Descriptive Content Analysis on E-Service Research

Descriptive Content Analysis on E-Service Research

Jung-Hwan Kim (Department of Retailing, College of Hospitality, Retail and Sport Management, University of South Carolina, Columbia, SC, USA) and Sharron J. Lennon (Department of Apparel Merchandising and Interior Design, Indiana University, Bloomington, IN, USA)
DOI: 10.4018/IJSSMET.2017010102
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Abstract

The current study systematically and thoroughly reviewed the extant literature on e-service quality research to examine 1) how e-service is defined by researchers, 2) how e-service quality is defined by researchers, 3) what e-service quality scales and dimensions have been identified, 4) what outcome variables have been assessed in the e-service quality literature, and 5) what theories have been applied in the literature. A total of 72 articles published between 2003 and 2013 were content analyzed. The selected articles focused primarily on e-service quality in the context of B2C e-retailing. The findings of the study provide valuable information to e-service researchers by identifying gaps and disparities in the e-service quality literature. This study provides several crucial suggestions and directions for future research.
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Introduction

Electronic commerce (e-commerce) emerged in the mid-1990s (Toufaily, Ricard, & Perrien, 2013). Over the last 20 years, with the rapid advent of the Internet and e-commerce and as more and more people become involved with online shopping, a growing number of research studies focused on e-service quality. Researchers developed various scales and dimensions to measure key elements of e-service quality. However, those e-service research studies oftentimes either did not provide a clear definition of e-service quality or the definition provided was unclear and ambiguous. Key dimensions of e-service quality were also frequently inconsistent across studies (Kim & Lennon, 2012; Ladhari, 2010; Yaya, Marimon, & Fa, 2012).

The concept of service quality is one of the most significant research topics in marketing because of its relation to financial performance, customer satisfaction, customer loyalty, and customer reassurance (Zahedifard, Mohebi, & Dastrain, 2014). Due to its importance e-service quality is one of the most investigated research topics in the context of e-commerce, and many researchers have identified new dimensions and developed new scales as a means of assessing e-service quality. In spite of these efforts, Akinci, Atilgan-Ina, and Aksoy (2010) pointed out that research on e-service quality is at a preliminary phase compared to the traditional service quality literature. There is little research conducted specifically to provide a systematic review of the extant research that provides a holistic overview of current e-service research and provides direction to the e-service quality literature. Without a holistic and comprehensive review of previous research on e-service quality to identify gaps and disparities in the literature, e-service quality research will not advance beyond the preliminary phase.

Recently in an attempt to address this issue, Kim and Lennon (2012) reviewed extant research articles on e-service quality to define e-service and to review dimensions of e-service quality. However, their research did not comprehensively content analyze the reviewed articles and did not conduct a systematic search to locate empirical research for analysis.

To address this limitation, the current study systematically and thoroughly content analyzed the extant literature on e-service quality research published during a 11 year period (January 2003 to December 2013) to examine 1) how e-service is defined by researchers, 2) how e-service quality is defined by researchers, 3) what e-service quality scales and dimensions have been identified, 4) what outcome variables have been assessed in the e-service quality literature, and 5) what theories have been applied in the literature. Content analysis is a widely used qualitative research method (Hsieh & Shannon, 2005) used in various fields to analyze text data (Cavanagh, 1997). It is an unobtrusive and nonreactive approach to provide knowledge and understand phenomena of interest (Hsieh & Shannon, 2005). Using content analysis, researchers can systematically and objectively understand a phenomenon by describing and quantifying it (Elo & Kyngäs, 2007).

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