Manish Gangwar is an Assistant Professor of marketing at the ISB. His research interest primarily lies in exploring marketing issues using quantitative models. In the past, he researched safety incentive programmes and the relationship between equipment technology and wages in US construction industry. His teaching at the ISB includes courses on new product management and pricing strategies.
An empirical examination of the pricing policies of brands in several categories reveals that the pricing distribution is multi-modal with firms offering shallow and deep discounts with varying frequencies. Another interesting feature of these pricing distributions is that they have several modes which sometimes are in the interior of the support. However, much of the extant theory on price promotions predicts that the equilibrium pricing density would be bi-modal and that the modes are at the ends of the support of the distribution. In this study, we develop a dynamic game-theoretic model which allows inter-temporal shifts in demand due to some consumers’ stockpiling during deep discounts periods. This threshold below which consumers engage in stockpiling is endogenously determined. We examine how such behavior affects firms’ pricing strategy in a setting where firms and consumers interact repeatedly over an infinite horizon. The pricing distributions predicted by our theory are remarkably consistent with the pricing patterns observed in practice. Interestingly, we find that in equilibrium, the more the consumers are willing to stockpile, the deeper the discounts are required to stockpile. The model allows us to generate interesting insights on the optimal promotional strategies of firms and its interplay with the clientele mix, market structure and other market factors.
The literature on grocery store loyalty views a consumer as possessing store loyalty
toward a particular store for her or his overall shopping needs. In this study, we argue that store
loyalty can be viewed as a category-specific trait, i.e., a consumer could be loyal to Store A in
category 1, but loyal to Store B in category 2. We call this store-category loyalty. With the
presence of store-category loyalty, we further argue that retailers should focus on consumers’
store preferences in individual categories to improve overall store loyalty and revenues. We use
an in-home scanning panel dataset that tracks 1321 households in 284 grocery categories across
16 retail chains over a 53-week period. The data first suggest little overall store loyalty, based on
the traditional view; however, once the category dimension is added, extensive store loyalty at
the category level is uncovered. In order to more carefully examine households’ store-category
loyalty, we propose a modified market share attraction model (Cooper and Nakanishi 1988). By
examining household purchases in multiple stores and multiple categories simultaneously, we are
able to estimate the heterogeneous effects of merchandising programs on household storecategory
loyalty, as well as the heterogeneous intrinsic store category attractions, across
categories and across households. We illustrate how the estimation results from the proposed
model can be used to help retailers improve overall store loyalty and store revenues.
Over 90% of wireless mobile subscribers in emerging wireless markets such as India
employ pay-as-you-go prepaid plans. In contrast, over 90% of subscribers in mature mar-
kets such as the US pick postpaid plans with long-term contracts. Indian wireless rms
fret about this because prepaid consumers generally have low loyalty and generate lower
average revenue per unit than postpaid consumers. However, the outcome is not surprising,
considering the pricing strategies employed in the two markets. Postpaid plans in India are
quite unattractive relative to prepaid plans, do not exhibit quantity discounts, and do not
encourage consumers towards higher-level tiers, unlike the US where postpaid plans oer
a much lower per-unit rate, feature aggressive quantity discounts, and impose such a high
penalty for above-allowance consumption that consumers tend to move towards higher-tier
plans. Why then do rms in India embed these characteristics into their pricing strategies?
We identify puzzling characteristics in the Indian market, develop an innovative model that
explains the pricing strategies employed in India, and propose evolutionary steps for wireless
rms to adapt their strategies as the market matures. We show that the pricing plans are
driven by rms' desire to compensate for xed costs of oering postpaid plans, and a focus
on instantaneous prot margins. Reversing the outcome will require shifting the focus to
lifetime revenues from customers, and a willingness to oer postpaid plans to customers
whose account size does not, at the time, justify incurring the additional xed cost of
Promotions induced sales increase often comes at the expense of competitors' sales; these sales come from consumers who have relatively weak brand preferences. Increased sales from consumers with strong brand preferences are more likely to occur at the expense of the promoted brand. In other words, brand loyal consumers take advantage of promotions to stockpile for future consumption. What is the effect of such stockpiling induced increase in sales by loyal consumers and firms’ price promotions taken together? To answer this question we model a duopoly competing for loyal and switching consumers.
It is well known that the competition for switchers results in promotions. We innovate by considering brand loyal consumers who stockpile opportunistically for future consumption when they encounter a sufficiently low price. In our model, strategic consumers derive optimal stockpiling rule based on firms’ promotion strategies and firms take these stockpiling rule explicitly into account in determining their equilibrium strategies.
We find that in the categories where consumption is constant, stockpiling by loyal consumers reduces firms’ profits. We provide an upper bound on the loss due to stockpiling and argue that it amounts to a relatively small percentage of profit. Furthermore, we show that in categories where stockpiling can induce higher consumption, firms’ can benefit from stockpiling. Nonetheless, only if consumers are patient enough, so that they always stockpile for future and perpetually maintain higher inventories and at the same time yield to the temptation of consuming more after stockpiling.
Though celebrity endorsements have long been used in advertisements, celebrity endorsements
are more prominent in some emerging markets such as China, Korea, India, and Latin America
than developed countries such as the United States and United Kingdom. Why are celebrity
endorsements more popular in emerging markets than developed countries? This research
examines whether the effectiveness of celebrity endorsers is consistent across cultures.
Specifically, power distance, a cultural orientation regarding the extent to which one expects and
accepts differences in power, is proposed to moderate the effect of celebrity endorsements on
advertisement evaluations. We theorize that celebrity endorsers should more positively influence
advertisement evaluations in countries with higher power distance because power distance varies
positively with consumers’ perceived source credibility (i.e., expertise, trustworthiness, and
attractiveness). To test our hypotheses we develop a mediated-moderation regression model that
we estimate using Markov chain Monte Carlo methods that enable the calculation of standard
errors for the mediated-moderation regression coefficients in a straight forward manner and
allow us to correct for endogeneity of the mediator (source credibility) using latent instrumental
variables. The results from analysis of data from a two country (India and United States)
experiment provide support for mediated-moderation and suggest that power distance does
explain the popularity of celebrity endorsements in emerging markets and that this moderating
effect of power distance is mediated by perceptions of source credibility.