Fairs for e-commerce: the benefits of aggregating buyers and sellers

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allow to study effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic

Anytime coalition structure generation on synergy graphs

We consider the coalition structure generation (CSG) problem on synergy graphs, which arises in many practical applications where communication constraints, social or trust relationships must be taken into account when forming coalitions. We propose a novel representation of this problem based on the concept of edge contraction, and an innovative branch and bound approach (CFSS), which is particularly efficient when applied to a general class of characteristic functions. This new model provides a non-redundant partition of the search space, hence allowing an effective paralleli-sation. We evaluate CFSS on two benchmark functions, the edge sum with coordination cost and the collective energy purchasing functions, comparing its performance with the best algorithm for CSG on synergy graphs: DyCE. The latter approach is centralised and cannot be efficiently parallelised due to the exponential memory requirements in the number of agents, which limits its scalability (while CFSS memory requirements are only polynomial). Our results show that, when the graphs are very sparse, CFSS is 4 orders of magnitude faster than DyCE. Moreover, CFSS is the first approach to provide anytime approximate solutions with quality guarantees for very large systems (i.e., with more than 2700 agents). Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.Cerquides and Rodríguez-Aguilar are funded by projects COR (TIN2012-38876-C02-01), AT (CSD2007-0022), and the Generalitat of Catalunya grant 2009-SGR-1434. This work was supported by the EPSRC-Funded ORCHID Project EP/I011587/1Peer Reviewe

Study of the Influence of Brand Image on Consumers\u27 Online Shopping Intention——in the Case of Cosmetics

With the rapid development of science and technology, people’s acceptance of online shopping is increasing. As an important part of online shopping, small and medium-sized cosmetics enterprises have the characteristics of small investment scale and flexible adjustment of brand strategy, but previous research lack sustained and effective methods and tools to analysis brand impact. The paper takes INOHERB as an example, to explore the connotation and feature of brand and brand image from the perspective of the cosmetics online shopping, as well as the relevant theories of online shopping intention. Through literature review, the paper applies the bell brand image measurement model, dividing brand image into corporate image and product or service image, and user image. It also adds the analysis on the consumption characteristics, so as to test result reasonableness of the brand image analysis’s influence on online shopping intention. Data were collected from college female students by print questionnaires and online surveys. The result indicated that corporate image has a strong influence on consumer online shopping intention. Besides, product and service image also have a significant influence on consumer online shopping intention, consumers are more willing to buy cosmetics online above average prices with positive word of mouth and good quality

Mechanism design for distributed task and resource allocation among self-interested agents in virtual organizations

The aggregate power of all resources on the Internet is enormous. The Internet can be viewed as a massive virtual organization that holds tremendous amounts of information and resources with different ownerships. However, little is known about how to run this organization efficiently. This dissertation studies the problems of distributed task and resource allocation among self-interested agents in virtual organizations. The developed solutions are not allocation mechanisms that can be imposed by a centralized designer, but decentralized interaction mechanisms that provide incentives to self-interested agents to behave cooperatively. These mechanisms also take computational tractability into consideration due to the inherent complexity of distributed task and resource allocation problems. Targeted allocation mechanisms can achieve global task allocation efficiency in a virtual organization and establish stable resource-sharing communities based on agentsâÃÂàown decisions about whether or not to behave cooperatively. This high level goal requires solving the following problems: synthetic task allocation, decentralized coalition formation and automated multiparty negotiation. For synthetic task allocation, in which each task needs to be accomplished by a virtual team composed of self-interested agents from different real organizations, my approach is to formalize the synthetic task allocation problem as an algorithmic mechanism design optimization problem. I have developed two approximation mechanisms that I prove are incentive compatible for a synthetic task allocation problem. This dissertation also develops a decentralized coalition formation mechanism, which is based on explicit negotiation among self-interested agents. Each agent makes its own decisions about whether or not to join a candidate coalition. The resulting coalitions are stable in the core in terms of coalition rationality. I have applied this mechanism to form resource sharing coalitions in computational grids and buyer coalitions in electronic markets. The developed negotiation mechanism in the decentralized coalition formation mechanism realizes automated multilateral negotiation among self-interested agents who have symmetric authority (i.e., no mediator exists and agents are peers). In combination, the decentralized allocation mechanisms presented in this dissertation lay a foundation for realizing automated resource management in open and scalable virtual organizations

Auctions and bidding: A guide for computer scientists

There is a veritable menagerie of auctions-single-dimensional, multi-dimensional, single-sided, double-sided, first-price, second-price, English, Dutch, Japanese, sealed-bid-and these have been extensively discussed and analyzed in the economics literature. The main purpose of this article is to survey this literature from a computer science perspective, primarily from the viewpoint of computer scientists who are interested in learning about auction theory, and to provide pointers into the economics literature for those who want a deeper technical understanding. In addition, since auctions are an increasingly important topic in computer science, we also look at work on auctions from the computer science literature. Overall, our aim is to identifying what both these bodies of work these tell us about creating electronic auctions. © 2011 ACM.This work was funded in part by HP under the “Always on” grant, by NSF IIS-0329037 “Tools and Techniques for Automated Mechanism Design”, and by IEA (TIN2006-15662-C02-01), OK (IST-4-027253-STP), eREP(EC-FP6-CIT5-28575) and Agreement Technologies (CONSOLIDER CSD2007-0022, INGENIO 2010).Peer Reviewe