PurposeThis paper aims to identify the generic service quality dimensions of technology‐based banking and to examine the effect of these dimensions on customer satisfaction and customer loyalty.Design/methodology/approachThe generic service quality dimensions are identified using an exploratory factor analysis (EFA). Next the reliability and validity of the factors and customer satisfaction and customer loyalty are established through confirmatory factor analysis (CFA) using AMOS 16.0 s/w. The related hypotheses were tested using structural equation modeling using AMOS 16.0.FindingsThe paper identifies four generic service quality dimensions in the technology‐based banking services – customer service, technology security and information quality, technology convenience, and technology usage easiness and reliability. It was found that customer service and technology usage easiness and reliability have positive and significant impact on customer satisfaction and customer loyalty. It was also found that technology convenience and customer satisfaction have significant and positive impact on customer loyalty.Practical implicationsThese dimensions of service quality should be viewed as the levers of improving perceived service quality with respect to technology‐based banking in the minds of its current customers. Examining the service quality dimensions' impact on customer satisfaction and customer loyalty for technology‐based banking can offer banks valuable insights regarding which aspects of the service to focus on in order to improve customer satisfaction and loyalty towards the firms.Originality/valueThis paper introduces the concept of generic service quality and its significance for customer satisfaction and loyalty in case of technology‐based banking wherein technology is used to deliver services.

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The rapid advancements in Internet technology have led to the development of numerous innovative smart technologies. This research investigates the customer acceptance and resistance of smart technologies in the retail sector by integrating the technology acceptance model, system characteristics, technology readiness, and store reputation literature. Data was collected using a quantitative survey and analysed using symmetrical PLS path modelling and asymmetrical fuzzy set qualitative comparative analysis (fsQCA). Results show complex relationships among perceived technology readiness, perceived ease of use, perceived usefulness, superior functionality, perceived adaptiveness, and store reputation in determining customers' attitude and behavioural intentions towards smart retail technologies. The findings also show that technology readiness does not directly affect customer attitude but indirectly through perceived innovation characteristics. The findings indicate that retail stores should focus on smart technologies that are simple, yet offer enhanced customer value by improving the shopping efficiency. Retail stores can engage in brand management strategies to improve customers' acceptance of SRT.

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