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Does reliable information matter? Towards a trustworthy co-created recommendation model by mining unboxing reviews

机译:可靠的信息重要吗?通过挖掘拆箱评论来建立可信赖的共同创建的推荐模型

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摘要

Online review forums provide customers with powerful platforms to express opinions and influence business trends, while allowing firms to collaborate and co-create value with customers. However, information overload due to the huge amount of reviews posted daily complicates the efforts of consumers to locate reliable information when making a purchase decision. Therefore, this study develops a trustworthy co-created recommendation model. The proposed model mines unboxing reviews, calculates the trust scores of the reviewers, and then generates the recommended products by combing this information with customer preferences using a multi-criteria decision-making method. An illustrative example of mobile phones demonstrates the recommendation procedure of the proposed model. The proposed model is evaluated via an empirical experiment to examine the satisfaction of study participants by using a seven-point Likert scale. An analysis of the structural equation modelling results indicates that three factors (i.e. confidence in decision quality, enhanced problem-solving ability, and satisfaction with resource expenditure) significantly and positively affect the purchase decision-making process. Moreover, the proposed model outperforms a baseline model in all four factors, ultimately increasing user satisfaction. In addition to its theoretical framework for co-creating value with customers to develop a trustworthy co-created recommendation model, as supported by various theories of trust, the proposed model provides further insights into the role of customer reviews in designing recommendation models, as well as the extent to which such models impact user decisions.
机译:在线评论论坛为客户提供了强大的平台,可以表达意见并影响业务趋势,同时允许公司与客户合作并共同创造价值。但是,由于每天发布大量评论而导致信息过载,使消费者在做出购买决定时寻找可靠信息的努力变得复杂。因此,本研究建立了一个值得信赖的共同创建推荐模型。提议的模型对拆箱评论进行挖掘,计算评论者的信任度,然后使用多准则决策方法,通过将该信息与客户偏好相结合,生成推荐产品。手机的说明性示例演示了所建议模型的推荐过程。通过实证实验对提出的模型进行评估,以使用七点李克特量表来检验研究参与者的满意度。对结构方程建模结果的分析表明,三个因素(即对决策质量的信心,增强的问题解决能力和对资源支出的满意度)显着且积极地影响了购买决策过程。此外,在所有四个因素方面,建议的模型均优于基准模型,最终提高了用户满意度。在各种信任理论的支持下,除了其与客户共同创造价值以开发可信赖的共同创建的推荐模型的理论框架外,该提议的模型还为客户评论在设计推荐模型中的作用提供了进一步的见解。这种模型在多大程度上影响了用户的决策。

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