Access over 20 million homework & study documents

Case Study Research Methods

Content type
User Generated
Type
Study Guide
Rating
Showing Page:
1/15
Case Study Research Methods for Geographic
Information Systems
Harlan J. Onsrud & Jeffrey K. Pinto
National Center for Geographic Information and Analysis
University of Maine
Orono, Maine 04469
and
Bijan Azad
Boston Redevelopment Authority &
Massachusetts Institute of Technology
Abstract
Although they are perhaps the most commonly-used and popular research methods, case studies and other
qualitative forms of social science research have long been criticized for their lack of generalizability to
the larger population and lack of sampling controls. These criticisms may be aptly addressed and
solutions constructed by evaluating the rules of scientific method within case research environments. By
using more logically consistent, rigorous, and systematic approaches, some of the shortcomings of case
study methods may be overcome. This article draws from the management information systems (MIS)
and organization behavior (OB) literature to make some suggestions on how to conduct and evaluate GIS
case study research. It reviews the requirements of natural science research models, particularly as
described by Lee (1989), and provides examples of how the substance of those requirements may be met
in the context of GIS case studies.
Introduction
Case study methodologies have been suggested within the GIS community as appropriate for researching
a range of GIS implementation, utilization, and diffusion issues (Zwart 1986, Niemann et. al. 1988,
NCGIA 1989, Craig 1989, Azad 1990). These issues include identifying the determinants of adoption
outcomes; isolating critical adoption factors and processes for particular classes of users; investigating the
stages at which change agent, opinion leader, and champion influences are most critical; assessing use
success; determining levels in the organizational structure where GIS products are used and to what
extent; identifying the forms of decision making which have utilized GIS; identifying factors and
processes leading to rejection of previously embraced GIS; and identifying organizational and societal
consequences of GIS (Onsrud and Pinto, 1991).
Case studies examine phenomena in their natural settings and typically involve collection of data by
several different means from a range of sources. When used as the sole research heuristic device, case
studies have been criticized for their limitations in terms of generalizability to the larger population and
lack of sampling controls (Piore 1979, Bariff and Ginzberg 1982, Bonoma 1985). It is generally
acknowledged in the social science research community that no single research methodology is most
appropriate for all research applications (Williams, Rice & Rogers 1988). In addition, it is generally
agreed that using multiple forms of research to investigate an issue leads to better and more reliable
results than using a single methodology (Yin and Heald 1975, Cook and Campbell 1979, McClintock,
Brannon & Maynard-Moody 1979, Kaplan and Duchon 1988). Case studies are often included and
occupy a lead position in the suite of methods used by researchers to evaluate intervention strategies
within organizations. However, there is a need to clarify the explicit methodological means by which case
studies within GIS application environments should be carried out.
For purposes of this paper, a case study is an examination of a phenomena in which the primary purpose
of the observer has been to carry out research rather than to implement a system or improve an
1

Sign up to view the full document!

lock_open Sign Up
Showing Page:
2/15
operational environment. That is, since the techniques suggested in this article are intended for
individuals testing theories relating to the efficacy of intervention strategies, they will be less useful to
practitioners who are implementing systems. Of course, the overall intent of investigating various case
study techniques is to aid researchers in building a relevant body of knowledge which eventually will aid
practitioners in their system implementation and improvement efforts.
Let us assume that the general GIS practitioner community is confronted with an implementation issue in
which the most appropriate intervention strategies to use in addressing that issue are difficult to
determine. For instance, organizations throughout the general GIS community currently are involved in
determining which processes they should follow and which factors they should consider to ensure that
their GIS systems are used to their greatest benefit over time. Another example is determining which
policies agencies should pursue in regard to public access to their GIS database and which organizational
and legal tools should be used in carrying out those policies. When confronted with these and similar
problems, the practitioner community engages in trial and error processes in attempting to find out "what
works." The brainstorming and testing engaged in by the practitioner community results in a substantial
body of valuable knowledge. This knowledge base of successes and dead ends is communicated by
various methods throughout and among the community. However, as the experience base grows and
system implementations become more diverse and complex, large numbers of conflicting and competing
messages may be received on what works or does not. At this point in the diffusion of a technology (i.e.
when the appropriate decision routes in addressing an issue are no longer intuitively obvious), social
science researchers can play an important role in providing direction to the user community.
Consequently, there is a need for social science researchers to construct research questions from the
existing experience base and to develop a body of research that builds up falsifiable hypotheses and tests
them through rigorous methods following the nature of scientific canons.
Utility of Case Study Approaches
The traditional phases of accruing knowledge within "learned" settings are often expressed as exploration,
hypothesis generation, and hypothesis testing (Glaser & Strauss, 1967). In the exploration phase,
researchers descriptively study how organizations have dealt with the constraints imposed upon them.
These knowledge capture studies form the basis for developing theories regarding phenomena and for
hypothesizing prescriptive strategies. After deriving the theories and generating hypotheses in support of
them, the researcher proceeds to the hypothesis testing phase.
Conventional thinking in the MIS literature indicates that case study approaches are highly appropriate
for the exploration and hypothesis generation phases but are generally ill-suited to the hypothesis testing
phase (Roethlisberger 1977, Bonoma 1983, Benbasat 1984). The argument made is that, although
disconfirmation of a hypothesis might be shown by a single case, reasonable confirmation of a hypothesis
requires analytic deductive testing of a representative and substantial sample (Benbasat, Goldstein &
Mead 1987). By this reasoning, data must be gathered in a form suitable for quantitative processing and
must be gathered for a significant number of cases to evidence confirmation of a hypothesis reliably
(Bariff and Ginzberg 1982, Dickinson, Benbasat & King 1982, Kauber 1986).
A recent article by Lee (1989) challenges the conventional wisdom with regard to the use of case studies
in the hypothesis testing stage. He argues that the data or results generated from case studies need not be
quantitative, statistical, or mathematical in order to be analytically rigorous or "scientific." We believe the
application of his approach to the evaluation of GIS implementations could provide a useful and practical
means for the GIS community to better isolate those factors and processes which are critical for inclusion
in prescriptive implementation and improvement strategies.
Croswell (1989) lists numerous obstacles to successful GIS implementation and categorizes them into
eleven major groups: apathy/fear of change; funding availability or justification; planning/management
support; organization coordination and conflicts; training/understanding of technology; staffing
availability/recruitment; software complexity/maturity of technology; data communication/networking;
data structure and source materials; data and software standards/data integration; and miscellaneous. The
2

Sign up to view the full document!

lock_open Sign Up
Showing Page:
3/15

Sign up to view the full document!

lock_open Sign Up
End of Preview - Want to read all 15 pages?
Access Now
Unformatted Attachment Preview
Case Study Research Methods for Geographic Information Systems Harlan J. Onsrud & Jeffrey K. Pinto National Center for Geographic Information and Analysis University of Maine Orono, Maine 04469 and Bijan Azad Boston Redevelopment Authority & Massachusetts Institute of Technology Abstract Although they are perhaps the most commonly-used and popular research methods, case studies and other qualitative forms of social science research have long been criticized for their lack of generalizability to the larger population and lack of sampling controls. These criticisms may be aptly addressed and solutions constructed by evaluating the rules of scientific method within case research environments. By using more logically consistent, rigorous, and systematic approaches, some of the shortcomings of case study methods may be overcome. This article draws from the management information systems (MIS) and organization behavior (OB) literature to make some suggestions on how to conduct and evaluate GIS case study research. It reviews the requirements of natural science research models, particularly as described by Lee (1989), and provides examples of how the substance of those requirements may be met in the context of GIS case studies. Introduction Case study methodologies have been suggested within the GIS community as appropriate for researching a range of GIS implementation, utilization, and diffusion issues (Zwart 1986, Niemann et. al. 1988, NCGIA 1989, Craig 1989, Azad ...
Purchase document to see full attachment
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Anonymous
Really great stuff, couldn't ask for more.

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Similar Documents