A note on government spending on infrastructure in an endogenous growth model with finite horizon

By extending the work of Mourmouras and Lee (1999), we show that the growth-maximizing income tax rate maximizes also the utilities of not only all current generations but also all future generations. This result means that the statement that the growth-maximizing income tax rate is equivalent to the welfare maximizing one holds true in a stronger sense than Barro (1990) and Mourmouras and Lee (1999) have pointed out.     

Towards a brain-to-society systems model of individual choice

Canonical models of rational choice fail to account for many forms of motivated adaptive behaviors, specifically in domains such as food selections. To describe behavior in such emotion- and reward-laden scenarios, researchers have proposed dual-process models that posit competition between a slower, analytic faculty and a fast, impulsive, emotional faculty. In this paper, we examine the assumptions and limitations of these approaches to modeling motivated choice. We argue that models of this form, though intuitively attractive, are biologically implausible. We describe an approach to motivated choice based on sequential sampling process models that can form a solid theoretical bridge between what is known about brain function and environmental influences upon choice. We further suggest that the complex and dynamic relationships between biology, behavior, and environment affecting choice at the individual level must inform aggregate models of consumer choice. Models using agent-based complex systems may further provide a principled way to relate individual and aggregate consumer choices to the aggregate choices made by businesses and social institutions. We coin the term “brain-to-society systems” choice model for this broad integrative approach.     

Advances in computation,statistical methods,and testing of discrete choice models

This paper gives a brief overview of recent developments in computation, estimation, and statistical testing of choice models, with marketing applications. Topics include statistical models for discrete panel data with heterogeneous decision-makers, simulation methods for estimation of high-dimension multinomial probit models, specification tests for model structure and for brand and purchase clustering, and innovations in numerical analysis for estimation and forecasting. In collaboration with Denis Bolduc, David Bunch, Michael Keane, Don Kridel, and Steve Stern.     

Information processing analysis of a stochastic model of brand choice

A formal and detailed comparison between Morrison's brand loyal model and its information processing counterpart reveals serious internal inconsistencies and other shortcomings of this stochastic model.     

The choice of appropriate technology in a general equilibrium model

This paper analyzes the general equilibrium aspects related to the choice of technology. The paper studies the problem from the perspective of a small, labor abundant open economy that does not generate its own technology. The economic planners must choose between two technologies, one better geared toward the production of labor intensive goods, the other to capital intensive goods. It is shown that the choice of technology not only will affect the welfare level, but it can also reverse the pattern of international trade. It is also shown that the imposition of a tariff can lead the planner to choose a different technology from the one that is optimal under free trade.     

A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data

We consider the problem of simultaneously performing market segmentation and predicting product choice for a given population of consumers. This behaviour-based segmentation model uses several types of information characterizing individual consumers and their market context: sociodemographic, psychographic and product choice data. These data are combined in a normative conceptual framework that posits the formation of latent segments, each of which displays differing degrees of sensitivity to relevant product attributes. This permits results obtained by the proposed model structure to differ significantly from those of traditional segmentation techniques, which usually produce a set of groups characterized by smaller within-group than between-group variation in sociodemographic and/or psychographic variables. By making the segments behaviour-based, it is argued that the segments produced by the model will be more actionable and more directly relevant to management decision-making. The proposed model is applied to a data set involving choice of a beauty product offered by five national brands. The results show that the explanatory power of the latent segmentation and choice model is far greater than that of the MNL model, which is nested within our more general specification. The types of results available from the model are illustrated through the application.     

A nested logit model of brand choice incorporating variety-seeking and marketing-mix variables

We model the effects of variety-seeking and marketing-mix variables on consumers' purchases of coffee using a nested logit model. We premise that on any given purchase occasion, the utilities of brands other than the one purchased on the previous occasion may be correlated due to the consumer's tendency to seek variety or to avoid variety. This results in a two-level hierarchical model where choice on any purchase occasion is conditioned on the brand purchased on the immediately preceding occasion. Such a structure accounts for variety seeking and inertia tendencies of consumers and is consistent with a hierarchical decision process, where consumers first decide whether or not to make a repeat purchase and then decide which brand size to purchase. The assumed hierarchical structure is shown to be consistent with observed coffee purchase behavior, and the model is shown to outperform a nonhierarchical logit model in predicting consumers' brand choices.     

Random disturbances and the choice of exchange regimes in an intergenerational model

An overlapping generational model is used to derive the consumption demand for individuals of each generation under expected utility-maximizing behavior: these demand functions are used to derive macroeconomic equilibrium under fixed and flexible exchange rates. The standard aggregate results concerning the insulating role of flexible rates for real external disturbances and fixed rates for internal disturbances are shown. However, the variability of an individual's utility need not be the same as the variability of aggregate variables. It is shown that the form of the utility function and the sources of disturbances are crucial in determining which exchange regime is preferable.     

Risk and the technology content of FDI: A dynamic model

This paper incorporates risk into the FDI decisions of firms. The risk of FDI failure increases with the gap between the South's technology frontier and the technology complexity of a firm's product. This leads to a double-crossing sorting pattern of FDI—firms of intermediate technology levels are more likely than others to undertake FDI. It is with the attempt to relax the upper bound of the technology content of FDI, we argue, that many FDI policies are created. The theory's predictions are consistent with the empirical patterns of FDI in China by US and Taiwanese manufacturing firms.     

Bayesian estimation of a simultaneous probit model using error augmentation: An application to multi-buying and churning behavior

Researchers in marketing are often interested in analyzing how an agent’s discrete choice decision affects a subsequent or concurrent discrete choice decision by the same or different agent. This analysis may necessitate the use of a simultaneous equations model with discrete and continuous endogenous variables as explanatory variables. In this paper, we offer an error augmentation approach to Hierarchical Bayesian estimation of a simultaneous bivariate probit model containing both discrete and continuous endogenous variables. We accomplish the error augmentation in our MCMC algorithm using a Metropolis-Hastings step that generates the error components of the latent variables in our model. Using simulated data, we demonstrate that our error augmentation algorithm recovers closely the true parameters of the simultaneous bivariate probit model. We then apply our algorithm to customer churn data from a wireless service provider. We formulate a simultaneous bivariate probit model to study the impact of a customer’s multiple product relationships with a firm (multi-buying) on the likelihood of churn by that customer. The empirical results show that the act of multi-buying significantly reduces churn even though the customers who are more predisposed to multi-buy have an inherently higher predisposition to churn.     

A dynamic quality ladder model with entry and exit: Exploring the equilibrium correspondence using the homotopy method

This paper explores the equilibrium correspondence of a dynamic quality ladder model with entry and exit using the homotopy method. This method is ideally suited for systematically investigating the economic phenomena that arise as one moves through the parameter space and is especially useful in games that have multiple equilibria. We briefly discuss the theory of the homotopy method and its application to dynamic stochastic games. We then present three main findings: First, the more costly and/or less beneficial it is to achieve or maintain a given quality level, the more a leader invests in striving to induce the follower to give up; the more quickly the follower does so; and the more asymmetric is the industry structure that arises. Second, the possibility of entry and exit gives rise to predatory and limit investment. Third, we illustrate and discuss the multiple equilibria that arise in the quality ladder model, highlighting the presence of entry and exit as a source of multiplicity.     

Extentions of probabilistic perceptual maps with implications for competitive positioning and choice

Perceptual product positioning maps which are derived from probabilistic scaling models possess some distinct advantages over their deterministic counterparts. However, many probabilistic models still labor under a number of restrictive mathematical conditions. This paper describes an anisotropic space extension that alleviates some of these limitations by explicitly modeling the dimensional variances and covariances of each brand in a product positioning map. To clarify the decisions necessary when using probabilistic scaling models and to illustrate some of their attractive properties, two sets of convenience goods data are analyzed. The applications focus on the model's implications for the understanding of brand positioning and choice probabilities.     

The diffusion of a new service: Combining service consideration and brand choice

We propose an individual-level model of a two-stage service diffusion process. In the first stage, customers decide whether to “consider” joining the service. This (Consideration) stage is modeled by a hazard model. Customers who decide to consider the service move on to the Choice stage, wherein they choose among the service alternatives and an outside No Choice option. This stage is modeled by a conditional Multinomial Logit model. The service provider does not observe the transition in the first stage of potential customers who have yet to choose a brand. Such potential customers may have started to consider joining the service, yet chose the outside alternative in each period thereafter. One of the main contributions of the model is its ability to distinguish between these two non-adopter types. We estimated the model using data on the adoption process of newly introduced service plans offered by a commercial bank. We employed the hierarchical Bayes Monte Carlo Markov Chain procedure to estimate individual as well as population parameters. The empirical results indicate that the model outperforms competing models in breadth of analysis, model fit, and prediction accuracy.     

Structural estimation and solution of international trade models with heterogeneous firms

We present an empirical implementation of a general-equilibrium model of international trade with heterogeneous manufacturing firms. The theory underlying our model is consistent with Melitz (2003). A nonlinear structural estimation procedure identifies a set of core parameters and unobserved firm-level trade frictions that best fit the geographic pattern of trade. Our estimation model is consistent with the specified general equilibrium model, and we conduct general equilibrium counterfactual analyses to illustrate model responses. We first assess the economic effects of reductions in measured tariffs. Taking the simple-average welfare change across regions the Melitz structure indicates welfare gains from liberalization that are four times larger than in a standard trade policy simulation. Furthermore, when we compare the economic impact of tariff reductions with reductions in estimated fixed trade costs we find that policy measures affecting the fixed costs are of greater importance than tariff barriers.     

Falling in love with brands: a dynamic analysis of the trajectories of brand love

This article presents a study designed to investigate and map the trajectories of brand love. Consumers described experiences related to the initiation and evolution of their relationships with their most loved brand. Participants were asked to graphically trace the course of their feelings toward their currently most loved brand and to recall the events that influenced those feelings. The paths toward brand love followed five distinct trajectories, labeled as “slow development,” “liking becomes love,” “love all the way,” “bumpy road,” and “turnabout.” The formative experiences shaping these trajectories often include individual, personal, and private experiences that are largely outside any marketer’s control.     

Development of a service continance model with IT service antecedents

This study make provides service marketers, particularly those delivering information technology (IT) related service, with insight to the factors that consumers use when evaluating IT services. We develop a service continuance model that includes the antecedents of the consumer׳s decision to continue using information technology (IT) related services in a B2C service environment. Using data from the smart phone service consumers, a covariance-based structural equation modeling analysis is used to test the research model. Results from our empirical study suggest that the association between service usefulness and service continuation intention is fully mediated by service satisfaction. Though both system-service quality and customer-service quality are positively associated with service satisfaction, consumers of IT related services attach greater importance to system-service quality than to custom service quality. Likewise, the indirect path to service continuation intention is stronger in system-service quality than in customer-service quality. Our findings have practical implication for growing market share in IT related services by recognizing the importance of system-service quality in technology service delivery.     

Problems in the choice of a system for costing and pricing of in-house computer services

The problem of pricing computer services has been discussed in the literature since the early days of computing. Costing and pricing have often been interchanged in the discussions. After a discussion of the problems of measurement of resource usage, pricing for cost recovery and for resource allocation are discussed. The paper concludes with suggestions for further research and a brief summary.     

The Role of Self-Definitional Principles in Consumer Identification with a Socially Responsible Company

This research analyses the influence of the perception of Corporate Social Responsibility (CSR image) on consumer–company identification (C–C identification). This analysis involves an examination of the influence of CSR image on brand identity characteristics which provide consumers with an instrument to satisfy their self-definitional needs, thereby perceiving the brand as more attractive. Also, the direct and mediated influences (through their effect on brand attitude), of CSR-based C–C identification on purchase intention are analysed. The results offer empirical evidence that CSR generates more C–C identification because it improves brand prestige and distinctiveness; brand coherence is also a powerful antecedent of brand attractiveness in the context of CSR communication. Finally, CSR-based C–C identification is able to generate directly better attitude towards the brand and greater purchase intention.