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首页> 外文期刊>Expert Systems with Application >An SEM-artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among low-cost and full-service airline
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An SEM-artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among low-cost and full-service airline

机译：廉价人工和全方位服务航空公司的SERVPERF，客户满意度和忠诚度之间关系的SEM人工神经网络分析

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There is a dearth of studies pertaining to the influence of SERVPERF on customer satisfaction and customer loyalty among low cost and full service airlines. Prior studies have measured service quality using the GAP-5 model with SERVQUAL; however this study offers a new perspective by using the SERVPERF with an SEM artificial-neural-networks predictive analytic approach. This is different from the previous studies as it contributes to application of expert systems and intelligent algorithms in the context of low cost and full service airline. The findings revealed significant influences of SERVPERF dimensions on customer satisfaction towards customer loyalty with 63.1% and 55.6% variance explained. The implications from this research may help CEOs and managers of the air travel and tourism industry players to make better decisions in their resource planning stage, at the same time improving customer satisfaction and loyalty. (C) 2015 Published by Elsevier Ltd.
机译：在低成本和全方位服务的航空公司中，尚缺乏关于SERVPERF对客户满意度和客户忠诚度影响的研究。先前的研究使用带有SERVQUAL的GAP-5模型来测量服务质量；然而，这项研究通过将SERVPERF与SEM人工神经网络的预测分析方法结合使用，提供了新的视角。这与以前的研究不同，因为它有助于在低成本和全方位服务的航空公司中应用专家系统和智能算法。调查结果表明，SERVPERF维度对客户满意度对客户忠诚度的影响显着，解释差异为63.1％和55.6％。这项研究的意义可能会帮助航空旅行和旅游业参与者的CEO和经理在其资源计划阶段做出更好的决策，同时提高客户满意度和忠诚度。 （C）2015年由Elsevier Ltd.出版

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