Accepted Papers

Design of a Multiagent-based E-Marketplace to Secure Service Trading on the Internet

Qin Li, Keith M. Martin and Jie Zhang

Abstract: Electronic marketplaces are not always easily regulated us- ing traditional legal systems. As a result, suitable dispute prevention and resolution mechanisms for electronic marketplaces are of interest to design. In this paper, we design a multiagent-based e-marketplace where participants represented by autonomous software agents may be egocentric, strategic and even malicious. Our marketplace focuses on trading arbitrable and replicatable services, such as computational resources and data storage, over the Internet. We propose a novel dispute prevention and resolution mechanism that is theoretically proven to be able to induce good conduct for marketplace participants. Our marketplace also features cost-effectiveness, robustness and budget balance.

Online information search and utilization of electronic word-of-mouth

Essi Pöyry, Petri Parvinen, Jari Salo, Hedon Blakaj, and Olli Tiainen

Abstract: Research on online consumer information search behavior has typically concentrated on search-type information instead of experience information. This article focuses on electronic word- of-mouth (eWOM) as a source of experience information, and we study the relationships between the antecedents, amount and utilization of eWOM searched. Using survey data from 1660 customers of two travel agencies, we find that 1) the search for eWOM differs distinctively from the search for marketer- generated online content, and 2) the more eWOM is being searched, the less it is being utilized in the final purchase decision.

Automated Analysis of Weighted Voting Games

Shaheen Fatima, Michael Wooldridge, and Nicholas Jennings

Abstract: Weighted voting games (WVGs) are an important mechanism for modeling scenarios where a group of agents must reach agreement on some issue over which they have different preferences. How- ever, for such games to be effective, they must be well designed. Thus, a key concern for a mechanism designer is to structure games so that they have certain desirable properties. In this context, two such properties are PROPER and STRONG. A game is PROPER if for every coalition that is winning, its complement is not. A game is STRONG if for every coalition that is losing, its complement is not. In most cases, a mechanism designer wants games that are both PROPER and STRONG. To this end, we first show that the problem of determining whether a game is PROPER or STRONG is, in general, NP-hard. Then we determine those conditions (that can be evaluated in polynomial time) under which a given WVG is PROPER and those under which it is STRONG. Finally, for the general NP-hard case, we discuss two different approaches for over- coming the complexity: a deterministic approximation scheme and a randomized approximation method.

A Dynamic Unit-Demand Auction Supporting Bid Revision

Chinmayi Krishnappa, and Greg Plaxton

Abstract: We present a dynamic unit-demand auction that supports arbitrary bid revision. Each round of the dynamic auction takes a tentative allocation and pricing as part of the input, and al- lows each bidder — including a tentatively allocated bidder — to submit an arbitrary unit-demand bid. We establish strong properties of the dynamic auction related to truthfulness and efficiency. Using a certain privacy preservation property of each round of the auction, we show that the overall dynamic auction is highly resistant to shilling. We present a fast algorithm for implementing the proposed auction. Using this algorithm, the amortized cost of processing each bidding operation is upper bounded by the complexity of solving a single-source shortest paths problem on a graph with nonnegative edge weights and a node for each item in the auction. We propose a dynamic price adjustment scheme that discourages sniping by providing incentives to bid early in the auction.

Conceptualizing E-Selling

Petri Parvinen, Olli Tiainen, Jari Salo, Essi Pöyry, and Hedon Blakaj

Abstract: This research explores and investigates the conceptualization of e- selling. A review and 42 in-depth interviews with industry experts show that e-selling is seen as an activity distinct from e- commerce, e-marketing and e-retailing - digital human-like interaction directed at increasing customer value by securing a business exchange. The article discovers 16 different interactivity cues that do not fit the traditional concepts of e-commerce and e- marketing. The results also identify several key issues for the future of e-selling, including value creation-orientation and serving hedonism.

An Empirical Investigation of Mobile Channel Usage and Mutual Influence with Internet Channel

Jonghun Jung, and Byungtae Lee

Abstract: Advances in information technology have increased the number of people using mobile device and have made mobile service pervasive. In spite of increase of rapid diffusion and usage of mobile service, previous papers mainly focused on figuring out factors influencing the mobile technology adoption but understanding of customer behavior regarding the usage of mobile channel is lacking. Moreover, mobile service channel is one of alternative channels and customer choice of one service channel affects customer use of other channels. We investigate the relationship between service channels. Specifically, this paper empirically investigates the mutual influence between internet and mobile channels in banking service through VAR test using data of Korea online banking service. Our result shows that, as customer’s use of mobile channel increases, it has influences on internet channel use, and vice versa. Customers using mobile banking service channel tend to use internet banking service as a complementary channel. On the contrary, the use of internet banking service does not have an influence on the use of mobile banking service channel. Additionally, the trait of this relationship depends on the characteristic of task. Also cross channel influence is differentiated by banking service task. This paper provides the understanding of customer behavior in multiple service channels and implication that strategic management of multi-channel has to be concerned in terms of relationship between service channels.

A Multi-Choice Offer Strategy for Bilateral Multi-Issue Negotiations Using Modified DWM Learning

Hae Young Noh, Kivanc Ozonat, Sharad Singhal, and Yinping Yang

Abstract: This paper introduces a “multi-choice” offer strategy for an automated agent conducting bilateral multi-issue negotiations in an agent-to-human negotiation setting. Assuming that a rational human counterpart is more likely to concede on less important issues, we developed a modified dynamic weighted majority (DWM) learning algorithm for the negotiation agent to estimate the issue weights and issue ranks of the human counterpart. The agent then utilizes these estimates to strategically propose counter-offers with multiple choices to the human counterpart. This strategy allows the agent to expedite the negotiation process and increase the chance of agreement by improving the satisfaction level of the counterpart. We validated this offer strategy using two sets of buyer behavior data: one simulated based on time-dependent behavior models used in the literature, and another collected from a human experiment on automated negotiations. Results indicate that, when compared to other offer strategies described in the literature with similar learning speeds, (i) the modified DWM-based learning algorithm estimates the counterpart’s issue weight/rank more accurately, and (ii) the multi-choice offer strategy utilizing the learning algorithm makes more attractive offers to the counterpart while maintaining the same utility for the agent.

Transforming Social Networking from a Service to a Platform: a Case Study of Ad-hoc Social Networking

Vedran Podobnik, and Ignac Lovrek

Abstract: In this paper we discuss how a synergy of fundamental concepts standing behind the Facebook (i.e., social networking) and the iPhone (i.e., mobile and pervasive platform) can generate a sustainable business model for the ICT industry. Namely, we will show that a transformation of social networking from a service to a mobile and pervasive platform can produce multiple benefits for both social network service providers as well communication operators/smartphone manufacturers, while provisioning end- users an added value. Additionally, we will demonstrate our proposal through a case study presenting ad-hoc social networking, a platform for managing ad-hoc social relationships (i.e., set up by (mobile) users located in a limited geographical area during a certain period in time).

Demographic Factors in Assessing Perceived Risk in Online Shopping

Anthony Griffin, Dennis Viehland

Abstract: Research in online shopping was the focus of many studies as the age of electronic commerce began in the late 1990’s. More recently, research in this area has declined, even as shopping on the Internet continues to increase and now dominates some product categories. This research offers a timely update on this literature by investigating online shopping from a perceived risk perspective. The results find that overall perceived risk is low with only some consumer concerns in psychological, time and performance risk. Analysis of perceived risk across six product categories and four demographic factors finds a significant level of perceived risk for lower income individuals when purchasing consumer electronics, but not in any other construct examined in this research. Overall, this study provides empirical evidence to substantiate the common perception that perceived risk in online shopping is declining and does not differ greatly across product category or demographic factor.

Investigation of Factors Influencing the Adoption of Mobile Data Services

Shu-Chun Ho, Wen-Yu Sun, Yu-Min Wang

Abstract: The increasing power and rapid advance of mobile devices has changed the way people access information. According to the International Telecommunication Union [18], the number of mobile cellular subscribers worldwide is estimated to reach 5.3 billion, including 940 million subscriptions to 3G services in the end of 2010. Commercialized 3G services are widespread in many countries and users have been rapidly switching to the 3G platform. The development of mobile devices and mobile applications has created great potential market for mobile data services. The objective of this research is to investigate the critical factors that affect consumers’ intention to using mobile data service. We build a theoretical framework that considers both the technology acceptance and economics perspectives. We conducted a survey research among the consumers of mobile data services and collected 310 valid questionnaires in late 2010. Our findings are as follows. First, consumers’ perceived service availability has a positive impact on perceived ease of use and perceived usefulness of mobile data services. Second, switching benefits and perceived ease of use have positive effects on consumers’ perceived usefulness of mobile data services. Third, perceived usefulness has a positive effect on the intention to use mobile data services. Overall, our research provides both theoretical and practical insights into the determinants of consumers’ intention to use mobile data services.

Mining Millions of Reviews: A Technique to Rank Products Based on Importance of Reviews

Kunpeng Zhang, Yu Cheng, Wei-keng Liao, and Alok Choudhary

Abstract: As online shopping becomes increasingly more popu- lar, many shopping web sites encourage existing customers to add reviews of products purchased. These re- views make an impact on the purchasing decisions of potential customers. At Amazon.com for instance, some products receive hundreds of reviews. It is overwhelm- ing and time restrictive for most customers to read, comprehend and make decisions based on all of these re- views. Customers most likely end up reading only a small fraction of the reviews usually in the order which they are presented on the product page. Incorporating various product review factors, such as: content related to product quality, time of the review, content related to product durability and historically older positive customer reviews will have different impacts on the products rankings. Thus, the automated mining of product reviews and opinions to produce a re-calculated product ranking score is a valuable tool which would allow potential customers to make more informed decisions. In this paper, we present a product ranking model that applies weights to product review factors to calculate a products ranking score. Our experiments use the customer reviews from Amazon.com as input to our product ranking model which produces product ranking results that closely relate to the products sales ranking as reported by the retailer.

Stakeholder Interaction and Internet Auction Outcomes: Analyzing Active Disclosure

Ananth Srinivasan, and Fangxing Liu

Abstract: Better understanding of information asymmetry in internet auctions by researchers has led to improved online auction designs, increased market efficiency, and therefore better outcomes for all stakeholders. In this paper we focus on a specific aspect of internet auctions that has not received much attention in the literature: the presence of interaction between buyers and sellers while an auction is in progress – so called “live interaction”. Examples of such interaction include characteristics of questions from buyers, answers and other disclosures from sellers, conversation threads, etc. We believe that such interaction differentiates active disclosure from seller volunteered information (passive disclosure). The facilitation of live interaction is a feature of the auction site TradeMe which represents 60% of all internet traffic in New Zealand. We collected data from 532 auctions of used cars over a three week period. In addition to data about the auction itself, we collected data about the number of questions asked and answered, the average length of the questions and answers, number of conversation threads and the use of specific textual triggers in the questions that encompass sentiments such as intent, politeness, and courtesy words. We modeled the problem using logistic regression to isolate live interaction based determinants of auction outcomes. We studied the effects of live interaction variables on outcomes in two ways: by themselves; and embedded in a larger model encompassing more traditional auction characteristics. The results show which specific aspects of live interaction between buyers and sellers are significant in determining auction outcomes. We propose that such interaction is greatly facilitated by the use of mobile devices and building it in as a necessary design feature can produce superior outcomes.

Decision Making Aid in Mobile Environment by Behavioral Characteristic

Mitsuaki Nakasumi

Abstract: Despite the explosive growth of mobile environment and the rapidly increasing number of consumers who use location based search, we cannot find how consumers make purchase decisions in such situation. An unique characteristic of mobile environment is that they allow retails to create marketing context with location. A desirable recommendation from a consumer perspective is the implementation of sophisticated decision aid to assist consumers in their purchase decisions by providing the recommendation mechanism to their individual preferences.

The availability of such decision aid, which we refer to as context based processes for consumers, may lead to a transformation of the way in which consumers search for product information and make purchase decisions. While making purchase decisions, consumers are often unable to evaluate all available alternatives in great depth and thus, they tend to use two-stage processes to reach their decisions.

At the first stage, consumers typically screen a large set of available products and identify a subset of the most promising alternatives. Subsequently, they evaluate the latter in more depth, perform relative comparisons across products on important attributes and make a purchase decision. Given the different tasks to be performed in such two-stage processes, context based processes that provide support to consumers in the following respects are particularly valuable: (1) the initial screening of available products to determine which ones are worth considering further, (2) the in-depth comparison of selected products before making the actual purchase decision. The decision aid also includes multi-attribute product choices based on expert (same as bell captain) behavioral characteristic.

This paper shows the nature of the effects that the context based decision aid may have on consumer decision making in mobile environment and the effects of two decision aid functions which designed to assist consumers in performing one of the above tasks on purchase decision making in mobile environment.

Transferring Workers’ Knowledge into the Information System: A Case of Recommendation System for Supplier Selection in e-Procurement Service Company

Gwangjae Jung, and Seonyoung Shim

Abstract: With the emergence of indirect procurement, it has become a global trend for companies to outsource their maintenance, repair, and operating (MRO) supplies to procurement service providers (PSPs). Due to the variety of MRO items, evaluation of numerous suppliers in various industries is a particularly complex task for PSPs. In order for companies to find suppliers that offer quality goods not just low prices, a systemized and transparent evaluation model is needed. However, many PSPs still evaluate and select suppliers based on the sourcing managers’ subjective experiences. IMK, the leading procurement service provider in Korea, tried to systemize its supplier evaluation and selection processes by developing a recommendation system (named WI) for supplier selection. This innovative system brought cost reduction and transparency in sourcing processes. IMK not only transferred sourcing managers’ knowledge of supplier evaluation into WI, but also made the system evolve by sourcing managers’ collective intelligence –one of the important features of Web 2.0 – in order to adapt dynamic changes in supplier and MRO markets. Because of these unique characteristics, the participation of the sourcing managers is very critical for WI’s performance. This case explains how IMK encouraged sourcing managers’ participation to improve WI’s performance. We classify several management issues, which are derived by the three maintenance projects for WI, into three perspectives of technology-organization- environment (TOE) framework. This case mainly shows that transferring too much tacit knowledge increases the system complexity and reduces the ease of use. Communication among users helps them to identify their roles in the system and facilitates knowledge contribution. A CEO-driven implementation stimulates system use in the beginning, but it cannot be maintained without sufficient understanding of the system on the user’s side. Coping with trial errors during the system development and maintenance, WI was successfully implemented and became the core competency in IMK’s business.

An Empirical Study on Quality Uncertainty of Products and Social Commerce

Kyunghee Lee, and Byungtae Lee

Abstract: With the advance of Social Network Service (SNS) like Facebook, Social Commerce (SC) such as Groupon now prospers, which provides daily deals at a highly discounted price by gathering buying power of consumers through SNS. From the perspective of quality-uncertainty, it is unusual to sell experience and credence goods/services on the internet as Groupon does. In traditional E- commerce (EC) purchasing decisions rely on information provided after the actual use of products by other consumers, while in Groupon it heavily depends on opinion even before purchasing. For example, traditional sites use a third-party recommendation including feedback mechanism, while Groupon encourages consumers to post and share their preference on goods/services over SNS. Given this difference, focusing on the effect of SNS, we collect and analyze changes of sales for deals Groupon provided, using an econometric model that reflects our understanding of consumer behavior in the presence of different degrees of quality-uncertainty. The information from SNS is captured by using a function called ―Facebook Like‖ that is a recommendation system in which suggestions are brought by one’s friends, and it is a module that can be installed in any website. In this study, we demonstrate that the information from SNS positively affects sales for deals, which implies that SNS provides recommendation and encourages consumers to purchase by reducing encountered uncertainty. In addition, we also find that the effect of SNS is enlarged as the extent of the quality- uncertainty increases. This result means that under the presence of high degree of uncertainty, the information from SNS gives consumers a stronger belief in quality than information from a third-party. Besides, as many other studies proved, we also confirm that the internet turns experience goods into search goods by substituting in-store visits with virtual encounters.

Anonymous reputation based reservations in e-commerce (AMNESIC)

Helena Rifà-Pous

Abstract: Online reservation systems have grown over the last recent years to facilitate the purchase of goods and services. Generally, reservation systems require that customers provide some personal data to make a reservation effective. With this data, service providers can check the consumer history and decide if the user is trustable enough to get the reserve. Although the reputation of a user is a good metric to implement the access control of the system, providing personal and sensitive data to the system presents high privacy risks, since the interests of a user are totally known and tracked by an external entity. In this paper we design an anonymous reservation protocol that uses reputations to profile the users and control their access to the offered services, but at the same time it preserves their privacy not only from the seller but the service provider.

Moving to the Mobile Internet: Analyzing Sedo's Domain Parking Services

Claudia Loebbecke, and Thomas Weiss

Abstract: In this exploratory case study, we examine Sedo, one of the world's leading domain trading and parking companies in its efforts of going mobile. We introduce domain parking services and investigate the opportunities and challenges resulting from the company's innovation efforts due to the trend towards the mobile Internet. Based on Henderson and Clark [1] and Atuahene-Gima and Ko [2], we find that incremental and architectural innovations mark Sedo's efforts to strengthen its mobile profile and to complement its desktop business. We discuss whether modular or radical innovations, which overturn the existing business could be an alternative recipe for success in mobile parking. Yet, our data lets us conclude that the peculiarities of domain parking limit the transferability of the parking business to the mobile world. This seemingly negative finding helps us to rethink business model contexts and contingencies in the overall hype for the mobile Internet.

Who are the Most Influential Users in a Recommender System?

Mohammad Amin Morid, Mehdi Shajari, and Alireza Hashemi Golpayegani

Abstract: Collaborative filtering (CF) is a popular method for personalizing product recommendations for e-commerce applications. In order to recommend a product to a user and predict her preference, CF utilizes product evaluation ratings of the like-minded users. This process of finding the like-minded users causes a social network to be formed among all users. In this social network, each link between a couple of users presents an implicit connection between them. Here, there are some users who have more connections with others and are called the most influential users. This paper attempts to model and analyze the behavior of these users by employing data mining techniques. First, the most important features which present a user’s influence were selected with a linear regression method, and then, the modeling was performed by a decision tree. Based on our results, the most influential users are users who show more interest to rate more than average number of items with low frequency. Moreover, other most influentials are users who rate in moderation items which have been seen in moderation. In addition, these items are rated with good degree of agreement with other users’ rates on the items. We achieved a high accuracy with this model.

Social Support Mechanism in Micro-blogosphere

Yung-Ming Li, Cheng-Yang Lai

Abstract: With the advance of Internet, online social networks could be seen as a large expert group exclusively belongs to online users. The social appraisal support involves the feedback about friends’ opinions which represent the opportunities for sales. In this paper, a mechanism composed with social network analysis (SNA), intuitionistic fuzzy sets (IFSs), and technique for order preference by similarity to ideal solution (TOPSIS) is proposed to achieve social appraisal support for online users within micro-blogosphere. The proposed mechanism can successfully summarize the collective opinions from online social network and further speed up the decision process in support users’ purchasing behaviors.

A Multi-Agent Prediction Market based on Partially Observable Stochastic Game

Janyl Jumadinova and Prithviraj Dasgupta

Abstract: We present a novel, game theoretic representation called POSGI (partially observable stochastic game with information) for distributed information aggregation using a multi- agent based prediction market model. We then describe a correlated equilibrium (CE)-based solution strategy for this game which enables each agent to dynamically calculate the prices at which it should trade a security in the prediction market. We have extended our results to risk averse traders and shown that a Pareto optimal correlated equilibrium strategy can be used to incentively truthful revelations from risk averse agents. Simulation results comparing our CE strategy with five other strategies commonly used in similar markets, with both risk neutral and risk averse agents, show that the CE strategy improves price predictions and provides higher utilities to the agents as compared to other existing strategies.

Preference of Internet-based Debit Payment Protocols

Kiyoon Sung, and Jae-Kyu Lee

Abstract: Debit payment is a low cost and low risk payment method in comparison with credit and pre-paid payment methods. In this study, we analyze the structures of Internet-based debit payment protocols and classified them into three types depending upon which party drives the authentication: Payment Gateway, customer‟s bank, or electronic merchant. For each type, real world protocols, SSL/D, SDT, and SET/D, respectively are exemplified. To compare the merchants‟ preference regarding these protocols, we have identified five distinctive factors that distinguish the characteristics of these three protocols: authentication method, risk of leaking bank account information, efficient recovery of failed authorization response, merchant‟s required implementation effort, and customer‟s ease of use. For these factors, the preferred features of each merchant are mapped to compute the preferences of the protocols.

In order to empirically evaluate the preferences of protocols, we surveyed the merchant‟s weighting of five factors and preferred features from 36 online merchants. Based on the obtained data, we computed the preferences of protocols and first found that the protocols have difference preference levels. Second, this study found that the game and content providers prefer SSL/D and real goods retailers prefer SDT. This preference value provides insight into the future demand of debit payment protocols.

A Model of Peer-to-Peer (P2P) Social Lending in the Presence of Identification Bias

Frederick J. Riggins, and David M. Weber

Abstract: The Internet has created new opportunities for peer-to-peer (P2P) social lending platforms to emerge which have the potential to transform the way microfinance institutions (MFIs) raise and allocate funds used for poverty reduction. Depending upon where decision making rights are allocated, there is the potential for identification bias whereby lenders may be motivated to give to specific projects with which they have a personal interest or affinity without regard to whether or not it represents a particularly sound financial investment. In this paper, we present an analytical model where an individual lender can use a P2P social lending network to provide funds to entrepreneurs seeking funding in developing nations. We show that in the presence of identification bias, the P2P social lending network can be used to increase overall contributions for poverty reduction despite the fact that such a network may result in inefficient allocation of funds. Even so, in the presence of strong identification bias this inefficient mechanism can result in improved poverty reduction through the provisioning of financial services in the microfinance industry.

Business Modeling for Online Video Services: Download vs. Streaming

Yung-Ming Li, Lien-Fa Lin, and Cheng-Yang Lai

Abstract: Download and streaming are two major approaches for delivering online video/movie. In this paper, considering their differentiated characteristics, we analyze the pricing issues in a market where both types of content distribution are available. We examine the impact of various technological and market factors on developing the business strategies under the scenarios that these distribution channels are owned by the same provider or two independent firms. We further examine the loyalty fee development when the video content is independently owned by another content provider. Our results shows that while the quality of two types of video distribution has significant impact on determining the content loyalty fee in a competitive market, loyalty fee is only affected by the characteristic of steaming service.

VoIP Pricing in Competitive Telephony Markets

Yung-Ming Li, and Shih-Wen Chiu

Abstract: As a disruptive technology, the Voice over Internet Protocol (VoIP) service has a great impact on telecommunication market. While VoIP over two end computers is free, VoIP providers generate profit from so-called phone-in and phone-out services, which allows the VoIP accessible users to contact conventional phone numbers. Compared with conventional public switched telephone network (PSTN) service, VoIP service has the advantage of a lower charge rate. However, it also incurs more quality uncertainty and security risk concerns. In this paper, utilizing game theoretic models, we analyze the market interactions of VoIP-to-PSTN service industry and prescribe the optimal pricing strategies with respect to both types of telephony services. Several perspectives have been addressed to help clarify the progress and evolution of VoIP services and intimations for both PSTN operators and VoIP service providers are also represented to develop several managerial implications.

Forecasting prices in dynamic heterogeneous product markets using multivariate prediction methods

Gianfranco Lucchese, Jan van Dalen, Wolfgang Ketter, and John Collins

Abstract: Hedonic modeling is used to measure the product price be- havior overall in high-tech markets. In a previous work, we showed the opportunity to extend the simple regression to a state space model evaluating hedonic prices from product prices. We created and tested an online estimation algo- rithm for those values. In that way, we can study time se- ries of implicit prices for individual components of a range of products. In this paper, we implement and compare the he- donic model forecast performances respect to standard au- toregressive models, univariate and multivariate. We find that hedonic values not only give extra information about supply market, but they can improve univariate predictions and in, certain periods, also multivariate ones. We show the correctness of algorithm using online version of it. An agent may predict prices for different products sharing a set of component, by taking into account the structure of produc- tion process. An application in a multi-agent supply chain simulation confirms the goodness of algorithm to be imple- mented in a future framework for online price analysis and prediction.

An investigation of the consequences of Basel III using an agent-based model

Luís Gonçalves de Faria, and Steve Phelps

Abstract: Many recent agent-based models of financial markets are single- asset models which do not consider risk-management strategies in which agents can invest in both riskless and risky assets. This makes them unsuitable for exploring the implications of regulatory proposals such as Basel III which require agents to balance their exposure to risk by maintaining a minimum ratio of capital to risk-weighted assets. In this paper, we will introduce an agent-based model of a financial market in which agents can invest in both risky and riskless assets. We will first validate our model against the empirically-observed stylized facts of financial time-series data and then we proceed to investigate the counter- factual implications of the Basel III proposals for systemic risk. We will also use our model to make testable predictions about the consequences of Basel III which we shall revisit if and when the regulation is implemented.

Some clues to the determinants of feedback behaviour

Domenico Colucci, Simone Salotti, and Vincenzo Valori

Abstract: We report the results of an experiment designed to investigate the determinants of feedback behaviour in electronic markets. Ratings driven by disconfirmed expectations should in principle reduce the asymmetric information problems of these markets. However, some other motives may influence the decisions of the sellers. In particular, empirical evidence suggests that the economic surplus obtained from the transaction may have some bearing on the way sellers are rated. Our design was meant to test whether and to what extent disconfirmed expectations and/or the transaction surplus play a role in determining the feedback behaviour of buyers in e-marketplaces. The results indicate that both factors affect the ratings, the latter having the stronger effect. One possible empirical implication could be that when an online purchase is a good deal a seller will typically get away with (moderately) exaggerated descriptions of the good on sale, obtaining a positive rating from the buyers.

A Diversity Dilemma in Evolutionary Markets

Peter R. Lewis, Paul Marrow, and Xin Yao

Abstract: Markets are useful mechanisms for performing resource al- location in fully decentralised computational and other systems, since they can possess a range of desirable properties, such as efficiency, decentralisation, robustness and scalability. In this paper we investigate the behaviour of co-evolving evolutionary market agents as adaptive offer generators for sellers in a multi-attribute posted-offer market. We demonstrate that the evolutionary approach enables sellers to automatically position themselves in market niches, created by heterogeneous buyers. We find that a trade-off exists for the evolutionary sellers between maintaining high population diversity to facilitate movement between niches and low diversity to exploit the current niche and maximise cumulative payoff. We characterise the trade-off from the perspective of the system as a whole, and subsequently from that of an individual seller. Our results highlight a deci- sion on risk aversion for resource providers, but crucially we show that rational self-interested sellers would not adopt the behaviour likely to lead to the ideal result from the system point of view.

Learning is Neither Sufficient Nor Necessary: A Dynamic Agent-Based Model of Long Memory in Financial Markets

Neil Rayner, Steve Phelps, and Nick Constantinou

Abstract: Financial time series data exhibits long memory phenomena, where certain behaviours in the market have a persistent influence on the market over time. It has been suggested that imitation of successful trader strategies by other less successful traders is an important factor in contributing to this persistence. We test this explanation by using an existing adaptive agent-based model and we find that the robustness of the model is directly related to the dynamics of learning; models in which learning converges to a stationary steady state fail to produce realistic time series data. In contrast, models in which learning leads to dynamic strategy switch- ing behaviour in the steady state are able to reproduce the long memory phenomena. We demonstrate that a model which incorporates contrarian trading strategies results in more dynamic behaviour in steady state, and hence is able to produce more realistic results. We also demonstrate that a non-learning contrarian model that performs dynamic strategy switching produces long memory phenomena and there- fore that learning is not necessary. Models that can be validated against properties of empirical high frequency financial data should allow exploration of the robustness and reliability qualities of market mechanism modifications.

Sequential Mixed Auctions

Boris Mikhaylov, Jesus Cerquides, and Juan A. Rodriguez-Aguilar

Abstract: Mixed multi-unit combinatorial auctions (MMUCAs) offer a high potential to be employed for the automated assembly of supply chains of agents. However, in order for mixed auctions to be effectively applied to supply chain formation, we must ensure computational tractability and reduce bidders’ uncertainty. With this aim, we introduce Sequential Mixed Auctions (SMAs), a novel auction model conceived to help bidders collaboratively discover supply chain structures. Thus, an SMA allows bidders progressively build a supply chain structure through successive auction rounds. Moreover, the incremental nature of an SMA provides its participants with valuable information at the end of each auction round to guide their bidding. Finally, we empirically show that SMAs significantly reduce the computational effort required by MMUCA at the expense of a slight decrease in the auctioneer’s revenue.

Market Niching in Multi-attribute Computational Resource Allocation Systems

Edward Robinson, Peter McBurney, and Xin Yao

Abstract: We propose a novel method for allocating multi-attribute computational resources via competing marketplaces. Trading agents, working on behalf of resource consumers and providers, choose to trade in resource markets where the resources being traded best align with their preferences and constraints. Market-exchange agents, in competition with each other, attempt to provide resource markets that attract traders, with the goal of maximising their profit. Because exchanges can only partially observe global supply and demand schedules, novel strategies are required to automate their search for market niches. Novel attribute-level selection (ALS) strategies are empirically analysed in simulated competitive market environments, and results suggest that using these strategies, market-exchanges can seek out mar- ket niches under a variety of environmental conditions.

Social learning and financial market stability

Daniel Ladley, Terje Lensberg, Jan Palczewski and Klaus Reiner Schenk-Hoppé

Abstract: Over-the-counter (OTC) financial markets, in which trader transact with each other directly, have been criticized for being opaque, illiquid and for exacerbating credit risk. To reduce these problems there have been calls, by regulators and observers, to move trade in many instruments, including derivatives, to centralized exchanges. It is the belief of proponents of this call that by forcing all trade to go through a central counterparty that markets will become more stable and less risky for the participants. The recent financial crisis, however, has highlighted how little is known about the interdependence between the architecture of markets and the behavior of traders who interact within them. Rather than disciplining their participants and delivering efficient allocations financial markets seem to have encouraged greed, excessive risk-taking and unethical behavior. The observation that markets can bring out the worst in those who trade in them, or attract traders who are the seed to its own destruction, is quite at odds with the conventional view of financial markets in economics and finance which sees them as quite, efficient and mostly self-regulating.

Accepted Posters

Succeeding In A Modern Online Travel Marketplace: What Do Consumers Need From A Travel Reservation Web Site?

Isaac J. Gabriel

Abstract: Online travel industry has been growing at a fast pace over the last several years and is expected to grow at a steady rate in the future. Since this market is very attractive, it becomes very competitive. In order to survive the competition, online travel providers need to make sure that their sites offer features that are critical to consumers.

This paper reports on results of an empirical pilot study that identified dimensions consumers use when selecting travel reservation web sites for their travel needs. Using current literature, a set of characteristics or features of travel reservation web sites was identified. Then a survey was constructed for subjects to rate these characteristics/features against each other. Data was analyzed using multidimensional scale analysis. As a result of statistical analysis, critical dimensions online consumers use to purchase travel packages on the Internet were identified.

This research identified two such dimensions: 1) Reliability & Information, and 2) Ease of Use & Reassurance. Consumers need to be confident that the site is reliable and their personal information is being handled adequately. In addition, there is an urge to get more information, whether it is related to their traveling destination or, simply, consists of comments and opinions of fellow travelers. Moreover, consumers are looking for intuitive and user-friendly web site interfaces as it has always been the case in the past while preferring to have a choice of using advanced search capabilities when needed. Finally, as it was critical in the past, consumers wish to get reassured that adequate secure technologies were utilized in the transmission of sensitive data when interacting with the web site. Another interesting observation is that security-related features remain to be critical to online consumers as it was in the past.

The Decision Method for Group-buying Websites Based on UEOWA Operator

Lifang Peng, Nannan Li and Qi Li

Abstract: With the popularity of group-buying websites in China, group- buying has become a particularly effective form of e-commerce now. With more and more group-buying websites emerging, it is difficult for consumers to make decisions about which website should they choose to participate in. Hence, this paper probes into how consumers can assess group-buying websites with multiple attributes and make quick decisions effectively. The assessment of them is a complex problem and has fuzziness, so we come up with this method based on UEOWA operator, which can solve this kind of problems. This study aims to supply a quantitative method for assessing the group-buying website based on UEOWA operator to help consumers make quick decisions among group- buying websites.