Almost universally, research and practice suggest that a brand that increases its product assortment, or variety, should benefit through increased market share. In this paper, we show this is not a...
Past research reveals an extraordinary number and variety of transaction games, often with different rules. For example, buy and sell offers can be take-it-or-leave-it, irrevocable, of limited duration, negotiable, contingent on events, et cetera. The possible sets of rules seem endless. Past (often, very insightful) research has focused on optimization, given particular rules of the game. This focus often overlooks why players choose to play the game. Indeed, assuming that an exchange will occur makes the marketing function (e.g., facilitating exchanges) inconsequential. Unlike inescapable market games between rival firms, buyers and sellers often choose whether to play transaction games. Hence, game design (i.e., setting the rules of the game) becomes vital, because the design determines both the likelihood of desirable outcomes (e.g., the best transaction price) and whether (or how many) players will choose to play. We need more research revealing the desirability of various rule sets for different target groups and revealing rules that enhance the benefits to all players. For example, a particular auction game might provide sellers with liquidity (i.e., faster transactions) while providing buyers with unique items at bargain prices. We should also explore the interaction of rules and player benefits (e.g., liquidity, anonymity, likelihood of a transaction, etc.).
Normative models typically suggest that prices rise in periods of high demand and cost. However, in many markets, prices fall when demand or costs rise. This inconsistency occurs because the normative models assume that competitive intensity does not change with demand and cost conditions over time. We therefore introduce the notion of time-varying competition by suggesting that it is important not only to account for the direct effect of demand and cost on prices (e.g., higher demand means higher prices), but also the indirect effect of demand and cost changes on competition (e.g., higher demand could cause more competition and, hence, lower prices). We develop a general, unified framework to empirically model the direct and indirect effects of demand and cost shifts on pricing in differentiated product markets. Our approach allows us to measure the indirect effect of multiple demand and cost drivers on competitive intensity and test predictions from alternative theories of repeated games. The empirical application is to the U.S. photographic film industry, where there are two main players, Kodak and Fuji. We find that the indirect effects are highly significant and comparable in magnitude to the direct effects. Competitive intensity is greater in periods of high demand and lower cost and is moderated by whether demand or costs are expected to grow or decline. Interestingly, we find asymmetries in the competitive responses of Kodak and Fuji. While Kodak is sensitive to demand factors, Fuji is sensitive to costs. Our results suggest that market characteristics such as observability of competitor prices can be an important determinant of how competitive intensity is affected by demand and cost conditions.
This paper draws on the quality profitability emphasis framework of Rust, Moorman, and Dickson (2002) (Rust, Roland T., Christine Moorman, Peter R. Dickson. 2002. Getting returns from service quality: Revenue expansion, cost reduction, or both. J. Marketing 66(October) 7–24.) to examine the association between customer satisfaction and long-term financial performance among firms that achieve a dual emphasis (focusing on both revenue-expansion and cost-reduction simultaneously, rather than solely emphasizing one over the other). Using a longitudinal data set of 77 firms from the United States, we test this hypothesis and find that the association between customer satisfaction and long-term financial performance is positive and relatively stronger for firms that successfully achieve a dual emphasis. We build on the work of Rust, Moorman, and Dickson (2002), who investigated the financial impact of engaging in the process of achieving a dual emphasis. Collectively, these studies show that while achieving a dual emphasis is desirable for long-run financial success, the process of achieving a dual emphasis may not be as financially rewarding in the short run. Firms pursuing a dual emphasis need to consider both short- and long-term consequences of their strategy.
The Practice Prize Reports consist of one article with two parts as follows: “Sinha, Ashish, J. Jeffrey Inman, Yantao Wang, Joonwook Park. Attribute drivers: A factor analytic choice map approach for understanding choices among SKUs” and “Tellis, Gerard J., Rajesh K. Chandy, Deborah MacInnis, Pattana Thaivanich. “Modeling the microeffects of television advertising: Which ad works, when, where, for how long, and why?”
This paper describes the development and application of a marketing model to help set an incumbent's defensive marketing strategy prior to a new competitor's launch. The management problem addressed is to assess the market share impact of a new entrant in the residential Australian long distance telephone call market and determine the factors that would influence its dynamics and ultimate market appeal. The paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss. We develop models at two levels of complexity to give both simple, robust forecasts and more detailed diagnostic analysis of the effect of marketing actions. The models are calibrated prior to the new entrant's launch, enabling preemptive marketing strategies to be put in place by the defending company. The equilibrium level of consideration of the new entrant was driven by respondents' strength of relationship with the defender and inertia, while trial was more price-based. Continued use of the defender depends on both service factors and price. The rate at which share loss eventuates is negatively related to the defender's perceived responsiveness, saving money being the only reason to switch, and risk aversion. Prelaunch model forecasts, validated six months after launch using both aggregate monthly sales data and detailed tracking surveys, are shown to closely follow the actual evolution of the market. The paper provides a closed-form multistate model of the new entrant's diffusion, a methodology for the prelaunch calibration of dynamic models in practice, and insights into defensive strategies for existing companies facing new entrants.
Building on the observation that competitive dynamics and market evolution are inextricably linked and underresearched, we propose a road map to guide and stimulate future research in the area. A number of rationales have been proposed to explain why there is relatively little research directed toward understanding the links between competitive dynamics and market evolution; these include the predominance of different research paradigms in each area, a lack of data appropriate for analyzing the two areas together, and the difficulty of obtaining robust and significant results with analysis that is by definition complex (it must consider factors and outcomes both across firms and over time). Using this last rationale as a starting point, we develop a series of research propositions related to key relationships where (a) insignificant or contradictory results have been obtained (in extant research) or (b) researchers have yet to delve. The propositions are designed to deepen our understanding of the relationship between the areas. Throughout the analysis, the key to developing the propositions is to recognize the importance of moderating factors, mediating factors, and covariates. In addition, where the approach to empirically test a proposition is new, we propose categories, measures, and comparisons that can be used.
Many emerging technologies exhibit path-dependent demands driven by positive network feedback. Such network effects profoundly impact marketing strategists' thinking in today's network economy. However, the significant network externalities expected by many people often fail to materialize in the emerging technology market. We analyze this phenomenon in the context of a technology distribution channel. By studying cheap-talk strategies under information asymmetry, we show that incentive-compatible contracts are essential for achieving credible information transmission. In our model, the better-informed technology vendor has an incentive to inflate the retailer's ex ante belief of network externalities when a wholesale price contract is adopted. When properly termed revenue-sharing contracts are implemented, there are information-efficient cheap-talk equilibria where truthful information transmission is mutually beneficial. When the vendor's information is imperfect, even revenue-sharing contracts cannot guarantee credible information transmission if there is significant prior belief disparity between the vendor and the retailer. This study demonstrates how information-inefficient equilibria (e.g., information blockage) arise because of the conflict of interest or the conflict of opinion among channel members. It also explores the role of cheap talk in facilitating channel coordination.
This research uses Procter & Gamble's value pricing initiative as a context for testing whether actual competitor and retailer response to a major policy change can be predicted using a game-theoretic model. We first estimate demand functions for P&G and competitor brands from the period before value pricing was initiated. We then formulate a dynamic manufacturer-retailer Stackelberg model that includes P&G, a national-brand competitor, and a retailer. The model takes P&G's move as given and prescribes the price and promotion response of the competitors and the retailer. We substitute the estimated demand parameters into the model to obtain prescriptions for each competitor and the retailer, and see whether these prescriptions are related to the actual response. We find that the dynamic game-theoretic model calibrated with empirical estimates of demand parameters has significant predictive power. We also test the predictive power of two benchmark models. The first is based on the reaction function approach of Leeflang and Wittink (Leeflang, Peter S. H., Wittink, Dick R. 1992. Diagnosing competitive reactions using (aggregated) scanner data. Internat. J. Res. Marketing 9 39–57.), and the second is a simplification of our dynamic model where the retailer is not strategic. The dynamic game-theoretic model performs better than either benchmark.
Adaptive metric utility balance is at the heart of one of the most widely used and studied methods for conjoint analysis. We use formal models, simulations, and empirical data to suggest that adaptive metric utility balance leads to partworth estimates that are relatively biased—smaller partworths are upwardly biased relative to larger partworths. Such relative biases could lead to erroneous managerial decisions. Metric utility-balanced questions are also more likely to be inefficient and, in one empirical example, contrary to popular wisdom, lead to response errors that are at least as large as nonadaptive orthogonal questions. We demonstrate that this bias is because of endogeneity caused by a “winner’s curse.” Shrinkage estimates do not mitigate these biases. Combined with adaptive metric utility balance, shrinkage estimates of heterogeneous partworths are biased downward relative to homogeneous partworths. Although biases can affect managerial decisions, our data suggest that, empirically, biases and inefficiencies are of the order of response errors. We examine viable alternatives to metric utility balance that researchers can use without biases or inefficiencies to retain the desired properties of (1) individual-level adaptation and (2) challenging questions.