To increase marketing's accountability, Journal of Marketing, Marketing Science Institute, and the Institute for the Study of Business Markets have advocated development of marketing metrics and linking marketing-mix activities with financial metrics. Although the marketing field has made progress, researchers have paid less attention to what drives managerial use of marketing and financial metrics and whether metric use is associated with marketing-mix performance. The authors propose a conceptual model that links firm strategy, metric orientation, type of marketing-mix activity, and managerial, firm, and environmental characteristics to marketing and financial metric use, which in turn are linked to performance of marketing-mix activities. An analysis of 1287 marketing-mix activities reported by 439 U.S. managers reveals that firm strategy, metric orientation, type of marketing-mix activity, and firm and environmental characteristics are more useful than managerial characteristics in explaining use of marketing and financial metrics and that use of metrics is positively associated with marketing-mix performance. The results help identify conditions under which managers use fewer metrics and how metric use can be increased to improve marketing-mix performance.

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Research on metrics is consistently designated a priority by academics and practitioners. However, less is known about how culture and cross-national differences can potentially impact metric use, which is theoretically and managerially limiting. This work develops a model that examines national and organizational cultural antecedents while controlling for the decision setting. Testing the model on data collected from 4,384 managerial decisions from 1,637 firms in 16 countries, reveals both levels of culture are associated with metric use but each has varying effects. Our results enable multinational executives to better understand and increase managerial metric use across different cultures and settings.

Purpose -In an effort towards building a contingent theory of drivers and consequences of managerial metric use in marketing mix decisions, this paper develops a conceptual framework to test whether the relationship between metric use and marketing mix performance is moderated by firm and managerial characteristics.• Design/methodology/approach -Based on (i) reviews of the marketing, finance, management, and accounting literatures and homophily, firm resource based, and decision maker based theories, and (ii) 22 managerial interviews, a conceptual model is proposed. It is tested via generalized least squares -seemingly unrelated regression estimation of 1,287 managerial decisions.• Findings -Results suggest the impact of metric use on marketing mix performance is lower in firms which are more market oriented, larger, and with worse recent business performance; and for marketing and higher level managers; while organizational involvement has a lesser nuanced effect.• Research limitations/implications -While much is written on the importance of metric use to improve performance, this work is a first step towards understanding which settings are more difficult than others to accomplish this.• Practical implications -Results allow identification of several conditional managerial strategies to improve marketing mix performance based on metric use.• Originality/value -This paper contributes to the metric literature since prior research has (i) paid little attention to understanding the relationship between managerial metric use and performance of the marketing mix decision and (ii) not considered how the relationship is moderated by firm and managerial characteristics.

T he information processing literature provides a wealth of laboratory evidence on the effects that the choice task and individual characteristics have on the extent to which consumers engage in alternative-based versus attribute-based information processing. Less attention has been paid to studying how the processing pattern at the point of purchase is associated with a consumer's propensity to buy in shopping settings. To understand this relationship, we formulate a discrete choice model and perform formal model comparisons to distinguish among several possible dependence structures. We consider models involving an existing measure of information processing, PATTERN; a latent variable version of this measure; and several new refinements and generalizations. Analysis of a unique data set of 895 shoppers on a popular electronics website supports the latent variable specification and provides validation for several hypotheses and modeling components. We find a positive relationship between alternative-based processing and purchase, as well as a tendency of shoppers in the lower price category to engage in alternative-based processing. The results also support the case for joint modeling and estimation. These findings can be useful for future work in information processing and suggest that likely buyers can be identified while engaged in information processing prior to purchase commitment, an important first step in targeting decisions.