Understanding the adoption of new brands through salespeople: a multilevel framework

So far there has been scant empirical attention paid to the role of the sales force in the adoption of new brands in the early implementation stages. We test a framework of internal (sales manager and salespeople) brand adoption using an empirical multilevel study. Our findings suggest that the construct of expected customer demand (ECD) plays an important role in sales force brand adoption. First, ECD directly influences salespeople’s and sales managers’ brand adoption. Second, ECD serves as a cross-level moderator of new brand adoption transmission. We find the influence of sales managers’ brand adoption on salespeople’s brand adoption to be stronger when salespeople’s ECD is lower.     

Dynamic employment adjustments over business cycles

This paper uses U.S. monthly industrial production employment data between 1964 and 2000 to examine the dynamic labor adjustments of production workers and nonproduction workers in both the short and long-run. The results from the short-run analysis show that the dynamic adjustment of production workers is consistent with business cycles. However, the adjustment of nonproduction workers is relatively fixed, lags behind the shocks over business cycle changes, and exhibits the quasi-fixed factor property. In the long-run, we found that nonproduction workers and production workers are cointegrated indicating that the two series are in long-run equilibrium.First version received: March 2002/Final version received: November 2003We would like to thank James McClure, participants in the Economics Department seminar series at Ball State University, and an anonymous referee for their comments and suggestions.     

A Note on Regulating Oligopolistic Industries: A Hierarchical Model

In a 1994 paper, extending the well-known incremental surplus subsidy scheme of Sappington and Sibley, Schwermer presented a non-Bayesian incentive scheme for regulating a Cournot oligopoly industry. This note designs an oligopolistic incentive scheme for a hierarchical Stackelberg model in which firms choose outputs sequentially.     

Testing for the Presence of Moral Hazard Using the Regulatory Reform in the Car Insurance Market: Case of Korea

The aim of this paper is to investigate the presence of the moral hazard phenomenon in the Korean car insurance market. In the context of natural experiment, I examine whether the regulatory reform introduced in 2000 generates significant difference in accident probability between before and after the reform. Further, I analyse the different effects of regulatory reform on different parts of the outcome distribution. In any case, I do not find the significant effects of regulatory reform on accident probability.     

A pre-diffusion growth model of intentions and purchase

In this paper, we investigate whether information on the history of purchase intentions is useful in predicting actual purchase behavior. The research is motivated by two factors. The first factor is the empirical finding in the literature that measuring intentions just prior to purchase provides better predictions of actual purchase as compared to when these intentions are measured earlier. The second factor is the role of the timing of the formation of intentions prior to purchase. While one stream of literature based on preference fluency predicts that early formation of intentions is more likely to lead to actual purchase, the other stream based on the memory-based “recency” effect predicts that formation of intentions just prior to purchase is more likely to lead to actual purchase. Together, these two factors motivate the potential need to account for the entire history of intentions prior to purchase. A canonical example of a market where intention histories are tracked is the movie industry, where “first choice” movie watching intentions are tracked up to (and in some cases beyond) the time of release. Accommodating the history of intentions in an econometric model that predicts actual box office performance is challenging due to the differing numbers of observations for the movies, the large numbers of observations for certain movies, as well as the role of various time-invariant and time-varying covariates influencing intentions. We propose a two-part model where the first part involves a hierarchical growth model that summarizes the trajectories of intentions via “growth factors.” These growth factors also reflect the role of the various covariates. The second part is a regression of the box office performance on the growth factors and other covariates. The models are simultaneously estimated within a Bayesian framework. Consistent with the previous literature, we find that including information on intentions improves our ability to predict behavior, with the recent intentions being the most informative. Importantly, when the history of intentions is accounted for, our results indicate that the data support the “recency” literature—intentions grow over time leading up to purchase, and this growth has a positive impact on opening box office performance. While a linear growth model performs best for most movies, there exists a subset of movies for which the quadratic growth model better captures the “spike” in intentions just prior to purchase. Further, accounting for information on the history of intentions dramatically improves model fit and forecasting performance relative to when only the intentions at one point in time (e.g., the ones just prior to purchase) are accounted for.