Discrete and Continuous Representations of Unobserved Heterogeneity in Choice Modeling

We attempt to provide insights into how heterogeneity has been and can be addressed in choice modeling. In doing so, we deal with three topics: Models of heterogeneity, Methods of estimation and Substantive issues. In describing models we focus on discrete versus continuous representations of heterogeneity. With respect to estimation we contrast Markov Chain Monte Carlo methods and (simulated) likelihood methods. The substantive issues discussed deal with empirical tests of heterogeneity assumptions, the formation of empirical generalisations, the confounding of heterogeneity with state dependence and consideration sets, and normative segmentation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46977/1/11002_2004_Article_230988.pd

Statistical Analysis of Choice Experiments and Surveys

Measures of households' past behavior, their expectations with respect to future events and contingencies, and their intentions with respect to future behavior are frequently collected using household surveys. These questions are conceptually difficult. Answering them requires elaborate cognitive and social processes, and often respondents report only their “best” guesses and/or estimates, using more or less sophisticated heuristics. A large body of literature in psychology and survey research shows that as a result, responses to such questions may be severely biased. In this paper, (1) we describe some of the problems that are typically encountered, (2) provide some empirical illustrations of these biases, and (3) develop a framework for conceptualizing survey response behavior and for integrating structural models of response behavior into the statistical analysis of the underlying economic behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47001/1/11002_2005_Article_5884.pd

Modelling internet diffusion across tourism sectors

This study investigates the Bass Diffusion model. Bass’ parameters of innovation (p) and imitation (q) help explain adoption, and the ratio of these parameters sheds insights on critical mass. This study compares the parameters p and q across 13 internet diffusion datasets in five tourism sectors across international, European and five national datasets. Information and communication technologies (ICTs) play an increasing role with tourists and tourism organisations. The data contain destination management organisations (Switzerland, Austria and Germany), tour operators (European and Swiss), accommodation providers (international chain hotels, Malaysian hotels, Swiss affiliated hotels and Swiss guest houses) and Swiss cable cars. This study also uses the Gamma/Shifted Gompertz model to incorporate heterogeneous adoption. Across the same datasets, tourism organisations showed heterogeneous adoption tendencies and the influence of critical mass. This exploratory research illustrates the usefulness of Bass’ parameters both as a foundation and to measure critical mass

Commentary--Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion

Isuggest five broad directions for future research on social influence and opinion leadership that could, if appropriately addressed, dramatically improve how we conceptualize and manage social contagions in a variety of domains.social networks, peer influence, behavioral contagion

The sales effect of word of mouth: a model for creative goods and estimates for novels

Weekly sales of creative goods—like music records, movies, or books—usually peak shortly after release and then decline quickly. In many cases, however, they follow a hump-shaped pattern where sales increase for some time. A popular explanation for this phenomenon is word of mouth among a population of heterogeneous buyers, but previous studies typically assume buyer homogeneity or neglect word of mouth altogether. In this paper, I study a model of new-product diffusion with heterogeneous buyers that allows for a quantification of the sales effect of word of mouth. The model includes Christmas sales as a special case. All parameters have an intuitive interpretation. Simulation results suggest that the parameters are estimable for data that are not too volatile and that cover a sufficiently large part of a title’s life cycle. I estimate the model for four exemplary novels using scanner data on weekly sales. Copyright Springer Science+Business Media, LLC 2007New-product diffusion, Word of mouth, Creative industries, C22, L82, M3,