Online customer experience in an emerging e-retail market

Izogo, Ernest Emeka

Abstract

Although customer experience has attracted significant attention in marketing theorizing for over three decades, research has barely progressed beyond the traditional conceptualizations of the concept. Specifically, research on multichannel retailing experience is scarce and fragmented despite previous calls to investigate how customer experience can be optimized at different channels. Additionally, although eWOM is fast supplanting traditional WOM as a determinant of consumer behavior whilst Internet platforms have been declared the future fronts for successful customer relationship management, previous studies rarely examined how consumers process and integrate multiple online reviews especially dissatisfied eWOM. Extrapolating from the foregoing, the following research question is posed: “How can online retailers exploit the link between previous shopping experiences and perceived credibility of negative experience reviews (PCoNERs) to enhance consumer-firm relationship quality?”

To answer the above research question, an experience-perception-attitude model was built on the foundations of two social cognitive psychology theories (i.e. the schema theory and the elaboration likelihood model (ELM)) and consequently tested through four scenario-based experiments mapped out into one pilot study and two main studies. The pilot study and study 1 utilized a 2 × 2 between-subject factorial design while study 2 employed 2 × 2 × 2 between-subject factorial design. Data was generated from undergraduate and postgraduate students recruited from two universities located in southern Nigeria. Exploratory factor analysis, partial least squares structural equation modelling procedure, independent sample t-test, Chi-square, one-way analysis of variance, and multivariate analysis of variance were the analytical techniques utilized.

Five major contributions are made. First, the thesis developed and tested a unique experience-perception-attitude model from the perspective of two social cognitive psychology theories. The experience-perception-attitude model not only portrayed the multi-channel character of online customer experience but also advanced Verhoef et al.’s (2009) holistic and dynamic model of customer experience by demonstrating how consumer-firm relationship quality can be enhanced through a simultaneous consideration of shopping experiences emanating from both company website and social media site. Second, the thesis extends the context-specific nature of customer experience by demonstrating that emotional experience is the most important driver of PCoNERs in a recession-ridden emerging e-retailing market. Third, the study advances the eWOM literature and ELM by drawing on the ELM to demonstrate that PCoNERs have negative effect on consumer-firm relationship quality; while also demonstrating that the effects of the two thresholds of elaboration (i.e. review source credibility and review frequency) become infinitesimal if consumers are exposed to reviews with consistent valence. Fourth, the thesis adds to the experimental design technique utilized by channel integration researchers and previous panel data-based studies by drawing on the netnographic research approach to utilize naturalistic narratives as experimental scenarios. Finally, the findings offer an evidence-based guide on how e-retailers can practically engage in the systematic management of customer clues. The findings will also assist all categories of e-retailers determine the strategic position to pursue based on their resources and capabilities.

Citation

Izogo, E. E. (2017). Online customer experience in an emerging e-retail market. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4220559

• Thesis Type: Thesis
• Deposit Date: Aug 10, 2018
• Publicly Available Date: Feb 23, 2023
• Keywords: Business; Marketing
• Public URL: https://hull-repository.worktribe.com/output/4220559
• Additional Information: Business School, The University of Hull
• Award Date: Sep 1, 2017