Integrating service quality as a second-order factor in a customer satisfaction and loyalty model

服务质量 结构方程建模 验证性因素分析 忠诚 服务(商务) 营销 顾客满意度 忠诚商业模式 质量(理念) 酒店业 计算机科学 知识管理 业务 旅游 哲学 机器学习 认识论 法学 政治学
作者
Robin Nunkoo,Viraiyan Teeroovengadum,Peta Thomas,Llewellyn Leonard
出处
期刊:International Journal of Contemporary Hospitality Management [Emerald Publishing Limited]
卷期号:29 (12): 2978-3005 被引量:120
标识
DOI:10.1108/ijchm-11-2016-0610
摘要

Purpose The study conceptualizes service quality as a second-order factor and analyzes its influence on customer satisfaction, perceived value, image, consumption emotions and customer loyalty by testing a structural equation model. Design/methodology/approach The model is tested using data collected from 672 guests staying in accommodation establishments located in South Africa. The study follows a hierarchical approach using confirmatory factor analysis to test the second-order factor model and structural equation modeling to test the overall model. Findings The results indicate that the second-order factor model is acceptable both empirically as well as conceptually and performs better than other competing models of service quality. The findings provide support for all hypotheses and evidence of a structural model with a high explanatory power. Research limitations/implications The second-order factor model is less useful when fine-grained analyses are needed, such as when a detailed assessment of the level of quality of service offered by a hospitality organization is required. Practical implications The second-order factor model allows for an analysis of service quality at different levels of abstraction. Accommodation managers interested in customers’ evaluation of service on a cumulative basis can make use of the global measure to determine service quality evaluations. Practitioners can also use the findings to manage the different dimensions of service quality. Originality/value The study demonstrates that service quality is best represented as a second-order factor, and in doing so, it provides an improved measurement of the construct. More so, by integrating the variable in a nomological network, the research develops a more parsimonious model than the existing ones.
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