E-Service Performance of Apparel E-Retailing Websites: A Longitudinal Assessment

E-Service Performance of Apparel E-Retailing Websites: A Longitudinal Assessment

Jung-Hwan Kim (Department of Retailing, College of Hospitality, Retail and Sport Management, University of South Carolina, Columbia, SC, USA), Minjeong Kim (Indiana University Bloomington, Bloomington, IN, USA) and Sharron J. Lennon (Indiana University Bloomington, Bloomington, IN, USA)
DOI: 10.4018/IJSSMET.2018010103


This article takes a longitudinal approach to examine the evolution of e-retail sites in reference to service delivery performance. Using a content analysis approach, product-related e-service attributes currently available on women's apparel websites were identified and quantified in order to compare them to data collected in an earlier time frame. A Chi-square Goodness-of-Fit test was conducted to compare availability of e-service attributes in 2011 and 2016. The current retailers provided more product description/presentation attributes on their websites than in the 2011 research. However, they are still at an unsatisfactory level that need further improvement. This article offers practical insights for fashion websites in terms of the areas of strengths and weakness in e-service performance by exploring how e-service performance of apparel e-retailers has changed over the past five years.
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With the advent of e-commerce, the retail industry has been revolutionized. With technological advances in information technology and telecommunications, the way people live and how business runs have dramatically changed (Alhawari, Alryalat, & Hunaiti, 2016; Tshin & Tanakinjal, 2014; Wahi, Medury, & Misra, 2015). The growth and maturation of e-commerce as a retail channel and the wide adoption of e-commerce led to the recent emergence of omni-channel retailing where online and offline distinctions are quickly disappearing. Consumers today have high expectations for e-retailers, demanding both efficiency and personalization in addition to competitive prices (E-tailing group, 2015). Additionally, as business boundaries between countries are diminished by the wide adoption of digital technology, growing global competition among e-retailers has been observed and is expected to continue (Barns, 2016).

Despite its strong potential, e-commerce sales in the U.S. are relatively low compared to other developed countries. For example, U.S. e-commerce sales accounted for 7.1% of the total retail sales in 2015 in contrast to 14.4% in the UK and 10.2% in Asia-Pacific (eMarketer, 2015b).

For e-retailers not only to keep up with the current emerging social and business trends, but also to effectively respond to fast changing consumer behavior in accordance with market shifts, they need to carefully monitor issues that affect consumer shopping/purchasing behavior in e-retailing. One such factor is e-service quality. Turk, Scholz, and Berresheim (2012) stated that e-service quality is an essential factor affecting the consumer online shopping experience. As e-commerce has matured in the retail industry, consumer expectation of e-service has likewise increased. It has become a norm among frequent online shoppers to expect free shipping, expedited shipping, or personalized service via live chat or social media. Tshin and Tanakinjal (2014) pointed out that e-service quality is one of the main determinants of retail business success since there is no face-to-face interaction available between consumers and retailers in the online setting.

During the last decade with the fast growth of e-commerce, e-service quality has received wide scholarly attention (e.g., Kim, Kim, & Lennon, 2011; Turk et al., 2012). Extant research offers useful insights into critical service dimensions affecting consumer evaluation of e-service quality across different product or service categories. However, most of these studies are cross-sectional research (i.e., taking snapshots of e-service quality performance at a given time). Despite an abundance of e-service quality research, there is a fundamental lack of understanding of how e-service quality has evolved over time. Due to a wide variety of samples used, direct comparisons across different cross-sectional research studies are not adequate to draw meaningful conclusions.

In order to make a meaningful longitudinal investigation of e-service quality, the current study utilizes two research publications that took a systematic assessment of e-service quality performance of fashion websites (Kim, Kim, & Lennon, 2006, 2011). These studies employed a large set of fashion websites in the U.S. and content analyzed an extensive list of e-service attributes available as cross-sectional research. Therefore, it was deemed relevant to adopt the coding guide developed and validated by Kim et al. (2006, 2011) and use it for the current longitudinal study of e-service quality. The findings of this study offer not only the up-to-date assessment of current e-service quality performance of U.S. fashion websites, but also new historical insights about how e-service quality of U.S. fashion websites has evolved over a recent five-year period. Such findings are expected to fill the gap in existing e-service quality literature and offer practical insights for fashion websites in terms of the areas of strengths and weaknesses in e-service performance.

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