Deterrence in the workplace: perceived certainty, perceived severity, and employee theft

The phenomenon of employee theft is examined empirically, utilizing a deterrence paradigm. Employees selected randomly from three different industry sectors and metropolitan areas were asked to self-report their involvement in a number of property theft activities within the employment setting. Using a weighted least-squares logit regression analysis, the study found that the perception of both the certainty and severity of organizational sanctions were related to employee theft. Males reported more theft than did females, but contrary to previous research, no gender/certainty or gender/severity interactions were observed. The best-fit model did, however, contain two significant first-order interactions: age/certainty and age/severity. These interactions strongly suggest that younger employees are not as deterrable as their older peers, especially under conditions of both high certainty and high severity of punishment. While a number of possible explanations might account for differential deterrability according to age, a commitment to or stakes in conformity explanation is proposed.     

Volatility-based Effects on Shareholder Value: Alliance Activity in the Computing Industry

We use an event-study analysis to understand how alliance activity affects firm risk. The risk measure is the implied volatility of a firm’s stock price and the events are alliance announcements to the market. We build on the previous event-studies in the alliance literature that focus on the change in shareholder value by taking the first step in delineating what part of that value arises from the changes in the firm’s risk. The analysis reveals that a number of factors within a firm’s control can be used to manipulate risk exposure in an alliance, including the similarity of the firm’s and the alliance’s core activities, the governance form of the alliance, and the function of the alliance.     

THE DEVELOPMENT OF AN INTEGRATIVE CURRICULUM IN AN UNDERGRADUATE BUSINESS PROGRAM*

This paper describes how the core portion of the undergraduate business program at Indiana University was revised to facilitate integration of basic functionally oriented decision making skills and thus help students gain a deeper understanding of the interdependence of business decisions. It relates, in essence, why and how a single computer-oriented case study which demanded a solution to a large-scale, unified finance-marketing-production problem was used at Indiana University, mentions how we plan to accomplish further integration of functional material, and provides some insight into student reaction to what was, in fact, a massive project from both student and administrative points of view.     

A METHOD FOR SOLVING LINEAR PROGRAMS WITH VARIABLE RESOURCES

This paper is concerned with the solution of linear and linear goal programming problems in which the values of the right-hand side parameters are not fixed constants. Specifically, we are concerned with linear optimization problems in which the right-hand sides of the constraining equations are free to vary subject to a set of linear constraining equations. By formulating a relaxed linear program wherein the right-hand sides are treated as variables, we show how it is possible to solve one larger linear program that yields as a solution not only the optimal values for the decision variables, but also the optimal values for the right-hand sides.     

A HEURISTIC ALGORITHM FOR RESOURCE LEVELING IN MULTI-PROJECT,MULTI-RESOURCE SCHEDULING

The utility of conventional project management techniques, such as PERT and CPM, is hampered by significant and realistic network attributes and managerial considerations. There are many situations which involve more than one project and numerous resources. Of major concern in such situations is the reduction of the maximum quantity of each required resource. The algorithm presented here is capable of scheduling the individual activities in multiple projects with multiple resources and leveling the overall quantity of each resource which is required. The basis of the algorithm is a sequencing procedure for examining various combinations of activity start times. The measure of effectiveness for each combination is the sum of the squares of the required quantity of each resource in each time period.     

Emotional Regulation and Display in Classroom Victims of Bullying: Characteristic Expressions of Affect, Coping Styles and Relevant Contextual Factors

Research suggests that victims of bullying may lack skills in emotional regulation, a process which facilitates coping with provocative situations to lessen the stress of negative emotions (Cicchetti, Ackerman, & Izard, 1995). The present study examined the emotional regulation and display patterns of victims during classroom bullying episodes. Children in grades one through six were observed during free play in the winter and spring of three consecutive school years. Results of the study indicated that the coping styles observed in victims of bullying can be grouped into two distinct clusters: 1) problem-solving strategies that are associated with the de-escalation and resolution of bullying episodes; and 2) aggressive strategies that tend to perpetuate and escalate the bullying interaction. Parallels were found between victims' and bullies' emotional displays. Results are discussed in the context of how maladaptive emotional regulation processes may act as risk factors for chronic victimization.     

Penalized Pseudolikelihood Inference in Spatial Interaction Models with Covariates

Given spatially located observed random variables ( x , z = {( x _i , z _i )} _i , we propose a new method for non-parametric estimation of the potential functions of a Markov random field p ( x | z ), based on a roughness penalty approach. The new estimator maximizes the penalized log-pseudolikelihood function and is a natural cubic spline. The calculations involved do not rely on Monte Carlo simulation. We suggest the use of B-splines to stabilize the numerical procedure. An application in Bayesian image reconstruction is described.