35 research outputs found

    Parameter Bias from Unobserved Effects in the Multinomial Logit Model of Consumer Choice

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    Over the past two decades, validation of choice models has focused on predictive validity rather than parameter bias. In real-world validation of choice models, true parameter values are unknown, so examination of parameter bias is not possible. In contrast, the main focus of this study is parameter bias in simulated scanner-panel choice data with known parameter values. Study of parameter bias enables the assessment of a fundamental issue not addressed in the choice modeling literature-the extent to which the logit choice model is capable of distinguishing unobserved effects that give rise to persistence in observed choices (e.g., heterogeneity and state dependence). Although econometric theory provides some information about the causes of bias, the extent of such bias in typical scanner data applications remains unclear. The authors present an extensive simulation study that provides information on the extent of bias resulting from the misspecification of four unobserved effects that receive frequent attention in the literature-choice set effects, heterogeneity in preferences and market response, state dependence, and serial correlation. The authors outline implications for model builders and managers. In general, the potential for parameter bias in choice model applications appears to be high. Overall, a logit model with choice set effects and the Guadagni-Little loyalty variable produces the most valid parameter estimates

    Commitment to marketing spending through recessions

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    When does metric use matter less?

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    A Taxonomy of Consumer Purchase Strategies in a Promotion Intensive Environment

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    This paper proposes a taxonomy of consumer purchase strategies based on household decisions about which brand to purchase, how much, and when to purchase in a promotion intensive environment. We infer decision rules at the household level from supermarket scanner panel data and then cluster the inferred choice routes in order to discover the major purchasing strategies used in our population of interest. Subsequently, we test for the distribution of these purchase strategies in our customer population. Results add to our knowledge of consumer behavior in response to promotions.promotion, consumer choice models, artificial intelligence, concept learning system

    Commitment to marketing spending through recessions Better or worse stock market returns?

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    Purpose - This paper aims to address two unique and important questions. First, how do recessions directly affect firms' marketing spending decisions? Second, and more importantly, do firms which are more committed to marketing spending through past recessions achieve better stock market returns? Design/methodology/approach - This study is based on a combination of National Bureau of Economic Research, COMPUSTAT and Center for Research in Security Prices data on 6,000 firms between 1982 and 2009 which are analyzed using panel data-based regression models. Findings - The authors find that firms cut marketing spending during recessions. However, firms committed to marketing spending during past recessions achieve better stock market returns. The findings are found to be robust across B2B and B2C industries, different periods and US firms which vary on the proportion of their global revenue from non-US sales. Research limitations/implications - Top executives cut marketing budgets during recessions; however, if they can resist the pressures, and strategically continue to make marketing investments during recessions, they will achieve higher stock market returns. Originality/value - This is the first paper to establish the longer-term (not short-term) positive stock market performance of continuous (not episodic) marketing spending through past recessions, i.e. the view that marketing spending is necessary (not discretionary) for stock returns
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