Agents in E-Commerce: State of the Art

This paper surveys the state of the art of agent-mediated electronic commerce (e-commerce), especially in business-to-consumer (B2C) e-commerce and business-to-business (B2B) e-commerce. From the consumer buying behaviour perspective, the roles of agents in B2C e-commerce are: product brokering, merchant brokering, and negotiation. The applications of agents in B2B e-commerce are mainly in supply chain management. Mobile agents, evolutionary agents, and data-mining agents are some special techniques which can be applied in agent-mediated e-commerce. In addition, some technologies for implementation are briefly reviewed. Finally, we conclude this paper by discussions on the future directions of agent-mediated e-commerce. Received 14 September 2000 / Revised 13 January 2001 / Accepted in revised form 27 February 2001     

The agent-based negotiation process for B2C e-commerce

B2C e-commerce is becoming more widespread as more people come to recognize its convenience and its ability to rapidly respond to requests and as more products and services become available. However, many electronic marketplaces, especially in the business-to-consumer, are in essence some kind of search engine where buyers look for the best product in a database of products offered by sellers. Usually, such e-marketplaces do not use agent technology at all although agents could significantly improve the services provided both for the buyers and the sellers. Further, negotiation capabilities are essential for B2C e-commerce systems. In an automated negotiation, intelligent agents engage in broadly similar processes to achieve the same end. In more detail, the agents prepare bids for and evaluate offers on behalf of the parties they represent with the aim of obtaining the maximum benefit for their users. Nevertheless, in the current situation, price is the only criterion by which agents are created. This factor is easy to measure and automate. However, the criteria for advanced transactions need to be elaborated, for example, details of giveback and dividend. In this paper, we present a multiple-attributes negotiation model for B2C e-commerce, which deploys intelligent agents to facilitate autonomous and automatic on-line buying and selling by intelligent agents while quickly responding to consumers. These include a 4-phase model, information collection, search, negotiation, and evaluation. We also apply fuzzy theory and analytical hierarchy process to develop the system interface to facilitate the user inputs. Finally, an example of the notebook purchasing process is illustrated.     

Do security and privacy policies in B2B and B2C e-commerce differ? A comparative study using content analysis

Security and privacy policies address consumer concerns related to security and privacy in e-commerce websites. As these policies represent only the vendor’s perspective, often there exists a mismatch between the stated and desired policy. Based on transaction cost theory, we speculate that business-to-business (B2B) and business-to-consumer (B2C) e-commerce customers use their transaction cost savings in order to obtain varying levels of security and privacy. These differences are bound to be reflected in the security and privacy policies of e-commerce companies. Therefore, in this paper, we perform a comparative content analysis of the security and privacy policies in B2C and B2B e-commerce. Results show that B2B vendors are more concerned about security than their B2C counterparts, while B2C vendors are anxious about intimacy and restriction privacy. Our findings have important implications for e-commerce consumers and vendors as individual and corporate consumers have varying concerns while transacting online. Individual consumers are concerned about maintaining security and intimacy privacy, whereas corporate users are anxious about regulatory issues. Therefore, B2C vendors should incorporate stringent measures dedicated to confidentiality and protection of consumer data as well as enhance intimacy privacy in their security policies, while their B2B counterparts should focus on enhancing restriction privacy.     

The evaluation of intelligent agent performance — An example of B2C e-commerce negotiation

Increasing demand for sophisticated software capable to collaborate, control, and organize all distributed activities has encouraged researchers in various disciplines to utilize and implement Intelligent Agent (IA). This paper develops a methodology to appraise performance of the IA and demonstrate the use in the B2C e-commerce negotiation process. An experiment was conducted to acquire empirical data and a survey was implemented to confirm advantage of the use of the IA. The computational results indicate that the proposed approach successfully evaluates IA performance and significantly distinguishes groups of using (vs. not using) the negotiation mechanism in B2C e-commerce.     

Adopters and non-adopters of business-to-business electronic commerce in Singapore

Although there has been an increase in research studies of business-to-business (B2B) electronic commence (e-commerce), most studies were carried out in the United States or Europe. There are very limited studies on B2B e-commerce in the Asian context. Our effort examined Web-based B2B e-commerce initiatives in Singapore, an island of 650 km² in South–East Asia. Data were collected from 108 firms using a mail survey, which showed that 52.8% firms have adopted B2B e-commerce; of these, two-third had a formal plan and/or task force for B2B e-commerce deployment. Customer-related applications were generally more common than supplier-related applications. Problems in B2B e-commerce adoption included the difficulty of measuring benefits, fear of granting suppliers and customers access to corporate systems and insufficient time for staff to develop new skills in e-commerce. Implications of the results are discussed.     

Adopters and non-adopters of business-to-business electronic commerce in Singapore

Although there has been an increase in research studies of business-to-business (B2B) electronic commence (e-commerce), most studies were carried out in the United States or Europe. There are very limited studies on B2B e-commerce in the Asian context. Our effort examined Web-based B2B e-commerce initiatives in Singapore, an island of 650 km² in South–East Asia. Data were collected from 108 firms using a mail survey, which showed that 52.8% firms have adopted B2B e-commerce; of these, two-third had a formal plan and/or task force for B2B e-commerce deployment. Customer-related applications were generally more common than supplier-related applications. Problems in B2B e-commerce adoption included the difficulty of measuring benefits, fear of granting suppliers and customers access to corporate systems and insufficient time for staff to develop new skills in e-commerce. Implications of the results are discussed.     

Looking back at struggles, looking ahead to opportunities[e-commerce]

At the beginning of 2000, people expected to see an explosion in business-to-business (B2B) e-commerce. Although B2B's allure drove many to launch initiatives, moving from a B2B vision to reality proved far more difficult than most companies realized     

Realising B2B e-commerce benefits: the link with IT maturity,evaluation practices,and B2BEC adoption readiness

Actual realisation of business-to-business electronic commerce (B2B e-commerce) benefits from IT investments has been a critical issue for large organisations. However, relatively little research has been undertaken to determine the drivers for realising B2B e-commerce benefits within these organisations. A survey research was conducted to examine the relationships between B2B e-commerce benefits, IT investment evaluation methodologies (IEM), IT benefit realisation processes (BRP), B2B e-commerce adoption readiness, and IT maturity in large Australian organisations. An IT investment management model was developed to test these relationships. The results had empirically validated the model and indicate that a higher level of BRP adoption and increased level of B2B e-commerce adoption readiness had a significant direct relationship with B2B e-commerce benefits. In addition, the level of B2B e-commerce adoption readiness, and the level of IEM and BRP adoption were significantly influenced by the level of IT maturity. However, the use of IEM alone had only an indirect positive influence on B2B e-commerce benefits through the higher level of BRP adoption and increased level of B2B e-commerce adoption readiness.     

Business value of B2B electronic commerce: the critical role of inter-firm collaboration

B2B (business-to-business) electronic commerce provides firms with different business value depending on how organizations use the online network. In this paper, we distinguish two different types of B2B e-commerce adoption: basic and collaborative B2B e-commerce. With “basic B2B e-commerce”, firms implement the electronic network simply to automate the exchange of commercial documents. In contrast, B2B networks are used to create new inter-firm operations with channel partners in “collaborative B2B e-commerce.” The central claim of this paper is that firms are unlikely to achieve significant benefits with Basic B2B e-commerce. B2B electronic networks offer dramatic performance improvement only when the B2B network is used to create new collaboration with channel partners. Based on the survey conducted in the grocery industry, this study suggests that the real source of performance improvement in the B2B electronic commerce is not an electronic linkage itself, but the collaboration enabled by the electronic network.     

An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching

The emergence of e-commerce marketplace, especially the business-to-business (B2B) e-commerce sector, has created a vast market opportunity for retailers and logistics service providers (LSPs). However, facing the structural changes in B2B logistics orders, without any transformation of logistics operating process in distribution centres, LSPs are experiencing serious challenges in handling B2B e-commerce orders. In order for LSPs to grasp the market pie of the logistics and distribution sector of the e-commerce business through improving the core capability of handling B2B e-commerce order in their distribution centres, this paper proposes a novel approach for LSPs to systematically execute B2B order pre-processing so that the B2B e-commerce orders are better managed. An intelligent B2B order handling system (IOHS) is developed for efficient management of discrete, frequently arrived B2B e-commerce orders. By applying the “warehouse postponement” concept through the development of IOHS integrating cloud database management, fuzzy logic, and genetic algorithm approach, B2B order grouping solutions are effectively generated. A case study is conducted in a Hong Kong-based logistics service provider who handles outsourced B2B e-commerce orders, indicating the feasibility of the proposed solution to facilitate e-order fulfilment under both fixed and variable time-window batching settings in distribution centres. A significant improvement in terms of the throughput rate of handling B2B e-commerce order in the distribution centre is found, thereby increasing the satisfaction of buyers and sellers throughout the order handling and delivery process, as well as facilitating LSPs’ capability to manage a larger number of orders received from B2B e-commerce platform, given the greater product exposure of sellers in today’s B2B e-business.     

Measuring the impact of organizational constraints on the success of business-to-business e-commerce efforts: a transactional focus

This study investigated the impact of two organizational constraints, technological compatibility and operational capacity, on the success of business-to-business (B2B) electronic commerce (e-commerce) efforts over a range of business settings. We focused specifically on the transactional efficiencies gained through the use of B2B e-commerce. To accomplish this, we considered an instrument originally developed to measure the benefits of intra-organizational information systems and applied it in two inter-organizational contexts: electronic data interchange (EDI) usage, and B2B technology usage by firms without EDI. Analysis was carried out on 86 firms in the consumer electronics industry, approximately half of which were product-manufacturing firms and the other half service-providing firms. Our findings showed that the inter-organizational context had a significant bearing on which constraints have a greater impact on the success of B2B e-commerce efforts.     

Evaluation of intelligent agents in consumer-to-business e-Commerce

Electronic commerce has changed traditional business trading behaviors, since consumers can easily consume through the Internet e-commerce platform. The Internet provides numerous products and services, but consumers find it is hard to choose their favorite ones. The consumer-to-business (C2B) is popular in recent years and it has become one of the best choices for customers forming a group to buy products. Thus, more and more consumers participate in online group buying. However, consumers anticipate to different prices when buying products and demand service. Thus, applying an intelligent agent into negotiation can effectively decrease efforts spent on collecting buyer information, transaction costs, and negotiation with sellers.This study proposed a system that applies an intelligent agent into the C2B e-commerce process, and evaluates the system through an experiment. Additionally, a questionnaire is used to investigate the benefits of the proposed intelligent agent systems. Analytical results show that the proposed intelligent system can increase user satisfaction, reduce performance risk, and raise perceived fairness, but nothing help on perceived value. It implied that the system still needs efforts and time to promote in nowadays commerce. If people can understand its value from finding the information they need, it must grant the more perceived value. Additionally, this system is not only applicable to C2B, but it can extend to other e-commerce models, because the agent can help the negotiation between the sellers and buyers.     

Combined Negotiations in E-Commerce: Concepts and Architecture

Combined Negotiations are a novel and general type of negotiation, in which the user is interested in many goods or services and consequently engages in many negotiations at the same time. The negotiations are independent of each other, whereas the goods or services are typically interdependent. Using currently available technology for electronic negotiations, the user conducts each negotiation separately, and has the burden of coordinating and reconciling them. The inherent complexity of combined negotiations in B2C as well as B2B e-commerce calls for software support.In our research, we aim to devise a Combined Negotiation Support System (CNSS) to help the user conduct all the negotiations at the same time. The CNSS enables the user to control and monitor the progress of the negotiations, makes sure that the specified dependencies are respected, and applies user-defined strategy rules. We have designed such a CNSS which we call CONSENSUS. The architecture of CONSENSUS relies on workflow technology, negotiating software agents, and rule engine technology. The originality of this architecture lies in the fact that the user of CONSENSUS models the combined negotiation at build time using a workflow that captures the sequencing of the individual negotiations and the dependencies between them. At runtime, software agents are assigned to individual negotiations, and they participate in the combined negotiation as actors in the workflow. The user can monitor the progress of the combined negotiation as a whole, and the progress of individual negotiations via dedicated graphical user interfaces. We rely on rule engine technology to enable the agents to use negotiation strategies.The paper introduces combined negotiations with a usage scenario. Then, combined negotiations are detailed, along with the approach taken to cope with their complexity. Afterwards, we describe the functionality a CNSS should provide, and present the architecture of CONSENSUS, together with a discussion of the underlying concepts and technologies. Furthermore, we report on our prototype implementation of CONSENSUS and illustrate it with an example. A discussion of related and future work concludes the paper.     

A novel method for coevolving PS-optimizing negotiation strategies using improved diversity controlling EDAs

In agent-mediated negotiation systems, the majority of the research focused on finding negotiation strategies for optimizing price only. However, in negotiation systems with time constraints (e.g., resource negotiations for Grid and Cloud computing), it is crucial to optimize either or both price and negotiation speed based on preferences of participants for improving efficiency and increasing utilization. To this end, this work presents the design and implementation of negotiation agents that can optimize both price and negotiation speed (for the given preference settings of these parameters) under a negotiation setting of complete information. Then, to support negotiations with incomplete information, this work deals with the problem of finding effective negotiation strategies of agents by using coevolutionary learning, which results in optimal negotiation outcomes. In the coevolutionary learning method used here, two types of estimation of distribution algorithms (EDAs) such as conventional EDAs (S-EDAs) and novel improved dynamic diversity controlling EDAs (ID²C-EDAs) were adopted for comparative studies. A series of experiments were conducted to evaluate the performance for coevolving effective negotiation strategies using the EDAs. In the experiments, each agent adopts three representative preference criteria: (1) placing more emphasis on optimizing more price, (2) placing equal emphasis on optimizing exact price and speed and (3) placing more emphasis on optimizing more speed. Experimental results demonstrate the effectiveness of the coevolutionary learning adopting ID²C-EDAs because it generally coevolved effective converged negotiation strategies (close to the optimum) while the coevolutionary learning adopting S-EDAs often failed to coevolve such strategies within a reasonable number of generations.     

Supply web co-ordination by an agent-based trading network with integrated logistics services

B2B interactions, like electronic negotiations and auctions between suppliers and customers, could be significantly improved by enabling the participants to adapt their bidding strategies to current logistics information (e.g., about transportation condition, cost or dates) while the negotiation goes on. We present an approach of an agent-based information and trading network (ITN) called CASA for dynamic production and sales of timber; the integrated services for logistics and e-commerce are efficiently coordinated by appropriate types of holonic structured intelligent agents of the network. We introduce the agent-based architecture and describe how the agents build their plans and optimize them afterwards. For optimizing their plans, the agents use various market-based negotiation mechanisms, i.e., several auction mechanisms and the simulated trading mechanism described in detail in this article. The effects of the different mechanisms on resulting cost and surplus have been evaluated by various simulation runs in different competitive and co-operative settings. It turned out that the simulated trading mechanism as well as matrix auction mechanisms for two or three items are especially suitable for supply web co-ordination and optimization tasks.     

Towards Autonomous and Automatic Evaluation and Negotiation in Agent-Mediated Internet Marketplaces

In an agent-mediated B2C Internet marketplace, agents, mobile or stationary, can act on behalf of customers to complete tasks involved in buying and selling products. In this paper, we first present a fuzzy-set based two-phase evaluation model allowing mobile agents to evaluate and filter online e-shops, and evaluate offers autonomously and automatically at the request from a consumer. The fuzzy evaluation criterion takes into account not only the attributes of offers, but also the reputation of corresponding e-shops. }Meanwhile, the two-phase operations can help reduce the scale of mobile agents dispatched to e-shops and thus reduce the network workload. Based on the same fuzzy evaluation criterion, an auction-like negotiation model is presented, where the consumer agent can autonomously determine the initial offer and negotiate with multiple shops simultaneously. The final best offer is determined not only by the attributes of the offers, but also the attributes of the e-shops as well as the preference the consumer specified. Finally, our models presented in this paper have been implemented in a prototype system where we conducted some experiments to evaluate their performance.     

基于F2C模式的“茶多网”成功因素研究

随着电子商务的飞速发展,电子商务模式也层出不穷。电子商务由最初的B2B模式发展到B2C模式、C2C模式,再到现在的F2C模式,不断给互联网用户带来新的体验。以F2C模式为代表的茶多网,经过1年多的运营,取得了巨大的成功,赢得了各方的高度好评。本文分析了F2C模式电子商务网站茶多网的主要成功因素,给出了其今后发展的思路。     

A fuzzy system approach to multilateral automated negotiation in B2C e-commerce

Software agents in e-commerce systems are assigned to the participants. Buyer and supplier agents into multi-agent system architecture of the e-commerce system negotiate with others through an automated negotiation mechanism. In this study, an automated negotiation to interact between buyer and supplier and attain agreement for both is presented. A fuzzy inference system was used to automate negotiation process and consider two effective factors in the negotiation process: requirements and preferences. Requirements are qualitative or quantitative values which the participants assign to the issues of negotiation. Preferences of the participants are priorities assigned by them to issues. These values express an importance measure of issues from a participant perspective. Proposed model applies different fuzzy inference system (FIS) schemes for qualitative and quantitative negotiation issues to enhance the satisfaction level of the buyer and supplier. The FISs infer based on the preferences and requirements of both parties. Additionally, analytic hierarchy process was used to get preferences of the issues. In this proposal, mediator uses issue trade-offs strategy in which multiple issues are traded-offs against one another. The model applies a fuzzy system approach to make trade-offs.     

Fuzzy e-negotiation agents

 The paper presents a prototype of Fuzzy e-Negotiation Agents (FeNAs) for autonomous multi-issue negotiation in e-commerce. It considers negotiation as a form of distributed decision making in the presence of limited common knowledge and imprecise/soft constraints that can be modeled as a distributed fuzzy constraint satisfaction problem (DFCSP). FeNAs incorporate the principles of utility theory within DFCSPs and use fuzzy constraint-based reasoning in order to find a consensus that maximizes the agent's utility and the level of its fuzzy constraint satisfaction subject to its acceptability by other agents. The paper presents aspects of problem representation and negotiation mechanisms used by FeNAs in the context of DFCSPs. An overview of FeNAs is provided and some capabilities for automated multi-issue negotiation are illustrated with two scenarios of e-commerce trading.