A micro-econometric approach to geographic market definition in local retail markets: demand side considerations

This paper formalizes an empirically implementable framework for the definition of local antitrust markets in retail markets. This framework rests on a demand model that captures the trade-off between distance and pecuniary cost across alternative shopping destinations within local markets. The paper develops, and presents estimation results for, an empirical demand model at the store level for groceries in the UK

Third Party Assurances: Mapping the Road to Trust in eRetailing

Consumer trust of Internet vendors is a major factor influencing the success of e-commerce. To enhance consumer trust, many e-retailers are experimenting with various trust-building strategies, including participation in third-party assurance programs. This study presents a model describing the relationship between third-party assurance seals, trust, and online purchasing intentions. Five manipulations of a simulated retail website were used to test eight model-derived hypotheses. Initial results do support hypothesized relationships between disposition to trust, trust of the e-retailer, perceived risk, attitude toward purchasing from the e-retailer, and intention to purchase. Hypotheses addressing a positive relationship between the viewing of assurance seals and consumer trust of a specific e-retailer are not supported. Contrary to early studies, post hoc results reveal that one seal type, the privacy assurance seal, did have a small, but significant, positive impact on consumer trust of an unfamiliar e-retailer

Engaging consumers on new integrated multichannel retail settings: challenges for retailers

The rapid diffusion of more channels for shopping posits new challenges for retailers, who need to compete in a complex environment for avoiding the problem of consumer cross-channel free riding. To discourage this behaviour, we propose a new environment where one retailer simultaneously handles more channels. The emerging integrated environment would engage more consumers if compared to the single handled channel, which in turn would avoid switching behaviours towards competitors’ channels. Our empirical research, based on the stimulus-organism-response paradigm, involves a sample of 237 consumers who were asked to explore the new retail settings simulated in a university lab. The results lead us to suggest the effective combination of multiple channels managed by one retailer as the new challenge for scholars and practitioners. We note that our participants showed positive emotional reactions towards the environment, which lead them to choose this environment for purchases

Keep it simple: Easy ways to estimate choice models for single consumers

We show with Monte-Carlo simulations and empirical choice data sets that we can quickly and simply refine choice model estimates for individuals based on methods such as ordinary least squares regression and weighted least squares regression to produce well-behaved insample and out-of-sample predictions of choices. We use well-known regression methods to estimate choice models, which should allow many more researchers to estimate choice models and be confident that they are unlikely to make serious mistakes

Optimal pricing using online auction experiments: A P\'olya tree approach

We show how a retailer can estimate the optimal price of a new product using observed transaction prices from online second-price auction experiments. For this purpose we propose a Bayesian P\'olya tree approach which, given the limited nature of the data, requires a specially tailored implementation. Avoiding the need for a priori parametric assumptions, the P\'olya tree approach allows for flexible inference of the valuation distribution, leading to more robust estimation of optimal price than competing parametric approaches. In collaboration with an online jewelry retailer, we illustrate how our methodology can be combined with managerial prior knowledge to estimate the profit maximizing price of a new jewelry product.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS503 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org