Bintong Chen and Charles Munson
Chen, B. and Munson, C. L., “Resource Allocation with Lumpy Demand: To Speed or Not to Speed?” Naval Research Logistics, 51(3) (April 2004), 363-385.

In the classical EPQ model with continuous and constant demand, holding and setup costs are minimized when the production rate is no larger than the demand rate. However, the situation may change when demand is lumpy. We consider a firm that produces multiple products, each having a unique lumpy demand pattern. The decision involves determining both the lot size for each product and the resource allocation for production rate improvement among the products. Under these conditions, each product's optimal production policy will take on only one of two forms: either continuous production or lot-for-lot production. The problem is then formulated as a nonlinear nonsmooth knapsack problem among products determined to be candidates for resource allocation. A heuristic procedure is developed to determine allocation amounts. The procedure decomposes the problem into a mixed integer program and a nonlinear convex resource allocation problem. Numerical tests suggest that the heuristic performs very well on average compared to the optimal solution. Both the model and the heuristic procedure can be extended to allow the company to simultaneously alter both the production rates and the incoming demand lot sizes through quantity discounts. Extensions can also be made to address the case where a single investment increases the production rate of multiple products.

Joseph Cote
Grewal, R.; Cote, J. A. and Baumgartner, H., "Multicollinearity and Measurement Error in Structural Equation Models: Implications for Theory Testing" Marketing Science, 23 (4), 519-529 (2004).

Statistical techniques used often used to predict various business outcome (e.g., sales). The techniques assume that the predictor variables (e.g., the advertising, pricing, and sales effort for you and your competitors) are not related to each other. When they are related, it is difficult to determine which predictors are truly important. A sophisticated statistical technique called structural equation modeling, allows for the predictor variables to be correlated. Most researchers assumed this corrected the problem of related predictors. Our research shows that this is only true under a limited set of conditions. We suggest ways to identify and correct for the problem of related predictor variables so we can determine their relative importance more accurately.

Joseph Cote and Joan Giese
Henderson, P. W.; Giese, J. L. and Cote, J. A., “Impression Management Using Typeface Design,” Journal of Marketing, 68 (4), 60-72 (2004).

The one-picture-to-a-thousand-words ratio unjustly downplays the importance of type styles. Academics and marketers have long known that the choice of font in logos and advertising copy greatly influences legibility, memorability, and public perception of the brand. Companies need typestyles that suit their image and reflect their intent. To help them choose the right fonts for their messages, we rounded up 210 typefaces and identified a half dozen discreet design components in each. We then looked at how those components affect response to brand. Specifically, we asked whether the fonts conveyed a message that was pleasing (likeable, warm, attractive); engaging (interesting, emotional); reassuring (calm, honest, familiar); and prominent (strong, masculine).

Dogan Gursoy
Gursoy, D. and Rutherford, D., “Host attitudes toward tourism: An improved structural model,” Annals of Tourism Research, 31(3): 495-516 (Lead article) (2004).

Drawing from current literature, a theoretical tourism support model with a series of hypotheses was proposed. The proposed model and the hypotheses were tested by utilizing a two-stage structural equation modeling approach. The findings of this study revealed that the host community backing for tourism development is affected directly and/or indirectly by nine determinants of residents’ support: the level of community concern, ecocentric values, utilization of tourism resource base, community attachment, the state of the local economy, economic benefits, social benefits, social costs, and cultural benefits. Further, results indicated that there are interactions among five dimensions of impacts. The proposed model explained majority of the variance.

Dogan Gursoy
Gursoy, D. and McCleary, K. W., “An integrative model of tourist’s information search behavior,” Annals of Tourism Research, 31(2): 353-373 (2004).

This article proposes a comprehensive theoretical model for understanding tourists’ information search behavior. The proposed model integrates the psychological/ motivational literature with literature from the economics of information search and consumer information processing into a cohesive whole. The model suggests that although many variables influence information search behavior, most of these effects are mediated by tourists’ familiarity and expertise with the destination, which are, in turn, mediated by the cost of external and internal information search.  Twenty-one propositions are developed for future testing based on this integrative model of tourists’ information search behavior.

Dogan Gursoy
Jurowski, C. and Gursoy, D., “Distance effects on residents’ attitudes toward tourism,” Annals of Tourism Research, 31(2): 296-312 (2004).

A theoretical model of resident support for tourism that is based on the social exchange theory was shown to be valid regardless of the distance between residents’ homes and tourist attractions. However, distance had a significant effect on how the costs and benefits were evaluated. Those who lived closest to the attraction and used the recreation resource base heavily felt more negatively about tourism than did recreation resource users who lived further away. Environmentally sensitive residents who lived closest to the recreation area were more supportive of tourism than more distant residents.

Dogan Gursoy
Gursoy, D. and McCleary, K. W., “Travelers’ prior knowledge and its impact on their information search behavior,” Journal of Hospitality and Tourism Research, 28(1): 66-94 (2004).

The purpose of this study was to examine the influence of prior knowledge on travelers’ information search behavior. This study examined prior knowledge as having two dimensions: familiarity and expertise. The influence of familiarity and expertise on information search was examined utilizing a structural equation modeling approach. The results of this study provide support for multi-dimensional prior knowledge. The results also indicate that expertise is a function of familiarity and both familiarity and expertise affect travelers’ information search behavior. However, the magnitude and direction of the effects of travelers’ familiarity on their information search behavior are different from the effects of their expertise. Findings suggest that while the effect of familiarity on internal search is positive and on external search is negative, the effect of expertise on internal search is negative and on external search is positive.

Dogan Gursoy and Terry Umbreit
Gursoy, D. and Umbreit, W. T., “Tourist information search behavior: Cross-cultural comparison of European Union Member States,” International Journal of Hospitality Management, 23(1): 55-70 (2004).

This study investigates the search behavior of travelers from the 15 European Union (EU) member states. Statistical information from EUROBAROMETER 48 is examined. This document identifies the population of the respective nationality of EU members, aged 15 years and over, residing in each of the member states. Data was collected between 12 October 1997 and 16 November 1997. Information search behavior of the residents of each EU state is examined by utilizing correspondence analysis. This analysis identifies five distinct market segments based on respondents’ information search patterns. Findings suggest that culture may influence a traveler’s information search behavior.

Charles Munson
Panos, K.; Rosenblatt, M. J. and Munson, C. L. “A Mathematical Programming Model to Global Plant Location Problems: Analysis and Insights,” IIE Transactions, 36 (February 2004), 127-144.

In this paper, we study the design of global facility networks. We present a mixed integer programming model that captures essential design tradeoffs of such networks and explicitly incorporates government subsidies, trade tariffs, and taxation issues. The resulting formulation can be solved for reasonable size problems with commercially available mathematical programming software. Focusing on special cases of the problem enables us to provide useful insights on preferable international facility networks for various environments. We demonstrate the pervasive, and often dominating, effects of subsidized financing, tariffs, regional trade rules, and taxation in shaping the manufacturing and distribution network of global firms.

Richard Sias
Sias, R., “Institutional Herding,” Review of Financial Studies, Volume 17, number 1, Spring 2004, pp. 165-206.

Institutional investors’ demand for a security this quarter is positively correlated with their demand for the security last quarter. We attribute this to institutional investors following each other into and out of the same securities (“herding”) and institutional investors following their own lag trades.  Although institutional investors are “momentum” traders, little of their herding results from momentum trading. Moreover, institutional demand is more strongly related to lag institutional demand than lag returns. Results are most consistent with the hypothesis that institutions herd as a result of inferring information from each other's trades.