No abstract

No abstract

We develop a rule-based contingency misfit model and related hypotheses to test empirically the Burton and Obel (1998) multi contingency model for strategic organizational design. The model is a set of "if-then" misfit rules, in which misfits lead to a loss in performance; they are complements to the strategy and organizational contingency theory fit rules. Using data from 224 small- and medium-sized Danish firms, misfits are categorized and identified. Then, performance hypotheses are developed and tested using regression models. We confirm the hypotheses that firms with situational misfits or contingency misfits, or both, incur performance losses in return on assets compared with firms with no misfits. Contrary to our hypotheses, we did not find that additional misfits lead to increased performance loss. Our results suggest that just one misfit of any kind may significantly compromise performance. These results yield a deeper understanding of organizational contingency theory, as well as implications for the rule-based fit-misfit organizational design model.Misfit, Contingency Theory, Organizational Design, Complexity Theory, Strategy Implementation

No abstract

Preface to the First EditionThis part also contains seven cases specifically developed to be used with Organizational Consultant. For Part 2, Nancy Keeshan is a coauthor.Although Part 1, Part 2, and Organizational Consultant can be considered as a unit, each is self-contained. For instance, Organizational Consultant can also be used with other textbooks in organizational theory such as Robbins (1990), Daft, (1992), and Mintzberg, (1984.Organizational Consultant is a teaching tool in itself. Explanation and help functions contain many parts of the theory. Extensive use ofOrganizational Consultant can teach the student many issues of the theory.The book and software have been developed over some years. We have used both the book and software in many courses both at The Fuqua School of Business and Odense University. We would like to thank our students for valuable comments and critique. Many students developed cases from their own organization as part of the courses and we were allowed to include some ofthese cases in Part 2 of this book. We would like to thank

Initiatives to redesign cities so that they are smarter and more sustainable are increasing worldwide. A smart city can be understood as a community in which citizens, business firms, knowledge institutions, and municipal agencies collaborate with one another to achieve systems integration and efficiency, citizen engagement, and a continually improving quality of life. This article presents an organizational framework for such collaboration and employs it to analyze Smart Aarhus, the smartcity initiative of Aarhus, Denmark. Based on the experiences of Smart Aarhus to date, it offers a set of lessons that can benefit the designers, leaders, and policymakers of other smart-city initiatives.

Cohen and Richard M. Cyert (1965) Computational models are widely applied to address fundamental and practical issues in organization science. Yet, computational modeling in organization science continues to raise questions of validity. In this paper, we argue that computational validity is a balance of three elements: the question or purpose, the experimental design, and the computational model. Simple models which address the question are preferred. Non-simple, imbalanced computational models are not only inefficient but can lead to poor answers. The validity approach is compared with well-known validity criteria in social science. Finally we apply the approach to a number of computational modeling studies in organization science, beginning with Cyert's. They were pioneering and are examples of well designed computational models.

We analyze performance and emotions as antecedents and consequences of team strategic decisions to explore a new routine versus exploiting an existing one. In a laboratory study, we examine team decision making over time and draw causal inferences about the relationships among team emotions, team performance, and explore–exploit decisions. We use self‐report data to measure team emotions, and validate results with psychophysiological data. We find that declines in performance increase the likelihood that teams decide to explore new routines rather than exploit existing ones. We also find a marginal positive effect of positive emotions, as measured by both self‐report and psychophysiological data, on team decisions to explore a new routine. Further, teams successful at implementing new routines report increased positive emotions, as measured by the self‐report data. This relationship is fully mediated by performance change. Copyright © 2015 John Wiley & Sons, Ltd.