Purpose The purpose of this paper is to investigate and examine the factors contributing to consumers’ mobile shopping continuance intention (CI) of food and non-food items via smartphones and other mobile terminals. Design/methodology/approach An integrated model was proposed on the basis of the technology acceptance model (TAM) and expectation confirmation model (ECM), focussing on perceived value (PV). The survey responses of 203 Chinese mobile shoppers (m-shoppers) were analysed using structural equation modelling with the partial least squares approach. Findings The results indicated that perceived usefulness does not motivate all user groups. Furthermore, satisfaction and perceived ease of use significantly impacted different user groups. For online food m-shoppers, value for money (VM) was the most important factor influencing satisfaction and CI. However, perceived usefulness only affected CI for non-food m-shoppers. Practical implications Marketers can improve users’ CI by enhancing VM and maximising effectiveness and enjoyment while minimising prices. Moreover, in determining strategies for different users, marketers should identify the behavioural differences among all groups and those between the two classified groups. Originality/value This is one of the studies attempting to explain Chinese mobile shopping consumers’ CI, but especially through an integrated model based on TAM and ECM with PV on food and non-food m-commerce perspective. It offers several implications for researchers and practitioners and contributes to the literature of technology acceptance and post-adoption behaviour in m-commerce.

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Ubiquitous learning (u-learning) has been recognized as an exciting approach to knowledge acquisition and skill development. However, a few studies have examined the factors influencing employees' acceptance of u-learning in a ubiquitous computing environment, and the impact of interaction-oriented learning systems' design factors on usage intention (UI) is rare as well. This paper proposes an integrated model derived from the technology acceptance model (TAM) by focusing on users' perceptions of interactivity (INT), software, and hardware design factors. A questionnaire survey was used, and responses of 368 Chinese knowledge workers as learners in Beijing were analyzed using the partial least square structural equation model. This paper successfully integrated three sub-dimensions-interaction, software, and hardware design-into a learning systems design model from a user perspective. The results reveal that perceived INT, perceived content, and perceived infrastructure significantly influence how employees adopt u-learning. This paper is among the first ones to explore INT as a critical factor influencing employee u-learning. Furthermore, it also explored two attitude dimensions toward ''formal'' and ''informal'' u-learning formats and found that these attitudes influence UI, and based on that the TAM is extended. This paper contributes to the literature by investigating the factors affecting employee acceptance of u-learning technology. This paper has several implications for both researchers and practitioners of u-learning and in the educational technology context. INDEX TERMS Ubiquitous learning, educational technology, perceived interactivity, perceived content, perceived infrastructure.

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