- Department Head, Marketing
- Professor, Marketing
- Member of the Graduate Faculty
Yong Liu is Professor of Marketing and Eller Professor at the Eller College of Management, University of Arizona. He received his Ph.D. in Marketing from the University of British Columbia, Vancouver, Canada. His research focuses on quantitative models of innovation and business models, social interactions and influence, media and entertainment markets (especially the movie industry), competitive strategies for business and nonprofits, and managing product-harm crisis. His current research projects include modeling information mechanisms in crowdfunding, pricing strategies in sporting marketing, consumer-controlled advertising exposure, and empirical studies on video games, online product reviews, social influence, and how firms should manage product recalls. His research has been published in journals such as Marketing Science, Management Science, Journal of Marketing, Quantitative Marketing and Economics, and Journal of Public Policy and Marketing. He teaches marketing strategy, marketing research, and innovation in undergraduate, graduate and executive education programs. He has won a number of teaching awards including Eller Dean’s Course Innovation Award, Eller College Award for Undergraduate Teaching Excellence, and the Executive MBA Award for Outstanding Module. He was named a Marketing Science Institute (MSI) Young Scholar, and currently serves on the Editorial Review Board of Marketing Science and as an Associate Editor for Journal of Retailing and Decision Sciences.
- Ph.D. Business Administration/Marketing
- University of British Columbia, Vancouver, British Columbia, Canada
- Essays on Competitive Strategies in the Broadcasting Television Industry
- M.S. Engineering Economics
- Tianjin University, Tianjin, Tianjin, China
- Social, Cultural and Environmental Impacts of Chinese Firms in Rural/Suburban Areas
- B.S. Engineering Economics, Computer and Applications
- Tianjin University, Tianjin, Tianjin, China
- University of Arizona, Tucson, Arizona (2017 - Ongoing)
- University of Arizona, Tucson, Arizona (2010 - 2017)
- University of Arizona, Tucson, Arizona (2006 - 2010)
- Syracuse University, Syracuse, New York (2002 - 2006)
- Eller Evening MBA Most Valuable Professor (Phoenix) Nomination
- Eller College, Fall 2017 (Award Nominee)
- Eller Professorship
- Eller College, Fall 2017
- The 52nd AMA-Sheth Foundation Doctoral Consortium Faculty, University of Iowa, 2017
- American Marketing Association, Summer 2017
- The 51st AMA-Sheth Foundation Doctoral Consortium Faculty
- American Marketing Association, Summer 2016
- Eller College Dean’s Course Innovation Award
- University of Arizona Eller college of Management, Spring 2016 (Award Finalist)
- Eller College Dean’s Award for Undergraduate Teaching Excellence
- Eller College, U of A, Spring 2015
- University of Arizona Honors College Outstanding Thesis Advisor Award
- Eller College, Spring 2015
- Journal of Retailing Outstanding Reviewer Award
- Journal of Retailing, Spring 2012
- Eller Faculty Fellow
- Eller College, Fall 2011
- Executive MBA Faculty Award for Outstanding Module
- Eller College, Fall 2011
- Eller College of Management, Fall 2011
- Journal of Interactive Marketing Best Paper Award Runner-up
- Journal of Interactive Marketing, Fall 2011 (Award Finalist)
- Journal of Interactive Marketing Best Paper Award
- Journal of Interactive Marketing, Spring 2011 (Award Finalist)
- Eller College Student Council Award for Outstanding Commitment and Contribution
- Eller College Student Council, Spring 2009
- Management Science Meritorious Service Award
- Management Science, Spring 2009
- Marketing Science Institute (MSI) Young Scholar
- Marketing Science Institute, Spring 2007
Models of marketing strategies in the following areas: (1) Social interactions and new media, (2) Marketing strategies for media and cultural products, especially movie marketing, (3) Competitive strategies for business and nonprofits, (4) Firm strategies during product-harm crisis.
Marketing strategy, Innovation & new product strategies, Entrepreneurship and innovation, Marketing research, Service marketing, Entertainment industries marketing, Social media.
Independent StudyMKTG 699 (Fall 2021)
Independent StudyMKTG 599 (Summer I 2021)
Marketing of InnovationsMKTG 579E (Summer I 2021)
DissertationMKTG 920 (Spring 2021)
Marketing Of InnovationMKTG 579 (Spring 2021)
Marketing of InnovationsMKTG 579E (Spring 2021)
Special Topics in MarketingMKTG 696 (Spring 2021)
Special Topics/MarketingMKTG 555E (Spring 2021)
DissertationMKTG 920 (Fall 2020)
Independent StudyMKTG 599 (Fall 2020)
Marketing of InnovationsMKTG 579E (Summer I 2020)
DissertationMKTG 920 (Spring 2020)
Independent StudyMKTG 599 (Spring 2020)
Marketing Of InnovationMKTG 579 (Spring 2020)
Marketing of InnovationsMKTG 579E (Spring 2020)
Product StrategyMKTG 559 (Spring 2020)
Special Topics in MarketingMKTG 696 (Spring 2020)
Special Topics/MarketingMKTG 555E (Spring 2020)
DissertationMKTG 920 (Fall 2019)
Marketing of InnovationsMKTG 579E (Summer I 2019)
Marketing Of InnovationMKTG 579 (Spring 2019)
Marketing of InnovationsMKTG 579E (Spring 2019)
Product ManagementMKTG 459 (Spring 2019)
Product StrategyMKTG 559 (Spring 2019)
DissertationMKTG 920 (Fall 2018)
Marketing of InnovationsMKTG 579E (Fall 2018)
Independent StudyMKTG 599 (Spring 2018)
Independent StudyMKTG 699 (Spring 2018)
Marketing of InnovationsMKTG 579E (Spring 2018)
Product ManagementMKTG 459 (Spring 2018)
Product StrategyMKTG 559 (Spring 2018)
Special Topics in MarketingMKTG 696 (Spring 2018)
Marketing of InnovationsMKTG 579E (Fall 2017)
Marketing of InnovationsMKTG 579E (Summer I 2017)
Custmr Value PropositionBNAD 503 (Spring 2017)
Independent StudyMKTG 699 (Spring 2017)
Marketing of InnovationsMKTG 579E (Spring 2017)
Product ManagementMKTG 459 (Spring 2017)
Product StrategyMKTG 559 (Spring 2017)
Independent StudyMKTG 499 (Fall 2016)
Marketing of InnovationsMKTG 579E (Fall 2016)
Mktg Res For EntrpreneurMKTG 480 (Fall 2016)
Custmr Value PropositionBNAD 503 (Spring 2016)
DissertationMKTG 920 (Spring 2016)
Honors ThesisMKTG 498H (Spring 2016)
Independent StudyMKTG 699 (Spring 2016)
Master's ReportMKTG 909 (Spring 2016)
Product ManagementMKTG 459 (Spring 2016)
Product StrategyMKTG 559 (Spring 2016)
ResearchMKTG 900 (Spring 2016)
Special Topics in MarketingMKTG 696 (Spring 2016)
- Liu, Y., Lusch, R. F., Chen, Y., & Zhang, J. (2016). The Emergence of Innovation as a Social Process: Theoretical Exploration and Implications for Entrepreneurship and Innovation. In Open Innovation, Ecosystems and Entrepreneurship: Issues and Perspectives. World Scientific Publishing.
- Liu, Y., Chen, Y., Ganesan, S., & Hess, R. (2012). Product-harm crisis management and firm value. In Handbook of Marketing and Finance(pp 293-314).
- Liu, Y., & Weinberg, C. B. (2009). Pricing for nonprofit organizations. In Handbook of Pricing Research in Marketing(pp 512-534).More infoAbstract: Pricing decisions are particularly challenging for nonprofit organizations. They have a social rather than a for-profit objective function, they must obey a legal restriction not to distribute possible financial surpluses to those who control the organization's assets, and they have the opportunity to receive donations. While historically nonprofits have not developed their pricing capabilities as fully as they might have, pricing is becoming increasingly important, especially as many nonprofit organizations face declining support from government and are unable to increase private giving significantly. The goal of this chapter is to discuss pricing practice and pricing research in the nonprofit sector. We demonstrate how theoretical models of pricing strategies for nonprofits are different from those of for-profit businesses. Moreover, although only limited empirical data on nonprofit pricing are available, the data we do have suggest that nonprofits charge different (and usually lower) prices than similarly situated businesses. We survey the literature of nonprofit pricing to discuss important theoretical and empirical findings, and highlight the unique characteristics of nonprofits and the various modeling issues they generate for pricing research. We also discuss unresolved problems and potential research opportunities in nonprofit pricing.
- Gao, W., Ji, L., Liu, Y., & Sun, Q. (2020). Branding Movies in International Markets: The Effects of Title Translation on the Sales of Hollywood Movies. Journal of Marketing, 84(3), 85-105.
- Chen, Y., Ghosh, M. G., Liu, Y., & Zhao, L. (2019). Media Coverage of Climate Change and Sustainable Product Consumption: Evidence from the Hybrid Vehicle Market. Journal of Marketing Research, 56(6), 995-1011.
- Lin, M., Liu, Y., & Viswanathan, S. (2017). Effectiveness of Reputation in the Presence of Contracts: Evidence from Online Labor Markets. Management Science.More infoPublished online December 16, 2016
- Liu, A., Liu, Y., & Luo, T. (2016). What Drives a Firm’s Choice of Product Recall Remedy? The Impact of Remedy Cost, Product Hazard, and the CEO. Journal of Marketing, 80, 79-95.
- Liu, Y., Yang, J., & Mai, S. (2015). Using Online Product Ratings to Study Network Externalities: The Case of Online Video Games. Marketing Letters, 26(4), 679-690.
- Liu, Y., Zhang, J., & Chen, Y. (2015). Social Learning in Networks of Friends versus Strangers. Marketing Science, 34(4), 573-589.
- Liu, Y., Liu, A., & Mazumda, T. (2013). Star Power in the Eye of the Beholder: A Study of the Influence of Stars in the Movie Industry. Marketing Letters, 1-12.
- Chen, Y., Liu, Y., & Zhang, J. (2012). When do third-party product reviews affect firm value and what can firms do? The case of media critics and professional movie reviews. Journal of Marketing, 76(2), 116-134.More infoAbstract: Third-party product reviews (TPRs) have become ubiquitous in many industries. Aided by communication technologies, particularly on the Internet, TPRs are widely available to consumers, managers, and investors. The authors examine whether and how TPRs of new products influence the financial value of firms introducing the products. An event study covering 14 major media and professional reviews of movies released by 21 studios shows that TPRs exert significant impact on stock returns in the direction of their valence. However, the impact comes from the valence of a review that is measured relative to other, previously published reviews and not from the absolute valence of the review itself. The authors further study the dynamics of TPR impact on firm value and find that the impact exists only for prerelease reviews and is the strongest on the product release date, though it disappears when sales information becomes available after product release. These results demonstrate that TPRs play significant roles as the investors update their expectation about new product sales potential. The authors also find that advertising spending increases the positive impact of TPRs on firm value and buffer the negative impact. Therefore, firms could strategically use marketing instruments such as advertising to moderate the impact of TPRs. © 2012, American Marketing Association.
- Li, X., Zeng, D. D., Liu, Y., & Yang, Y. (2011). Click Fraud and the Adverse Effects of Competition. IEEE Intelligent Systems, 31--39.
- Chakravarty, A., Liu, Y., & Mazumdar, T. (2010). The Differential Effects of Online Word-of-Mouth and Critics' Reviews on Pre-release Movie Evaluation. Journal of Interactive Marketing, 24(3), 185-197.More infoAbstract: In this paper, we examine the persuasive influences of online user comments (or word-of-mouth) and of the reviews by movie critics on moviegoers' evaluation of to-be-released movies. Two distinctive features of this study are: (1) moviegoers are considered to be heterogeneous in their movie going frequency and (2) word-of-mouth and critical reviews are concurrently available, and the views expressed in the two messages are in conflict. Using three experiments with natural stimuli, we find that the persuasive effect of online word-of-mouth is stronger on infrequent than on frequent moviegoers, especially when it is negative (Study 1). The effect of negative word-of-mouth on infrequent moviegoers is enduring even in the presence of positive reviews by movie critics (Study 2). The relative influence of word-of-mouth and critical reviews are asymmetric with infrequent moviegoers more influenced by word-of-mouth, while frequent moviegoers more influenced by the reviews (Study 3). We validate this source-segment alignment through secondary data analysis. © 2010 Elsevier B.V.
- Liu, Y., Chen, Y., Lusch, R. F., Chen, H., Zimbra, D., & Zeng, S. (2010). User-Generated content on social media: Predicting market success with online word-of-mouth. IEEE Intelligent Systems, 25(1), 75-78.
- Lusch, R. F., Liu, Y., & Chen, Y. (2010). Evolving Concepts of Markets & Organizations: The New Intelligence and Entrepreneurial Frontier. IEEE Intelligent Systems.
- Chen, Y., Ganesan, S., & Liu, Y. (2009). Does a firm's product-recall strategy affect Its financial value? An examination of strategic alternatives during product-harm crises. Journal of Marketing, 73(6), 214-226.More infoAbstract: Product-harm crises often result in product recalls, which can have a significant impact on a firm's reputation, sales, and financial value. In managing the recall process, some firms adopt a proactive strategy in responding to consumer complaints, while others are more passive. In this study, the authors examine the impact of these strategic alternatives on firm value using Consumer Product Safety Commission recalls during a 12-year period from 1996 to 2007. Using the event study method, the authors show that regardless of firm and product characteristics, proactive strategies have a more negative effect on firm value than more passive strategies. An explanation for this surprising result is that the stock market interprets proactive strategies as a signal of substantial financial losses to the firm. When a firm proactively manages a product recall, the stock market infers that the consequence of the product-harm crisis is sufficiently severe that the firm had no choice but to act swiftly to reduce potential financial losses. Therefore, firms dealing with product recalls must be sensitive to how investors might interpret a proactive strategy and be aware of its potential drawbacks. © 2009, American Marketing Association.
- Zhao, X., Atkins, D., & Liu, Y. (2009). Effects of distribution channel structure in markets with vertically differentiated products. Quantitative Marketing and Economics, 7(4), 377-397.More infoAbstract: This study examines how the structure of distribution channels may influence firms' quality and price strategies and how they may in turn affect consumer welfare. It treats product quality as a decision variable so that the degree of product substitution becomes endogenous rather than exogenous as in previous studies. We find that, with vertically differentiated firms, the changes in channel structure have asymmetric effects depending on whether they occur in the high-quality channel or in the low-quality channel. The product quality of the high-quality channel decreases when it decentralizes unilaterally. However, product quality of the low-quality channel would increase when it decentralizes. The high-quality manufacturer and its channel suffer more from decentralization in comparison with their low-quality counterparts, and the low-quality manufacturer actually receives greater profits when both channels are decentralized. An important driver behind these asymmetries is the interaction between firms' pricing incentives in integrated versus decentralized channels and what consumer segments they serve. Our analysis indicates that decentralization may reduce consumer welfare, but decentralization in the high-quality channel hurts consumers more than that in the low-quality channel. Therefore in a competitive environment where firms make both quality and price decisions, channel integration would have significant welfare enhancement effects through the elimination of double marginalization, especially if it happens in the high-quality channel. Moreover, we demonstrate that once quality is endogenized, integration is the only equilibrium of channel structure choices. This suggests that the private incentives of firms may actually benefit consumers but do not have to be in line with the general preference of industry regulation for decentralization. © Springer Science+Business Media, LLC 2009.
- Krider, R. E., Tieshan, L. i., Liu, Y., & Weinberg, C. B. (2008). Demand and distribution relationships in the ready-to-drink iced tea market: A graphical approach. Marketing Letters, 19(1), 1-12.More infoAbstract: The relationship between distribution coverage and market share for an incumbent brand and for new entrants in the ready-to-drink iced tea market during its growth phase is explored using state space diagrams. This graphical visualization method was originally developed to disentangle lead-lag relationships between short nonstationary time series, a situation in which standard econometric methods have difficulty. In this research we show the usefulness of this method for long time series in offering complementary insights to econometric models, in providing a simple and managerially useful tool, and in conducting exploratory data analysis to guide subsequent modeling decisions. In the ready-to-drink iced tea market, usage of this method shows that during introduction of new brands and growth of the category, demand leads distribution, but that as the market matures, the dominant incumbent can defend with a distribution-leading-demand dynamic. Further, distribution coverage eventually becomes relatively stable so that short term fluctuations in demand (probably due to responses to promotion) have minimal impact on distribution. © 2007 Springer Science+Business Media, LLC.
- Putler, D. S., Li, T., & Liu, Y. (2007). The value of household life cycle variables in consumer expenditure research: An empirical examination. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 24(4), 284--299.
- Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of Marketing, 70(3), 74-89.More infoAbstract: This article uses actual word-of-mouth (WOM) information to examine the dynamic patterns of WOM and how it helps explain box office revenue. The WOM data were collected from the Yahoo Movies Web site. The results show that WOM activities are the most active during a movie's prerelease and opening week and that movie audiences tend to hold relatively high expectations before release but become more critical in the opening week. More important, WOM information offers significant explanatory power for both aggregate and weekly box office revenue, especially in the early weeks after a movie opens. However, most of this explanatory power comes from the volume of WOM and not from its valence, as measured by the percentages of positive and negative messages. © 2006, American Marketing Association.
- Liu, Y., Putler, D. S., & Weinberg, C. B. (2006). A reply to "a comment on 'is having more channels really better? A model of competition among commercial television broadcasters' ". Marketing Science, 25(5), 543-546.More infoAbstract: Liu et al. [Liu, Y., D. S. Putler, C. B. Weinberg. 2004. Is having more channels really better? A model of competition among commercial television broadcasters. Marketing Sci. 23(1) 120-133] examine the television broadcast industry using a model in which profit-maximizing broadcasters seek to gain viewers by choosing the type of program to offer and by spending money to set program quality, allowing broadcasters to sell access to those viewers (through inserted advertisements) at a fixed rate per viewer. Wu and Chou [Wu, C., S. Chou. 2006. Commentary on "Is having more channels really better? A model of competition among commercial television broadcasters". Marketing Sci. 25(5) 541-545] argue that the duopoly result for a certain range of the cost parameter in Liu et al. is not a pure strategy Nash equilibrium. They further propose some modifications to the original model to restore Liu et al.'s results. In this reply, we demonstrate how a single strategy, not included in the strategy space of the Liu et al. duopoly model leads to the difference between our analysis and that of Wu and Chou. While we had intended to rule out this strategy, the text was not entirely clear on this issue; Wu and Chou's comment provides an opportunity to clarify the situation. We provide both empirical and theoretical support for excluding this strategy, which allows us to focus on the more plausible competitive situations in television broadcasting. We also reply to Wu and Chou's other comments on several issues, such as the relative importance of program type versus quality. © 2006 INFORMS.
- Liu, Y., Putler, D. S., & Weinberg, C. B. (2006). The welfare and equity implications of competition in television broadcasting: The role of viewer tastes. Journal of Cultural Economics, 30(2), 127-140.More infoAbstract: This paper studies the behavior of commercial television broadcasters in markets where the distribution of viewer tastes varies. Our results show that a highly "clustered" market enables the broadcaster to offer a program of a popular type but with lower quality (i.e., lower production values) than is the case when viewers have more diffused tastes. We find that viewer equity in the television market (i.e., the percentage of all potential viewers who have at least one program they consider worth watching) and viewer welfare (i.e., total consumer surplus) may not coincide. Depending upon the distribution of viewer tastes and the cost of providing quality programming, the number of broadcasters required to fully cover the market to avoid market failure may be greater than the number of broadcasters that produce greater viewer welfare. The study suggests that regulatory bodies need to pay attention to the distribution pattern of viewer tastes and the broadcasters' desire for return on programming investments, since both factors have important implications for competitive outcomes and viewer well-being. © Springer Science+Business Media B.V. 2006.
- Kride, R. E., Tieshan, L. i., Liu, Y., & Weinberg, C. B. (2005). The lead-lag puzzle of demand and distribution: A graphical method applied to movies. Marketing Science, 24(4), 635-645.More infoAbstract: Understanding the lead-lag relationship between distribution and demand is an important and challenging issue for all marketers. It is particularly challenging in the movie industry, where the very short lifespan and decaying revenue and exhibition patterns of motion pictures means that the associated time series are short and nonstationary, rendering existing econometric methods unreliable. We propose an alternate method that uses state-space diagrams to determine lead-lag relationships. Straightforward to apply and interpret, it takes advantage of the eye's ability to see patterns that algebra-based formulations cannot easily recognize. A number of validation tests are provided to illustrate the usefulness and limitations of the method. We study the weekly data for 231 major movies released in 2000-2001. While econometric methods do not provide consistent results, the graphical method of visually inferred causality clearly shows a pattern that demand leads distribution for most movies. In other words, the dominant industry pattern is one of movie exhibitors monitoring box office sales and then responding with screen allocation decisions. The managerial implications of these findings are discussed. © 2005 INFORMS.
- Liu, Y., & Weinberg, C. B. (2004). Are nonprofits unfair competitors for businesses? An analytical approach. Journal of Public Policy and Marketing, 23(1), 65-79.More infoAbstract: This study examines duopoly price competition between a for-profit firm and a nonprofit organization. It shows that the competitive outcome is predominantly the consequence of their different objective functions. The damage to the for-profit caused by the nonprofit's policy and regulatory advantages is only marginal. Moreover, the for-profit can protect itself by acquiring Stackelberg price leadership.
- Liu, Y., Putler, D. S., & Weinberg, C. B. (2004). Is having more channels really better? A model of competition among commercial television broadcasters. Marketing Science, 120--133.
- Liu, Y. (2017, February). Contingency Selling under Product Uncertainty and Service Capacity Constraint: A New Pricing Model with Applications to Sports Events. AMA Winter Educator’s Conference. Orlando, FL: American Marketing Association.
- Liu, Y. (2017, June). Capturing Virtual Business Opportunities from Real-World Events: Findings and Insights from Sports Video Games. Wharton Customer Analytics Initiative (WCAI). San Francisco, CA: University of Pennsylvania.
- Liu, Y. (2017, June). How Does the Effect of Product Recalls Extend Beyond Country Boundaries? A Study of the Automobile Market in China and the United States. INFOMS Marketing Science Conference. Los Angeles, CA: University of Southern California, INFORMS.
- Liu, Y. (2017, June). Strategic Behaviors in Online Reviews: A Study of Yelp.com. INFOMS Marketing Science Conference. Los Angeles: University of Southern California, INFORMS.
- Liu, Y. (2016, June). Consumer Choice in On-Demand Video Service: The Effects of Previews. INFORMS Marketing Science Conference.
- Liu, Y., Ghosh, M. G., & Wang, P. (2016, June). Modeling the Impact of Digital Piracy on Quality Competition. INFORMS Marketing Science Conference.
- Liu, Y. (2015, June). The Effects and Mechanisms of Online Product Reviews. Invited talk, Zhejiang University. Hangzhou, China.
- Liu, Y. (2015, November). The Effects and Mechanisms of Online Product Reviews. The 2nd Conference on Marketing and Internet Economy. Guilin, China.
- Liu, Y. (2015, October). The Concentration of Start-ups in Incubators. Society of Interdisciplinary Business Research (SIBR) Conference. Hong Kong, China.
- Liu, Y. (2015, September). Consumer Choice in On-Demand Video Service: The Effects of Previews. China India Customer Insight Conference. New York City: Yale School of Management/Cheung Kong Graduate School of Business.
- Liu, Y. (2015, September). Consumer Choice in On-Demand Video Service: The Effects of Previews. Yale School of Management China India Customer Insight Conference.
- Liu, Y. (2014, September). Advertising Decisions in Anticipation of Word-of-Mouth. SIBR 2014 Hong Kong Conference. Hong Kong: Society for Interdisciplinary Business Research.
- Liu, Y., & Weinberg, C. (2014, April). Modeling Quality and Price Decisions of Nonprofit Organizations and the Nonprofit / For-profit Competition. UA/ASU Research Symposium. Tempe, Arizona.
- Liu, Y., Chen, Y., & Zhang, J. (2014, September). The Impact of Social Network on the Success of Innovation: A Study of the Hollywood Movie Industry. International Conference on Culture Creative Industry and e-Business. Shanghai, China.