The Impact of Reputation and Promotion on Internet Auction Outcomes: Evidence from Huuto.net

Internet auctions have become increasingly popular in the 21st century. However, asymmetric information induced issues, such as the inability to trust the seller and product quality uncertainty, might discourage the buyers' willingness to bid according to their true valuations. In order to alleviate trust issues, sellers are able to build an online reputation through successful online transactions. The purpose of this Master's thesis is to explore the impact of seller's reputation and chosen promotion methods on auction outcomes in Finnish Huuto.net online auction website. The fundamental concepts of auction theory, such as valuation models, the basic four auction types, the revenue equivalence theorem and optimal auctions are introduced. Signaling theory is discussed in addition to the bidding mechanisms and reputation systems of internet auctions. The recent literature considering the impact of a seller's reputation and promotion methods on auction outcomes is reviewed. The hypotheses set to be tested are derived from the recent empirical studies and auction theory. The statistical method used in the tests of hypotheses is multiple linear regression analysis. The dataset analyzed in this study consists of 227 auctions of iPhone 4S 16 GB mobile phones posted up for auction by 138 individual sellers. The main finding of this study is that the sellers who have acquired a costless identification from Huuto.net achieve a hefty increase in the final sales price. It also turns out that sellers who have not established an online reputation experience a steep decline in the realized closing price of the auction. The impact of negative feedback is significant as well; the increase of negative feedback points decreases the final sales price. Purchasing display-enhancing promotional options does not increase the price or probability of sale. In short, establishing reputation, avoiding negative feedback and acquiring identification pays off. The promotional options are not worth the cost.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Multiple criteria decision making in application layer networks

This work is concerned with the conduct of MCDM by intelligent agents trading commodities in ALNs. These agents consider trustworthiness in their course of negotiation and select offers with respect to product price and seller reputation. --Grid Computing

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

Merchant differentiation through integrative negotiation in agent-mediated electronic commerce

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 1998.Includes bibliographical references (p. [149]-153).This thesis proposes to fix online shopping by guiding it away from price comparisons and toward value comparisons. Though price comparisons may be adequate for simple products (e.g., books and music), they are inadequate for facilitating transactions of complex products (e.g., computers and automobiles). Consumers often must consider qualities other than price in their buying decisions and merchants usually prefer to differentiate themselves along alternative dimensions such as brand, customer service, delivery time, warranty, and other value-added services. Tete-a-Tete is an agent-mediated comparison shopping system that allows consumers to consider dimensions other than price in their buying decisions for complex products. The system helps shoppers answer two questions: what to buy and who to buy from. Tete-a- Tete's integrative negotiation interaction model (based on bilateral argumentation), together with a decision support module (based on multi-attribute utility theory), create an improved online shopping environment for both consumers and merchants. Consumers gain increased satisfaction as their search costs for complex products are reduced and merchants potentially increase sales as a result of their enhanced differentiation in the marketplace.Robert H. Guttman.S.M

Exploring auction based energy trade with the support of MAS and blockchain technology

This document describes a simulation of the local energy market with support of multi-agent approach and blockchain technology. The investigated points include blockchain technology and its applications, Ethereum platform and smart contracts as a tool for storing data of operations and creating assets, multi-agent approach to model the local energy market. The document explores building a solution for proposed problem with blockchain technology, agent interactions on the simulated market and auction models, that provide sustainability and profit for the local energy market overall

Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

Blockchain-based distributive auction for relay-assisted secure communications

Physical layer security (PLS) is considered as a promising technique to prevent information eavesdropping in wireless systems. In this context, cooperative relaying has emerged as a robust solution for achieving PLS due to multipath diversity and relatively lower transmission power. However, relays or the relay operators in the practical environment are unwilling for service provisioning unless they are incentivized for their cost of services. Thus, it is required to jointly consider network economics and relay cooperation to improve system efficiency. In this paper, we consider the problem of joint network economics and PLS using cooperative relaying and jamming. Based on the double auction theory, we model the interaction between transmitters seeking for a particular level of secure transmission of information and relay operators for suitable relay and jammer assignment, in a multiple source-destination networks. In addition, theoretical analyses are presented to justify that the proposed auction mechanism satisfies the desirable economic properties of individual rationality, budget balance, and truthfulness. As the participants in the traditional centralized auction framework may take selfish actions or collude with each other, we propose a decentralized and trustless auction framework based on blockchain technology. In particular, we exploit the smart contract feature of blockchain to construct a completely autonomous framework, where all the participants are financially enforced by smart contract terms. The security properties of the proposed framework are also discussed

Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing