Retailing Innovations in a Globalizing Retail Market Environment

In recent years, the combination of economic growth and population growth in emerging markets and less developed markets has accelerated the progression of globalization of retailing and globalization by retailers. The challenges faced by global and globalizing retailers (retailers who currently have or intend to establish a market presence in mature markets, emerging markets and less developed markets) can be more daunting compared to those faced by firms in other industries such as automobiles, steel, and computers. Retailing innovations that are responsive to the characteristics of distinctive national markets and broader aggregations of markets such as mature, emerging and less developed markets are critical to the success of global and globalizing retailers. Against this backdrop, this paper focuses on retailing innovations in the context of a globalizing retailing environment. It attempts to shed insights into the characteristics of retailing innovations conducive to superior performance in distinctive national markets and across broader aggregations of markets. Towards this end, we first examine the environmental conditions of markets in different development stages, namely mature, emerging and less developed markets, and explore consumer based, industry based, and legal/regulatory based challenges faced by globalizing retailers in these markets. Second, we show how these challenges can be transformed into opportunities with retailing innovations. We conclude with a roadmap for future research and present propositions on future development with respect to retailing innovations in these markets.     

Statistical disclosure in general three-dimensional tables

Statistical offices are concerned with problems of protecting confidential information when publishing data in statistical tables. One method to avoid disclosure is the method of cell suppression, in which the values of the sensitive cells in the table are suppressed from publication. To prevent the values of the sensitive cells from being calculated from the tables totals, additional suppressions are necessary. The problem of minimizing the loss of information caused by the additional suppressions is a difficult optimization problem. We present and compare the performance of some heuristics for cell suppression for general three-dimensional tables.     

Combining Sources of Preference Data for Modeling Complex Decision Processes

We review current state-of-the-art practices for combining preference data from multiple sources and discuss future research possibilities. A central theme is that any one data source (e.g., a scanner panel source) is often insufficient to support tests of complex theories of choice and decision making. Hence, analysts may need to embrace a wider variety of data types and measurement tools than traditionally have been considered in applied decision making and choice research. We discuss the viability of preference-stationarity assumptions usually made when pooling data, as well as random-utility theory-based approaches for combining data sources. We also discuss types of models and data sources likely to be required to make inferences about and estimate models that describe choice dynamics. The latter discussion is speculative insofar as the body of literature on this topic is small.     

Budget allocation for permanent and contingent capacity under stochastic demand

We develop a model of budget allocation for permanent and contingent workforce under stochastic demand. The level of permanent capacity is determined at the beginning of the horizon and is kept constant throughout, whereas the number of temporary workers to be hired must be decided in each period. Compared to existing budgeting models, this paper explicitly considers a budget constraint. Under the assumption of a restricted budget, the objective is to minimize capacity shortages. When over-expenditures are allowed, both budget deviations and shortage costs are to be minimized. The capacity shortage cost function is assumed to be either linear or quadratic with the amount of shortage, which corresponds to different market structures or different types of services. We thus examine four variants of the problem that we model and solve either approximately or to optimality when possible. A comprehensive experimental design is designed to analyze the behavior of our models when several levels of demand variability and parameter values are considered. The parameters consist of the initial budget level, the unit cost of temporary workers and the budget deviation penalty/reward rates. Varying these parameters produce several trade-offs between permanent and temporary workforce levels, and between capacity shortages and budget deviations. Numerical results also show that the quadratic cost function leads to smooth and moderate capacity shortages over the time periods, whereas all shortages are either avoided or accepted when the cost function is linear.     

Situation variation in consumers’ media channel consideration

In this article, the authors investigate consumers’ consideration of media channels during different usage situations. They develop a model that explains consumers’ media channel consideration as a function of the media channel’s perceived benefits. In addition, they hypothesize that the usage situation affects consumers’ media channel consideration and that situation-based benefit requirements moderate the effect of the benefits on their channel consideration. The authors test the hypothesized relationships using survey data from 341 consumers regarding their consideration of 12 different media channels used by manufacturers to communicate product information across three product-related usage situations. The results of the analyses support the proposed model structure and confirm the expected relationships among perceived media channel benefits, usage situations, media channel requirements, and consumers’ media channel consideration. Sonja Wendel (s.wendel@mw.unimaas.nl) is currently a Ph.D. candidate in the Department of Marketing at Maastricht University, the Netherlands. Her research interests lie in the area of consumer behavior, services marketing, and communications. She is particularly interested in exploring manufacturer-consumer communications. Benedict G. C. Dellaert (b.dellaert@mw.unimaas.nl) is Meteor Research Chair and a professor in the Department of Marketing at Maastricht University, the Netherlands. His research interests are in consumer decision making, consumer-producer interaction, customization and personalization, retailing, and tourism. His work has appeared in journals such as theInternational Journal of Research in Marketing, theJournal of Interactive Marketing, theJournal of Marketing Research, andMarketing Letters.     

Tourism development: Assessing Social Gains and Losses

Resident attitudes toward tourism, and perceptions of its impacts, are often diverse, with development often generating gains for some and losses for others. The net effect has been discussed conceptually for many years. This study illustrates an empirical evaluation of it, as well as of gains to tourists. Survey responses to hypothetical ski resort development in Åre, Sweden, indicate that some residents gain from such an expansion while others lose; the net effect on the community is negative over the range of slopes evaluated. Tourists gain from expansion, but their gains are not great enough to outweigh the net losses for residents, such that the welfare change for society as a whole is negative.     

Family Members' Projections of Each Other's Preference and Influence: A Two-Stage Conjoint Approach

Two important sources of error that may limit the accuracy of individual family members' projections of joint family preferences are: (i) misperceptions of other members' preferences, and (ii) misperceptions of other members' influence in joint family evaluations. We propose a two-stage conjoint approach to study these potential errors. Stage one compares family members' projections of each other's preferences to members' self-reported preferences. Stage two compares family members' projections of each other's influence to observed influence in joint family preferences. An empirical illustration shows that family members are relatively poor predictors of preference, but fairly accurate predictors of influence, in the area of family holiday preferences.     

Choice in Interactive Environments

In the early 21st century, firms are thinking seriously and practically about an interactive marketing paradigm—one that integrates mass scale with individual responsiveness. The focus of this paper is on how this interactive environment is changing the customer decision-making process. With the increased amount of information available, the existence of sophisticated decision aids such as intelligent agents, and more latitude in how to interact beyond the basic desktop and laptop computers (e.g., personal digital assistants, cellular phones, tablet computers), customers have more choices than ever about how, when, and how much to interact with companies and each other. In this paper, we attempt to cover a few of the major areas of research on how customers make decisions in these environments.     

Beyond nudges: Tools of a choice architecture

The way a choice is presented influences what a decision-maker chooses. This paper outlines the tools available to choice architects, that is anyone who present people with choices. We divide these tools into two categories: those used in structuring the choice task and those used in describing the choice options. Tools for structuring the choice task address the idea of what to present to decision-makers, and tools for describing the choice options address the idea of how to present it. We discuss implementation issues in using choice architecture tools, including individual differences and errors in evaluation of choice outcomes. Finally, this paper presents a few applications that illustrate the positive effect choice architecture can have on real-world decisions.     

Shopping context and consumers’ mental representation of complex shopping trip decision problems

Depending on the shopping context, consumers may develop different mental representations of complex shopping trip decision problems to help them interpret the decision situation that they face and evaluate alternative courses of action. To investigate these mental representations and how they vary across contexts, the authors propose a causal network structure that allows for a formal representation of how context-specific benefits requirements affect consumers’ evaluation of decision alternative attributes. They empirically test hypotheses derived from the framework, using data on consumers’ mental representations of a complex shopping trip decision problem across four shopping contexts that differ in terms of opening hour restrictions and shopping purpose, and find support for the proposed structure and hypotheses.