Ethical Rationality: A Strategic Approach to Organizational Crisis

In this paper, we present an ethical and strategic approach to managing organizational crises. The proposed crisis management model (1) offers a new approach to guide an organization’s strategic and ethical response to crisis, and (2) provides a two-by-two framework for classifying organizational crises. The ethically rational approach to crisis draws upon strategic rationality, crisis, and ethics literature to understand and address organizational crises. Recent examples of corporate crises are employed to illustrate the theoretical claims advanced. Finally, the paper provides guidelines for a morally optimal outcome for the organization and its stakeholders. Peter Snyder is a Ph.D. student in Organizations and Strategic Management at the University of Wisconsin-Milwaukee. His research interests include strategy making and corporate governance. Molly Hall is an attorney who practices international and environmental law in Milwaukee, Wisconsin. She teaches adjunct courses in business ethics, environmental policy, and the European Union. Joline Robertson is a Ph.D. candidate in Organizations and Strategic Management at the University of Wisconsin-Milwaukee. Her research interests include international business. Tomasz Jasinski is a Ph.D. student in Organizations and Strategic Management at the University of Wisconsin-Milwaukee. His research interests include strategic alliances. Janice S. Miller received her Ph.D. from Arizona State Univerity in Business Administration with a concentration in Human Resource management. She has been on the faculty at the University of Wisconsin-Milwaukee UWM since 1996 and has served as the Associate Dean for Academic Programs in the School of Business Administration since 2002. Dr. Miller’s primary research interests include performance management, compensation and ethical issues in organizations.     

Software to support business teams

Organizations are increasingly using the business team concept to gain competitive advantage. Collaboration support software is gaining acceptance as a viable tool among both researchers and practitioners, and an opportunity exists to investigate the specific needs of teams: users working in longitudinal time frames on a variety of tasks. In this article, team software requirements are first derived from a theoretical perspective: office automation and task literature are used to identify a set of domain-independent individual tasks. Group process literature is then used to develop a set of collaborative tasks composed of these individual task components. These individual and collaborative tasks are aggregated with team task and communication support requirements to develop requirements for an integrated software environment that effectively supports business teams. Design considerations for a comprehensive team support system are outlined, a prototype implementation is described, and project contributions and key future research considerations are summarized.     

TRACTABLE ROBUST EXPECTED UTILITY AND RISK MODELS FOR PORTFOLIO OPTIMIZATION

Expected utility models in portfolio optimization are based on the assumption of complete knowledge of the distribution of random returns. In this paper, we relax this assumption to the knowledge of only the mean, covariance, and support information. No additional restrictions on the type of distribution such as normality is made. The investor’s utility is modeled as a piecewise‐linear concave function. We derive exact and approximate optimal trading strategies for a robust (maximin) expected utility model, where the investor maximizes his worst‐case expected utility over a set of ambiguous distributions. The optimal portfolios are identified using a tractable conic programming approach. Extensions of the model to capture asymmetry using partitioned statistics information and box‐type uncertainty in the mean and covariance matrix are provided. Using the optimized certainty equivalent framework, we provide connections of our results with robust or ambiguous convex risk measures, in which the investor minimizes his worst‐case risk under distributional ambiguity. New closed‐form results for the worst‐case optimized certainty equivalent risk measures and optimal portfolios are provided for two‐ and three‐piece utility functions. For more complicated utility functions, computational experiments indicate that such robust approaches can provide good trading strategies in financial markets.