• The Advantages of Entry in the Growth Stage of the Product Life Cycle: An Empirical Analysis


    by Venkatesh Shankar, Gregory S. Carpenter, and Lakshman Krishnamurthi

    This article was published in Journal of Marketing Research, 36 (May 2009), 269-276.

    Empirical research on sequential brand entry shows market share advantages for pioneers arising from a direct impact of order or timing of entry on market share and indirect effects of order of entry on a brand’s market response.  Analyses demonstrating these effects implicitly assume that a brand’s diffusion and market response parameters are independent of the stage of the life cycle in which a brand enters.  In this paper, we examine how the stage of market life in which a brand enters affects its sales through brand growth and market response, after controlling for the order of entry effect and time-in-market.  We develop a dynamic brand sales model in which brand growth and market response parameters vary by stage of life cycle entry, i.e., by pioneers, growth-stage and mature-stage entrants.  We estimate the model using data on 29 brands from six pharmaceutical markets. Our results reveal advantages associated with entering during the growth stage.  Brands that enter in the growth stage of the product life cycle reach their asymptotic sales level faster than pioneers or mature-stage entrants, are not hurt by competitor diffusion, and enjoy a higher response to perceived product quality than pioneers and mature-stage entrants. We find that pioneers reach their asymptotic sales levels more slowly than later entrants, and pioneer’s sales, unlike later entrants’ sales, are hurt by competitor diffusion over time.  On the positive side for pioneers, buyers are most responsive to marketing spending by pioneers.  Mature-stage entrants are most disadvantaged; they grow more slowly than growth-stage entrants, have lower response to product quality than growth-stage entrants, and have the lowest response to marketing spending.  We outline the implications of these results.

  • Late Mover Advantage: How Innovative Late Entrants Outsell Pioneers


    by Venkatesh Shankar, Gregory S. Carpenter, and Lakshman Krishnamurthi

    This article was published in Journal of Marketing Research, 35 (February 1998), 54-70.

    Although pioneers outsell late movers in many markets, in some cases, innovative late entry has produced some remarkably successful brands that outsell pioneers.  The mechanisms through which innovative late movers outsell pioneers are unclear.  To identify these mechanisms, we develop a brand-level model in which brand sales are decomposed into trials and repeat purchases.  The model captures diffusion and marketing mix effects on brand trials and includes the differential impact of innovative and non-innovative competitors’ diffusion on these effects.  We develop hypotheses on how the diffusion and marketing mix parameters of the brands will differ by market entry strategy (pioneering, innovative late entry, and non-innovative late entry).  We test these hypotheses using data from 13 brands in two pharmaceutical product categories.  The results show that an innovative late mover can create a sustainable advantage by enjoying a higher market potential and a higher repeat purchase rate than either the pioneer or non-innovative late movers, by growing faster than the pioneer, by slowing the pioneer’s diffusion, and by reducing the pioneer’s marketing spending effectiveness.  Innovative late movers are asymmetrically advantaged in that their diffusion can hurt the sales of other brands, but their sales are not affected by competitors’ diffusion.  In contrast, non-innovative late movers face smaller potential markets, lower repeat rates and less marketing effectiveness compared to the pioneer.

  • An Empirical Analysis of Determinants of Retailer Pricing


    by Venkatesh Shankar and Ruth N. Bolton

    This article was published in Marketing Science, 23 (Winter 2004), 28-49.

    This paper empirically investigates the determinants of retailers’ pricing decisions with a focus on competitor factors. We classify the different types of pricing strategies based on four underlying dimensions.  These dimensions are price consistency, price-promotion intensity, price-promotion coordination, and relative brand price.  We develop and estimate a simultaneous equation model of how each of the underlying dimensions of retailers’ pricing strategies is influenced by variables representing the market, chain, store, category, brand, customer and competition. Our empirical analysis is based on optical scanner data that describe 1364 brand-store combinations from six categories of consumer packaged goods in fiveU.S.markets over a two year time period. The four underlying pricing dimensions are statistically related to: (1) competitor price and deal frequency (competitor factors), (2) storability and necessity (category factors), (3) chain positioning and size (chain factors), (4) store size and assortment (store factors), (5) brand preference and advertising (brand factors), and (6) own price and deal elasticities (customer factors).  Competitor factors explain the most variance in retailer pricing strategy, followed by category and chain factors.  Only in the cases of price-promotion coordination and relative brand price, do category and chain factors explain much variance in retailer pricing.  Store, brand and customer factors capture an insignificant proportion of explained variance in retailer pricing. These findings are useful to retailers in profiling alternative pricing strategies.  They can also help manufacturers make informed decisions about the levels of marketing support spending for their brands that are appropriate for different retailers.  We outline the managerial implications based on the results.

  • Network Effects and Competition: An Empirical Analysis of the Video Game Industry


    by Venkatesh Shankar and Barry L. Bayus

    This article was published in Strategic Management Journal, 24 (2003), 375-384.

    Building on the Resource-Based View of the firm, we advance the idea that a firm’s customer network can be a strategic asset. We suggest that network effects are a function of network size (i.e., installed customer base) and network strength (i.e., the marginal impact of a unit increase in network size on demand).  We empirically study these network effects in the 16-bit home video game industry in which the dominant competitors were Nintendo and Sega. In the spirit of the new empirical IO framework, we estimate a structural econometric model assuming the data are equilibrium outcomes of the best fitting non-cooperative game in price and advertising. After controlling for other effects, we find strong evidence that network effects are asymmetric between the competitors in the home video game industry. Specifically, we find that the firm with a smaller customer network (Nintendo) has higher network strength than the firm with the larger customer base (Sega).  Thus, our results provide a possible explanation for this situation in which the firm with a smaller customer network (Nintendo) was able to overtake the sales of a firm with a larger network size (Sega).


  • Mobile Marketing in the Retailing Environment: Current Insights and Future Research Avenues

    Shankar Venkatesh Hofacker Naik JIM 2010

    by Venkatesh Shankar, Alladi Venkatesh, Charles Hofacker, and Prasad Naik

    This article was published in the Journal of Interactive Marketing, 24 (2010), 111-120.

    Mobile marketing, which involves two- or multi-way communication and promotion of an offer between a firm and its customers using the mobile, a term that refers to the mobile medium, device, channel, or technology, is growing in importance in the retailing environment. It has the potential to change the paradigm of retailing from one based on consumers entering the retailing environment to retailers entering the consumer’s environment through anytime, anywhere mobile devices. We propose a conceptual framework that comprises three key entities, the consumer, the mobile, and the retailer. The framework addresses key related issues such as mobile consumer activities, mobile consumer segments, mobile adoption enablers and inhibitors, key mobile properties, key retailer mobile marketing activities and competition. We also address successful retailer mobile marketing strategies, identify the customer-related and organizational challenges on this topic, and outline future research scenarios and avenues related to these issues.

  • Innovations in Shopper Marketing: Current Insights and Future Research

    Shankar Inman Mantrala…JR 2011

    by Venkatesh Shankar, J. Jeffrey Inman, Murali Mantrala, Eileen Kelley, and Rozz Rizley

    This article was published in the Journal of Retailing, 87S (1, 2011), S29-S42.

    Shopper marketing refers to the planning and execution of all marketing activities that influence a shopper along, and beyond, the entire path-to-purchase, from the point at which the motivation to shop first emerges through to purchase, consumption, repurchase, and recommendation. The goal of shopper marketing is to enable a win-win-win solution for the shopper-retailer-manufacturer. Shopper marketing has emerged as a key managerial practice among manufacturers and retailers, who are eagerly embracing innovations in the different aspects of shopper marketing. We review current and potential innovations in shopper marketing. We identify the managerial challenges to achieving new win-win-win solutions among shoppers, manufacturers, and retailers in shopper marketing and outline future scenarios and research issues related to these challenges.

  • A Practical Guide to Combining Products and Services

    by Venkatesh Shankar, Leonard L. Berry, and Thomas Dotzel

    This article was published in the Harvard Business Review, November 2009.

    As companies look to the future, they will need to pay increasing attention to hybrid offerings (product and service bundles) if they want to increase their top and bottom lines. Hybrid offerings attract new customers and improve demand among existing customers by offering them superior value. They enable firms to broaden their customer base, boost their revenue and profit streams, and improve liquidity at low risk. Considering the rules of hybrid offerings can help executive identify successful hybrid offerings.

  • Mobile Marketing: A Synthesis and Prognosis

    Shankar Balasubramanian JIM 2009

    by Venkatesh Shankar and Sridhar Balasubramanian

    This article was published in the Journal of Interactive Marketing, 23 (2009), 118-129.

    Mobile marketing refers to the two- or multi-way communication and promotion of an offer between a firm and its customers using a mobile medium, device, or technology.  We present the conceptual underpinnings of mobile marketing and a synthesis of the relevant literature. We identify and discuss four key issues: drivers of mobile device/service adoption, the influence of mobile marketing on customer decision-making, formulation of a mobile marketing strategy, and mobile marketing in the global context.  We outline research directions related to these issues and conclude by delineating the managerial implications of mobile marketing insights.

  • The Effects of New Franchisor Partnering Strategies on Franchise System Size


    by Scott Shane, Venkatesh Shankar, and Ashwin Aravindakshan

    This article was published in Management Science, 52 (May 2006), 773-787.

    Why do some franchisors (corporate entities) such as Pearle Vision and Jazzercise grow larger than others? Is it due to effective pricing policy decisions, such as the royalty rates franchisors charge the franchisees for use of the franchise name and product and the up-front fixed fees? Or is it due to appropriate decisions related to strategic control of the franchise system, including the number and proportion of outlets owned and operated by the franchisor, the initial franchisee investment and how much financing the franchisor can offer? This paper examines what partnering strategies contribute to the expansion of a franchise system.  We analyzed the evolution of franchise systems from their inception using data on 1,292 business format franchise systems from 152 industries that were established in theUnited Statesbetween 1979 and 1996. Our results show that franchisors that open more outlets typically: Lower royalty rates as their systems age; have low up-front franchise fees and raise them over time; own a small proportion of outlets and lower that percentage over time; keep franchisees’ initial investment low; and, finally, finance their franchisees. These strategic decisions increase the value of the franchise brands, reduce franchisee risk, and increase the attraction of new franchisees, thus explaining the growth to a larger franchise system.  We also find that franchise system growth is negatively related to the proportion of company-owned outlets, which highlights the merits of minimizing ownership to achieve widespread growth. Hence, franchisors who want to grow larger may be able to use their financial resources to keep their franchisees’ initial investment in the outlets low and to finance franchisees, both of which can drive the expansion of a franchise system.

  • Multiple-Category Decision-Making: Review and Synthesis

    Russell_Ratneshwar_- Shankar_MLetters_1999

    by Gary J. Russsell, S. Ratneshwar, Allan D. Shocker, David Bell, Anand Bodapati, Alex Degeratu, Lutz Hildenbrandt, Namwoon Kim, S. Ramaswami, and Venkatesh Shankar

    This aricle was published in Marketing Letters, 10 (3, 1999), 319-332.

    In many purhcase environments, consumers use information from a number of product categories prior to making a decision. These purchase siuaions create dependences in choice outcomes across categories. As such, these decisions cannot be modeled using a single-category, single-choice paradigm commonly used by researchers in marketing. We outline a conceptual framework for categorization, and then discuss three types of cross-category dependence: cross-category consideration, cross-category learning, and product bundling. We argue that the key modeling choice dependence across categories is knowledge of the goals driving consumer behavior.