65,057 research outputs found

    The Impact of Trust on Acceptance of Online Banking

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    Major benefits of Online Banking include for banks cost savings, and for customers convenience. Nevertheless, many people perceive Internet banking as risky. This paper introduces a tentative conceptual framework. Trust will be integrated into the Technology Acceptance Model – TAM - (Davis, 1989). Recent research showed that Trust has a striking influence on user willingness to engage in online exchanges of money and personal sensitive information. Detailed literature about Online Banking and Trust is provided. TAM is discussed in depth; external variables that are suitable for the Online Banking context is suggested. In addition the theoretical justification for the conceptual framework integration is discussed. Finally managerial implications and recommendations for Online Banking acceptance are suggested

    The State of e-Banking Implementation in Nigeria: A Post-Consolidation Review

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    The most widely used e-Banking instrument in �igeria is e-Payment, particularly the automatic teller machine (ATM) card. However, with the adoption of e-Banking by all the banks in �igeria, the volume of cash in circulation has continued to increase pre-and-post bank recapitalization/consolidation exercise. Furthermore, some of the 25 banks that survived the exercise were found lately to have depleted their capital base and have lost credibility before the consumers, e-Banking implementation notwithstanding. Therefore, in this paper, we review the state of e-Banking implementation in �igeria and evaluate the influence of trust on the adoption of e-Payment using an extended technology acceptance model (TAM). Similarly, we investigate organizational reputation, perceived risk and perceived trust in the management of banks as a factor for enhancing customer loyalty. The findings in this work reveal that perceived ease of use and perceived usefulness are not only antecedent to ebanking acceptance, they are also factors to retain customers to the use of e-banking system such as organizational reputation, perceived risk and trust

    Insurance Industry and E-Business

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    亀井利明教授古稀記念特

    Business-to-business e-commerce: an innovative tool for food chain management

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    A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials, transformation of these materials into intermediate and finished goods, and the distribution of the final goods to customers. The management of food chains, particular of fresh produce chains, need to achieve two goals: (a) create efficient physical flows of products by minimising logistics cost, and reducing lead times (b) run an effective value chain by safeguarding mutual gains for all members of the chain, building trust between suppliers and buyers and at the same time maintaining quality for end consumers. Food chain management was always at a loss for tools to leveraging its efforts on achieving value for chain members and eventually the end-consumers. Although food industry, both in USA and Europe, has experimented with various alternative solutions to this multimillion chain management, yet more can be expected. Business-to-business e-commerce (B2B) appears to be an innovative tool that meets the high standards of the industry and the potential growth. This study examines the uses of B2B in food industry to give chain management solutions. It reviews the uses of B2B and, in particular, highlights the applications of B2B by small agribusiness in order to forge their ring in food chains. It builds upon communication in supply chain. It describes contracting as an example how B2B e-commerce can advance supply activities and reports the development of a B2B olive oil supply chain application. It concludes that B2B can be a strong leverage for food chain management to achieve its goals and produce value for the members of the chain and the end consumers

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

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    The biological immune system (BIS) is characterized by networks of cells, tissues, and organs communicating and working in synchronization. It also has the ability to learn, recognize, and remember, thus providing the solid foundation for the development of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. These randomly generated detectors suffer from not been able to adequately cover the non-self space, which diminishes the detection performance of the V-Detectors algorithm. This research therefore proposed CSDE-V-Detectors which entail the use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in optimizing the random detectors of the V-Detectors. The DE is integrated with CS at the population initialization by distributing the population linearly. This linear distribution gives the population a unique, stable, and progressive distribution process. Thus, each individual detector is characteristically different from the other detectors. CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness of the detector set in the search space. In comparison with V-Detectors, cuckoo search, differential evolution, support vector machine, artificial neural network, na¨Ĺve bayes, and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms other algorithms with an average detection rate of 95:30% on all the datasets. This signifies that CSDE-V-Detectors can efficiently attain highest detection rates and lowest false alarm rates for anomaly detection. Thus, the optimization of the randomly detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly detection tasks

    Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

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    The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented

    A new model to support the personalised management of a quality e-commerce service

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    The paper presents an aiding model to support the management of a high quality e-commerce service. The approach focuses on the service quality aspects related to customer relationship management (CRM). Knowing the individual characteristics of a customer, it is possible to supply a personalised and high quality service. A segmentation model, based on the "relationship evolution" between users and Web site, is developed. The method permits the provision of a specific service management for each user segment. Finally, some preliminary experimental results for a sport-clothing industry application are described
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