This study investigates how collective corruption appears, using a computational method. Specifically, acknowledging that the characteristics of collective corruption process are analogous to percolation phenomena, we illuminate that collective corruption is formed by ongoing social interactions in an organizational boundary. By formulating a percolation-based system dynamics model, we consider the behavioral characteristics of collective corruption in terms of individuals’ corruption preferences governed by personal attributes on corruption. We also propose and examine scenarios regarding the formation of collective corruption.

In a rare opportunity, the authors gathered data from two matched health care providers managed by an insurance company where auditors had discovered theft by employees in one of the matched organizations. Data were gathered about the organizations' ethical work climates (EWCs). Analysis revealed statistically significant differences in EWCs across the two organizations. As predicted, the organization with the morally preferred EWCs did not have theft. Both macro- and micro-organizational influences are explored to explain these differences, along with implications for (...) practitioners and academic research. This is the first study to suggest that a priori EWCs can be useful in predicting observable behavior. (shrink)

Building on earlier work on the relationship between corporate social performance (CSP) and a firm’s financial performance, this integrative empirical study supports the theoretical argument that the higher a firm’s CSP the lower its financial risk. Specifically, the relationship between CSP and risk appears to be one of reciprocal causality, because prior CSP is negatively related to subsequent financial risk, and prior financial risk is negatively related to subsequent CSP. Additionally, CSP is more strongly correlated with measures of market risk (...) than measures of accounting risk. Of all CSP measures, reputation for social responsibility appears to be the most important one in terms of its risk implications. (shrink)