a micro analytic threshold model for the timing of first purchases of durable goods a micro analytic threshold model to describe the timing of household purchases of consumer durable goods is developed and tested the model incorporates unobserved heterogeneity via a generalized gamma distribution and accounts for time varying covariates further we employ estimation methods applicable or purchase data observed at periodic intervals of time the model outperforms other competing models for predicting the timing of purchase of durable goods in terms of fit and predictive ability in particular this model outperforms the logit model and the diffusion model the generalized gamma timing model predicts well the time to purchase the durable good we show how it can be employed for micro segmentation of households several research directions and applications are described

a prelaunch diffusion model for evaluating market defense strategies this paper describes the development and application of a marketing model to help set an incumbent s defensive marketing strategy prior to a new competitor s launch the management problem addressed is to assess the market share impact of a new entrant in the residential australian long distance telephone call market and determine the factors that would influence its dynamics and ultimate market appeal the paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss we develop models at two levels of complexity to give both simple robust forecasts and more detailed diagnostic analysis of the effect of marketing actions the models are calibrated prior to the new entrant s launch enabling preemptive marketing strategies to be put in place by the defending company the equilibrium level of consideration of the new entrant was driven by respondents strength of relationship with the defender and inertia while trial was more price based continued use of the defender depends on both service factors and price the rate at which share loss eventuates is negatively related to the defender s perceived responsiveness saving money being the only reason to switch and risk aversion prelaunch model forecasts validated six months after launch using both aggregate monthly sales data and detailed tracking surveys are shown to closely follow the actual evolution of the market the paper provides a closed form multistate model of the new entrant s diffusion a methodology for the prelaunch calibration of dynamic models in practice and insights into defensive strategies for existing companies facing new entrants

modeling purchase timing and brand switching behavior incorporating explanatory variables and unobserved heterogeneity the authors use a continuous time semi markov approach to analyze in a single framework the purchase timing and brand switching decisions of households for a frequently purchased product the analysis provides more insights into the dynamics of household purchase behavior than could be obtained from conventional discrete choice models such as logit or probit the authors find that the probability distribution of interpurchase times is not the same for various switching between brands revealing extra information about the purchase timing decisions further they find that though the marketing mix and household demographic variables explain a large part of the variation in the brand switching rates they account for only a small part of the variation in the repeat purchase rates another finding from the analysis is that the rates of switching between brands due to promotional activities such as special displays and price reductions are in reverse order to the share of purchases of the various brands

dynamic analysis of consumer response to marketing strategies this paper develops a methodology for modeling consumer response that integrates previous research in stochastic brand selection diffusion of innovation test market analysis and new product design the methodology makes it practical to extend brand selection models to include diffusion phenomena such as awareness trial and information flow purchase timing and brand selection are interdependent and both phenomena depend jointly on managerial controls such as advertising coupons price off promotion product positioning and consumer characteristics within this general structure we provide practical estimation procedures a least squares approximation to the maximum likelihood estimates to determine the parameters which link managerial controls to consumer response closed form solutions are derived for cumulative awareness cumulative trial penetration expected sales and purchases due to promotion all as a function of time we also provide simplified expressions for equilibrium t market share tradeoffs among complexity of the diffusion process number of managerial variables nonstationarity complexity of purchase timing consumer segmentation and sample size are made explicit so that the marketing scientist can customize his analyses to the managerial problems that he faces the effects of sample size data interval frequency and collinearity in the explanatory variables are investigated with simulations based on a five state consumer response process which depends on 8 10 marketing variables the paper closes with a brief description of the application and predictive test of a consumer response model based on the methodology

a new product growth for model consumer durables this article originally appeared in management science january 1969 volume 15 number 5 pp 215 227 published by the institute of management sciences a growth model for the timing of initial purchase of new products is developed and tested empirically against data for eleven consumer durables the basic assumption of the model is that the timing of a consumer s initial purchase is related to the number of previous buyers a behavioral rationale for the model is offered in terms of innovative and imitative behavior the model yields good predictions of the sales peak and the timing of the peak when applied to historical data a long range forecast is developed for the sales of color television sets

prelaunch forecasting of new automobiles this paper develops and applies a prelaunch model and measurement system to the marketing planning of a new automobile the analysis addresses active search by consumers dealer visits word of mouth communication magazine reviews and production constraints issues that are important in understanding consumer response to durable goods we address these issues with a detailed consumer flow model which monitors and projects key consumer transitions in response to marketing actions a test vs control consumer clinic provides data which with judgment and previous experience are used to calibrate the model to fit the sales history of the control car we illustrate how the model evolved to meet management needs and provided suggestions on advertising dealer training and consumer incentives comparison of the model s predictions to actual sales data suggests reasonable accuracy when an implemented strategy matches the planned strategy

the impact of deregulation on the production structure of the motor carrier industry empirical analysis of the motor carrier industry pre and post regulatory reform reveals that deregulation resulted in significant changes in firm production structure and lower real average costs translog cost functions for firms operating in 1977 and 1983 were estimated and compared for other specialized commodity carriers fitted average costs were computed from these functions the results indicate significant differences in the cost functions and real costs that cannot be attributed to technological changes but rather suggest efficiency gains the results also suggest that it is inappropriate to predict outcomes of deregulation using empirical analyses of firms in the regulated environment

removing heterogeneity bias from logit model estimation this paper introduces a new estimation procedure for the logit model that is an extension of a conditional estimation procedure developed by chamberlain chamberlain g 1978 on the use of panel data working paper harvard university 1 52 chamberlain g 1980 analysis of covariance with qualitative data rev econom stud 47 225 238 the method eliminates heterogeneity bias which is present in the estimates produced by traditional estimation techniques it improves the goodness of fit and explanatory power of these models while incorporating purchase event feedback

a multiattribute model of consumer choice during product learning the processes of consumer preference formation during product learning are analyzed a hypothesis about how individuals form attribute expectations is used to derive a dynamic multinomial logit model of individual choice which endogenously recognizes product learning the model and its underlying assumptions are then tested in the context of an interactive grocery store learning game the results support most elements of the proposed model structure an assumption of temporal stationarity in attribute salience however could not be supported approaches to implementation of the model are discussed and implications for marketing management and research in individual choice modeling are addressed

an examination of consumer heterogeneity in a stochastic model of consumer purchase dynamics with explanatory variables abstract a stochastic model of brand choice and purchase incidence is proposed that relates marketing variables including advertising exposures to brand performance measures such as market share penetration and depth of repeat purchase dynamics over time the approach considers various aspects of consumer heterogeneity including individual differences in brand loyalty levels advertising exposures and purchase rates for a population of consumers a major focus of this study is on the evaluation of the impact of consumer heterogeneity in alternative models on the basis of single source scanner panel data for an actual market situation in particular we demonstrate the critical importance of considering heterogeneity over a consumer population as a means of enhancing descriptive and predictive model fit as well as for allowing the analysis of advertising media schedules

moviemod an implementable decision support system for prerelease market evaluation of motion pictures in spite of the high financial stakes involved in marketing new motion pictures marketing science models have not been applied to the prerelease market evaluation of motion pictures the motion picture industry poses some unique challenges for example the consumer adoption process for movies is very sensitive to word of mouth interactions which are difficult to measure and predict before the movie has been released in this article we undertake the challenge to develop and implement moviemod a prerelease market evaluation model for the motion picture industry moviemod is designed to generate box office forecasts and to support marketing decisions for a new movie after the movie has been produced or when it is available in a rough cut but before it has been released unlike other forecasting models for motion pictures the calibration of moviemod does not require any actual sales data also the data collection time for a product with a limited lifetime such as a movie should not take too long for moviemod it takes only three hours in a consumer clinic to collect the data needed for the prediction of box office sales and the evaluation of alternative marketing plans the model is based on a behavioral representation of the consumer adoption process for movies as a macroflow process the heart of moviemod is an interactive markov chain model describing the macro flow process according to this model at any point in time with respect to the movie under study a consumer can be found in one of the following behavioral states undecided considerer rejecter positive spreader negative spreader and inactive the progression of consumers through the behavioral states depends on a set of movie specific factors that are related to the marketing mix as well as on a set of more general behavioral factors that characterize the movie going behavior in the population of interest this interactive markov chain model allows us to account for word of mouth interactions among potential adopters and several types of word of mouth spreaders in the population marketing variables that influence the transitions among the states are movie theme acceptability promotion strategy distribution strategy and the movie experience the model is calibrated in a consumer clinic experiment respondents fill out a questionnaire with general items related to their movie going and movie communication behavior they are exposed to different sets of information stimuli they are actually shown the movie and finally they fill outpostmovie evaluations including word of mouth intentions these measures are used to estimate the word of mouth parameters and other behavioral factors as well as the movie specific parameters of the model moviemod produces forecasts of the awareness adoption intention and cumulative penetration for a new movie within the population of interest for a given base marketing plan it also provides diagnostic information on the likely impact of alternative marketing plans on the commercial performance of a new movie we describe two applications of moviemod one is a pilot study conducted without studio cooperation in the united states and the other is a full fledged implementation conducted with cooperation of the movie s distributor and exhibitor in the netherlands the implementations suggest that moviemod produces reasonably accurate forecasts of box office performance more importantly the model offers the opportunity to simulate the effects of alternative marketing plans in the dutch application the effects of extra advertising extra magazine articles extra tv commercials and higher trailer intensity compared to the base marketing plan of the distributor were analyzed we demonstrate the value of these decision support capabilities of moviemod in assisting managers to identify a final plan that resulted in an almost 50 increase in the test movie s revenue performance compared to the marketing plan initially contemplated management implemented this recommended plan which resulted in box office sales that were within 5 of the moviemod prediction moviemod was also tested against several benchmark models and its prediction was better in all cases an evaluation of moviemod jointly by the dutch exhibitor and the distributor showed that both parties were positive about and appreciated its performance as a decision support tool in particular the distributor who has more stakes in the domestic performance of its movies showed a great interest in using moviemod for subsequent evaluations of new movies prior to their release based on such evaluations and the initial validation results moviemod can fruitfully and inexpensively be used to provide researchers and managers with a deeper understanding of the factors that drive audience response to new motion pictures and it can be instrumental in developing other decision support systems that can improve the odds of commercial success of new experiential products

a multivariate polya model of brand choice and purchase incidence in this paper we develop an integrated stochastic model of purchase timing and brand selection which incorporates the influence of marketing mix variables seasonality and trend and also allows for various individual choice mechanisms our approach rests on the assumptions of a zero order choice process a poisson timing process and purchase rates following a multivariate gamma distribution over the population the scale parameters of which vary according to marketing activities and time the resulting model is a multivariate polya process and the distribution of brand choice probabilities turns out to be a generalized dirichlet distribution thus most currently used zero order models can be considered to be special cases of this approach furthermore we derive a number of market diagnostics which provide insights into market structure and demonstrate the model s use for marketing strategy simulation based on extensive testing of the underlying hypotheses we finally validate the model using empirical data and show that it fits the market in question

liaisons dangereuses increasing connectivity risk sharing and systemic risk the recent financial crisis poses the challenge to understand how systemic risk arises endogenously and what architecture can make the financial system more resilient to global crises this paper shows that a financial network can be most resilient for intermediate levels of risk diversification and not when this is maximal as generally thought so far this finding holds in the presence of the financial accelerator i e when negative variations in the financial robustness of an agent tend to persist in time because they have adverse effects on the agent s subsequent performance through the reaction of the agent s counterparties 2012 elsevier b v all rights reserved

a generalized model of pricing for homogeneous goods under imperfect information this paper generalizes the model developed in wilde and schwartz 1979 to allow downward sloping demand curves and u shaped average cost curves it shows that the basic qualitative conclusions of wilde and schwartz still hold moreover it shows that the critical proportion of comparison shoppers needed to generate a competitive equilibrium falls as demand becomes more elastic or average costs become more inelastic finally it shows that when imperfect information generates non competitive outcomes they are bounded below in welfare terms by the monopolistically competitive equilibrium

the inaugural isms practice prize competition isms practice prize competition chairman gary l lilien special section introduction by the isms practice prize competition chairman finalists joseph a foster peter n golder gerard j tellis predicting sales takeoff for whirlpool s new personal valet john h roberts pamela d morrison charles j nelson implementing a prelaunch diffusion model measurement and management challenges of the telstra switching study

formal choice models in marketing the paper gives an overview and evaluates the theoretical traditions underlying choice models that are used in marketing in particular the emphasis of this essay is on the underlying assumptions limitations and empirical demands of these choice models four fundamental choice models are used as a basis to analyze this complex field the neoclassical economic theory as extended by lancaster the risk preference theory of choices under uncertainty the strict utility theory and the random utility theory these four choice models and their extensions are compared and contrasted along the three critical steps in the model building process theory generation parameterization and estimation

an empirical investigation of the dynamic mcfadden model of purchase timing and brand choice implications for market structure purchase timing and brand choice decisions of households are jointly investigated using the dynamic mcfadden model of heckman and singer the hazard of brand purchase is decomposed into the category purchase hazard and the probability of brand choice conditional on category purchase the former is modeled using the hazard function approach and the latter using a logit model unobserved heterogeneity in brand preferences marketing effects and baseline hazard parameters is accounted for in the empirical analysis the distribution of preference heterogeneity identifies the locations of brands in multiattribute perceptual space and the distribution of attribute importance weights across households

household level innovation diffusion model of photo voltaic pv solar cells from stated preference data we focus on predicting the adoption time probabilities of photo voltaic solar panels by households using discrete choice experiments and an innovation diffusion model the primary objective of this research is cohesively mapping the theory of disruptive innovation into diffusion of innovations to aid policy makers by linking two critical uncertainties of new technology 1 whether households prefer the new attributes of the new technology and how these preferences vary by market segments and 2 when are they going to adopt if at all our study uses recent developments of discrete choice experiments and establishes a causal link between the attributes of the technology attitudinal constructs and socio demographics and adoption time probabilities using the bass diffusion model the data was collected from ontario a province of canada the innovation diffusion model allows us to compute the cumulative probability of adoption over time per household technology awareness and energy cost saving have a significant effect on the adoption probability reinforcing the need for effective education these findings also suggest that campaigns should explain more about investment criteria feed in tariffs and environmental attributes this study findings call for a need to use seeding strategies to accelerate exogenous word of mouth wom for this new technology

too interconnected to fail financial network of us cds market topological fragility and systemic risk a small segment of credit default swaps cds on residential mortgage backed securities rmbs stand implicated in the 2007 financial crisis the dominance of a few big players in the chains of insurance and reinsurance for cds credit risk mitigation for banks assets has led to the idea of too interconnected to fail titf resulting as in the case of aig of a tax payer bailout we provide an empirical reconstruction of the us cds network based on the fdic call reports for off balance sheet bank data for the 4th quarter in 2007 and 2008 the propagation of financial contagion in networks with dense clustering which reflects high concentration or localization of exposures between few participants will be identified as one that is titf those that dominate in terms of network centrality and connectivity are called super spreaders management of systemic risk from bank failure in uncorrelated random networks is different to those with clustering as systemic risk of highly connected financial firms in the cds or any other financial markets is not priced into their holding of capital and collateral we design a super spreader tax based on eigenvector centrality of the banks which can mitigate potential socialized losses

chapter 7 pretest market forecasting 6 summary pretest market models provide a low cost and rapid method to test the combined product advertising price promotion selling and distribution plan the full proposition analyses are sufficiently accurate to identify most winners and eliminate most losers they provide an effective way to control the risks of failure and supply actionable managerial diagnostics to improve the product the output is a high quality product that meets customer needs and reaches the market quickly pretest market models are an accepted practice for most frequently purchased products but are relatively new for consumer durables they are now being developed and tested for really new industrial products and services since pretest markets are extremely valuable in reducing risk and increasing the expected benefit of new products we expect that proven models will soon be available for all products and services research on premarket forecasting in these new industries should be the highest priority for future work

is regulation necessary for value of service pricing this article presents evidence for the existence of value of service pricing in the neverregulated market for trucking services to haul florida produce rates per truckload are found to increase by eleven to twelve cents for every one dollar increase in the average daily loss in the value of the cargo due to product deterioration ceteris paribus this result is at variance with the commonly held belief that value of service pricing in transportation is a form of price discrimination made possible by the policies of rate bureaus and regulatory agencies

financial networks contagion commitment and private sector bailouts i develop a model of financial networks in which linkages not only spread contagion but also induce private sector bailouts where liquid banks bail out illiquid banks because of the threat of contagion introducing this bailout possibility i show that linkages may be optimal ex ante because they allow banks to obtain some mutual insurance even though formal commitments are impossible however in some cases e g when liquidity is concentrated among a small group of banks the whole network may collapse i also characterize the optimal network size and apply the results to joint liability arrangements and payment systems linkages among agents in financial markets are a concern because of the risk of financial contagion that is the risk that a small shock to one agent will spread to other agents in a domino effect whether we should worry about these linkages is an open question the main goal of this paper is to show that a network in which agents are closely interlinked may be optimal both because of and despite the potential for contagion another goal is to characterize optimal networks that is whether and how agents should be linked to one another the basic intuition is as follows linkages present the threat of contagion to prevent collapse of the whole network agents who are lucky ex post may be willing to bail out those who are not in this way agents obtain the benefits of mutual insurance even though they cannot precommit to making payments

a probit model of choice dynamics there are many products which are repeatedly purchased by consumers in such cases it is likely that choice history that is the sequence of choices made in the past as well as marketing variables affect subsequent choice decisions attempts to model the effects of choice history have been generally based on the inclusion of variables that represent brand loyalty and or variety seeking behavior in this paper we present a model of dynamic choice behavior which is more general and incorporates four characteristics the first characteristic labeled preference reinforcement and preference reduction represents loyalty and variety seeking the second is the short term reluctance of a consumer to move from the current brand inertia or the willingness to move to another brand mobility the third characteristic captures the effect of repetitive consumption the long term effect on inertia and mobility the fourth characteristic incorporates the similarity or dissimilarity of choice alternatives this is important in a dynamic model because choice on the current purchase occasion can be affected by whether a similar or dissimilar alternative was chosen on the previous occasion similarities of alternatives are represented in terms of distances the effect of price on choice behavior is also modeled individual level purchase data from a consumer panel are used to estimate a covariance probit and an independent probit specification of the model from a substantive perspective the model gives interesting insights into the dynamics of choice behavior the model predicts switches better than a benchmark model which incorporates only loyalty in addition it is superior to three benchmark models in overall predictive ability