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Plant-based (PB) and meat-reduced (MR) diets have a positive impact on human and environmental health, yet consumer acceptance of such diets is relatively low. Research investigating factors influencing consumer behavior around PB and MR diets is emerging; however studies lack strong theoretically underpinned, comprehensive theoretical frameworks. In this paper we synthesize factors from current literature and propose a comprehensive theoretical model across different consumer dietary types (e.g. omnivore, flexitarian, pesco-vegetarian) and account for consumer cognitive dissonance to facilitate a transition to MR diets.

The factors are examined in a five-step integrative literature review of empirical literature about PB/MR-related consumer behavior since 1989. Studies are critically assessed across four theories commonly used to explain the different antecedents of sustainable consumer behavior. We focus on the theoretical domains framework with COM-B (capability, opportunity, motivation and behavior) framework, as it provides the strongest foundation for modelling the consumer behavior of interest.

107 studies have empirically investigated PB/MR consumer behavior. Of these, 81 studies applied some COM-B domains, but no study has captured all domains. Scant studies investigating cognitive dissonance in the PB/MR literature have been published. Different consumer dietary types are featured across 47 studies; however, none of the studies comprehensively capture all dietary types and psychological discomfort in different consumer dietary types and cognitive dissonance theory.

To synthesize the findings of the present study, we propose an alternative model to address the before-mentioned gaps identified in our critical analysis. The alternative model captures the relationships between the 12 domains of the COM-B model constructs, psychological discomfort and consumer dietary types in the PB/MR foods setting.

The proposed research model facilitates the transition from MB diets to PB diets in three ways: (1) By differentiating consumer dietary types in terms of the COM domains influencing their PB/MR behaviors, PB-producing businesses could better target their foods to hitherto overlooked consumer dietary categories, such as lacto-vegetarians or emerging categories, such as flexitarians, through more refined segmentation and sharper profiling of consumers. (2) Knowing the level of capabilities of consumers in respect of cooking skills and knowledge about purchasing and preparing PB foods could help marketers develop strategies to improve buyers' skills and knowledge. (3) With an understanding of the opportunities (from the Opportunity domain of the COM-B model), including environmental context and resources and social influences, PB food businesses could more effectively market their PB food products. (4) It provides an understanding of capability, motivation and opportunity factors separately but also the interrelationship between these COM domains, as all these variables are intertwined.

Our ILR with the proposed model and the resulting research helps facilitate progress in the transition to PB diets necessary for more sustainable global food production and consumption.

The paper is the first to critically assess existing PB/MR literature regarding each of the COM-B domains, psychological discomfort and the six dietary types. We propose an alternative research model to address the gaps in literature and explain the antecedents and moderators in PB/MR dietary transition. The proposed model may provide information for practitioners and future researchers to understand a wider range of relevant factors influencing consumer’s behavior in transitioning to PB/MR diets.

Despite the widespread use of mobile government (m-government) services in developed countries, the adoption and acceptance of m-government services among citizens in developing countries is relatively low. The purpose of this study is to explore the most critical determinants of acceptance and use of m-government services in a developing country context.

The unified theory of acceptance and use of technology (UTAUT) extended with perceived mobility and mobile communication services (MCS) was used as the theoretical framework. Data was collected from 216 m-government users across Bangladesh and analyzed in two stages. First, structural equation modeling (SEM) was used to identify significant determinants affecting users' acceptance of m-government services. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of the determinants of acceptance of m-government services.

The results show that facilitating conditions and performance expectancy are the two important precedents of behavioral intention to use m-government services, and performance expectancy mediates the relationship between MCS, mobility and the intention to use m-government services.

Academically, this study extended and validated the underlying concept of UTAUT to capture the adoption behavior of individuals in a different cultural context. In particular, MCS might be the most critical antecedent towards mobile application studies. From a practical perspective, this study may provide valuable guidelines to government policymakers and system developers towards the development and effective implementation of m-government systems.

This study has contributed to the existing, but limited, literature on m-government service adoption in the context of a developing country. The predictive modeling approach is an innovative approach in the field of technology adoption.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

The purpose of this study was to investigate the factors that would influence the intention to use social banking during the coronavirus disease 2019 (COVID-19) pandemic. This study integrated two theories, namely the integrated technology acceptance model (TAM), which focused on the acceptance of technology by consumers, and electronic word of mouth (eWOM), which focused on consumer behavior. This study also applied the significant variables in the context of Thailand, which were trust and perceived risk.

A quantitative research method was applied by collecting data from 411 consumers during the COVID-19 pandemic in Thailand. A combined multi-analytic approach of a structural equation model (SEM)-neural network was used to analyze the data. In the first step, the SEM was used to determine the important factors that affected the adoption of social banking. In the second step, a neural network model was used to prioritize the important factors to confirm the results of the SEM method in step 1.

The empirical results of the data analysis using the SEM method showed that the perceived ease of use, perceived usefulness and trust were the most significant determinants of adopting social banking. This was consistent with the neural network method of the important factors.

The results of this research could initiate issues that should be developed for the continued use of online banking among consumers in the context of developing countries, such as Thailand.

This research model provided guidelines for the effective development of mobile banking applications for use on mobile devices. The results of this research made strong theoretical contributions to the existing literature on online banking and offered procedures and information to the relevant sectors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2022-0709