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Theory-Building with Cases
Theory-building with cases comprises (a) formulating new propositions that emerge from the empirical evidence in a sample of cases and (b) testing them in the same sample. The main difference with most other forms of generating new propositions (e.g., analyzing the theoretical literature, brainstorming) is its empirical character. The empirical character of theory-building with cases is the main difference between this process and most other forms of generating new propositions (e.g., analyzing the theoretical literature, brainstorming). In this empirical process, theoretical formulations are accepted only when they are confirmed in a test in the sample from which the proposition was built. Thus such theory-building differs from other forms of discovering new propositions in empirical evidence (e.g., in “exploratory” research).
Conceptual Overview and Discussion
A theory-building study always requires a sample of cases, because this is needed for the test of the new probabilistic propositions. Each new proposition that is built needs to be tested in other cases. The Yin-Eisenhardt approach is only one influential and frequently cited approach to theory-building with cases in the literature. This entry first describes and evaluates this approach and then discusses and illustrates a revision of it. For illustrative purposes, an example is used that is taken from another publication by Kathleen Eisenhardt, in which she builds a number of new propositions concerning the determinants and effects of fast strategic decision making in firms in high-velocity environments based on empirical evidence collected in eight microcomputer firms. The example used here is the following proposition: “The greater the use of RealTime information, the greater the speed of the strategic decision process.”
Application
The Yin-Eisenhardt Approach
The core of the Yin-Eisenhardt approach to theory-building with cases consists of three steps: (1) within-case analysis, (2) cross-case pattern search, and (3) replication.
- Within-Case Analysis. Within-case analysis typically involves detailed case study write-ups for each site. These write-ups are often simply pure descriptions. The overall idea is to become intimately familiar with each case as a standalone entity. Because the unit of analysis in the study of decision making in microcomputer firms is the decision, the case study write-up in this study was a “decision story” that was developed by combining the collected data into a time line that included all events relevant to the decision.
- Cross-Case Pattern Search. A number of tactics can be used in this crucial step in which the theory (at least its building blocks, propositions) is actually built. One tactic is to select categories or dimensions and then to look for within-group similarities coupled with intergroup differences. A second tactic is to select pairs of cases and then to list the similarities and differences between each pair. Overall, the idea behind these (and other) cross-case searching tactics is to force investigators to go beyond initial impressions. Consider the example of a pair of cases presented in Table 1.
Starting from the evidence in the decision stories generated in the within-case analysis, a number of indicators of RealTime information use were developed, such as (a) the presence of a vice president for finance, (b) the number and kind of performance measures and targets that are reviewed regularly, and (c) the number of meetings regularly scheduled to review current operations. Table 1 presents the scores on these indicators as well as the decision duration for two cases. It is not difficult to see how a proposition such as “The greater the use of RealTime information, the greater the speed of the strategic decision process” could emerge from the evidence in this pair of cases and how the researcher's belief in this proposition could be reinforced by evidence from other pairs of cases showing a similar pattern.
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