Customer Segmentation Strategy of Crowdfunding Platform with Completion Time Uncertainty

While crowdfunding allows firms to raise external capitals from a large group of audience, firms are often unable to control their production process, and the project may fail without being completed on time. Having this in mind and knowing that consumers are heterogeneous in accepting late completion, fundraising firms often offer multiple reward plans to do customer segmentation to maximize the fund they may raise. Popular segmentation tools include early shipment promise and refund policy. Using a game-theoretic model, we show that the firm should adopt one of the two screening tools, but not both. Which tool a fundraising firm should choose is also examined. Our conclusions offer insights into managerial decisions for firms using crowdfunding in their early project development

MAY A HEALTHCARE SOCIAL NETWORKING SITE HELP REVEAL HIDDEN QUALITY OF A HEALTHCARE PROVIDER?

In this study, we discuss an information asymmetry problem between a healthcare provider and consumers, and examine the strategy for a platform owner to mitigate this problem. Because the Internet has become a major media for healthcare information sharing, we believe that social networking sites may mitigate the problem of information asymmetry by providing a more efficient way to facilitate information sharing and quality disclosure. We develop a game-theoretic model describing the process of information exchange among healthcare consumers themselves and the platform on a social networking site. We show that this “strategy” of engaging in social networking sites is indeed helpful for revealing the quality information of a healthcare provider, and the existence of a healthcare social networking site does benefit patients. Finally, we discuss factors affecting the platform owner’s decision

Pricing and Diversification of Massive Online Open Course Platforms

Massive Open Online Courses (MOOCs) have recently received a great deal of attention in higher education. MOOCs demonstrate universities’ efforts in offering high-quality digital learning materials to everyone in the world, which should be encouraged. Nevertheless, as a MOOC platform must ensure its financial sustainability, it is questionable whether a platform’s profit-seeking pricing strategy will hurt the diversity of courses, such as eliminating courses with low certificate purchasing rates. To address this question, we adopt a game-theoretic framework to model the interaction and strategic choices of a MOOC platform, learners, and universities. Based on the certificate prices and revenue sharing ratios chosen by the platform for courses with various certificate purchasing rates, universities consider the competition intensity and decide their course quality levels, to attract learners. We conclude that all types of course will exists in equilibrium throughout the lifecycle of a MOOC platform, regardless of the technology maturity and competition intensity. We also find that course qualities may decrease when MOOCs become more accessible to learners. Finally, qualities of courses with different certificate purchasing rates are compared

PLATFORM DELIVERY: A GAME-THEORETIC ANALYSIS OF A NEW DELIVERY MODEL IN THE SHARING ECONOMY

Owing to the advances in technology, new types of service delivery spring up in the sharing economy. Owning no warehouse and hiring no full-time shippers, Instacart runs its grocery delivery service by delivering grocery from independent retailers by independent contractors to its consumers. This “platform delivery” model is formulated as a game-theoretic model and investigated. We discuss the profitability of three common pricing strategies, membership-based pricing, transaction-based pricing, and cross subsidization. It is shown that these three strategies generate the same amount of profit for the perfectly patient platform. However, in general the membership-based strategy would be better than the others

The Optimal Pricing Strategy of a Mobile Payment Service in a Two-sided Market

Acknowledging the high penetration rate of mobile devices, mobile payment is currently a hot topic and is expected to reach the tipping point of rapid growth. For such a nascent market, how to run a successful mobile payment platform remains unanswered. Therefore, we devote this study to investigate the pricing strategy of proximity mobile payment. Mobile payment serves as a two-sided platform connecting merchants and customers. By leveraging the emergent mobile payment knowledge, we present a game-theoretic model featuring network externality. In the short run, we find the platform will have incentives to apply “divide and conquer” strategy by subsidizing customers to adopt the mobile payment service at the beginning of the business. After the ignition, the platform then becomes profitable by charging per transaction fee from the merchants. In the long run, the subsidization strategy is suggested to be applied when the bank is not taking too much processing fee and leaves sufficient market share to the mobile payment platform. In terms of contributions to practice, this study offers a step forward of method to identify this promising market for mobile payment executives, financial institutes and all others ecosystem

Price Negotiation for Taxi Services under Private Customer Urgency

We study whether the efficiency of the taxi industry can be improved by introducing price negotiation into the current pricing scheme. In particular, we examine a new business model for a taxi company to offer multiple contracts with various guaranteed travel times and prices when a customer books a taxi service. By considering the fact that customers can privately observe their urgency levels, we show that the proposed new pricing scheme in equilibrium induces higher taxi speed, serves more customers, and may enhances the utilities of the company and customers simultaneously

Mechanism Design for Multi-layer Supply Chains

In this dissertation, we consider a three-layer supply chain with a manufacturer, a reseller, and a salesperson. In the manufacturer's target market, the sales outcome is jointly determined by the market condition and the salesperson's sales effort. While the salesperson can privately observe both, the manufacturer observes none. If the manufacturer contracts with the salesperson directly, it faces a mixture of the adverse selection and moral hazard problems. Because the reseller has a closer contact to the market and the salesperson, she can better monitor the two pieces of private information. Therefore, the manufacturer may delegate the sales responsibility to the reseller to indirectly mitigate the inefficiency caused by information asymmetry. As different resellers have different monitoring expertise, the manufacturer faces a supply chain construction problem by deciding which reseller to delegate to. Unlike traditional two-layer principal-agent problems in which the principal searches for the optimal direct monitoring functions, this dissertation studies the optimal strategy of indirect monitoring. Using the mechanism design approach and extending the traditional principal-agent model, we discuss the manufacturer's reseller selection strategy and the embedded salesforce compensation problem faced by the reseller. When the reseller can either observe the market condition or the sales effort, we show that the manufacturer should delegate to the latter one. We then study the reseller's resource allocation problem when the reseller can estimate the two aspects, both imperfectly, subject to a fixed budge constraint. When the reseller can only estimate the market condition, we show that the manufacturer's expected profit is convex on the reseller's accuracy. Collectively, our results deliver insights to manufacturers in selecting their reselling partners with various monitoring abilities and answers how the reseller's monitoring functions affect the supply chain performance

Autonomous vehicle services or ride-sharing services? A game theoretic investigation

Transportation service is rapidly changing in past few decades. On one hand, ride- sharing services in the sharing economy impacts the transportation industry. On the other hand, autonomous vehicles may also revolutionize transportation services. We consider a transportation service provider choosing between offering ride-sharing services or autonomous vehicle services. For each service mode, we derive its optimal prices, subsidies, revenue sharing proportions, and quantity of vehicle deployment. A comparison between these two modes is then conducted. We find that the autonomous vehicle service is more profitable than the ride-sharing one under economy of scale. Interestingly, the optimal service price decreases in the cost of deploying autonomous vehicles. Our study thus sheds lights in the choice of quality incentive and price incentive

Quantifying the Risk of Innovation: A Patent Knowledge Management Approach

Innovation can enhance the usefulness of products and services, but technological innovation may be hindered by many potential barriers. One important potential barrier is patent infringement, whose risk must be evaluated and quantified when a firm works on innovation. Previous studies have focused on patent quality, patent value, and the use of patents as indicators of company competitiveness, but to our knowledge there have been no previous studies discussing the evaluation or forecasting of patent infringement risk. To address this issue, we conduct a knowledge management study to reexamine the relationship between patent quality/value and patent litigation, identify patent risk factors, and build a regression model for evaluating patent infringement risk. We make two important discoveries during the course of this study. First, we found that certain factors do not hold significant amounts of impact in all technological fields. Second, we discover that the same factor may not have the same impact in differing technological fields