3 resultados para WebSphere Commerce REST Service

em Aston University Research Archive


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Electronic commerce (e-commerce) has become an increasingly important initiative among organisations. The factors affecting adoption decisions have been well-documented, but there is a paucity of empirical studies that examine the adoption of e-commerce in developing economies in the Arab world. The aim of this study is to provide insights into the salient e-commerce adoption issues by focusing on Saudi Arabian businesses. Based on the Technology-Organisational-Environmental framework, an integrated research model was developed that explains the relative influence of 19 known determinants. A measurement scale was developed from prior empirical studies and revised based on feedback from the pilot study. Non-interactive adoption, interactive adoption and stabilisation of e-commerce adoption were empirically investigated using survey data collected from Saudi manufacturing and service companies. Multiple discriminant function analysis (MDFA) was used to analyse the data and research hypotheses. The analysis demonstrates that (1) regarding the non-interactive adoption of e-commerce, IT readiness, management team support, learning orientation, strategic orientation, pressure from business partner, regulatory and legal environment, technology consultants‘ participation and economic downturn are the most important factors, (2) when e-commerce interactive adoption is investigated, IT readiness, management team support, regulatory environment and technology consultants‘ participation emerge as the strongest drivers, (3) pressure from customers may not have much effect on the non-interactive adoption of e-commerce by companies, but does significantly influence the stabilisation of e-commerce use by firms, and (4) Saudi Arabia has a strong ICT infrastructure for supporting e-commerce practices. Taken together, these findings on the multi-dimensionality of e-commerce adoption show that non-interactive adoption, interactive adoption and stabilisation of e-commerce are not only different measures of e-commerce adoption, but also have different determinants. Findings from this study may be valuable for both policy and practice as it can offer a substantial understanding of the factors that enhance the widespread use of B2B e-commerce. Also, the integrated model provides a more comprehensive explanation of e-commerce adoption in organisations and could serve as a foundation for future research on information systems.

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Purpose - The purpose of this paper is to construct a new e-commerce innovation and adoption model that takes into account various stages of e-commerce adoption (interactive, non-interactive and stabilised) and covers technological, organisational and environmental factors. This was tested using data collected from manufacturing and service companies in Saudi Arabia (SA) to reveal inhibitors and catalysts for e-commerce adoption. Design/methodology/approach - This study uses new data from surveys from 202 companies and then uses exploratory factor analysis and structural equation modelling for analyses. Findings - This study shows that the new stage-oriented model (SOM) is valid and can reveal specific detailed nuances of e-commerce adoption within a particular setting. Surprising results show that SA is not so very different to developed western countries in respect to e-commerce adoption. However there are some important differences which are discussed in detail. Research limitations/implications - A new SOM for e-commerce adoption is provided which may be used by other IS adoption researchers. Practical implications - Managers responsible for the adoption of e-commerce in SA, the Middle East and beyond can learn from these findings to speed up adoption rates and make e-commerce more effective. Social implications - This work may help spread e-commerce use throughout SA, the Middle East and to other developing nations. Originality/value - The results add to the extremely limited number of empirical studies that has been conducted to investigate e-commerce adoption in the context of Arabic countries.

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In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.