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Shopping or buying with a mobile device (M-shopping henceforth) has become an increasingly important topic that has drawn much attention in both industry and academia. Forrester Research (Husson 2014) predicts that media companies and... more
Shopping or buying with a mobile device (M-shopping henceforth) has become an increasingly important topic that has drawn much attention in both industry and academia. Forrester Research (Husson 2014) predicts that media companies and retailers receive more than 50 % of online traffic from mobile devices. M-shopping is also expected to grow substantially compared to the rest of the retail space. Deloitte Consulting (2012) predicts that $31 billion worth of retail revenues will be transacted using mobile devices by 2016. While the overall retail revenue annual growth rate is forecasted at 4 % for 2015 through 2016, mobile commerce is estimated to grow at 21 %–29 % (Mulpuru et al. 2013). The growth in M-shopping provides ample potential for marketers and advertisers to leverage the channel. Using a unique dataset from an Internet-based firm, we are able to compare customers’ behavior based on whether they use mobile devices, i.e., smartphones, tablets, and/or personal computers (PCs) when composing, modifying or placing orders online. We find that purchase probability and order size, i.e., the size of the order in dollars, increase as customers become accustomed to M-shopping. In addition to the cumulative effect, orders that are made with one or more mobile devices are more likely to lead to shorter times-to-next-order than PC-only orders. However, not all mobile orders are the same. Orders made with two or more device types are larger than those that are made with only a single device, e.g., smartphone-only orders. Orders made with all three device types, i.e., smartphones, tablets and PCs, are the largest. We propose that customers utilize mobile devices because the technology provides ubiquitous convenience, which leads them to incorporate M-shopping into their habitual routines. Managerially, we recommend that firms should not only promote their mobile platforms, but also encourage their customers to engage through multiple devices, including PCs. Firms can increase their customers’ spending by leveraging anytime, anywhere access and customer engagement via multiple devices.
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Pricing drives three of the most important elements of firm success: revenue and profits, customer behavior and firm image. This book provides an introduction to the basic principles for thinking clearly about pricing. Unlike other... more
Pricing drives three of the most important elements of firm success: revenue and profits, customer behavior and firm image. This book provides an introduction to the basic principles for thinking clearly about pricing. Unlike other marketing books on pricing, the authors use a more analytic approach and relate ideas to the basic principles of microeconomics. Rakesh Vohra and Lakshman Krishnamurthi also cover three areas in greater depth and provide more insight than may be gleaned from existing books: 1) the use of auctions, 2) price discrimination and 3) pricing in a competitive environment.
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A new chi-square test is proposed to assess significance of attributes for nonparametric conjoint models. The key idea is to form subsets of rankings and test the dependence between the attribute levels and the sets of rankings. The null... more
A new chi-square test is proposed to assess significance of attributes for nonparametric conjoint models. The key idea is to form subsets of rankings and test the dependence between the attribute levels and the sets of rankings. The null hypothesis ...
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A trend reported by both academics and practitioners is that advertising on TV has become increasingly energetic. This study investigates the association between the energy level in ad content and consumers' tendency of ad-watching or... more
A trend reported by both academics and practitioners is that advertising on TV has become increasingly energetic. This study investigates the association between the energy level in ad content and consumers' tendency of ad-watching or ad-avoidance. Using a data set of over 27,000 TV commercials delivered to U.S. homes during the period between 2015 and 2018, the authors first present a framework to algorithmically measure the energy level in ad content from the video of ads. This algorithm-based measure is then compared to the human-perceived energy levels, where the results suggest that the measure can serve as a proxy for the level of arousal stimulated by ad content. By relating the energy levels in ad content with the tendency of ad-watching using two empirical approaches, the authors document the following. Overall, more energetic commercials are likely to be watched more or avoided less by viewers. The positive association between energy levels in ad content and ad-watching is statistically significant after controlling for placement and other aspects of commercials. However, the association varies across product categories and program genres. The authors discuss these results and their<br>implications for advertisers.
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Hill and Cartwright examined the relative performance of ordinary least squares, the Equity estimator, and the Stein estimator on four scanner data sets. Based on this limited simulation, they claimed that the Stein estimator is an... more
Hill and Cartwright examined the relative performance of ordinary least squares, the Equity estimator, and the Stein estimator on four scanner data sets. Based on this limited simulation, they claimed that the Stein estimator is an attractive alternative to the Equity ...
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... One method of introducing information is through the use of constraints on the parameters.&amp;#x27; Constraints may be either a priori or sample derived. ... Another method of introducing information is through the use of... more
... One method of introducing information is through the use of constraints on the parameters.&amp;#x27; Constraints may be either a priori or sample derived. ... Another method of introducing information is through the use of additional parameters such as those in the Ridge estimator. ...
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DESCRIPTION We investigate how adoption of a retailer’s factory outlet channel impacts customers’ spending in the retailer’s traditional retail store channel. We find that although customers who adopt the outlet channel spend less with... more
DESCRIPTION We investigate how adoption of a retailer’s factory outlet channel impacts customers’ spending in the retailer’s traditional retail store channel. We find that although customers who adopt the outlet channel spend less with the retailer compared to store-only customers, the difference cannot be attributed to the impact of adoption of the outlet channel. After controlling for heterogeneity and selection effects, we uncover a positive spillover to the retail store channel from adoption of the outlet channel. Customers who adopt the outlet channel not only make incremental purchases at the outlet channel but also increase their spending in the retail store channel after adoption. The increase in spending is due to more frequent store purchases and not due to larger per purchase expenditure.
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DESCRIPTION We investigate how adoption of a retailer’s factory outlet channel impacts customers’ spending in the retailer’s traditional retail store channel. We find that although customers who adopt the outlet channel spend less with... more
DESCRIPTION We investigate how adoption of a retailer’s factory outlet channel impacts customers’ spending in the retailer’s traditional retail store channel. We find that although customers who adopt the outlet channel spend less with the retailer compared to store-only customers, the difference cannot be attributed to the impact of adoption of the outlet channel. After controlling for heterogeneity and selection effects, we uncover a positive spillover to the retail store channel from adoption of the outlet channel. Customers who adopt the outlet channel not only make incremental purchases at the outlet channel but also increase their spending in the retail store channel after adoption. The increase in spending is due to more frequent store purchases and not due to larger per purchase expenditure.
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ABSTRACT
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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.... more
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
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... One method of introducing information is through the use of constraints on the parameters.&amp;#x27; Constraints may be either a priori or sample derived. ... Another method of introducing information is through the use of... more
... One method of introducing information is through the use of constraints on the parameters.&amp;#x27; Constraints may be either a priori or sample derived. ... Another method of introducing information is through the use of additional parameters such as those in the Ridge estimator. ...
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Page 1. MARKETING SCIENCE Vol. 7, No. 1, Winter 1988 Printed in USA A MODEL OF BRAND CHOICE AND PURCHASE QUANTITY PRICE SENSITIVITIES LAKSHMAN KRISHNAMURTHI AND SP RAJ Northwestern University ...
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The authors use a simulation that explores the same factors used by Wildt (1993), but provides results that refute several of the findings reported in that study. The authors maintain that, under conditions of multi-collinearity, the... more
The authors use a simulation that explores the same factors used by Wildt (1993), but provides results that refute several of the findings reported in that study. The authors maintain that, under conditions of multi-collinearity, the Equity estimator provides estimates that are typically closer to the true parameters than the ordinary least squares and Ridge estimates.
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... Consumer psychologists have theoized diffetent models of the effect of advertising which provide a pertinent background for our study. As reviewed by Ray (1973), advertising can have either an attitude-behavior path or a... more
... Consumer psychologists have theoized diffetent models of the effect of advertising which provide a pertinent background for our study. As reviewed by Ray (1973), advertising can have either an attitude-behavior path or a behavior-attitude path (first suggested by Krugman 1965 ...
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In this article, the authors examine how the stage of product life cycle in which a brand enters affects its sales through brand growth and mar-ket response, after controlling for the order-of-entry effect and time in market. The authors... more
In this article, the authors examine how the stage of product life cycle in which a brand enters affects its sales through brand growth and mar-ket response, after controlling for the order-of-entry effect and time in market. The authors develop a dynamic brand sales ...
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... Carmone, Frank J., Green, Paul E., and Jain, Arun K. (1978), "The Robustness of Conjoint Analysis: Some Monte Carlo Results," Journal of Marketing Research,- 15, 300-3. Currim, Imran S., Weinberg, Charles B., and Wittink,... more
... Carmone, Frank J., Green, Paul E., and Jain, Arun K. (1978), "The Robustness of Conjoint Analysis: Some Monte Carlo Results," Journal of Marketing Research,- 15, 300-3. Currim, Imran S., Weinberg, Charles B., and Wittink, Dick R. (1981), "The Design of Subscription ...
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ABSTRACT
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Hill and Cartwright examined the relative performance of ordinary least squares, the Equity estimator, and the Stein estimator on four scanner data sets. Based on this limited simulation, they claimed that the Stein estimator is an... more
Hill and Cartwright examined the relative performance of ordinary least squares, the Equity estimator, and the Stein estimator on four scanner data sets. Based on this limited simulation, they claimed that the Stein estimator is an attractive alternative to the Equity ...
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... Hays, William L., 1973. Statistics for the social sciences. New York: Hold, Rinehart and Winston. Jain, Arun K., Franklin Acito, Naresh K. Malhotra and Vijay Mahajan, 1979. ... Journal of Marketing Research 16 (August), 313322.... more
... Hays, William L., 1973. Statistics for the social sciences. New York: Hold, Rinehart and Winston. Jain, Arun K., Franklin Acito, Naresh K. Malhotra and Vijay Mahajan, 1979. ... Journal of Marketing Research 16 (August), 313322. Krishnamurthi, Lakshman, 1983. ...