Estimating the Value of Brand Alliances in Professional Team Sports

Yang, Yupin; Shi, Mengze; Goldfarb, Avi

doi:10.1287/mksc.1090.0513

Cited by 90 publications

(80 citation statements)

References 36 publications

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“…As discussed in other papers (Yang et al, 2009;Akkus et al, 2014), coe¢ cients related to the researcher only or to the …rm only, or …xed e¤ects to any collaboration, such as the running costs, cannot be identi…ed because they will cancel out in the local maximization condition (3). We can only estimate interaction terms.…”

Section: Maximum Score Estimationmentioning

confidence: 99%

Endogenous Matching in University-Industry Collaboration: Theory and Empirical Evidence from the United Kingdom

2018

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent AbstractWe use a two-sided matching framework to analyze collaboration between heterogeneous academics and …rms. We consider both horizontal and vertical characteristics, i.e., those related to a¢ nity (e.g., preferences for a type of scienti…c research) and those related to ability (e.g., capacity to produce high-quality scienti…c output). We build a unique dataset based on the teams of academics and …rms that proposed research projects to the UK's Engineering and Physical Sciences Research Council. Our results are suggestive of positive assortative matching in terms of ability and type while the matching is negative assortative in terms of their interactions. The most able and the most applied academics are the ones that are more likely to propose collaborative as opposed to non-collaborative projects. JEL Classi…cation numbers: O32, I23

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Section: Maximum Score Estimationmentioning

confidence: 99%

Endogenous Matching in University-Industry Collaboration: Theory and Empirical Evidence from the United Kingdom

2018

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“…Note that Yang et al (2009) show the empirically estimated impact on a brand of joining teams with varying levels of equity. Since the equity of a team goes up from the efforts of the "other" members of the team, the entries in the table are indicative of the varying magnitude of the indirect linkage under discussion.…”

Section: The Under-investment Effectmentioning

confidence: 99%

Spillovers and Other Externalities in Pharmaceutical Marketing

Desiraju

Tran

2013

International Series in Quantitative Marketing

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This chapter highlights the impact of spillovers and other externalities on the pharmaceutical manufacturer's marketing strategy. First, a spillover arises when a marketer's action affects either an unintended audience or the targeted audience in an unintended manner; an externality is defined more broadly in the sense that all spillovers are externalities, but all externalities need not be spillovers. Next, the pharmaceutical industry is characterized by three relatively unique features: (1) unlike other consumer settings, ethical drugs can be dispensed to patients only when they are prescribed by a licensed practitioner; (2) drug manufacturers have patent protection; and (3) there is variation in how marketing activities are regulated across different segments or geographical regions. These features facilitate the existence of certain types of spillovers and externalities. For instance, direct-to-consumer advertising (DTCA) is permitted in the USA but not in Canada; this suggests the possibility of a spilloveronto the unintended Canadian consumers from DTCA in the USA. For illustration, we use IMS data on nasal steroids to explore empirically both the existence of a spillover and its impact. The empirical analysis suggests that the DTCA spillover into Canada contributes around 4-6 % to the US long-term DTCA return on investment. Such results underscore the value of accounting for spillover effects in developing and evaluating marketing strategy. More generally, this chapter juxtaposes the unique features of the pharmaceutical industry with the extant work on spillovers and other relevant externalities to identify knowledge gaps that warrant research attention. Chapter 23 Spillovers and Other Externalities in Pharmaceutical Marketing Ramarao Desiraju and Thanh Van TranThanks are due to the two anonymous reviewers, Siva K. Balasubramaniam and Pradeep Chintagunta for their insightful comments and valuable suggestions on an earlier draft of this manuscript. The usual caveat applies.

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“…Its main contribution is to propose and demonstrate an estimation method derived from the first principles of the value-based framework due to Stuart (1996, 2007) that yields estimates consistent with the assumption of competitive behavior, instead of taking existing econometric methods and imperfectly mapping the value-based framework onto them. The method was originally developed for cooperative game theory models known as matching games (Fox, 2008(Fox, , 2010, and has been recently applied in the strategic management literature to study alliances (Mindruta, 2013;Mindruta, Moeen, and Agarwal, 2016) while also finding notable applications in marketing (Yang, Shi, and Goldfarb, 2009) and corporate finance (Akkus, Cookson, and Hortaçsu, 2015). We illustrate how it can be further developed to estimate value creation in formal models based on biform games and show how empirical estimates can be leveraged in a model of value capture.…”

Section: Introductionmentioning

confidence: 99%

Estimating Value Creation from Revealed Preferences: Application to Value-Based Strategies

Chatain

Mindruta

2016

SSRN Journal

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Research summary: We develop and apply a new set of empirical tools consistent with the tenets of valuebased business strategies, leveraging the principle that "no good deal comes undone" and the methods of revealed preferences, to empirically estimate drivers of value creation. We demonstrate how to use these tools in an analysis of value creation in buyer-supplier relationships in the UK corporate legal market. We show that our approach can uncover evidence of subtle mechanisms that traditional methods cannot easily distinguish from each other. Furthermore, we show how the estimates can be used as parameters of biform games for outof-sample analyses of strategic decisions. With readily available data on relationships between firms, this approach can be applied to many other contexts of interest to strategy researchers.Managerial summary: Managers need to understand the drivers of value creation for customers in order to make competitive positioning decisions and understand when they can capture value under competition. However, estimates of the relative importance of each driver are typically difficult to obtain. In this article, we help remedy this problem by demonstrating a novel method that obtains estimates of the contribution of various drivers of value creation from commonly available data of buyer-supplier relationships. These estimates can then be used to inform the strategy-making process. Research abstractWe develop and apply a new set of empirical tools consistent with the tenets of value-based business strategies, leveraging the principle that "no good deal comes undone" and the methods of revealed preferences, to empirically estimate drivers of value creation. We demonstrate how to use these tools in an analysis of value creation in buyer-supplier relationships in the UK corporate legal market. We show that our approach can uncover evidence of subtle mechanisms that traditional methods cannot easily distinguish from each other. Furthermore, we show how the estimates can be used as parameters of biform games for out-of-sample analyses of strategic decisions. With readily available data on relationships between firms, this approach can be applied to many other contexts of interest to strategy researchers.Word count: 125 words.Keywords: value-based strategy, revealed preferences, cooperative game theory, buyer-supplier relationships, client-specific economies of scope Managerial abstractManagers need to understand the drivers of value creation for customers in order to make competitive positioning decisions and understand when they can capture value under competition. However, estimates of the relative importance of each driver are typically difficult to obtain. In this paper, we help remedy this problem by demonstrating a novel method that obtains estimates of the contribution of various drivers of value creation from commonly available data of buyer-supplier relationships. These estimates can then be used to inform the strategy-making process.Word count: 84 words.3

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Estimating the Value of Brand Alliances in Professional Team Sports

Cited by 90 publications

References 36 publications

Endogenous Matching in University-Industry Collaboration: Theory and Empirical Evidence from the United Kingdom

Endogenous Matching in University-Industry Collaboration: Theory and Empirical Evidence from the United Kingdom

Spillovers and Other Externalities in Pharmaceutical Marketing

Estimating Value Creation from Revealed Preferences: Application to Value-Based Strategies

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