26,215 research outputs found

    Using webcrawling of publicly available websites to assess E-commerce relationships

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    We investigate e-commerce success factors concerning their impact on the success of commerce transactions between businesses companies. In scientific literature, many e-commerce success factors are introduced. Most of them are focused on companies' website quality. They are evaluated concerning companies' success in the business-to- consumer (B2C) environment where consumers choose their preferred e-commerce websites based on these success factors e.g. website content quality, website interaction, and website customization. In contrast to previous work, this research focuses on the usage of existing e-commerce success factors for predicting successfulness of business-to-business (B2B) ecommerce. The introduced methodology is based on the identification of semantic textual patterns representing success factors from the websites of B2B companies. The successfulness of the identified success factors in B2B ecommerce is evaluated by regression modeling. As a result, it is shown that some B2C e-commerce success factors also enable the predicting of B2B e-commerce success while others do not. This contributes to the existing literature concerning ecommerce success factors. Further, these findings are valuable for B2B e-commerce websites creation

    Effectiveness of Corporate Social Media Activities to Increase Relational Outcomes

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    This study applies social media analytics to investigate the impact of different corporate social media activities on user word of mouth and attitudinal loyalty. We conduct a multilevel analysis of approximately 5 million tweets regarding the main Twitter accounts of 28 large global companies. We empirically identify different social media activities in terms of social media management strategies (using social media management tools or the web-frontend client), account types (broadcasting or receiving information), and communicative approaches (conversational or disseminative). We find positive effects of social media management tools, broadcasting accounts, and conversational communication on public perception

    Report on the Information Retrieval Festival (IRFest2017)

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    The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

    Exploring Voice of Customers to Chatbot for Customer Service with Sentiment Analysis

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    Abstract. Chatbots have been widely employed across a wide variety of companies and industries, from small- and medium-sized businesses to large corporations, and from e-commerce to financial institutions. Although chatbots have proven to be far more efficient and quicker than human agents, they do not always provide customers with a satisfactory experience because they lack a personal touch. Customer issues are often left unresolved and many are unsatisfied with chatbot services. This is unfavorable for firms that use chatbots for customer services as this jeopardizes their relationship with valued consumers. Thus, customer input is essential to streamline the product innovation process. This study uses a hybrid method involving lexicon-based TextBlob and logistic regression techniques to identify the sentiments of consumers toward chatbots for customer services based on user-generated content on Twitter. The results show that although people generally have positive encounters with chatbots, the gap between positive and negative sentiments is relatively small. This research provides insights that businesses can use to improve chatbot technology based on the voice of the customer to provide users with higher quality customer services in the future, especially since unsatisfied customers could be a threat to a business’s performance. Keywords:  chatbot, customer services, sentiment analysis, social media mining, voice of customers

    Toward Universal Broadband in Rural Alaska

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    The TERRA-Southwest project is extending broadband service to 65 communities in the Bristol Bay, Bethel and Yukon-Kuskokwim regions. A stimulus project funded by a combination of grants and loans from the Rural Utilities Service (RUS), TERRA-Southwest has installed a middle-mile network using optical fiber and terrestrial microwave. Last-mile service will be through fixed wireless or interconnection with local telephone networks. The State of Alaska, through its designee Connect Alaska, also received federal stimulus funding from the National Telecommunications and Information Administration (NTIA) for tasks that include support for an Alaska Broadband Task Force “to both formalize a strategic broadband plan for the state of Alaska and coordinate broadband activities across relevant agencies and organizations.” Thus, a study of the impact of the TERRA project in southwest Alaska is both relevant and timely. This first phase provides baseline data on current access to and use of ICTs and Internet connectivity in rural Alaska, and some insights about perceived benefits and potential barriers to adoption of broadband. It is also intended to provide guidance to the State Broadband Task Force in determining how the extension of broadband throughout the state could contribute to education, social services, and economic activities that would enhance Alaska’s future. Results of the research could also be used proactively to develop strategies to encourage broadband adoption, and to identify applications and support needed by users with limited ICT skills.Connect Alaska. The National Telecommunications and Information Administration. General Communications Incorporated.Part 1: An Analysis of Internet Use in Southwest Alaska / Introduction / Previous Studies / Current Connectivity / Analytical Framework and Research Methodology / Demographics / Mobile Phones: Access and Use / Access to the Internet / Internet Useage / Considerations about Internet Service / Interest in Broadband / Sources of News / Comparison with National Data / Internet Use by Businesses and Organizations / What Difference may Broadband make in the Region? / Conclusiongs / Part 2 Literature Review / Reference

    The Partial Evaluation Approach to Information Personalization

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    Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems have emerged as an important segment of the Internet economy. This paper presents a systematic modeling methodology - PIPE (`Personalization is Partial Evaluation') - for personalization. Personalization systems are designed and implemented in PIPE by modeling an information-seeking interaction in a programmatic representation. The representation supports the description of information-seeking activities as partial information and their subsequent realization by partial evaluation, a technique for specializing programs. We describe the modeling methodology at a conceptual level and outline representational choices. We present two application case studies that use PIPE for personalizing web sites and describe how PIPE suggests a novel evaluation criterion for information system designs. Finally, we mention several fundamental implications of adopting the PIPE model for personalization and when it is (and is not) applicable.Comment: Comprehensive overview of the PIPE model for personalizatio
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