8,897 research outputs found
E-Business Models In The Travel Industry
Drawing on recently published data, this report examines some of the trends in travel e-commerce. Using a case study approach, the author examines in detail some of the e-business models impacting on the travel industry both in the Business-to-Business (B2B) and Business-to-Consumer (B2C) markets. Although B2C leisure transactions currently account for just 1% of the value of global travel, there is real potential for future growth. However to be successful both new entrants and existing players will need to ensure their e-business model adds value for the customer, otherwise their position in the value chain will be threatened. The most immediate potential for growth and profitability lies in the B2B market, particularly in the development of vertical portals or community extranets. These are virtual spaces enabling travel buyers and suppliers to trade online. The integration of legacy systems with Internet Protocol (IP) technology is taking place across a range of travel sectors and will provide the platform on which a wide range of e-business applications can be developed. This development will lead to the ultimate catalyst for travel e-business -- the convergence of data (internet), voice (telephone) and video (television)
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Integrity protection for code-on-demand mobile agents in e-commerce
The mobile agent paradigm has been proposed as a promising solution to facilitate distributed computing over open and heterogeneous networks. Mobility, autonomy, and intelligence are identified as key features of mobile agent systems and enabling characteristics for the next-generation smart electronic commerce on the Internet. However, security-related issues, especially integrity protection in mobile agent technology, still hinder the widespread use of software agents: from the agent’s perspective, mobile agent integrity should be protected against attacks from malicious hosts and other agents. In this paper, we present Code-on-Demand(CoD) mobile agents and a corresponding agent integrity protection scheme. Compared to the traditional assumption that mobile agents consist of invariant code parts, we propose the use of dynamically upgradeable agent code, in which new agent function modules can be added and redundant ones can be deleted at runtime. This approach will reduce the weight of agent programs, equip mobile agents with more flexibility, enhance code privacy and help the recoverability of agents after attack. In order to meet the security challenges for agent integrity protection, we propose agent code change authorization protocols and a double integrity verification scheme. Finally, we discuss the Java implementation of CoD mobile agents and integrity protection
Ontology acquisition and exchange of evolutionary product-brokering agents
Agent-based electronic commerce (e-commerce) has been booming with the development of the Internet and agent technologies. However, little effort has been devoted to exploring the learning and evolving capabilities of software agents. This paper addresses issues of evolving software agents in e-commerce applications. An agent structure with evolution features is proposed with a focus on internal hierarchical knowledge. We argue that knowledge base of agents should be the cornerstone for their evolution capabilities, and agents can enhance their knowledge bases by exchanging knowledge with other agents. In this paper, product ontology is chosen as an instance of knowledge base. We propose a new approach to facilitate ontology exchange among e-commerce agents. The ontology exchange model and its formalities are elaborated. Product-brokering agents have been designed and implemented, which accomplish the ontology exchange process from request to integration
Designing an Agent for Information Extraction from Persian E-shops
E-shops are among the most conventional applications of Electronic Commerce. In these shops, the buyers search for their goods through key words or classifications and read the product description provided by the sellers. Though, when the number of items is high, this gets to be difficult for the users. On the one hand, there are too many e-shops, and browsing in these shops to find the best and most appropriate goods is a difficult and time-consuming process. On the other hand, product descriptions are not the same in different websites, and there are different product forms. This study investigates about products and sellers in various websites based on the conditions and user requirements through software agents which present the extracted information in the form of a table to the users which enables them to compare prices and each seller’s conditions without spending too much time for browsing. Using this method increases precision and recall indices comparing to a conventional user browsing
A market-oriented agent-based model for information retrieval
International audienceInformation Retrieval in the World Wide Web (Web IR) is essential for a number of activities and it is an active domain of research and development. The main challenges concern the relevance of the results provided to users' queries and the performance regarding respond-time. On the other hand, agent-based market systems prove to be efficient for implementing e-commerce or B2B applications on the internet, thanks to inherent properties such as prominency of interactions, scalability, flexibility, interoperability, etc. Although the use of agents in other application domains is not yet widespread, the integration of mobile agents into market mechanisms bring clear and efficient solutions to Quality of Service issues encountered in most distributed applications and notably in Web IR systems. Mobility allows defining the seller – buyer model of interaction, where agents act on behalf of final users or devices providing re-sources, while the generic Market Place architecture provides an organizational setting for the matching of demands and offers. The paper shows how this framework applies to Web IR and provides experimental validation results from a Jade implementation
Scalability and robustness of a market-based network resource allocation system
In this paper, we consider issues related to scalability and robustness in designing a market-based multi-agent system that allocates bandwidth in a communications network. Specifically, an empirical evaluation is carried out to assess the system performance under a variety of design configurations in order to provide an insight into network deployment issues. This extends our previous work in which we developed an application that makes use of market-based software agents that compete in decentralised marketplaces to buy and sell bandwidth resources. Our new results show that given a light to moderate network traffic load, partitioning the network into a few regions, each with a separate market server, gives a higher call success rate than by using a single market. Moreover, a trade-off in the number of regions was also noted between the average call success rate and the number of messages received per market server. Finally, given the possibility of market failures, we observe that the average call success rates increase with an increasing number of markets until a maximum is reached
Market-Based Task Allocation Mechanisms for Limited Capacity Suppliers
This paper reports on the design and comparison of two economically-inspired mechanisms for task allocation in environments where sellers have finite production capacities and a cost structure composed of a fixed overhead cost and a constant marginal cost. Such mechanisms are required when a system consists of multiple self-interested stakeholders that each possess private information that is relevant to solving a system-wide problem. Against this background, we first develop a computationally tractable centralised mechanism that finds the set of producers that have the lowest total cost in providing a certain demand (i.e. it is efficient). We achieve this by extending the standard Vickrey-Clarke-Groves mechanism to allow for multi-attribute bids and by introducing a novel penalty scheme such that producers are incentivised to truthfully report their capacities and their costs. Furthermore our extended mechanism is able to handle sellers' uncertainty about their production capacity and ensures that individual agents find it profitable to participate in the mechanism. However, since this first mechanism is centralised, we also develop a complementary decentralised mechanism based around the continuous double auction. Again because of the characteristics of our domain, we need to extend the standard form of this protocol by introducing a novel clearing rule based around an order book. With this modified protocol, we empirically demonstrate (with simple trading strategies) that the mechanism achieves high efficiency. In particular, despite this simplicity, the traders can still derive a profit from the market which makes our mechanism attractive since these results are a likely lower bound on their expected returns
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