Case Study Guidelines

DRAFT ideas for discussion at Leuven meeting.

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
• Possible audiences: academic, DSS developers, forest managers, DSS funders
• types of case studies: exploratory, descriptive, explanatory

Specific

What factors make a forest DSS successful?

For a DSS to be successful, a simple model considers three stages: development of the DSS itself > adoption of the DSS by users > use of the DSS

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
• If purposes are different, relevant theories will be too

Specific

• Does the adoption and use of DSS vary by problem type?

Methods - Case definition options

• A particular DSS over its lifetime
• The application of a single DSS to a particular problem
• The application of DSS (possibly multiple) in a problem domain (eg fire)

Methods - Selecting studies

General

• Representative sample of problem types
• 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

• 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 - conceptual frameworks

Methods - maintaining objectivity

• 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

• Add to wiki
• Publish most developed case studies as journal articles (seek special issue?)

Other issues