Case writing: An art and A science
The study of management in the food system is undergoing a fundamental change with the growing use of the cash study method of instruction. This approach has been found to produce the higher order thinking skills desired in managers. Unfortunately, the number of management cases dealing with the food system is very limited. This article helps address this need by explaining how those interested in writing cases might do so. First the article describes the context of case writing. Then ten characteristics found in most good cases are explained. Finally a process for writing cases is presented which describes how the ten characteristics are developed when a case is being written. Though case writing is presented as a process, it is seen as an art, and a good case is seen as a literary accomplishment.
Using the case method of teaching
The case method is increasingly popular with instructors teaching about management in the food system. While many have adopted this approach, others would like to but feel they need to know more about the method before doing so. This article aims to help them by explaining this technique. It starts by describing what case studies, or simply “cases,” are, and the benefits of their discussion in class. Then it describes the roles and responsibilities of students and instructors when working with cases. Finally, it gives instructors pointers on how to produce effective class discussions using cases. © 1998 John Wiley & Sons, Inc.
The Search for Environmental Complexity
Contingency organization theory suggests that the match between environmental complexity and formal structure is an important determinant of organizational performance. However, there are a number of different interpretations of environmental complexity which may or may not be related. The purpose of this paper is to outline several different views of environmental complexity and empirically test the extent to which they predict the performance of 26 mechanistically structured antipoverty agencies. Statistical analysis is based on multiple linear regression. Measures for complexity include the general level of socioeconomic development, the occupational mix in the surrounding area, the uncertainty in the immediate environment of the agency, and the reliance of the agency on outside units. The performance criteria are based on an analysis of the degree of goal attainment of the sample units. Results suggest that there are considerable differences in different interpretations of environmental complexity in regard to predicting agency performance. It appears that the combined impact of general environment conditions (socioeconomic development and occupational mix) and reliance on external units forms a basis for measuring environmental complexity.