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The Recoverability of Segmentation Structure from Store-Level Aggregate Data
16 references·14 citing·41 second hop
The Recoverability of Segmentation Structure from Store-Level Aggregate Data (2004)The Recoverability of Segmentation Struct…Competitive Price Discrimination Strategies in a Vertical Channel Using Aggregate Retail Data (2003)Competitive Price Discriminat…Endogeneity and Heterogeneity in a Probit Demand Model: Estimation Using Aggregate Data (2001)Endogeneity and Heterogeneity…Mixed MNL models for discrete response (2000)Mixed MNL models for discrete…Investigating Household State Dependence Effects across Categories (1999)Investigating Household State…Commercial Use of UPC Scanner Data: Industry and Academic Perspectives (1999)Commercial Use of UPC Scanner…Determining Segmentation in Sales Response across Consumer Purchase Behaviors (1998)Determining Segmentation in S…Principles of Statistical Inference from a Neo-Fisherian Perspective (1997)Principles of Statistical Inf…Do Household Scanner Data Provide Representative Inferences from Brand Choices: A Comparison with Store Data (1996)Do Household Scanner Data Pro…Understanding Brand Competition Using Micro and Macro Scanner Data (1994)Understanding Brand Competiti…On Using Demographic Variables to Determine Segment Membership in Logit Mixture Models (1994)On Using Demographic Variable…Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households (1993)Investigating Purchase Incide…Brand Choice, Purchase Incidence, and Segmentation: An Integrated Modeling Approach (1992)Brand Choice, Purchase Incide…Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data (1991)Investigating Heterogeneity i…A Simultaneous Approach to the Whether, What and How Much to Buy Questions (1991)A Simultaneous Approach to th…A Probabilistic Choice Model for Market Segmentation and Elasticity Structure (1989)A Probabilistic Choice Model …Impact of Sales Promotions on When, What, and How Much to Buy (1988)Impact of Sales Promotions on…Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing (2019)Addressing endogeneity in agg…Sales Promotion Models (2017)Sales Promotion ModelsValuing Subscription-Based Businesses Using Publicly Disclosed Customer Data (2016)Valuing Subscription-Based Bu…Pricing strategy & practice (2015)Pricing strategy & practiceA computationally fast estimator for random coefficients logit demand models using aggregate data (2015)A computationally fast estima…Using graphical statistics to better understand market segmentation solutions (2014)Using graphical statistics to…Diagnosing Brand Performance: Accounting for the Dynamic Impact of Product Availability with Aggregate Data (2014)Diagnosing Brand Performance:…Modeling Credit Card Share of Wallet: Solving the Incomplete Information Problem (2012)Modeling Credit Card Share of…A Latent Class Nested Logit Model of Intercity Bus Carrier Choice (2011)A Latent Class Nested Logit M…A Comparison of Sales Response Predictions From Demand Models Applied to Store-Level versus Panel Data (2010)A Comparison of Sales Respons…Brand morphing across Wal-Mart customer segments (2009)Brand morphing across Wal-Mar…Using store level scanner data to improve category management decisions: Developing positioning maps (2008)Using store level scanner dat…Latent segmentation using store‐level scanner data (2008)Latent segmentation using sto…Estimating Demand Heterogeneity Using Aggregated Data: An Application to the Frozen Pizza Category (2008)Estimating Demand Heterogenei…A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Customer Switching Behavior in Service Industries: An Exploratory Study (1995)Adoption of Internet banking by Australian consumers: an empirical investigation (1999)Pursuing the Value-Conscious Consumer: Store Brands versus National Brand Promotions (2001)Limited-dependent and qualitative variables in econometrics (1983)Discrete Choice Analysis (1985)Is 75% of the Sales Promotion Bump Due to Brand Switching? No, Only 33% Is (2003)Business Model Innovation Performance: When does Adding a New Business Model Benefit an Incumbent? (2015)Retail forecasting: Research and practice (2019)The World of Goods (1982)Advances in Consumer Research (1983)An Empirical Investigation of the Spillover Effects of Advertising and Sales Promotions in Umbrella Branding (2002)Modeling Multiple Sources of State Dependence in Random Utility Models: A Distributed Lag Approach (2004)Do Switching Costs Make Markets Less Competitive? (2009)Conditional logit analysis of qualitative choice behavior (1972)Econometric Models for Count Data with an Application to the Patents-R & D Relationship (1984)Success in High-Technology Markets: Is Marketing Capability Critical? (1999)Analysis of Panel Data (2003)Modeling the Clickstream: Implications for Web-Based Advertising Efforts (2003)Academic collaborations and firm innovation performance in China: The role of region-specific institutions (2014)Empirical research on nominal exchange rates (1995)Measuring Market Power in the Ready-to-Eat Cereal Industry (1998)A latent class model for discrete choice analysis: contrasts with mixed logit (2003)The Mixed Logit model: The state of practice (2003)MODELING THE CHOICE OF RESIDENTIAL LOCATION (1978)Economics and Consumer Behavior (1980)Specification Tests for the Multinomial Logit Model (1984)Modeling Consumer Demand for Variety (2002)A multiple discrete–continuous extreme value model: formulation and application to discretionary time-use decisions (2004)The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions (2007)Latent Structure Analysis. (1969)Issues and Advances in Segmentation Research (1978)International market segmentation: issues and perspectives (2002)Consumer Shopping and Spending across Retail Formats (2004)The theory and practice of econometrics (1986)The Role of the Scale Parameter in the Estimation and Comparison of Multinomial Logit Models (1993)Discrete Choice Methods with Simulation (2001)Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach (2002)Consumer price sensitivity and price thresholds14 14Sangman Han is Associate Professor, School of Business Administration Sungkyunkwan University, 53 3-ga, Myongnyun-dong, Chongno-gu, Seoul (phone: 82-2-760-0456, email: smhan@yurim.skku.ac.kr). Sunil Gupta is Meyer Feldberg Professor of Business (phone: 212-854-3467, email: sg37@columbia.edu) and Donald R. Lehmann is George E. Warren Professor (phone: 212-854-3465, email: drl2@columbia.edu), both at the Graduate School of Business, Columbia University, New York, NY 10027. All correspondence should be directed to Sunil Gupta. (2001)The Effectiveness of Customized Promotions in Online and Offline Stores (2009)Estimating Primary Demand for Substitutable Products from Sales Transaction Data (2012)
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References

  • 2000Mixed MNL models for discrete response4,354 cited
  • 1989A Probabilistic Choice Model for Market Segmentation and Elasticity Structure1,348 cited
  • 1988Impact of Sales Promotions on When, What, and How Much to Buy1,052 cited
  • 1994On Using Demographic Variables to Determine Segment Membership in Logit Mixture Models385 cited
  • 1993Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households347 cited
  • 1992Brand Choice, Purchase Incidence, and Segmentation: An Integrated Modeling Approach336 cited
  • 1991Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data305 cited
  • 1999Investigating Household State Dependence Effects across Categories268 cited
  • 1991A Simultaneous Approach to the Whether, What and How Much to Buy Questions261 cited
  • 1998Determining Segmentation in Sales Response across Consumer Purchase Behaviors232 cited
  • 1999Commercial Use of UPC Scanner Data: Industry and Academic Perspectives207 cited
  • 2003Competitive Price Discrimination Strategies in a Vertical Channel Using Aggregate Retail Data190 cited
  • 1997Principles of Statistical Inference from a Neo-Fisherian Perspective156 cited
  • 1996Do Household Scanner Data Provide Representative Inferences from Brand Choices: A Comparison with Store Data107 cited

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  • 2001Endogeneity and Heterogeneity in a Probit Demand Model: Estimation Using Aggregate Data105 cited
  • 1994Understanding Brand Competition Using Micro and Macro Scanner Data91 cited
  • Cited by

    • 2016Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data117 cited
    • 2008Estimating Demand Heterogeneity Using Aggregated Data: An Application to the Frozen Pizza Category50 cited
    • 2017Sales Promotion Models39 cited
    • 2015Pricing strategy & practice36 cited
    • 2015A computationally fast estimator for random coefficients logit demand models using aggregate data35 cited
    • 2014Using graphical statistics to better understand market segmentation solutions32 cited
    • 2012Modeling Credit Card Share of Wallet: Solving the Incomplete Information Problem32 cited
    • 2009Brand morphing across Wal-Mart customer segments25 cited
    • 2014Diagnosing Brand Performance: Accounting for the Dynamic Impact of Product Availability with Aggregate Data24 cited
    • 2010A Comparison of Sales Response Predictions From Demand Models Applied to Store-Level versus Panel Data21 cited
    • 2008Latent segmentation using store‐level scanner data12 cited
    • 2008Using store level scanner data to improve category management decisions: Developing positioning maps8 cited
    • 2019Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing8 cited
    • 2011A Latent Class Nested Logit Model of Intercity Bus Carrier Choice6 cited