Foodservice hygiene factors—The consumer perspective

Food safety is important to today's food industry operators as consumers have become increasingly concerned about risks related to food. Unlike foodservice operators or health inspectors, consumers can only rely on the visible cues, particularly those associated with food hygiene to judge the level of food safety in eating establishments. While previous research highlighted the influence of foodservice hygiene perception on consumer dining out decision, study examining the constructs of food safety cues that consumers employed is scant. This research aims to bridge the gap by exploring the topic from the consumer perspective. Results indicate that foodservice hygiene is one of the top three considerations when consumers select a dining place. Results of confirmatory factor analysis reveal a four-factor model encompasses staff and handling, food and location, premise and practices, and scent aspects. Further substantiation in different settings is needed for generalization purpose.     

Defying Distance? Cross‐Border Acquisitions by Emerging‐Economy Firms

We argue that emerging‐economy firms’ international location choices are driven by the pursuit of dynamic efficiency rather than the immediate minimization of transaction and learning costs, and hence the relationship between country distance and the number of cross‐border acquisitions will be less negative for these firms relative to advanced‐economy firms. We then test the hypothesis with respect to four measures of country distance—geographic, economic, cultural, and institutional—and find support for the hypothesis. Our study provides empirical support for claims in the literature about differences in the international expansion behavior of emerging‐economy firms with respect to location. In addition, our study makes a theoretical contribution by showing that the theoretical perspective of dynamic efficiency can explain the difference in the location choices for cross‐border acquisitions by emerging‐economy firms relative to those by advanced‐economy firms. © 2016 Wiley Periodicals, Inc..     

Tree Diversity and Carbon Sinks: Role of Village Agro-ecosystems in the Western Ghats,Karnataka, India

Tree species richness, diversity index, standing biomass and biomass carbon stocks were estimated in six villages located under three agro-ecological zones, namely, coastal, hill and plains of Uttara Kannada district, Western Ghats, Peninsular India. The study showed that land use categories other than forest support higher tree species diversity. High basal area, standing biomass and carbon stock in non-forest land categories indicates their potential as carbon sinks and for promotion of species diversity. Inclusion of other non-forest land use categories in afforestation programmes for promotion of multipurpose tree species for conservation of diversity and for enhancing carbon sinks is suggested. There is a need to promote synergy between biodiversity conservation and carbon sequestration under carbon mitigation projects.     

A delay estimation technique for single and double-track railroads

To route and schedule trains over a large complex network can be computationally intensive. One way to reduce complexity could be to “aggregate” suitable sections of a network. In this paper, we present a simulation-based technique to generate delay estimates over track segments as a function of traffic conditions, as well as network topology. We test our technique by comparing the delay estimates obtained for a network in Los Angeles with the delays obtained from the simulation model developed by Lu et al. [Lu, Q., Dessouky, M.M., Leachman, R.C., 2004. Modeling of train movements through complex networks. ACM Transactions on Modeling and Computer Simulation 14, 48–75], which has been shown to be representative of the real-world delay values. Railway dispatchers could route and schedule freight trains over large networks by using our technique to estimate delay across aggregated network sections.     

A minimum chi-squared method for indirect parameter estimation from Poisson data

In this paper, we introduce a new algorithm for estimating non-negative parameters from Poisson observations of a linear transformation of the parameters. The proposed objective function fits both a weighted least squares (WLS) and a minimum χ² estimation framework, and results in a convex optimization problem. Unlike conventional WLS methods, the weights do not need to be estimated from the datas, but are incorporated in the objective function. The iterative algorithm is derived from an alternating projection procedure in which "distance" is determined by the chi-squared test statistic, which is interpreted as a measure of the discrepancy between two distributions. This may be viewed as an alternative to the Kullback-Leibler divergence which corresponds to the maximum likelihood (ML) estimation. The algorithm is similar in form to, and shares many properties with, the expectation maximization algorithm for ML estimation. In particular, we show that every limit point of the algorithm is an estimator, and the sequence of projected (by the linear transformation into the data space) means converge. Despite the similarities, we show that the new estimators are quite distinct from ML estimators, and obtain conditions under which they are identical.     

Optimal Resource Allocation with Time-varying Marketing Effectiveness,Margins and Costs

The importance of optimal marketing communications mix decisions is well-recognized by both marketing scholars and practitioners. A significant volume of work has addressed the problem of dynamic marketing mix optimization assuming constant effectiveness of marketing instruments. However, the effectiveness of marketing communications varies over time for a variety of reasons. Moreover, due to factors such as inflation or deflation in media prices and/or raw material inputs, there can be differential changes in the costs of communications and/or margins on the good (or service) sold over time. The academic literature offers little normative direction on how time-varying marketing effectiveness and costs drive optimal marketing-mix levels and their relative allocation. The authors shed light on these issues by solving a monopoly firm's finite horizon dynamic marketing communications mix optimization problem involving two marketing instruments with time-varying parameters, i.e., the marketing effectiveness parameters, media costs, and product margin are all allowed to vary over time. First, they find that the structure of the solutions is similar to that of the classic Nerlove–Arrow model, for a completely general nature of time-varying effectiveness. Second, their model can be used by managers to exactly determine whether and when to switch their marketing-mix emphasis (defined by the marketing element receiving the dominant portion of the budget) over a finite planning horizon. In sum, the authors expand knowledge on optimal allocation of marketing resources with time-varying effectiveness. They also extend their solution to incorporate multiple (more than two) marketing instruments.     

Estimation of posterior probabilities of consumer situational choices with neural network classifiers

This study shows how neural networks can be used to estimate the posterior probabilities in a consumer choice situation. We provide the theoretical basis for its use and illustrate the entire neural network modeling procedure with a situational choice data set from AT&T. Our findings supported the appropriateness of this application and clearly illustrate the nonlinear modeling capability of neural networks. The posterior probability estimates clearly add to the usefulness of the technique for marketing research.     

Why is Assortment Planning so Difficult for Retailers? A Framework and Research Agenda

When retailers conduct product assortment planning (PAP), they determine (1) The variety of merchandise, (2) The depth of merchandise, and (3) Service level or the amount of inventory to allocate to each stock-keeping unit (SKU). Despite longstanding recognition of its importance, no dominant PAP solution exists, and theoretical and decision support models address only some of the factors that complicate assortment planning. This article simultaneously addresses the variety, depth, and service level aspects of PAP to provide a more thorough understanding. A review of current academic literature and best trade practices identifies open questions and directions for further research and applications.