Using historical data from the third-party payment acquiring industry, I develop a statistical model to predict the probability of fraudulent transactions by the merchants. The model consists of two levels of analysis – the first focuses on fraud detection at the store level, and the second focuses on fraud detection at the merchant level by aggregating store level data to the merchant level for merchants with multiple stores. My purpose is to put the model into business operations, helping to identify fraudulent merchants at the time of transactions and thus mitigate the risk exposure of the payment acquiring businesses. The model developed in this study is distinct from existing fraud detection models in three important aspects. First, it predicts the probability of fraud at the merchant level, as opposed to at the transaction level or by the cardholders. Second, it is developed by applying machine learning algorithms and logistical regressions to all the transaction level and merchant level variables collected from real business operations, rather than relying on the experiences and analytical abilities of business experts as in the development of traditional expert systems. Third, instead of using a small sample, I develop and test the model using a huge sample that consists of over 600,000 merchants and 10 million transactions per month. I conclude this study with a discussion of the model’s possible applications in practice as well as its implications for future research.

Mobile applications (Apps) markets with App stores have introduced a new approach to define and sell software applications with access to a large body of heterogeneous consumer population. Several distinctive features of mobile App store markets including – (a) highly heterogeneous consumer preferences and values, (b) high consumer cognitive burden of searching a large selection of similar Apps, and (c) continuously updateable product features and price – present a unique opportunity for IS researchers to investigate theoretically motivated research questions in this area. The aim of this dissertation research is to investigate the key determinants of mobile Apps success in App store markets. The dissertation is organized into three distinct and related studies. First, using the key tenets of product portfolio management theory and theory of economies of scope, this study empirically investigates how sellers’ App portfolio strategies are associated with sales performance over time. Second, the sale performance impacts of App product cues, generated from App product descriptions and offered from market formats, are examined using the theories of market signaling and cue utilization. Third, the role of App updates in stimulating consumer demands in the presence of strong ranking effects is appraised. The findings of this dissertation work highlight the impacts of sellers’ App assortment, strategic product description formulation, and long-term App management with price/feature updates on success in App market. The dissertation studies make key contributions to the IS literature by highlighting three key managerially and theoretically important findings related to mobile Apps: (1) diversification across selling categories is a key driver of high survival probability in the top charts, (2) product cues strategically presented in the descriptions have complementary relationships with market cues in influencing App sales, and (3) continuous quality improvements have long-term effects on App success in the presence of strong ranking effects.

Due to the booming young mothers and fathers in the new era as well as the changes in the concept of parenting and the favorable liberalization of China's second child policy, the maternal-baby nursing market continues to grow, and it has become a must for businesses nowadays. In 2020, the size of the maternal-baby nursing market will reach 3.6 trillion. (Data: Yibang Power China's Maternal and Child Industry White Paper 2017).

The rapid development of mobile Internet, highly transparent information, consumers grasp the sovereignty, along with the rise of the middle class, consumption increase encouraged personalized, customized needs. The boundaries between online and offline are becoming increasingly blurred. Consumers are more inclined to choose multi-category with service channel providers. If the retailers still rely on good market resources, and the difference between the sales and purchase of commodities, they will face a huge challenge of the decrease in passenger flow and a decline in performance.

The paper takes the relationship between maternal-baby nursing retailers and targets customers as the study object, based on customer service of maternal-baby nursing retailer data, empirical studies, we found that this particular group, mothers and babies, especially value safety, quality, public praise and community review. If the retail enterprise attaches importance to establishing relationships with customers and enhances the relational viscosity through mutual trust, emotional formation and spread of public praise, it will help to increase the traffic volume and increase the output value of single customers.

The maternal-baby nursing retailers form a strong relationship between enterprises and customers by establishing a strong relationship between products and customers, employees and customers, and customers to customers. Maternal-baby nursing retailers operate single-customer value deeply, build a heavy membership system and manage customer assets, thereby enhancing their brand and performance.

The research on the method of establishing the strong tie can be considered as an analysis of feasibility. The research results of this paper will help to improve the overall customer service experience and satisfaction of the mother and infant retail industry, enhance the development of the whole industry and draw significance lessons from other service industries.

The emergence and fast growth of shared workspaces have attracted increasing attention from investors, practitioners, and researchers. Overall, this industry is still at an early stage of development and the business models of shared workspace providers are still evolving. To enhance the understanding of the different business models adopted by the leading shared workspace providers, I conduct an in-depth qualitative analysis of three current market leaders - Regus, WeWork, and UrWork – using the Business Model Canvas proposed by Osterwalder (2008). My analysis suggests that shared workspace providers creates value by offering three tiers of services: (1) satisfying users’ needs for physical office spaces, (2) helping them build an enterprise eco-system, and (3) facilitating the development of a user community. I further use the PEST model to analyze how the macro-environmental factors in China and U.S. may have contributed to the development of different shared workspace business models in these two countries. Based on the above analyses, I propose a list of factors that may be critical to investors’ valuations of shared workspace companies.

As securities companies occupy an increasingly important position in the national economy, and the most valuable competitive advantage for whom is human resources; therefore, Security Industry practitioners pay close attention to the influences of securities companies' incentive mechanisms regarding to various business types.

This paper finds that asymmetry of information in business models is the motivation of the gaming for all participants, through analyzing the differences of various business models of securities brokerage services. Further, various incentive mechanisms under different circumstances result in diverse strategies of gaming. It varies development paths of securities companies. Therefore, the purpose of the paper is to theoretically deduce the most reasonable and optimal securities companies’ incentive mechanism.

This paper intends to identify the principle component factors influencing securities brokerage services via questionnaire investigations towards 75 branches under the same securities company and 13 different securities companies, respectively. In addition, based on historical data, the paper aim to explain rationales between adjustments of incentive mechanisms and market shares of securities brokerage services.Lastly, combining author’s personal experience of various incentive mechanisms and development tracks in four securities companies that hopefully presents valuable information and clues for deducing the optimal securities company incentive mechanism.

There are two critical agency relationships in securities brokerage services. One is between principals, securities companies, and agents which are directors of branches. The other is between principals, securities companies, and agents which are securities marketers or brokers. Because of such operational setup, information is highly asymmetrical between all parties. It brought prominent problems regarding agency relationship and motivation aspects.

Under the certain circumstances, implementation of Incomplete Contracting Theory with franchising models in securities companies is quite useful. Specifically, for the former relationship between securities companies and marketers, the motivation effects of sub-license franchising are better than bonus compensation structure. Fixed salaries without bonus have the worst stimulating effects in such business model. For the latter relationship between securities companies and directors of branches, the agents focus on long term residual value claim rights, since it coincides with agents’ appraisals, focusing on incremental market shares and profit drawings.

Valuation adjustment mechanism has been widely applied in acquisitions of listed companies in China today, and is usually agreed upon future financial performance indicators of acquired companies (mostly net income). This paper examines how changes of key contents of VAM agreement affect firms’ ability to meet performance commitments from the perspective of incentive effects. Empirical results show that as the performance goals set in VAM agreement becomes higher, the incentive for management to meet performance commitments will initially increase and then decrease, so that the ratio of actual profits to promised profits for target firms will reach peak at some reasonable performance goal and then decrease. Second, as the level of the information asymmetry between buyer and seller turns higher, the incentive effect of performance goals becomes lower. Third, compared with cash-based compensation, stock-based compensation shows significantly higher incentive effects on promisors thus increasing the ability for target firms to achieve performance commitments.

As an alternative to the traditional public transportation system, (urban) rail transit has many advantages such as large capacity, fast speed, tight schedule, safety and comfort, and punctuality, , and has gradually become a top choice of many cities in countering environmental pollution and optimizing traffic quality. At the same time, we must also see that huge amounts of capital are required for the construction of rail transit. The traditional reliance on government investment clearly has its own limitations. The investment not only has a long cost-recovery cycle and a low rate of return, but also hardly attracts investments from the private sector. Therefore, when the government vigorously promotes the construction of a rail transit system, it is generally faced with problems such as a large funding gap and an overall financial loss. Therefore, how to establish a reasonable and efficient mode of investment and financing and further broaden the financing channels for rail transit projects is of great practical significance for improving the profitability of rail transit enterprises and realizing the sustainable development of rail transit. This thesis attempts to study the issue, in general, and further exmines a detailed case study of metro rail transit in a Chinsese city (city A), in particular.

The thesis first studies the concept and attributes of urban rail transit, and analyzes four modes and corresponding cases of urban rail transit investment and financing., It then discusses the characteristics of investment and financing of urban rail transit projects and the concept of investment and financing. Moreover, this thesis focuses on the current situation, characteristics and challenges of city A’s rail transit construction,. More specifically, it takes an in-depth look at the financial planning, investment and financing planning and the investment and financing channels products. The study innovatively puts forward three models, namely, PPP, TOD, ABS of rail transit investment and financing products. Based on the AHP decision-making method, the study shows PPP as the optimal integrated choice for city A. Finally, based on the core issues of the domestic urban rail transit project investment and financing, this thesis analyzes the rationality of the PPP model thoroughly and comes up with some managerial and policy suggestions on how to further optimize the investment and financing of the urban rail transit construction from the perspectives of the government management and the rail transit enterprises

This study examines the 3 key questions of media budget allocation, to find our a better invest model. Including spending share of traditional media and digital media, program selection strategy and duration mix optimization to analyse the trend of sample A (a global cosmetic brand) . Based on every test media campaign, we do research of media performance and sales volumn, add youth consumer behavior result, to develop a media investment ROI model for this brand. Create the evaluation system according to past big data and find the learnings of different length TVC usage. Of course all relavant findings and implications will be summarized after every section.

Private placement is an important financing tool for listed companies in China, and the lock-up arrangement is its supporting system. The Efficient Market Hypothesis suggests that, if investor expectations are unbiased, there will be no abnormal fluctuations in the stock prices of listed companies before and after the unlocking day. However, around the time of the unlocking of private placement shares, the stock prices generally show a V-shaped pattern.

Through the empirical analysis of the Chinese A-share stocks from May 8th,2006 to December 31st, 2016, I found that from the 40th day before the unlocking day to the 90th day after, the stock price showed an evident first-downward-then upward trend. The lowest price appeared near the unlocking day. Meanwhile, the greater stocks fall before the unlocking day, the greater prices rise after that. The characteristics of the distinctive difference between the stock prices before and after the unlocking day can provide investment opportunities.

By reviewing research on investor behavior, this paper suggests that the V-shaped pattern can be explained by the influence of investors’ psychological factors on their trading behavior. The general performance of the stocks before the unlocking day is negative due to the increasing uncertainty perceived by investors. After the unlocking day, the uncertainty gradually disappears and the stock rebounds. In addition, I found that stock returns during the lock-up period, shareholder background, and the length of lock-up period also had significant impacts on the V-shaped price trend.

Under the background of the "new normal" of China's economy and the contraction of traditional financial sector, the development of Internet finance provides new financing channels for SMEs and individual financial needs. But with rapid development of the Internet finance, the overall risk also appears gradually as well as the platform differentiation appears more evidently. China's Internet financial industry enters the stage of standardization development. In order to effectively prevent and resolve Internet financial risks and create a good internet financial environment, we need to identify the risk factors of Internet financial industry. Through reference carding of the existing literature, this paper proposes a research hypothesis that the industrial economic background is negatively related to the operating risk of the Internet financial platform. After descriptive statistical analysis of the current situation of the Internet financial industry in China, this paper collects 600 P2P net-lending platforms data manually, and uses Probit model to test the research hypothesis. Ceteris paribus, the result show that compared with the platform without industrial economic background, the risk probability of the industrial economic background platform will be reduced by 6.5 percentage points， and there is no regional difference in this result. This paper explains the result from two layers which are the relieving information asymmetry and the platform’s reputation mechanism. The study also finds that in addition to the industrial economic background, the P2P platform's registered capital, operation time, whether the platform funds have the corresponding third-party guarantee and the information disclosure of platform executives will significantly reduce business risk probability of the platforms. The above research conclusions also passed the robust test. Finally, this paper makes a case analysis of the two Internet Financial platforms in Suning Finance and Tuniu Finance, which have different industrial economic background and mode of operation. It also summarizes the risk control system.