Abstract

PurposeThe post-pandemic recognises changes are required; universities need to rethink their e-servicescapes strategies by offering different approaches to enhance students’ learning. This study aims to draw on learning self-efficacy trajectories and propose a conceptual model for exploring the predictive validity of satisfaction. In addition, it explores the mediating role of e-servicescapes and the moderating relationship effect of mature and younger students.Design/methodology/approachLearning self-efficacies is incorporated into the design of the model in an attempt to understand student cognition. The influences of e-servicescape on adopting online preferences and satisfaction are also examined. The model was empirically validated by surveying 266 respondents. Structural equation modelling and multi-group analysis were used to analyse the data.FindingsThe results of this study show learning self-efficacies has no significant influence on satisfaction. Yet, they showed a significant influence on e-servicescapes. E-servicescapes positively influenced satisfaction and preference for adopting online learning. E-servicescapes also had a mediating effect between self-efficacy to complete a course and satisfaction, as well as self-efficacy to interact with instructors and satisfaction. It had a negative suppressed effect on social interaction.Originality/valueThe research makes the following contributions. Firstly, the conceptualised model identifies an association between learning self-efficacies and e-servicescapes, suggesting universities as service providers can maximise the value offerings of their customer assets. Secondly, e-servicescapes demonstrate a full mediating effect between self-efficacies and satisfaction, indicating that if universities are to compete successfully in dynamic markets, they should co-create value in their e-servicescapes domain to increase satisfaction. Thirdly, the study recognises the need for a hybrid system of both face-to-face and online delivery because the multi-group analysis shows mature age preference for online learning is required to make this transformation successful.

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