Yi Liu, Pinar Yildirim, Z. John Zhang (Under Review), Implications of Revenue Models and Technology for Content Moderation Strategies.
Abstract: This paper develops a theoretical model to study the economic incentives for a social media platform to moderate user-generated content. We show that a self-interested platform can use content moderation as an effective marketing tool to expand its installed user base, to increase the utility of its users, and to achieve its positioning as a moderate or extreme content platform.
For the purpose of maximizing its own profit, a platform will balance pruning some extreme content, thus losing some users, with gaining new users because of a more moderate content on the platform. This balancing act will play out differently depending on whether users will have to pay to join (subscription vs advertising revenue models) and on whether the technology for content moderation is perfect.
We show that when conducting content moderation optimally, a platform under advertising is more likely to moderate its content than one under subscription, but does it less aggressively compared to the latter when it does. This is because a platform under advertising is more concerned about expanding its user base, while a platform under subscription is also concerned with users' willingness-to-pay. We also show a platform's optimal content moderation strategy depends on its technical sophistication. Because of imperfect technology, a platform may optimally throw away the moderate content more than the extreme content. Therefore, one cannot judge how extreme a platform is by just looking at its content moderation strategy. Furthermore, we show that a platform under advertising does not necessarily benefit from a better technology for content moderation, but one under subscription does, as the latter can always internalize the benefits of a better technology. This means that platforms under different revenue models can have different incentives to improve their content moderation technology. Finally, we draw managerial and policy implications from our insights.
Yi Liu, Pinar Yildirim, Z. John Zhang (Under Revision), Consumer Preferences and Firm Technology Choice.
Abstract: Advances in intelligent technologies change the way consumers search and shop for products. Emerging is the trend of home-shopping devices such as Amazon's Alexa and Google Home, which allow consumers to search or order products using voice commands. We study the impact of such artificial intelligence (AI) enabled devices on a brand's channel strategy and its price discrimination across these channels. After making a theoretical breakdown of the functionalities of the AI-enabled shopping devices into (1) adding convenience in ordering procedure ("OC") and (2) providing support in purchase decision-making ("DS"), we document via a set of experiments that consumers who have strong (weak) shopping preferences are less-inclined to shop through AI-enabled devices with the functionality of DS (OC) compared to their existing shopping heuristics. The hesitation of the group to adopt AI-enabled shopping devices makes it efficient for a brand operating in a competitive environment to price discriminate across distribution channels. In the second part of the paper, we build an analytical model and derive the equilibrium distribution and pricing strategies for competing brands conditional on the heterogeneity of consumers with respect to their willingness to adopt AI-enabled devices. We also analyze the welfare impact of the introduction of AI technology as a new possible distribution channel.
Pinar Yildirim, Yanhao Wei, Christophe Van den Bulte, Joy Lu (2020), Social Network Design for Inducing Effort, Quantitiave Marketing and Economics, 18, pp. 381-417.
Abstract: Many companies create and manage communities where consumers observe and exchange information about the effort exerted by other consumers. Such communities are especially popular in the areas of fitness, education, dieting, and financial savings. We study how to optimally structure such consumer communities when the objective is to maximize the total or average amount of effort expended. Using network modeling and assuming peer influence through conformity, we find that the optimal community design consists of a set of disconnected or very loosely connected sub-communities, each of which is very densely connected within. Also, each sub-community in the optimal design consists of consumers selected such that their “standalone” propensity to exert effort correlates negatively with their propensity to conform and correlates positively with their propensity to influence others.
Pinar Yildirim (2020), Social Network Design for Inducing Effort, Quantitative Marketing and Economics.
Pinar Yildirim, Are Political and Charitable Giving Substitutes? Evidence from the United States.
Abstract: We provide evidence that individuals substitute between political contributions and charitable contributions, using micro data from the American Red Cross and Federal Election Commission. First, we find that foreign natural disasters, which are positive shocks to charitable giving, crowd out political giving. Second, we show that political advertisement campaigns, which are positive shocks to political giving, crowd out charitable giving. Our evidence suggests that individuals give to political and charitable causes to satisfy similar needs, and some of the drivers of charitable giving, such as other-regarding preferences, may be driving political giving too.
Pinar Yildirim (2018), Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives, European Journal of Operations Research.
Pinar Yildirim (Working), Could “Less” Be “More” in Signaling Wealth?.
Hanna Halaburda, Mikolaj Jan Piskorski, Pinar Yildirim (2016), Competing by Restricting Choice: The Case of Search Platforms, Management Science.
Pinar Yildirim, Jessie Liu, Z. John Zhang (Working), Conspicuous Consumption on the Long Tail: How can luxury brands benefit from counterfeits?.
Pinar Yildirim, Jennifer Shang, Guoquan Zhang (2016), Optimal Pricing for Group Buying with Network Effects, Omega, 63 (September), pp. 69-82.
Less Is More: Redefining the Luxury Goods Market