Organizational configurations, sets of firms with similarities in a number of essential characteristics, provide important insights into the synergies inherent to certain combinations of structural attributes and the performance effects of firms’ retention of, adaptation to, or decoupling from high-performing configurations. The fundamental assumption is that the better a firm’s “fit” with an ideal type configuration, the higher its performance. Although configurations are multidimensional constructs, researchers often simplify the dynamics of structural changes of configurations and the movement of firms within and between them. This simplification risks mis-specifying the organizational changes necessary for firms to achieve high performance. Using a mix of set-theoretic and econometric methods, we analyze a balanced panel of 244 Swiss firms in 2005, 2008, and 2011. We identify four temporally stable high-performing configurations: the “professional service firm,” the “organic,” the “mechanistic,” and the “small bureaucracy,” and demonstrate that even within this relatively short period, firms are exceptionally versatile in their change tracks. Thus high-performing configurations appear enduring not despite but because of firms' movements through these configurations. Furthermore, we demonstrate the complexity of the fit-performance association and argue that firms with a good fit will not only benefit from implementing an efficient yet firm-unspecific organizational structure, but will—through this configuration additionally improve their ability to exploit inimitable firm-specific resources.
This paper studies stability aspects of solutions of parametric mathematical programs and generalized equations, respectively, with disjunctive constraints. We present sufficient conditions that, under some constraint qualifications ensuring metric subregularity of the constraint mapping, continuity results of upper Lipschitz and upper Hölder type, respectively, hold. Furthermore, we apply the above results to parametric mathematical programs with equilibrium constraints and demonstrate, how some classical results for the nonlinear programming problem can be recovered and even improved by our theory.
In order to promote risky behavior, it is a common practice that casinos incentivize their customers through the provision of free financial means, i.e., free play. Thereby, casino operators try to exploit what is known as the house money effect. However, evidence from the field is scarce and prior research provides explanations that predict different behavioral outcomes. This experimental study analyzes the gambling behavior of 765 casino customers and finds that incentivized customers show not higher but significantly lower levels of risk-seeking behavior, expressed through lower wagers per game and overall smaller losses. This study thus provides evidence against the existence of a house money effect.
This article deals with the analysis of large or complex system dynamics (SD) models, exploring the benefits of a multimethodological approach to model analysis. We compare model analysis results from SD and social network analysis (SNA) by deploying SNA techniques on a pertinent example from the SD literature—the world dynamics model. Although SNA is a clearly distinct method from SD in that it focuses on social actors and their interrelationships, we contend that SD can indeed learn from SNA, particularly in terms of model structure analysis. Our argumentation follows renowned system dynamicists who acknowledge the potential of SD to synthesize and advance theories in social science at both the conceptual and technical levels.
