE Research Methods Database)

Optional Reading

Chapters in the following book goes into much more detail on data collection techniques – including quantitative analysis in case studies.

Gillham, B. (2000). Case Study Research Methods. London: Continuum (EBSCO eBook Collection)

The following is a good all-around reference for case study methods. Chapters 7, 8 and 16 are particularly helpful and cover material on computer-based qualitative data analysis:

Byrne, D. & Ragin, C. C. (2009).The SAGE handbook of case-based methods London, : SAGE Publications Ltd (SAGE Research Methods Database)

Hamilton, L. & Corbett-Whittier, C. (2013). Using technology to manage and analyse your data. InBera/sage Research Methods in Education: Using case study in education research (pp. 147-156).