As businesses and governments increasingly explore innovative strategies to promote pro-environmental behavior, autonomous vehicles (AVs) have emerged as a key initiative for fostering sustainable communities. However, the specific norms—personal, descriptive, and subjective—that influence behavioral intentions regarding AV adoption remain underexplored. This research addresses this gap by integrating the extended theory of planned behavior (TPB) with pro-environmental variables to examine both direct and indirect influences on behavioral intentions. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the proposed model was validated with data from 516 domestic Chinese tourists. The findings highlight that subjective norms and trust significantly shape positive intentions toward adopting autonomous vehicles. Furthermore, environmental knowledge and concerns exert a significant indirect impact on these intentions, underscoring the complex interplay of factors that drive pro-environmental behavior. These results provide valuable insights for policymakers and practitioners aiming to enhance the acceptance of AVs in China and offer a foundation for future research on the role of norms in technology adoption.

Electronic healthcare services are becoming an increasingly essential form of information and communication technology (ICT) that enables the fast and smooth delivery of health care, specifically in countries with scarce resources such as Pakistan. A better understanding of factors contributing to the adoption of electronic health care is needed, yet this remains an under-researched phenomenon. Grounded in the united theory of acceptance and use of technology, this article attempts to fill the gap by proposing and empirically testing the contribution of trust, privacy, task-technology fit, and personal innovativeness of patients’ intentions to adopt electronic health technology. A survey questionnaire was used to collect data from 353 patients in major hospitals in Islamabad, Pakistan. This study used Partial Least Square Structural Equation Modeling for the analysis. Results indicate that the intention to adopt electronic health technology is determined mostly by effort expectancy, social influence, facilitating conditions, task-technology fit, trust, privacy, and personal innovativeness in information technology. The study concludes with several managerial implications and future research directions, which give further opportunities to researchers and practitioners in the field of e-health technology.

Purpose: Generative artificial intelligence (GenAI) is one of the most diffused AI technologies, capable of generating manifold forms of content, including music, text, images and synthetic data. The purpose of this study is to analyze the determinants that affect GenAI acceptance and its outcomes on both the explorative and exploitative forms of innovation.Design/methodology/approach: The study employs a conceptual framework based on the technology-organization-environment (TOE) paradigm. Through Smart-PLS analysis, it examines empirical data retrieved from an online survey where 302 manufacturing companies took part.Findings: It is found that GenAI has the potential to facilitate both exploratory and exploitative innovation, particularly via the moderating effect of environmental dynamism. Hence the adoption of GenAI has potential to improve organizational performance.Originality/value: The study is the first empirical project to investigate factors that influence manufacturing firms' adoption of GenAI. As the first project to have integrated the TOE paradigm when examining the impact of environmental dynamism on exploratory and exploitative innovation, the study emphasizes the double innovation potential of GenAI in organizational performance improvement.

The demand for mobile payments using smartphones to substitute the need for cash, credit cards, or checks is swiftly increasing in Pakistan. This study investigates the factors determining consumers’ behavioral intention to adopt near-field communication mobile payment from a developing country’s viewpoint. A conceptual framework was adopted based on the mobile technology acceptance model (MTAM), integrating self-efficacy theory, critical mass theory, flow theory, and system and service quality to elucidate the behavioral intention. Data were collected through a self-administered questionnaire applied to 310 nonusers of near-field communication mobile payment in Pakistan. The analysis was performed using SmartPLS3.0. The results demonstrated that other independent variables are the main predictors of the intention to adopt mobile payment besides technology self-efficacy, perceived critical mass, and mobile ease of use. The study concludes with key implications and future work directions concerning the limitation of this study.

Purpose: The purpose of this paper is to empirically evaluate the significant influence of four sustainability dimensions in predicting the residents’ satisfaction with the development of sustainable tourism in the emerging tourism industry of Pakistan.