Writing performance and moral reasoning in business education?

This study investigates the connection of moral reasoning to demographic and performance variables in business education, especially business and technical writing. The moral reasoning construct serves as the foundation for one's decision making when confronted with moral dilemmas. Significant relationships are reported between subjects' writing skill and their moral reasoning scores. This research serves as a foundation for questions about writers' moral reasoning and the ethical decisions each writer makes in written communication. In addition, this study supports further research into the connection between moral reasoning and written communication, given the significant relationships reported and the noticeable shortage of related, data-based research.J. Lynn Johnson is an Associate Professor of Management at the University of North Texas, Denton, Texas. He is coauthor ofManagement: Theory and Practice, is an active consultant in the SouthWest, and has published over 20 other journal articles and training manuals. He has also been active in designing the curriculum for undergraduate and masters programs in personnel and industrial relations, hotel and restaurant management, and small business administration.Robert Insley is an Assistant Professor of Management and coordinator of the business communication program at the University of North Texas, Denton, Texas. He has presented numerous papers at national and international business communication and international business conferences, conducts interviewing skills workshops, has published several journal articles, and is presently in the process of co-authoringBusiness Communication Today and Tomorrow.Jaideep Motwani is an Assistant Professor of Management at Grand Valley State University, Grand Rapids, Michigan. He has presented numerous papers and chaired sessions at regional, national, and international meetings of the Decision Sciences, Society for Advancement of Management, ASQC, and other professional societies. He has published several journal articles.Imad Zbib is an Assistant Professor of Management at Central Missouri State University, Warrensburg, Missouri. His teaching and research interests range from production planning and control and manufacturing strategy to international management and business communication. He has presented papers at several regional, national, and international conferences and has published several journal articles.     

Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem

This paper investigates whether a regime switching model of stochastic lumber prices is better for the analysis of optimal harvesting problems in forestry than a more traditional single regime model. Prices of lumber derivatives are used to calibrate a regime switching model, with each of two regimes characterized by a different mean reverting process. A single regime, mean reverting process is also calibrated. The value of a representative stand of trees and optimal harvesting prices are determined by specifying a Hamilton-Jacobi-Bellman Variational Inequality, which is solved for both pricing models using a implicit finite difference approach. The regime switching model is found to more closely match the behavior of futures prices than the single regime model. In addition, analysis of a tree harvesting problem indicates significant differences in terms of land value and optimal harvest thresholds between the regime switching and single regime models.     

On Solving the Multirotational Timber Harvesting Problem with Stochastic Prices: A Linear Complementarity Formulation

This article develops a two-factor real options model of the harvesting decision over infinite rotations assuming a known stochastic price process and using a rigorous Hamilton–Jacobi–Bellman methodology. The harvesting problem is formulated as a linear complementarity problem that is solved numerically using a fully implicit finite difference method. This approach is contrasted with the Markov decision process models commonly used in the literature. The model is used to estimate the value of a representative stand in Ontario's boreal forest, both when there is complete flexibility regarding harvesting time and when regulations dictate the harvesting date.     

Contrasting two approaches in real options valuation: Contingent claims versus dynamic programming

This paper compares two well-known approaches for valuing a risky investment using real options theory: contingent claims (CC) with risk neutral valuation and dynamic programming (DP) using a constant risk adjusted discount rate. Both approaches have been used in valuing forest assets. A proof is presented which shows that, except under certain restrictive assumptions, DP using a constant discount rate and CC will not yield the same answers for investment value. A few special cases are considered for which CC and DP with a constant discount rate are consistent with each other. An optimal tree harvesting example is presented to illustrate that the values obtained using the two approaches can differ when we depart from these special cases to a more realistic scenario. We conclude that for real options problems the CC approach is preferred when data exists (such as futures prices) that allow the estimation of the market price of risk or convenience yield. Even when such data do not exist we argue that the CC approach is preferred as it has the advantage of allowing the individual specification of the prices of different sources of risk.     

On the option to invest in pollution control under a regime of tradable emissions allowances

Abstract.  Optimal decisions of a firm facing the option of retrofitting its plant to reduce pollution and thereby eliminate the need to purchase emissions allowances are analysed. The decision is treated as a real option with the price of pollution permits following a known stochastic process. The model is formulated as a set of one‐dimensional partial differential equations. At discrete points in time, the firm owner makes optimal decisions about the retrofit, including whether to mothball temporarily. The model is used to analyse a firm's decision to instal a scrubber as a result of the 1990 U.S. Clean Air Act. JEL Classification: Q25, D81, G31
Sur la possibilité d'investir dans le contrôle de la pollution dans un régime de permis d'émission de pollution échangeables commercialement.  Ce mémoire examine les décisions optimales d'une entreprise face à la possibilité d'adapter ses installations pour réduire la pollution, et ce faisant d'éliminer le besoin de se procurer des permis d'émission de pollution sur le marché. Le décision est traitée comme une option réelle où le prix des permis résulte d'un processus stochastique connu. Le modèle est formulé sous forme d'un ensemble d'équations différentielles partielles à une dimension. A des points discontinus dans le temps, le propriétaire de l'entreprise prend des décisions optimales de mise à niveau des installations – y compris la possibilité de les fermer temporairement. Le modèle est utilisé pour analyser une décision d'installer un épurateur suite à la mise en place de la loi américaine de 1990 (Clean Air Act).