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C2C环境下服装零售感知服务质量综合评价模型 被引量:2

Comprehensive evaluation model of apparel retailing service quality perception under C2C environment
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摘要 为分析C2C服装网购顾客对服务质量评价的主要因素并构建评价模型,以经典的e Tail Q、E-S-Qual服务质量模型为理论框架,基于中国消费者视角及C2C环境下服装零售的特性,设计开发评价量表。通过焦点小组访谈、问卷调查和数据分析,构建了服装零售服务质量的测评模型,包括履行性、隐私性、功效性、享乐性、补偿性5个维度18个测量指标。验证性因子分析结果显示该模型具有良好信度和效度,同时也验证了e Tail Q、E-S-Qual模型并不适用于中国C2C交易环境。通过实证的方法分析维度对服务质量的预测能力,结果表明,履行性和享乐性维度对服务质量的预测最为显著,功效性和补偿性维度次之,隐私性维度对服务质量的预测并不显著。 In order to analyze the main factors of service quality evaluation by customers of C2 C online apparel shopping and to construct the evaluation model,using the classical e Tail Q,E-S-Qual service quality model as the theoretical framework and based on the Chinese consumers' perspective and the characteristics of apparel retailing in C2 C environment,an evaluation scale was designed. By means of focus group interview,questionnaire survey and data analysis,the evaluation model of apparel retailing service quality was constructed,including the five dimensions of performance,privacy,efficiency,hedonic,compensation and 18 measurement indicators. The results of confirmatory factor analysis show that the model has good reliability and validity,and the e Tail Q and E-S-Qual models are not applicable in China's C2 C trading environment. The prediction capability of dimensions on service quality by empirical methods were analyzed. The results show that the performance and hedonic dimensions are the most significant predictors of service quality,efficiency and compensatory dimensions are secondary predictors,and the privacy dimension has no significant predictability on service quality.
作者 高广明 朱江晖 许丽慧 孙莉 谷芬芬 GAO Guangming;ZHU Jianghui;XU Lihui;SUN Li;GU Fenfen(College of Fine Arts and Design,Wenzhou University,Wenzhou,Zhejiang 325035,China;Hangzhou Anshe E-Commerce Co.,Ltd.,Hangzhou,Zhejiang 311100,China)
出处 《纺织学报》 EI CAS CSCD 北大核心 2018年第8期164-170,共7页 Journal of Textile Research
基金 浙江省教育厅一般科研项目(Y201737109) 温州市公益性科技计划项目(R20170026)
关键词 C2C环境 服装零售 感知服务质量 因子分析 综合评价 C2C environment apparel retailing perception of service quality factor analysis comprehensive evaluation
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