دانلود مقاله ISI انگلیسی شماره 3429
عنوان فارسی مقاله

مدل مبتنی بر عامل برای تجارت الکترونیک B to C

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
3429 2008 13 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
An agent-based model for consumer-to-business electronic commerce
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 34, Issue 1, January 2008, Pages 469–481

کلمات کلیدی
تجارت الکترونیک - عامل هوشمند - مدل - گروه تصمیم گیری - مذاکره
پیش نمایش مقاله
پیش نمایش مقاله مدل مبتنی بر عامل برای تجارت الکترونیک B to C

چکیده انگلیسی

Electronic commerce has changed the outlook of traditional business trading behavior. It is now common to see business-to-business (B2B), business-to-consumer (B2C) and consumer-to-consumer (C2C) commerce on the Internet. However, another type of model, consumer-to-business (C2B), is seldom found. A possible reason for this phenomenon is transaction cost; to unite a group of candidate buyers’ common needs and preferences to buy a product or service is uneasy. Difficulties arise, for example, in how to synthesize individual’s preferences into a group’s consensus, how to communicate with each other within the group, and how to collectively negotiate with a seller, etc. To establish a successful business model in the electronic market, however, these processes have to be implemented. We address these issues in this paper, and propose a Buyer Collective Purchasing (BCP) model implemented in a multi-agent framework. A prototype system, which uses a laptop computer purchasing case as an example, is created to demonstrate the idea and show how the model works.

مقدمه انگلیسی

The explosion of Internet and the ensuing applications in electronic commerce (e-commerce) have permanently changed the outlook of traditional business trading behavior. Different business parties are now made easy to interact through Internet with others to conduct transactions in a more efficient way. Based on the nature of transactions, e-commerce is classified into following types (Turban, Lee, King, & Chung, 1999): business-to-business (B2B), business-to-consumer (B2C), consumer-to-consumer (C2C), consumer-to-business (C2B), non-business e-commerce, and intra-business e-commerce. Compared to the three frequently mentioned models: B2B, B2C, and C2C, which are now very popular, the progress of the other one (i.e., C2B) is far left behind; it is seldom seen on the Internet. A possible reason for this situation is the high transaction cost. It takes effort to unify a group of buyers’ common needs and preferences and to interact between the buyer’s party and the potential venders in order to complete a transaction. Moreover, it is not clear how to do it; there is little research into this problem. For example, how to synthesize individual’s needs into a group’s consensus? What is the mechanism to communicate with each other within the group? How does the group collectively negotiate with a seller? All these problems need a solution if one wants to create a successful C2B trading model. Collective purchasing is not new to the traditional business. Friends sometimes invite each other to go to a restaurant for a meal and share the expense. People join a tour to share the expense of transportation, hotels and other expenditure. In these cases, people scarify some of their personal preferences in order to gain benefits from the collectively purchasing behavior. Likewise, can we transfer such consumer behavior to the e-market? If with a suitable model and mechanism, we believe Internet will be an enabler, not an obstacle, to collective purchasing behavior because people there get easier to setup a group with common interests. In this paper, we define and propose a model for buyer collective purchasing (BCP) behavior, which consists of a number of steps, each for a specific task, e.g., product description, buyer invitation, needs synthesis, negotiation, etc. A multi-agent architecture is devised to facilitate this job. In the framework, different agents, each assigned with a specific role, cooperate together to support the process. For example, there is an agent for each buyer who participates in collective purchasing to record the buyer’s needs and preferences. Similarly, there are agents for sellers to represent their offers to the purchase. An agent is responsible for collecting and synthesizing the buyers’ needs. Another plays the role for negotiation. Among these agents, the platform itself supports communication and interaction within the group. Behind the multi-agent framework, there need algorithms to collect and synthesize the buyers’ preferences and to negotiate with sellers. An AHP (Analytic Hierarchy Process) algorithm is devised to synthesize the common needs from the buyer group. Based on the created AHP tree, a one-to-many negotiation algorithm takes place to seek for the best deal from potential sellers that carry products satisfying the group’s needs. Based on the proposed BCP model, we implement a prototype system to demonstrate the idea, which uses a laptop computer purchasing case to show how the model works. The remainder of this paper is organized as follows. Section 2 discusses C2B buying behavior and defines the buyer collective purchasing model. Section 3 implements the model with a multi-agent framework. Preferences synthesis and alternatives ranking are described in Section 4, in which the algorithm of AHP used in this paper is illustrated. Section 5 describes a one-to-many negotiation algorithm that can bargain with several potential sellers simultaneously based on the information given by the constructed AHP-tree. The prototype implementation and demonstration that realize the whole idea are presented in Section 6. Finally, we conclude the paper with future research issues in Section 7.

نتیجه گیری انگلیسی

Collective purchasing is a well-known consumer behavior in traditional business but is new to electronic commerce market. Also, it has not received much attention yet in the Internet. One of the many factors for this phenomenon is due to its high transaction cost; there is lack of convenient tools and environment support to facilitate the collective purchasing behavior. Furthermore, there is little academic research on its business model to realize it. In this paper, we try to solve these problems both theoretically and practically. For the first part, we defined the buyer collective purchasing (BCP) model and proposed two methods for preference synthesis and negotiation strategy, respectively. For the practical part, we devise a multi-agent framework that supports the proposed business model and implement a workable prototype system on .NET platform. We demonstrate the whole business process with an example case that shows how interested persons participate in an on-line buyer’s group and then the agents take over to bargain with sellers and complete the entire transaction. Despite of what has shown in this paper, we have to admit that collective purchasing or consumer-to-business (C2B) is still a very young business model in its primitive stage. This paper is just the first attempt that tries to promote it to the Internet eCommerce community. Our proposal for the business model (i.e., BCP) and the multi-agent framework, of course, can be further explored and improved. In particular, there are many details that are not considered in this paper. But, to make the business model practical, they are necessary without speaking. From this perspective, there is a long way to go to make this business model real. However, it is our hope that this paper can at least be served as a starting point to the final goal. Future research will follow the comments explained above. Although we have invented methods to reduce the transaction cost in collective purchasing behavior, there are many issues that need to be verified. For example, will users accept the results by our preference synthesis algorithm? What are the exceptions? Will the negotiation strategy work? What are the exceptions? The real performance of this proposed framework needs more field studies, and from there, we believe many new and better results will be derived.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.