Sellers in Online Auction Markets: Introducing a Feedback-Based Classification

Trading in the online consumer-to-consumer (C2C) auction market necessitates buyers and sellers to engage in transactions with anonymous counterparts. The sequence of paying first and then taking delivery introduces a great amount of risk for potential buyers. In order to assist buyers in dealing with this risk, online auction markets (OAMs) are employing reputation-scoring systems and traders can be classified in terms of their online reputation scores. A review of the literature suggests a conspicuous absence of the study on any standard classification of sellers in OAMs. Lack of such a classification hinders systematic research and theory development. Therefore, a classification of sellers, based on the total number of unique feedbacks (a surrogate measure for certainty regarding repetition of past behaviors), negative feedback rate (a surrogate measure for risk based on prior poor performance), and nature of negative feedbacks (a surrogate measure for the degree of risk), is proposed to advance our understanding of the online C2C auction markets. Toward demonstrating the classification’s systemic power, we present a propositional inventory developed from the classification and discuss how the classification accommodates current research and furthers theory building

Negative Reputation Rate as the Signal of Risk in Online Consumer-to-Consumer Transactions

Previous online reputation research has been focused on the effects of positive and negative reputations on trust formation, trading price, and probability of sale. We propose that negative feedback rate (NFR) is the most important indicator of the risk of buying from a seller online. This proposition has been supported by an empirical study based on data collected from eBay.com. We found that the 6-month NFR in the current period predicts much better the future risk measured by the NFR in the next 6-month period than did net reputation score and negative reputation score. A seller’s life-long negative score in fact was not significant in predicting the future risk. In addition, a seller’s age in the market was found to have similar predicting power on risk as did net reputation score

USING NON-FINANCIAL DATA TO ASSESS THE CREDITWORTHINESS OF BUSINESSES IN ONLINE TRADE

Assessing the creditworthiness of prospective business partners is the first step in conducting trade. Traditionally the creditworthiness of partners was assessed using transactional methods, methods based on close observation of the other party and the heavy use of mostly subjective, soft information. During recent decades, however, these relational methods were largely replaced with transactional methods relying almost exclusively on objective financial data, otherwise known as hard data. A considerable portion of firms involved in business to business trade are now small companies that do not to have any reliable or comparable financial information. In the absence of such information, transactional methods of assessing business creditworthiness have very limited practical value. To provide a remedy, this study proposes using non-financial information available from the Web and thus a return to the more transactional methods. We identify sources of credit-related information available from a typical business to business exchange and test if such information can predict firm creditworthiness. We conduct a study with a group of online businesses on a major B2B exchange and empirically show that a number of non-financial factors can in fact predict online businesses’ level of creditworthiness

Control in Open Source Software Development

Open source software is a revolution in software development, and has great impact on the software industry today. It is significantly different from the traditional software development in organization, process and management. Control mechanisms are important to the success of collaborative work, especially for open source software development which is community-based and loosely structured in nature. This paper investigates the control modes in open source community based on control theories and finds that portfolios of outcome, clan and self-controls are used in open source community, and the control modes change with the evolution of an open source community

A Comparative Study on Hotel Consumers’ Online Feedback Behaviors

This paper is intended to analyze the interrelationship between the textual comment and the itemized rating in consumers\u27 online feedback, and to study differentiations among diversified segments of consumers who leave the feedback. The data were collected from both an international top tourism service website which operates hotel booking services internationally and offers online hotel reputation feedback services, and its China host website. Based on the coded comments and itemized ratings from the dataset, our study shows that different customer segments demonstrate varied interrelationship behavioral patterns, and factors like satisfaction and contextual backgrounds will matter. The findings from this research may help hotels to develop varied marketing strategies for different segment of customers, and help online reputation sites to improve their services by distinguishing dissimilar behavioral patterns in different customer segments

Integrating PPC and Flat Fee Pricing Schemes to Optimize the Internal Search Engine Revenue in the Electronic Market

Currently, the predominant pricing plan for the search engine (SE) advertising services in a proprietary electronic market is a flat fee (FF) pricing. These services have faced the challenge of customer attrition recently since FF pricing results in the inequality of service surplus among subscribers. A more sustainable and profitable pricing model would be to distinguish advertising resources by providing an additional usage-based pricing for certain user groups to transfer the service surplus among subscribers. We conceive a hybrid model integrating Pay-Per-Click (PPC) pricing into FF pricing. This proposed scheme can offer an incentive-compatible mechanism to attract more subscribers by relieving the inequity of service surplus, and eventually result in the increasing revenue of service providers

IEEE 802.20 Based Broadband Railroad Digital Network – The Infrastructure for M-Commerce on the Train

The broadband wireless access is emerging as a promising technology to meet the ever-increasing demand of M-commerce on the train. The traditional railroad communication system (RCS) is not only in charge of the traditional train scheduling, but also offers broadband WLAN services to passengers and provides the network platform to the intelligent railroad information system. This imposes a major challenge on the capability of the RCS in response to the increasing application requirements, particularly, the one for ubiquitous Internet access. To take the advantage of the rapid evolving mobile communication technology, this paper proposes an IEEE 802.20 based broadband railroad digital network, namely BRDN, for the next generation RCS. The paper further presents the scenario how BRDN operates and identifies the IP mobility as the major technical issue to be solved for BRDN. The predictability of mobile IP for the train-based applications will ease the difficulties in implementing BRDN. With the availability of IP standard for the next generation Internet - IPv6, BRDN will eventually become a reality

Social Network Effect on Bidding Strategy Adoption in Online P2P Lending Market

Bidding strategy in online auctions, as a sort of strategic behavior, can help bidders to get what they want more efficiently and effectively. It receives much attention in many researches. However, the determinants of bidding strategy adoption still remain unclear. In this study, we investigate the role of social network in bidding strategy adoption using real transaction data from an online P2P lending market. The analyses reveal that 1) bidding strategy tends to be homogeneous in different online social networks. 2) Joining an online social network does not change the bidding strategy adoption behavior significantly. 3) The size of social network will affect bidding strategy adoption and smaller ones are more homogeneous than bigger ones. 4) In a social network, bidders with different roles have different preferences on bidding strategies. Our findings can be considered as important empirical evidences for theories about social influence and human behavior

A Cost-Effective Critical Path Approach for Service Priority Optimization in the Grid Computing Economy

The advancement in the utilization and technologies of the Internet has led to the rapid growth of grid computing; and the perpetuating demand for grid computing resources calls for an incentive-compatible solution to the imminent QoS problem. This paper examines the optimal service priority selection problem that a grid computing network user will confront. We model grid services for a multi-subtask request as a prioritized PERT graph and prove that the localized conditional critical path, which is based on the cost-minimizing priority selection for each node, sets the lower bound for the length of cost-effective critical path that commits the optimal solution. We also propose a heuristic algorithm for relaxing the nodes on the noncritical paths with respect to a given critical path.link_to_subscribed_fulltex