Sports franchises derive significant portions of their revenues from season ticket holders who pre-purchase tickets with large price discounts but significant uncertainty of game quality. A recent trend that may have meaningful consequences for season ticket management is the development of legitimate secondary markets. This research investigates the value of secondary markets to season ticket holders. We find that, on one hand, secondary markets provide an option value to list tickets to resell in addition to attendance and forgoing. On the other hand, the secondary markets may attract listing, push down resale prices, and make the resale option unattractive. We assemble a unique panel data that combines season and single ticket purchase records with ticket usage records on attend, forgo, list, and resale. We build a structural model of ticket purchase and usage. Our policy experiments suggest that overall secondary markets increase season ticket purchase rates by 5.97%, equivalent to $2,633,394 revenue increase over 6 years. The impacts of secondary markets are most pronounced for lower quality seat tickets.
Keywords: Sports Marketing, Season Ticket Holders, Ticket Resale, CRM
Movies are among the US’s most successful exports, and China is by far the largest market. China welcomes high-quality US movies in order to grow its own theatrical market, while also diligently protecting locally produced movies. This paper evaluates the relative impact of these dual motives. China is known to limit the number of foreign movies, half of which are delayed beyond the US release date by four or more weeks. We empirically study the Chinese government’s import decisions using Chinese market data and develop a movie market demand model, along with two models on simultaneous and delayed-releases where we consider release timing as an implicit trade barrier. We find that China prefers to import US movies with relatively high production budgets but limits them when the potential cannibalization effect from US blockbusters is high and when the market share of local movies is relatively low. Delayed-releases of US movies are strongly associated with weaker box-office performance in China, making control of release schedule another vehicle that China leverages in import decisions.
Keywords: Movies, Import Regulation, Chinese Theatrical Market, International Marketing
The paper empirically investigates whether and how the recently developed mobile hailing technology affects taxi driver’s productivity. The new technology reduces information asymmetry between drivers and riders by allowing the taxi drivers to observe the nearby pickup and drop-oﬀ locations of potential customers. In this study, we take leverage of minute-by-minute geo-location data of taxi drivers. We propose a modiﬁed change-point model with supplemented survey data on the adoption of mobile hailing technology and its associated change in drivers’ hourly earnings. We ﬁnd that adopting mobile hailing technology immediately increases driver productivity by 25 to 50%. Yet the productivity gains decline as more drivers adopt the technology. At the end of our sample period in June 2014, productivity increases by 13% on average across all the drivers in the market. Comparing driving patterns before and after the technology adoption, we show that productivity gains are largely achieved by sorting requests and selecting more proﬁtable higher-fare trips rather than by the reduction in search time between trips. In terms of overall eﬀect among drivers, we do not ﬁnd support for app-induced digital inequality. Indeed, the low skilled drivers gain more from the technology.
Keywords: Mobile Hailing Apps, Productivity, Productivity Disparity, Technology Adoption
The asymmetric dominance eﬀect, first introduced by Huber et al. (1982), has been robustly documented in various lab experiments in the literature. However, the practical validity and significance in a real marketplace has never been veriﬁed. In this paper, we empirically test the existence of this eﬀect and, more importantly, quantify its magnitude using a unique panel data set from a major online jewelry market. We estimate a proportional hazard model that is derived from consumer choice primitives, including consumer arrival process, consumer consideration set formation, conditional choice probabilities with embedded asymmetric dominance eﬀect. Our model estimates suggest that in general consumers have low probability of detecting the existence of the dominance relationships in the marketplace; however once they discover, the decoy diamonds significantly increase sales likelihoods of dominant diamonds. We quantify the overall proﬁt impact of asymmetric dominance and ﬁnd that it contributes about 21.4% of the retailer’s gross proﬁt. We also ﬁnd that the existing decoy pricing in the marketplace improves the retailer’s overall gross proﬁt by 19%, compared to a uniform pricing strategy with no dominance relationship. Finally, we explore various strategies that the retailer can adopt to improve its profitability through further utilizing the asymmetric dominance eﬀect. We ﬁnd that there is a great potential for the retailer to gain additional proﬁts.
Consumer showrooming – the behavior of examining a product in a brick-and-mortar store and later buying it from an online retailer – is seen as a major threat to brick-and-mortar retailers. To combat showrooming, Best Buy announced a price-matching policy in 2012 to compete with major online retailers. In this paper, we examine the impact of Best Buy’s price-matching policy on the price competition between Best Buy and Amazon across a wide variety of product categories. We empirically explore Best Buy’s and Amazon’s pricing patterns using unique datasets collected from different sources, and ﬁnd robust results that the competitive eﬀect of the price-matching policy depends on the showrooming value of the product. For those products that oﬀer consumers large value from physical-store experiences – i.e., the “showrooming” products – price-matching led to more intense price competition. Moreover, Amazon cut prices more aggressively than Best Buy. For those products that oﬀer relatively small showrooming value – i.e., the “non-showrooming” products – price-matching alleviated price competition. We further provide theoretical explanations in perspective of channel differentiation, consumer search, and competition for market share.
Co-authored with Kaifu Zhang and Jack (Xinlei) Chen.
Based on a unique dataset from a major e-commerce platform, this paper studies the extortion of online sellers by organized criminals. The extortionists register as normal buyers, purchase from the sellers, demand cash or goodies and threat with negative reviews if their requests are declined. We study how extortionists choose their targets and quantify the short-run and long-run impacts of extortionist attacks on their target. The evidences suggest that the extortionists choose their targets in a systematic way. Furthermore, we find that a single instance of extortion leaves a long-term detriment to a seller’s performance. Extortionist attacks not only decrease the number of orders a seller receives, but also appear to make the victim less willing to deal with innocent buyers who are in fact not extortionists. Moreover, extortion victims seem to overreact to declining sales by cutting prices too deep. As such, extortionists create costs on the marketplace that is far greater than the monetary payments they extract or the physical damage they inflict.
Original design manufacturers (ODM) is a new form of global outsourcing. Traditional outsourcing only transfers the production of a product from brands to manufacturers. An ODM, in contrast, not only manufactures the product for a brand, but also designs the product. Using an analytical model, we investigate strategic design outsourcing decisions of ﬁrms. Two ﬁrms competing in a horizontally differentiated market decide whether to design the products by themselves or to outsource product design to an ODM. We consider two different channel structures – one in which each ﬁrm partners with an exclusive ODM and the other in which both ﬁrms partner with a common ODM. We ﬁnd that both symmetric and asymmetric outsourcing outcomes can arise in the equilibrium, even though competing ﬁrms are assumed to be completely symmetric. Surprisingly, ﬁrms’ outsourcing incentive can be inversely related to the cost of designing a product, i.e., neither ﬁrm outsources product design when the cost is high, one ﬁrm outsources product design and the other insources when the cost is in an intermediate range, and both ﬁrms outsource product design when the cost is low. We also ﬁnd that ﬁrms are more likely to outsource product design when there is a common ODM in the channel than when there are exclusive ODMs.
Co-authored with Sky Leung and Jack (Xinlei) Chen.
In this paper, we empirically quantify the short term and long term profitabilities of daily deal promotions and investigate the role of revenue sharing and platform competition in determining the profits. To achieve this, we build a structural empirical framework to model the strategic decisions made by the platforms, vendors as well as consumers. Our results show that daily deals serve as loss-leaders for vendors where most of them would incur a negative profit in the promotional period while expect to gain a substantial profit in the subsequent periods from returning customers. The degree of long term profitability varies across platforms and over periods. Overall, daily deal promotions generate positive welfare for platforms, vendors as well as consumers. Policy simulations reveal that alleviating platform competition by committing to a fixed revenue sharing percentage would increase the welfare of platforms and consumers, but at the cost of local businesses.
Keywords: Daily Deals, Platform Competition, Economic Value
Co-authored with Hai Che, Tat Y. Chan and Xianghua Lu
This paper investigates the economic value of online reviews for consumers and restaurants. We use a dataset from Dianping.com, a leading Chinese website providing user-generated reviews, to study how consumers learn from reading online reviews the quality and cost of dining at restaurants. We propose a learning model that has three novel features: (1) different reviews offer different informational value to different types of consumers; (2) consumers learn own preferences, and not the distribution of preferences among the entire population, for multiple product attributes; and (3) consumers update not only the expectation but also the variance of their preferences. Based on estimation results, we conduct a series of counterfactual experiments and find that the value from Dianping is about 7 CNY for each user, and about 8.6 CNY from each user for the reviewed restaurants in this study. The majority of the value comes from reviews on the quality of restaurants, and contextual comments are more valuable than numerical ratings in reviews.
Keywords: Online Reviews, User-generated Content, Consumer Choice under Uncertainty, Learning, Economic Value to Consumer and Firm
Advertising networks have recently played an increasingly important role in the online advertising market. Critical to the success of an advertising network are two mechanisms: an allocation mechanism that efficiently matches advertisers with publishers and a pricing scheme that maximally extracts surplus from the matches. In this paper, we quantify the value and investigate the determinants of a successful advertiser-publisher match, using data from Taobao’s advertising network. A counterfactual experiment reveals that the platform’s profit under a decentralized allocation mechanism is close to the profit level when the platform centrally assigns the matching under perfect knowledge. In another counterfactual experiment, we explore the effect of platform technology and revenue model on the strategic choice of the pricing schemes of list price vs. GSP auction pricing. We find that platforms that profit from the advertiser side may have less incentive to adopt GSP auction than platforms that profit from the publisher side.
Keywords: Advertising Network, Matching Game, Maximum Score Estimation, Generalized Second Price Auction, Platform Design
Our main objective in this paper is to measure the value of customers acquired from Google search advertising accounting for two factors that have been overlooked in the conventional method widely adopted in the industry: (1) the spillover effect of search advertising on customer acquisition and sales in off-line channels and (2) the lifetime value of acquired customers. By merging Web traffic and sales data from a small-sized U.S. firm, we create an individual customer-level panel that tracks all repeated purchases, both online and off-line, and tracks whether or not these purchases were referred from Google search advertising.
To estimate the customer lifetime value, we apply the methodology in the customer relationship management literature by developing an integrated model of customer lifetime, transaction rate, and gross profit margin, allowing for individual heterogeneity and a full correlation of the three processes. Results show that customers acquired through Google search advertising in our data have a higher transaction rate than customers acquired from other channels. After accounting for future purchases and spillover to off-line channels, the calculated value of new customers using our approach is much higher than the value obtained using conventional method. The approach used in our study provides a practical framework for firms to evaluate the long-term profit impact of their search advertising investment in a multichannel setting.