In this paper, we investigate the effectiveness of a firm's proactive management of customer-to-customer communication. We are particularly interested in understanding how, if at all, the firm shou...
This paper investigates the issues concerning a film producer that finances production costs not only by the conventional funding from an institutional investor, but also by “Internet funding,” financing through the Internet from so-called netizen investors. In Internet funding, netizen investors engage in word-of-mouth activities. Assuming that information asymmetry exists between the producer and investors, we investigate how the Internet funding size varies with the word-of-mouth effect, the monitoring effect of the institutional investor, and the bargaining power of the producer over investors. When the producer has no bargaining power, the Internet funding size is determined by balancing the word-of-mouth effect with the monitoring effect by the institutional investment. If there is no word-of-mouth effect, there may be no Internet funding, because netizen investors interpret Internet funding as an indicator of a negative profit. When the producer has high bargaining power, full Internet funding is possible if the information asymmetry of the film quality is resolved. We discuss how information asymmetry can be resolved by the monitoring of the film quality, the producer's reputation, or the insurance on investment returns. Our model helps to capture several interesting aspects of Internet funding in the Korean film industry.
This paper studies a manufacturer's optimal decisions on extending its product line when the manufacturer sells through either a centralized channel or a decentralized channel. We show that a manufacturer may provide a longer product line for consumers in a decentralized channel than in a centralized channel if the market is fully covered. In addition, a manufacturer's decisions on the length of its product line may not always be optimal from a social welfare perspective in either a centralized or a decentralized channel. Under certain conditions, a decentralized channel can provide the product line length that is socially optimal, whereas a centralized channel cannot.
We introduce the work of the finalists in the 2007 ISMS Practice Prize Competition, representing the best examples of rigor plus relevance that our profession produces. The winner, describing a collaboration between National Academies Press and a team based at the University of Maryland, involves a sequenced program of research to calibrate price sensitivity of digital media. The other two finalists address a model to optimize the distribution of used cars geographically depending on local conditions, and a model to use price and distribution strategies to improve product profitability of P&G's heavy-duty detergent brands in India.
When a firm allows the return of previously purchased merchandise, it provides customers with an option that has measurable value. Whereas the option to return merchandise leads to an increase in g...
A common theme in marketing literature is the acquisition and retention of customers as they trade up from inexpensive introductory offerings to those of higher quality. We develop a nonhomothetic choice model to accommodate effects of advertising, professional recommendation, and other factors that facilitate the description and management of trade-up. Our model allows advertising to affect the relative superiority or inferiority of products. This allows for a wide variety of trade-up patterns beyond those obtained from a standard random utility formulation of the logit model. Our nonhomothetic model allows for advertising to affect more than just brand intercepts (perceived quality), but also the rate at which consumers are willing to trade up to higher-quality brands. Advertising effects are measured using a randomized treatment and evaluated by considering their direct implications for firm pricing and profits.
We examine the specification and interpretation of discrete-choice models used in behavioral theory testing, with a focus on separating “coefficient scale” from “error scale,” particularly over time. Numerous issues raised in the thoughtful commentaries of Louviere and Swait [Louviere, J., J. Swait. 2010. Discussion of “Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test.” Marketing Sci. 29(1) 18–22] and Hutchinson, Zauberman, and Meyer (HZM) [Hutchinson, J. W., G. Zauberman, R. Meyer. 2010. On the interpretation of temporal inflation parameters in stochastic models of judgment and choice. Marketing Sci. 29(1) 23–31] are addressed, specifically the roles of response scaling, preference covariates, actual versus hypothetical consumption, “immediacy,” and heterogeneity, as well as key differences between the experimental setup in Salisbury and Feinberg [Salisbury, L. C., F. M. Feinberg. 2010. Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test. Marketing Sci. 29(1) 1–17] and those typifying intertemporal choice and construal level theory. We strongly concur with most of the general conclusions put forth by the commentary authors, but we also emphasize a central point made in our research that may have been lost: that the temporal inflation effects observed in our empirical analysis could be attributed to stochastic effects, deterministic influences, or an amalgam; appropriate inferences depend on the nature of one's data and stimuli. We also report on further analyses of our data, as well as a meta-analysis of HZM's Table 1 that is consistent with our original findings. Implications for, and dimensions relevant to, future research on temporal stochastic inflation and its role in choice-based research are discussed.
Prior marketing literature has overlooked the role of regulatory regimes in explaining international sales growth of new products. This paper addresses this gap in the context of new pharmaceuticals (15 new molecules in 34 countries) and sheds light on the effects of regulatory regimes on new drug sales across the globe. Based on a time-varying coefficient model, we find that differences in regulation substantially contribute to cross-country variation in sales. One of the regulatory constraints investigated, i.e., manufacturer price controls, has a positive effect on drug sales. The other forms of regulation such as restrictions of physician prescription budgets and the prohibition of direct-to-consumer advertising (DTCA) tend to hurt sales. The effect of manufacturer price controls is similar for newly launched and mature drugs. By contrast, regulations on physician prescription budgets and DTCA have a differential effect for newly launched and mature drugs. Whereas the former hurts mature drugs more, the latter has a larger effect on newly launched drugs. In addition to these regulatory effects, we find that national culture, economic wealth, and lagged sales also affect drug sales. Our findings may be used as input by managers for international launch and marketing decisions. They may also be used by public policy administrators to assess the role of regulatory regimes in pharmaceutical sales growth.
The implications of Salisbury and Feinberg's (2010) paper [Salisbury, L. C., F. M. Feinberg. 2010. Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test. Marketing Sci. 29(1) 1–17] for the process of model development and testing in the field of intertemporal choice analysis is explored. Although supporting the overall thrust of Salisbury and Feinberg's critique of previous empirical work in the area, we also see their paper as illustrating the dangers of drawing strong inferences about the behavioral interpretation of statistical model parameters without seeking convergent empirical evidence. In particular, we are skeptical about the extent to which the reported effects of temporal distance on the estimated scale parameter, σ c , are uniquely, or even primarily, due to unobserved error inflation that reflects consumer's uncertainty about future utility. This interpretation is brought into question by several lines of reasoning. Conceptually, we note that “uncertainty” is different from “error” and that, for choice data, the error inflation model is mathematically identical to a model in which the scale parameter is a deterministic function of the temporal discount rate. Empirically, a reanalysis of data from previously published experiments does not consistently support temporal error inflation, temporal convergence of choice shares, or the scale parameter as an explanation of variety seeking in choice sequences. In our opinion, the cumulative results of research on intertemporal choice require models in which the attributes of choice alternatives are differentially discounted over time. Despite these findings, we advocate that choice researchers should indeed follow Salisbury and Feinberg's advice to not assume that error variances will be unaffected by experimental manipulations, and such effects should be explicitly modeled. We also agree that uncovering effects on error variance is just the first step, and the ultimate goal should be to rigorously explain the reasons for such effects.
This paper examines demand elasticities using an integrated framework proposed by Hanemann [Hanemann, M. W. 1984. Discrete/continuous models of consumer demand. Econometrica 52(3) 541–561], which models the incidence, brand choice, and quantity decisions of a consumer as an outcome of her utility maximization subject to budget constraints. Although the Hanemann framework has been the mainstay of earlier efforts to examine these decisions jointly, empirical researchers who have used the it to study purchase behavior have often found that the quantity elasticities are around −1, regardless of the brand or category. We attempt to uncover the underlying reasons for this finding and propose approaches to get as close to the “true” quantity elasticities as possible. We do this by (i) analytically demonstrating how assumptions on the distribution of the brand-specific econometrician's errors imply certain restrictions that in turn force quantity elasticities to −1, (ii) discussing how these restrictions can be alleviated by considering a suitable specification of unobserved parameter heterogeneity, and (iii) using scanner data to empirically illustrate the impact of the restrictions on quantity elasticities and the relative efficacy of multiple specifications of unobserved heterogeneity in easing those restrictions. We find that the specification of unobserved heterogeneity crucially influences estimates of quantity elasticities and that the mixture normal specification outperforms the alternatives.