E-SERV-EX: A Multi-item Scale for Measuring Customer Expectations from the Online Retail Services

Purpose: The purpose of this article is the scale development, refinement, and psychometric evaluation of the multi-item scale (E-SERV-EX) for assessing the customers’ expectations from the online retail services and exploring the impact of different demographic and behavioral factors on customer’s expectation. Design/Methodology/Approach: It was conclusive research, which is quantitative and cross-sectional in nature. Data were collected through a survey method using a structured questionnaire from 518 respondents, selected through judgmental sampling from Delhi NCT. The primary statistical tools used in the study were exploratory factor analysis, confirmatory factor analysis for scale development, and partial least square-structural equation modelling for hypothesis testing. Findings: The final scale had 31 items divided into nine dimensions. Assurance/trust, efficiency, fulfillment/reliability, responsiveness, security/privacy, web-design, personalization, price aspects, and customer engagement. Scales demonstrated good psychometric properties based on the findings from various reliability and validity tests conducted in this study. Web design was the most crucial factor, and personalization was the least important factor expected. When we speak about demographic factors, males had more expectations than females in individual and overall expectations. With an increase in age and income, customers’ expectations from online retailer services decrease. With the increase in distance from the physical retail outlet, customers’ expectations from online retail service increase. Consumers with more experience in internet usage and online retail usage had higher expectations. Consumers who surf and purchase more from online retailers also expect more. Practical Implications: The e-expectation scale developed in this study will help marketers and retailers better understand e-service quality expectations. Knowing the consumers’ expectations would help the retailers in framing the e-marketing mix and strategies. The expectations scale can be used in policy formulation and web designing. This scale will also help fill GAP 1 (expected service and management’s perceptions of consumer expectations) and GAP 5 (customer expectations and customer perceptions) of the service quality gap model of Parasuraman, Zeithaml, and Berry. Originality/Value: This research paper contributes to the literature by developing, refining, and evaluating a novel multi-item scale, E-SERV-EX, with good psychometric properties for measuring customer expectations from online retail services whereas most of the papers in the past measured the perceptions. E-SERV-EX can be employed by marketers, retailers, and policymakers to develop effective e-marketing strategies, web designs, and policy formulation by understanding consumer expectations. Most importantly, this scale helps fill GAP 1 (expected service and management’s perceptions of consumer expectations) and GAP 5 (customer expectations and customer perceptions) of the service quality gap model proposed by Parasuraman, Zeithaml, and Berry.