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On the Effects of User Ratings on the Profitability of Cloud Services

机译:关于用户评级对云服务盈利能力的影响

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In todays cloud market, providers are taking advantage of consumer reviews and ratings as a new marketing tool to establish their credibility. However, to achieve higher ratings, they need to enhance their service quality which comes with an additional cost. In this paper, we model this conflicting situation as a Stackelberg game between a typical service provider and multiple service users in a cloud environment. The strategy of the service provider is to adjust the price and IT capacity by predicting the users ratings as well as their demands variation in response to his given price, quality and rating. The game is solved through a backward induction procedure using Lagrange function and Kuhn-Tucker conditions. To evaluate the proposed model, we performed experiments on three real world service providers who have low, medium and high average of users' ratings, obtained from the Trust Feedback Dataset in the Cloud Armor project. The results show that improvement in ratings is mostly profitable for highly rated providers. The surprising point is that providers having low ratings do not get much benefit from increasing their average ratings, meanwhile, they can perform well when they lower the service price.
机译:在今天的云市场中,提供商正在利用消费者评论和评级作为一种新的营销工具来建立他们的信誉。但是,为了实现更高的评级,他们需要提高其服务质量,额外的费用。在本文中,我们将这种冲突的情况模拟作为云环境中的典型服务提供商和多个服务用户之间的Stackelberg游戏。服务提供商的策略是通过预测用户评级来调整价格和IT能力,以及他们的需求变化,以响应他的价格,质量和评级。使用拉格朗日功能和Kuhn-Tucker条件,通过向后感应过程解决游戏。为了评估所提出的模型,我们对三个真实世界服务提供商进行了实验,该提供商具有低,中等和高平均用户评级,从云盔甲项目中的信任反馈数据集获得。结果表明,评级的改进主要是对高度评价的提供商有利可图。令人惊讶的观点是,具有低评级的提供者不会因增加平均评级而得到了很大的益处,同时,它们可以在降低服务价格时表现良好。

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