Multiple-Constraint Choice Models with Corner and Interior Solutions

Satomura, Takuya; Kim, Jaehwan; Allenby, Greg M.

doi:10.1287/mksc.1110.0636

Cited by 60 publications

(19 citation statements)

References 17 publications

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“…The basic approach starts with Wales and Woodland (1983), who outline the derivation of demand from the KKT conditions associated with the maximization of a direct utility function, allowing for binding nonnegativity constraints and corner solutions. Variants and extensions of the model include Kim et al (2002Kim et al ( , 2007, Bhat (2008), Lee et al (2010), and Satomura et al (2011). The model has proven successful in 9 Homothetic preferences imply that utility can be produced from consumption according to a constant returns-to-scale technology; i.e., doubling consumption of all goods doubles utility.…”

Section: Direct Utility Approachmentioning

confidence: 99%

Structural Workshop Paper—Discrete-Choice Models of Consumer Demand in Marketing

Chintagunta

Nair

2011

Marketing Science

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M arketing researchers have used models of consumer demand to forecast future sales, to describe and test theories of behavior, and to measure the response to marketing interventions. The basic framework typically starts from microfoundations of expected utility theory to obtain an econometric system that describes consumers' choices over available options, and to thus characterize product demand. The basic framework has been augmented significantly to account for quantity choices, to accommodate purchases of several products on a single purchase occasion (multiple discreteness and multicategory purchases), and to allow for asymmetric switching between brands across different price tiers. These extensions have enabled researchers to bring the analysis to bear on several related marketing phenomena of interest. This paper has three main objectives. The first objective is to articulate the main goals of demand analysis-forecasting, measurement, and testing-and to highlight several considerations associated with these goals. Our second objective is to describe the main building blocks of individual-level demand models. We discuss approaches built on direct and indirect utility specifications of demand systems, and we review extensions that have appeared in the marketing literature. The third objective is to explore a few emerging directions in demand analysis, including considering demand-side dynamics, combining purchase data with primary information, and using semiparametric and nonparametric approaches. We hope researchers new to this literature will take away a broader perspective on these models and see the potential for new directions in future research.

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Section: Direct Utility Approachmentioning

confidence: 99%

Structural Workshop Paper—Discrete-Choice Models of Consumer Demand in Marketing

Chintagunta

Nair

2011

Marketing Science

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“…Work is also needed on utility functions that can represent complementarity at the product category level while retaining the additive separable assumption for brands within each category. Dotson and Allenby (2010) and Satomura et al (2011) expand the analysis of models of goal-directed behavior to include aspects of the budget constraint. Alternative constraint specifications are studied by Dotson and Allenby (2010) that imply different locations of managerial control of budgets in a study of consumer satisfaction on firm financial performance.…”

Section: Extensionsmentioning

confidence: 99%

“…Alternative constraint specifications are studied by Dotson and Allenby (2010) that imply different locations of managerial control of budgets in a study of consumer satisfaction on firm financial performance. A direct utility model with multiple binding constraints is developed by Satomura et al (2011) to reflect choices that are more constraint-influenced than in models with only a budgetary constraint present.…”

Section: Extensionsmentioning

confidence: 99%

Modeling marketplace behavior

Allenby

2011

J. of the Acad. Mark. Sci.

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Marketplace behavior refers to aspects of the purchase behavior of individuals and firms that leads to marketplace demand. It is characterized by the presence of many variables, most of which have nothing to do with a specific venture or specific consumer. This paper discusses three challenges of analysis commonly found in quantitative models of marketplace data: heterogeneous consumers, goal-directed behaviors, and the selective attention to some but not all variables in extended models of behavior. Bayesian solutions to these challenges are discussed.

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“…At the same time that spatial considerations are receiving widespread attention in the discrete choice literature, multiple discrete‐continuous (MDC) models have also seen substantial application in different disciplines, including regional science (Kaza, Towe, and Ye, ), transportation (Bhat, , ; Bhat, Castro, and Khan, ), time use (Habib and Miller, ; Pinjari and Bhat, ), marketing and retailing (Kim, Allenby, and Rossi, ; Allenby, Garratt, and Rossi, ; Satomura, Kim, and Allenby, ), energy economics (Ahn, Jeong, and Kim, ), environmental economics (see von Haefen, Phaneuf, and Parsons, ; Kuriyama, Hanemann, and Hilger, ), and tourism (LaMondia, Bhat, and Hensher, ; Van Nostrand, Sivaraman, and Pinjari, ). In MDC situations, consumers may consume multiple alternatives at the same time, with a continuous dimension of the amount of consumption associated with each alternative.…”

Section: Introductionmentioning

confidence: 99%

A New Spatial Multiple Discrete‐continuous Modeling Approach to Land Use Change Analysis

Bhat

Dubey

Alam

et al. 2015

Journal of Regional Science

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This paper formulates a multiple discrete-continuous probit (MDCP) land-use model within a spatially explicit economic structural framework for land-use change decisions. The spatial MDCP model is capable of predicting both the type and intensity of urban development patterns over large geographic areas, while also explicitly acknowledging geographic proximity-based spatial dependencies in these patterns. At a methodological level, the paper focuses on specifying and estimating a spatial MDCP model that allows the dependent variable to exist in multiple discrete states with an intensity associated with each discrete state. The formulation also accommodates spatial dependencies, as well as spatial heterogeneity and heteroscedasticity, in the dependent variable, and should be applicable in a wide variety of fields where social and spatial dependencies between decision agents (or observation units) lead to spillover effects in multiple discrete-continuous choices (or states). A simulation exercise is undertaken to evaluate the ability of the proposed maximum approximate composite marginal likelihood (MACML) approach to recover parameters from a cross-sectional spatial MDCP model. The results show that the MACML approach does well in recovering parameters. An empirical demonstration of the approach is undertaken using the city of Austin parcel level land use data.

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Multiple-Constraint Choice Models with Corner and Interior Solutions

Cited by 60 publications

References 17 publications

Structural Workshop Paper—Discrete-Choice Models of Consumer Demand in Marketing

Structural Workshop Paper—Discrete-Choice Models of Consumer Demand in Marketing

Modeling marketplace behavior

A New Spatial Multiple Discrete‐continuous Modeling Approach to Land Use Change Analysis

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