The Influence of Price Discrimination from Airports on the Route Development Behavior of Airlines

Given the prominence and magnitude of airport incentive schemes,it is surprising that literature hitherto remains silent as to their effectiveness.In this paper,the relationship between airport incentive schemes and the route development behavior of airlines is analyzed.Because of rare and often controversial findings in the extant literature regarding relevant influencing variables for attracting airlines at an airport,expert interviews are used as a complement to formulate testable hypotheses in this regard.A fixed effects regression model is used to test the hypotheses with a dataset that covers all seat capacity offered at the 22 largest German commercial airports in the week 46 from 2004 to 2011.It is found that incentives from primary choice,as well as secondary choice airports,have a significant influence on Low Cost Carriers.Furthermore,Low Cost Carriers,in general,do not leave any of both types of airports when the incentives cease.In the case of Network Carriers,no case is found where one joins a primary choice airport and receives an incentive.Insufficient data between Network Carriers and secondary choice airports in the time when incentives have ceased means that no statement can be given.

A Blockchain-Based Protocol for Malicious Price Discrimination

Serious price discrimination emerges with the development of big data and mobile networks,which harms the interests of consumers.To solve this problem,we propose a blockchain-based price consensus protocol to solve the malicious price discrimination faced by consumers.We give a mathematical definition of price discrimination,which requires the system to satisfy consistency and timeliness.The distributed blockchain can make the different pricing of merchants transparent to consumers,thus satisfying the consistency.The aging window mechanism of our protocol ensures that there is no disagreement between any node on the consensus on price or price discrimination within a fixed period,which meets the timeliness.Moreover,we evaluate its performance through a prototype implementation and experiments with up to 100 user nodes.Experimental results show that our protocol achieves all the expected goals like price transparency,consistency,and timeliness,and it additionally guarantees the consensus of the optimal price with a high probability.

Applied Study of Price Discrimination Implemented on a Two-Path Route Expressway

This study aims at implementing price discrimination to get maximum revenue on a two-path route expressway, focusing on the problems which occur in traffic forecasting when applying a ＂profit-maximizing＂ toll designed to maximize revenue for a certain toll road in Japan. A break-even discussion is inevitable in the process of planning a certain toll road. According to the theory of transportation economics, market segmentation price discrimination is supposed to be efficient in the transportation market to increase the revenue of fixed facilities. In the model, a bypass and an adjacent expressway form a two-path route section. Two different toll levels are implemented for the bypass： one is for through traffic, and the other is for insideinside and inside-outside traffics. This two-path route plus two-toll-level system thus causes difficulty in traffic assignment that is based on the minimum route searching method. In the study, a rational approach of adjusting the through traffic is implemented to predict the traffic flow as well as revenue on two parallel routes with different toll levels. The approximate calculation method that fixes the split rate of the passing through traffic flow is applied to solve the two-path route plus two-toll-level problem since passing through traffic is price elastic. Market segmentation pricing, which gives two toll levels in a toll road, is proved to be practical for increasing revenue. The results are also verified to be rational by using the survey data of Meishin Expressway.

A model of targeted advertising with customer recognition

A two-period duopoly model is developed to examine the competitive effects of targeted advertising with customer recognition （TACR）. In the model, two competing firms sell goods to end consumers in the first period, during which customer recognition is obtained. In the second period, advertising can be targeted toward different consumer types. Advertising is assumed to be persuasive in the way that consumer valuation is increased. Equilibrium decisions and profits in each period are derived, showing that the firm who loses the current competition will win in the future. As a result, forward-looking firms price less aggressively so that their long-term profits can be enhanced with the help of TACR. Particularly, TACR improves profits through three important effects： valuation increasing, customer poaching, and anti-competition. Finally, this paper investigates the welfare issues, showing that firms enhance profits at the expense of consumer surplus. It is, therefore, suggested that public sectors take a step to protect consumers with the rapid development of targeting technology.

Imperfect targeted advertising with two-period competition

A two-period model is developed to investigate the competitive effects of targeted advertising with imperfect targeting in a duopolistic market. In the first period, two firms compete in price in order to recognize customers. In the second period, targeted advertising plays an informative role and acts as a price discrimination device. The firms＇ optimal advertising and pricing strategies under imperfect targeting are compared with those under perfect targeting. Equilibrium decisions show that, under imperfect targeting, when the advertising cost is low enough, both firms will choose to target ads at the rivals＇ old segments. This equilibrium, which could not exist under perfect targeting, results in two opposite results. When cost is high, the effect of mis-targeting will soften price competition and increase profits; on the contrary, when cost is low enough, it will lead to aggressive price competition and profit loss with the increase of imperfect targeting, so firms may have incentives to reduce the mis- targeting degree.

Business Analysis of Didi Chuxing in the Chinese Ride-hailing Market

This essay presents my analysis of Didi Chuxing’s ride-hailing business in the Chinese market considering economic concepts and tools such as market structure,economies of scale and price anchoring to understand aspects of Didi Chuxing such as its cost structure,pricing strategies and marketing methods.As the largest ride-hailing platform in China,the success of Didi Chuxing can offer important guidelines for the healthy development and expansion of this industry to other countries.

The Role of Consumer Privacy Concerns in Shaping Platform Strategy for Online Markets

We investigate the effects of consumer privacy concerns on the pricing and personal data collection strategy of an online platform.The online platform derives revenues from disclosing consumer information to firms.Firms compete for the information in order to enable them to price discriminate and thus derive revenues from consumer purchases.A novel aspect of our research is that we allow the online platform to sell only a subset of consumer data.We develop analytical models where consumers can/cannot protect their privacy.Our analysis yields three main conclusions.First,in the monopoly case,we find that when the consumer privacy disclosure aversion cost is relatively low,it is optimal for the platform to sell all consumer information to the firm.Second,in the duopoly case,we illustrate that when the consumer privacy disclosure aversion cost is relatively low,the platform will sell all consumer information to only one firm;when the cost is moderate,the platform will choose to sell the information of only some consumers and to only one firm;when the cost is relatively high,the platform will select only some of the consumers and sell their information to both firms.Third,it will be better for the platform to provide the information protection service for free when the privacy cost is low.

Computational pricing in Internet era

Pricing plays a central rule to a company＇s prof- itability, and therefore has been extensively studied in the literature of economics. When designing a pricing mech- anism/model, an important principle to consider is ＂price discrimination＂, which refers to selling the same resources with different prices according to different values of buy- ers. To meet the ＂price discrimination＂ principle, especially when the number of buyers is large, computational methods, which act in a more accurate and principled way, are usu- ally needed to determine the optimal allocation of sellers＇ re- sources （whom to sell to） and the optimal payment of buyers （what to charge）. Nowadays, in the Internet era in which quite a lot of buy and sell processes are conducted through Internet, the design of computational pricing models faces both new challenges and opportunities, considering that （i） nearly real- time interactions between people enable the buyers to reveal their needs and enable the sellers to expose their information in a more expressive manner, （ii） the large-scale interaction data require powerful methods for more efficient processing and enable the sellers to model different buyers in a more precise manner. In this paper, we review recent advances on the analysis and design of computational pricing models for representative Internet industries, e.g., online advertising and cloud computing. In particular, we introduce how computa- tional approaches can be used to analyze buyer＇s behaviors （i.e., equilibrium analysis）, improve resource utilization （i.e., social welfare analysis）, and boost seller＇s profit （i.e., revenue analysis）. We also discuss how machine learning techniques can be used to better understand buyer＇s behaviors and design more effective pricing mechanisms, given the availability oflarge scale data. Moreover, we make discussions on future re- search directions on computational pricing, which hopefully can inspire more researchers to contribute to this important domain.

A Characterization for Dominant Strategy Implementation

We introduce a perfect price discriminating mechanism for allocation prob- lems with private information. A perfect price discriminating mechanism treats a seller, for example, as a perfect price discriminating monopolist who faces a price schedule that does not depend on her report. In any perfect price discriminating mechanism, every player has a dominant strategy to truthfully report her private infor- mation. We establish a characterization for dominant strategy implementation： Any outcome that can be dominant strategy implemented can also be dominant strategy implemented using a perfect price discriminating mechanism. We apply this charac- terization to derive the optimal, budget-balanced, dominant strategy mechanisms for public good provision and bilateral bargaining.