Difference between revisions of "Case Study Guidelines"
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* types general types of case studies: | * types general types of case studies: | ||
# exploratory: explores a relatively unknown issue, generally unstructured, develop hypotheses for further research | # exploratory: explores a relatively unknown issue, generally unstructured, develop hypotheses for further research | ||
| − | # descriptive: | + | # descriptive: some important features of the case(s) have been identified beforehand and are used to structure the case write-up |
| − | # explanatory | + | # explanatory: a cause-effect hypothesis is stated, and the case is structured to test this relationship |
===Specific=== | ===Specific=== | ||
====Exploratory==== | ====Exploratory==== | ||
| + | An example of an exploratory research question is: What are the concrete impacts of DSS in sustainable forest management? | ||
| + | |||
====Descriptive==== | ====Descriptive==== | ||
| + | The [Participatory_planning_case_template] describes the roles of participation and DSS in particular cases using a descriptive structure based on Simon's (1960) stages of decision making: organization-intelligence-design-choice-monitoring | ||
| + | |||
====Explanatory==== | ====Explanatory==== | ||
| − | + | An example of an explanatory research question is: What factors make a forest DSS successful? | |
| − | + | For a DSS to be successful, a simple model could consider three stages: 1) development of the DSS itself > 2) adoption of the DSS by users > 3) use of the DSS. A case could focus on one of these stages or try to cover all three. | |
; DSS development factors | ; DSS development factors | ||
; DSS adoption (by users) factors | ; DSS adoption (by users) factors | ||
| Line 56: | Line 60: | ||
** organization, intelligence, design, choice, monitoring | ** organization, intelligence, design, choice, monitoring | ||
==Methods - maintaining objectivity== | ==Methods - maintaining objectivity== | ||
| + | * Case study is known as a triangulated research strategy. Snow and Anderson (cited in Feagin, Orum, & Sjoberg, 1991) asserted that triangulation can occur with data, investigators, theories, and even methodologies. Stake (1995) stated that the protocols that are used to ensure accuracy and alternative explanations are called triangulation. The need for triangulation arises from the ethical need to confirm the validity of the processes. In case studies, this could be done by using multiple sources of data (Yin, 1984). ([http://www.nova.edu/ssss/QR/QR3-2/tellis1.html Tellis 1997]) | ||
| + | ===Specific=== | ||
* How to guarantee the “fairness” in evaluating case studies? | * How to guarantee the “fairness” in evaluating case studies? | ||
** Each of us works only on CS in which is not directly involved; widening the group; …; the problem does not exist | ** Each of us works only on CS in which is not directly involved; widening the group; …; the problem does not exist | ||
Revision as of 07:04, 2 November 2011
DRAFT ideas for discussion at Leuven meeting.
Contents
- 1 What is a case study?
- 2 Purpose(s) of FORSYS Case Studies
- 3 Methods - Theory development
- 4 Methods - Case definition options
- 5 Methods - Selecting studies
- 6 Methods – Data sources & collection methods
- 7 Methods - describing cases
- 8 Methods - maintaining objectivity
- 9 Reporting results
- 10 Other issues
What is a case study?
Excerpted from Wikipedia Case Study:
Thomas[4] offers the following definition of case study: "Case studies are analyses of persons, events, decisions, periods, projects, policies, institutions, or other systems that are studied holistically by one or more methods. The case that is the subject of the inquiry will be an instance of a class of phenomena that provides an analytical frame — an object — within which the study is conducted and which the case illuminates and explicates."
Rather than using samples and following a rigid protocol (strict set of rules) to examine limited number of variables, case study methods involve an in-depth, longitudinal (over a long period of time) examination of a single instance or event: a case. They provide a systematic way of looking at events, collecting data, analyzing information, and reporting the results. As a result the researcher may gain a sharpened understanding of why the instance happened as it did, and what might become important to look at more extensively in future research. Case studies lend themselves to both generating and testing hypotheses.[5]
Purpose(s) of FORSYS Case Studies
General
- (Forsys general) Produce guidelines for the development and use of forest decision support systems
- types general types of case studies:
- exploratory: explores a relatively unknown issue, generally unstructured, develop hypotheses for further research
- descriptive: some important features of the case(s) have been identified beforehand and are used to structure the case write-up
- explanatory: a cause-effect hypothesis is stated, and the case is structured to test this relationship
Specific
Exploratory
An example of an exploratory research question is: What are the concrete impacts of DSS in sustainable forest management?
Descriptive
The [Participatory_planning_case_template] describes the roles of participation and DSS in particular cases using a descriptive structure based on Simon's (1960) stages of decision making: organization-intelligence-design-choice-monitoring
Explanatory
An example of an explanatory research question is: What factors make a forest DSS successful? For a DSS to be successful, a simple model could consider three stages: 1) development of the DSS itself > 2) adoption of the DSS by users > 3) use of the DSS. A case could focus on one of these stages or try to cover all three.
- DSS development factors
- DSS adoption (by users) factors
- A commonly used perspective on the adoption of technologies, such as DSS, relies on theories of innovation diffusion. Rogers (2003) text on innovation diffusion theory states that adoption rates depend on five attributes of innovations: relative advantage, compatibility, complexity, triability and observability.
- DSS use factors
- Once the decision is made to use a DSS, both technical and social factors are likely to influence its success. DeLone and McLean (1992, 2003) have developed a widely cited framework for technical factors, which begins with: system quality, information quality, and service quality. Gordon (2006) reviewed social success factors, and reduced them to DSS effects on: participation, communication, translation, and mediation.
Methods - Theory development
General
- One or more existing theories vs. grounded theory
Specific
- Does the adoption and use of DSS vary by problem type?
Methods - Case definition options
- The application of a single DSS to a single problem (probably the most common type of case definition)
- A particular DSS over its lifetime (multiple problems)
- The application of DSS (possibly multiple) in a problem domain (eg fire)
Methods - Selecting studies
General
- Replication strategy: same DSS & same context OR same DSS & different contexts OR different DSS & same context, etc
- How many cases do we undertake?
- Depends on the detail needed (cases could be short or long, depending on purposes)
Specific
- Representative sample of problem types
- asking other FORSYS members preferences; looking at country reports; looking at wiki contents; …lottery
Methods – Data sources & collection methods
- six general sources for case studies: documents, archival records, interviews, direct observation, participant observation, physical artifacts
Methods - describing cases
- The participatory planning case studies used a descriptive framework based on Simon's (1960) stages of decision making
- organization, intelligence, design, choice, monitoring
Methods - maintaining objectivity
- Case study is known as a triangulated research strategy. Snow and Anderson (cited in Feagin, Orum, & Sjoberg, 1991) asserted that triangulation can occur with data, investigators, theories, and even methodologies. Stake (1995) stated that the protocols that are used to ensure accuracy and alternative explanations are called triangulation. The need for triangulation arises from the ethical need to confirm the validity of the processes. In case studies, this could be done by using multiple sources of data (Yin, 1984). (Tellis 1997)
Specific
- How to guarantee the “fairness” in evaluating case studies?
- Each of us works only on CS in which is not directly involved; widening the group; …; the problem does not exist
Reporting results
General
- Possible audiences: academic, DSS developers, forest managers, DSS funders
Specific
- Add to wiki
- Publish most developed case studies as journal articles (seek special issue?)
