Chengdu Jincheng College, Chengdu 611731, China.
Jiangxi University of Technology, Nanchang 330098, China.
J Environ Public Health. 2022 May 23;2022:5907900. doi: 10.1155/2022/5907900. eCollection 2022.
The development trend of tourism performance networking, although convenient for audience consumption, also makes the performance information present the development trend of big data. In the mass of information, how to accurately locate products and improve audience satisfaction is an urgent problem to be solved. In order to better explore the evaluation of tourism performance by the customer satisfaction evaluation model, analyze the development prospect of tourism in Jiangxi Province in the future, improve the customer satisfaction evaluation model with rough set, and propose a composite customer satisfaction evaluation model. By setting the adjustment value of the evaluation index, the model not only avoids the "false eigenvalue" of the satisfaction evaluation result but also simplifies the calculation process of the model and improves the accuracy, calculation efficiency, and single data processing capacity of the satisfaction evaluation. According to the MATLAB simulation results, the composite customer satisfaction evaluation model constructed in this study is better, the calculation accuracy is >97%, and the calculation time is 40 seconds, which are better than the original customer satisfaction evaluation model. Therefore, the composite customer satisfaction evaluation model can be applied to the evaluation of tourism performance products to provide data support for the evaluation price of audience satisfaction in Jiangxi Province.
旅游绩效网络的发展趋势,虽然方便了观众的消费,但也使得演出信息呈现出大数据的发展趋势。在大量的信息中,如何准确地定位产品并提高观众满意度是一个亟待解决的问题。为了更好地通过客户满意度评价模型来探索旅游绩效的评价,分析江西省未来的旅游发展前景,利用粗糙集对客户满意度评价模型进行改进,提出了一种复合客户满意度评价模型。通过设置评价指标的调整值,该模型不仅避免了满意度评价结果的“虚假特征值”,而且简化了模型的计算过程,提高了满意度评价的准确性、计算效率和单数据处理能力。根据 MATLAB 的模拟结果,本研究构建的复合客户满意度评价模型更好,计算精度>97%,计算时间为 40 秒,优于原始客户满意度评价模型。因此,复合客户满意度评价模型可应用于旅游绩效产品的评价,为江西省观众满意度评价价格提供数据支持。