Scielo RSS <![CDATA[Journal of theoretical and applied electronic commerce research]]> vol. 6 num. 3 lang. es <![CDATA[SciELO Logo]]> <![CDATA[<b>Editorial</b>: <b>Editorial Board Communication System</b>]]> <![CDATA[<b>E-business for Nations</b>: <b>A Study of National Level Ebusiness Adoption Factors Using Country Characteristics-Business-Technology-Government</b> <b>Framework</b>]]> Earlier studies on e-business adoption factors have been conducted from a firm level perspective or from a single country level perspective. In this study, we propose a framework entitled country characteristics- business-technology-government model that addresses a theoretical perspective on e-business adoption factors required for a nation level e-business development. The major goal of this study is four-fold: (i) to review existing key literature on e-business across the countries and identify key factors affecting e-business adoption, (ii) to propose a research model based on the identified factors, (iii) to test the proposed model empirically using the national level macro economic data from secondary sources, and (iv) to provide insightful discussions for country administrators, policy makers, and academics. The limitations and future directions of the study are also discussed. <![CDATA[<b>Understanding Organizational Barriers Influencing Local Electronic Government Adoption and Implementation</b>: <b>The Electronic Government Implementation Framework</b>]]> Researches in electronic government have indicated a number of organizational barriers that hinder the adoption and implementation of electronic government. This paper proposes a research framework for analysing how organizational barriers influence the adoption and implementation of e-government at local levels. The framework is constructed based on four organizational dimensions; adaptability, involvement, mission, and bureaucracy drawn from organizational theories and e-government literature. We found that organizational barriers which are identified in major e-government literature link to the dimensions of organizational culture and effectiveness. Our conclusion is that the framework is relevant to understand organizational barriers influencing adoption and implementation of local e-government. The limitation of this study is that the framework has been developed based on the application of a theoretical lens on the e-government literature. It is now necessary to test this model in different contexts. <![CDATA[<b>The Impact of Trust and Relative Advantage on Internet</b> <b>Voting Diffusion</b>]]> Internet voting is an emerging e-government phenomenon. In the United States, several state and local governments have experimented with Internet voting. This study presents a model of Internet voting adoption that integrates diffusion of innovation theory, institution-based trust and e-government utilization. To test the model a survey is administered to 372 citizens. The results of structural equation modeling indicate that relative advantage, Internet trust, and e-government information utilization have a significant impact on intention to use Internet voting. In addition to these direct effects, disposition to trust has a significant impact on Internet trust and accessibility has a significant impact on relative advantage. Not only are citizens interested in using the Internet to obtain government information, but also to cast their ballot. As a result, opportunities for Internet use in the political process are constantly emerging. Government agencies should take advantage of technological innovations to improve the accessibility of the electronic ballot, to communicate the advantages of this phenomenon and to engender trust among the citizenry. <![CDATA[<b>Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation</b> <b>Systems</b>]]> The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation system. In this article, we first analyze the capabilities of existing approaches for coping with unfair ratings in different challenging scenarios, including ones where the majority of buyers are dishonest, buyers lack personal experience with sellers, sellers may vary their behavior, and buyers may provide a large number of ratings. We then present a personalized modeling approach (PMA) that has all these capabilities. Our approach allows a buyer to model both the private reputation and public reputation of other buyers to determine whether these buyers' ratings are fair. More importantly, in this work, we focus on experimental comparison of our approach with two key models in a simulated dynamic e-marketplace environment. We specifically examine the above mentioned scenarios to confirm our analysis and to demonstrate the capabilities of our approach. Our study thus provides the extensive experimental support for the personalized approach that can be effectively employed by reputation systems to cope with unfair ratings. <![CDATA[<b>The Learning of an Opponent's Approximate Preferences in Bilateral Automated Negotiation</b>]]> Autonomous agents can negotiate on behalf of buyers and sellers to make a contract in the e-marketplace. In bilateral negotiation, they need to find a joint agreement by satisfying each other. That is, an agent should learn its opponent's preferences. However, the agent has limited time to find an agreement while trying to protect its payoffs by keeping its preferences private. In doing so, generating offers with incomplete information about the opponent's preferences is a complex process and, therefore, learning these preferences in a short time can assist the agent to generate proper offers. In this paper, we have developed an incremental on-line learning approach by using a hybrid soft-computing technique to learn the opponent's preferences. In our learning approach, first, the size of possible preferences is reduced by encoding the uncertain preferences into a series of fuzzy membership functions. Then, a simplified genetic algorithm is used to search the best fuzzy preferences that articulate the opponent's intention. Experimental results showed that our learning approach can estimate the opponent's preferences effectively. Moreover, results indicate that agents which use the proposed learning approach not only have more chances to reach agreements but also will be able to find agreements with greater joint utility. <![CDATA[<b>Developing a Fuzzy Multi-attribute Matching and Negotiation Mechanism for Sealed-bid Online Reverse Auctions</b>]]> Online reverse auctions have benefits in reducing business purchasing costs and lead times. Previous research focused on developing new mechanisms for open-cry and multiple rounds of auctions, which is not appropriate for direct goods purchasing. Moreover, the implementation issues in the web-site design are not considered. We construct an easily-computed fuzzy multi-attribute matching mechanism for sealed-bid and single round auctions, which include price and attributes like quality, due dates, credit rating, etc, and are suitable for procuring direct input goods. To improve the negotiation quality, an aftermath negotiation mechanism is also developed so that the auctioneer can negotiate with the bidders for certain attribute values when the bid does not meet the requirement of the auctioneer. We further build an online fuzzy negotiation system (FNS) to evaluate the proposed mechanism. <![CDATA[<b>Hyperlink Analysis of E-commerce Websites for Business Intelligence</b>: <b>Exploring Websites of Top Retail Companies of</b> <b>Asia Pacific and USA</b>]]> Hyperlinks, which connect web pages on the World Wide Web, are rich sources of hidden information. E- Commerce Websites, which are created for different purposes from online sales to company promotion, would benefit if they receive more links from other websites as this would lead to increase the traffic to these websites. This paper analyses the structure of e-commerce websites using webometric approach to uncover any hidden information from the hyperlinks. The top 50 retail companies' e-commerce websites each from Asia Pacific and USA are chosen for this study. Our results found a positive relationship between the external inlinks count pointing to a retail company e-commerce website and one of its business measures, sales. But no association has been found between hyperlink metrics and business measure like revenue. However this conclusion does not hold good for all categories of companies. Comparing the web presence, US private retail companies are more visible on the Web than the Asia pacific retailers. Furthermore this study has found that counts of links pointing to a retail websites are positively correlated with the website age. That is older websites in English language received more external inlinks. Such a correlation does not exist for Japan, China and Korean language websites.