Reducing exposure to exchange rate risk: A case study

During the last decade, with the advent of large fluctuations in the values of currencies, business managers came to realize that effective international financial management could be a major contributor to a firm's profitability. This same period showed aggressive marketing by U.S. firms in foreign markets. The resulting expansions have led to requirements for increased knowledge concerning foreign consumer behavior, pricing procedures and trade regulations. In addition, transactions with foreign customers have resulted in a more complex cash management environment. The firms may desire all payments received to be denominated in U.S. dollars, but such a policy could result in reduced exports if potential foreign importers wished to make payment in their own currency. Consequently, the U.S. firms should accomodate importers' desires and then implement a strategy to deal with the exchange rate risk. This paper develops such a strategy and illustrates how the strategy can be applied to a realistic case.     

Caught in a Winding,Snarling Vine: The Structural Bias of Political Process Theory

The study of social movements has recently been energized by an explosion of work that emphasizes political opportunities—a concept meant to come to grips with the complex environments that movements face. In the excitement over this new metaphor, there has been a tendency to stretch it to cover a wide variety of empirical phenomena and causal mechanisms. A strong structural bias is also apparent in the way that political opportunities are understood and in the selection of cases for study. Even those factors adduced to correct some of the problems of the political opportunity approach—such as mobilizing structures and cultural framing—are subject to the same structural distortions. We recommend social movement analysis that rejects invariant modeling, is wary of conceptual stretching, and recognizes the diverse ways that culture and agency, including emotions and strategizing, shape collective action.     

Precision,bias, and uncertainty for state population forecasts: an exploratory analysis of time series models

Many researchers have used time series models to construct population forecasts and prediction intervals at the national level, but few have evaluated the accuracy of their forecasts or the out-of-sample validity of their prediction intervals. Fewer still have developed models for subnational areas. In this study, we develop and evaluate six ARIMA time series models for states in the United States. Using annual population estimates from 1900 to 2000 and a variety of launch years, base periods, and forecast horizons, we construct population forecasts for four states chosen to reflect a range of population size and growth rate characteristics. We compare these forecasts with population counts for the corresponding years and find precision, bias, and the width of prediction intervals to vary by state, launch year, model specification, base period, and forecast horizon. Furthermore, we find that prediction intervals based on some ARIMA models provide relatively accurate forecasts of the distribution of future population counts but prediction intervals based on other models do not. We conclude that there is some basis for optimism regarding the possibility that ARIMA models might be able to produce realistic prediction intervals to accompany population forecasts, but a great deal of work remains to be done before we can draw any firm conclusions.     

Hispanic Immigration and Black Violence at the Macro‐Level: Examining the Conditioning Effect of Victim Race/Ethnicity

Much attention has been devoted to the relationship between Hispanic immigration and violent offending at the macro‐level, including how it varies across racial and ethnic groups. Unfortunately, little attention has been paid to the conditioning effect of the race/ethnicity of the victim, or how Hispanic immigration is associated with crime by one racial/ethnic group against members of the same or different groups. Using National Incident‐Based Reporting System offending estimates and American Community Survey data, we examine the association between Hispanic immigration and black intra‐ and intergroup (black‐on‐white and black‐on‐Hispanic) homicide, robbery, and serious index violence in over 350 U.S. communities. We employ advanced imputation methods to address missing data that have constrained much prior research, as well as utilize crime measures adjusted for the likelihood of random contact between groups. Findings suggest that (1) Hispanic immigration has a positive association with black violence on the whole, but that (2) this association is conditioned by the race/ethnicity of the victim. Our results reinforce the importance of distinguishing across offender–victim dyads in research on the immigration–crime nexus, particularly in light of competing theoretical expectations. Directions for future research and policy are discussed.     

Optimal Dynamic Pricing of Perishable Items by a Monopolist Facing Strategic Consumers

We introduce a dynamic pricing model for a monopolistic company selling a perishable product to a finite population of strategic consumers (customers who are aware that pricing is dynamic and may time their purchases strategically). This problem is modeled as a stochastic dynamic game in which the company's objective is to maximize total expected revenues, and each customer maximizes the expected present value of utility. We prove the existence of a unique subgame‐perfect equilibrium pricing policy, provide equilibrium optimality conditions for both customer and seller, and prove monotonicity results for special cases. We demonstrate through numerical examples that a company that ignores strategic consumer behavior may receive much lower total revenues than one that uses the strategic equilibrium pricing policy. We also show that, when the initial capacity is a decision variable, it can be used together with the appropriate pricing policy to effectively reduce the impact of strategic consumer behavior. The proposed model is computationally tractable for problems of realistic size.     

Enterprise Resource Planning (ERP) Competence Constructs: Two‐Stage Multi‐Item Scale Development and Validation*

This paper defines and operationalizes eight ERP competence constructs. We define ERP competence as a portfolio of managerial, technical and organizational skills and expertise posited as antecedents to improved business performance occurring after an ERP system is operational and functionally stable. To improve responses to changes in markets and products, manufacturers are increasingly adopting ERP systems. However, anecdotal accounts indicate that the realization of ERP's potential benefits is rare. Because of its pervasive influence on manufacturing and business performance, the need for scientifically developed and tested multi‐item scales pertaining to ERP competence is highly relevant to manufacturing strategy research. We follow a two‐stage normative process of scale development. First, we identify a portfolio of eight generic constructs that are hypothesized to be associated with successful ERP adoption. Each construct is then operationalized as a multi‐item measurement scale by applying a manual item sorting technique iteratively to independent panels of expert judges until tentative reliability and validity is established. Second, we further refine and validate the multi‐item scales using survey data from 79 North American manufacturing users of ERP systems.