563 research outputs found

    Context-aware Helpfulness Prediction for Online Product Reviews

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    Modeling and prediction of review helpfulness has become more predominant due to proliferation of e-commerce websites and online shops. Since the functionality of a product cannot be tested before buying, people often rely on different kinds of user reviews to decide whether or not to buy a product. However, quality reviews might be buried deep in the heap of a large amount of reviews. Therefore, recommending reviews to customers based on the review quality is of the essence. Since there is no direct indication of review quality, most reviews use the information that ''X out of Y'' users found the review helpful for obtaining the review quality. However, this approach undermines helpfulness prediction because not all reviews have statistically abundant votes. In this paper, we propose a neural deep learning model that predicts the helpfulness score of a review. This model is based on convolutional neural network (CNN) and a context-aware encoding mechanism which can directly capture relationships between words irrespective of their distance in a long sequence. We validated our model on human annotated dataset and the result shows that our model significantly outperforms existing models for helpfulness prediction.Comment: Published as a proceeding paper in AIRS 201

    Global delivery models: the role of talent, speed and time zones in the global outsourcing industry

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    Global delivery models (GDMs) are transforming the global IT and business process outsourcing industry. GDMs are a new form of client-specific investment promoting service integration with clients by combining client proximity with time-zone spread for 24/7 service operations. We investigate antecedents and contingencies of setting up GDM structures. Based on comprehensive data we show that providers are likely to establish GDM location configurations when clients value access to globally distributed talent and speed of service delivery, in particular when services are highly commoditized. Findings imply that coordination across time zones increasingly affects international operations in business-to-business and born-global industries

    Humic Substances Enhance Chlorothalonil Phototransformation via Photoreduction and Energy Transfer

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    ABSTRACT: The photodegradation of chlorothalonil, a polychlorinated aromatic fungicide widely used in agriculture, was investigated under ultraviolet–visible irradiation in the presence and absence of different humic substances that significantly enhance the chlorothalonil phototransformation. On the basis of a kinetic model, an analytical study, the effect of scavengers, the chlorothalonil phosphorescence measurement, and varying irradiation conditions, it was possible to demonstrate that this accelerating effect is due to their capacity to reduce the chlorothalonil triplet state via H-donor reaction and to energy transfer from the triplet humic to ground state chlorothalonil. Energy transfer occurs at wavelengths below 450 nm and accounts for up to 30% of the reaction in deoxygenated medium upon irradiation with polychromatic light (300–450 nm). This process is more important with Elliott humic and fulvic acids and with humic acids extracted from natural carbonaceous material than with Nordic NOM and Pahokee peat humic acids. The obtained results are of high relevance to understanding the processes involved in chlorothalonil phototransformation and the photoreactivity of humic substances. Chlorothalonil is one of the rare molecules shown to react by energy transfer from excited humic substances

    Catching-up in the global factory: analysis and policy implications

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    MNEs shape the location of activities in the world economy, linking diverse regions in what has been called the global factory. This study portrays the evolution of incomes and employment in the global factory using a quantitative input–output approach. We find emerging economies forging ahead relative to advanced economies in income derived from fabrication activities, handling the physical transformation process of goods. In contrast, convergence in income derived from knowledge-intensive activities carried out in pre- and post-fabrication stages is much slower. We discuss possible barriers to catching-up and policy implications for emerging economies in developing innovation capabilities, stressing the pivotal role of MNEs

    Bookselling online: an examination of consumer behaviour patterns.

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    Based upon empirical research, and using a range of methods, this paper examines the behaviour and experiences of consumers in online bookselling settings and offers comparison between online and offline (traditional) bookselling. The research finds that while the convenience of online bookshops is important, the key factors enticing consumers online are a combination of breadth of range, ease of access to obscure titles, as well as personalised recommendations and customer reviews. The research is of value to the book trade, highlighting consumer responses to widely adopted online marketing approaches. The research also contributes to scholarly knowledge in the fields of consumer behaviour, e-marketing and e-commerce in online bookselling, as well as providing findings which can be tested in other online settings, informing future theoretical research

    What lies between market and hierarchy? Insights from internalization theory and global value chain theory

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    In this paper, we suggest that internalization theory might be extended by incorporating complementary insights from GVC theory. More specifically, we argue that internalization theory can explain why lead firms might wish to externalize selected activities, but that it is largely silent on the mechanisms by which those lead firms might exercise control over the resultant externalized relationships with their GVC partners. We advance an explanation linking the choice of control mechanism to two factors: power asymmetries between the lead firms and their GVC partners, and the degree of codifiability of the information to be exchanged in the relationship

    Assessing Order Effects in Online Community-based Health Forums

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    Measuring the quality of health content in online health forums is a challenging task. The majority of the existing measures are based on evaluations of forum users and may not be reliable. We employed machine learning techniques, text mining methods, and Big Data platforms to construct four measures of textual quality to automatically determine the similarity of a given answer to professional answers. We then used them to assess the quality of 66,888 answers posted on Yahoo! Answers Health section. All four measures of textual quality revealed a higher quality for asker-selected best answers indicating that askers, to some extent, have a proper judgment to select the best answers. We also studied the presence of order effects in online health forums. Our results suggest that the textual quality of the first answer positively influences the mean textual quality of the subsequent answers and negatively influences the quantity of subsequent answers
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