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Three-dimensional (3D) food printers are revolutionizing food production with personalized, sustainable and efficient meal creation. This study aims to explore the factors driving consumer intentions to purchase three-dimensional (3D) food printers. These innovative devices are gaining popularity for their ability to produce intricate, customizable food designs with remarkable precision and convenience. By leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the research examines key variables such as performance expectancy, effort expectancy, social influence, facilitating conditions (FCD), hedonic motivation and perceived product value. The aim is to understand how these factors shape consumer behavior and decision-making, providing insights into the adoption dynamics of 3D food printers for professional and domestic use.

This study collected 973 valid responses through an online survey. The data were analyzed using partial least squares structural equation modeling.

Performance expectancy, social influence and perceived product value significantly enhance consumers’ intention to purchase 3D food printers. In contrast, effort expectancy, FCD and hedonic motivation show no statistically significant impact on their usage intention.

Companies in the 3D food printing industry should prioritize improving product performance and leveraging social influencers to spark consumer interest. Educating the public about the benefits of 3D food printing is essential for building market acceptance and demand. Governments should contemplate implementing policies and regulations encouraging companies to invest in research and development in this field. This study acknowledges its limitations and recommends directions for future research.

This study establishes its originality by integrating hedonic motivation and perceived product value with the original UTAUT framework to investigate Chinese households’ intentions to use a 3D food printer.

This study aims to identify the significant factors that influence the continuation intention (CI) to use a digital wallet in the regions with low technology infrastructure and among the consumers possessing low levels of digital and financial literacy.

Data for the study were collected from the rural parts of South India with 295 digital wallet users. Co-variance-based structural equation modelling (SEM) (CB-SEM) using maximum likelihood estimation method and Bayesian SEM (BSEM) approaches were executed to test the influence of independent variables on the dependent variable and to ensure the validation of the proposed hypothetical model.

The results showed that trust, incentives, technology satisfaction (TS), facilitating condition, performance expectancy, effort expectancy, habit and hedonic motivation significantly influenced the CI to use a digital wallet. In addition, incentives positively impact habit for the CI to use a digital wallet.

The present study is based on the samples from the regions with low technology infrastructure and among the consumers possessing low levels of digital and financial literacy in the rural parts of South India, which limits the generalisation of results.

The results provide impetus to the government, digital wallet marketers and users regarding how the CI to use a digital wallet can be encouraged among the low-adoption regions.

This study remains unique as the assessment of CI to use a digital wallet was conducted in low-adoption regions (rural parts of India) in extending Unified theory of acceptance and use of technology 2 with TS. A comparison of results arrived from CB-SEM with those of the BSEM ensures that the validation of the hypothetical model is found to be another major methodological contribution towards the consumer behaviour literature.