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Augmented reality (AR) adoption has boomed globally in recent years. The prospective of AR to seamlessly integrate digital information into the actual environment has proven to be a challenge for academics and industry, as they endeavor to understand and predict the influence on users' perceptions, adoption intentions and usage. This study investigates the factors affecting consumers’ behavioral intention to adopt AR technology in shopping malls by offering the mobile technology acceptance model (MTAM).

This conceptual framework is based on mobile self-efficacy, rewards, social influence and enjoyment of existing MTAM constructs. A self-administered questionnaire, constructed by measuring questions modified from previous research, elicited 311 usable responses from mobile respondents who had recently used AR technology in shopping malls. This analysis was performed using SmartPLS3.0.

Grounded on the findings of the study, it was found that, aside from factors such as mobile usefulness, ease of use and social influence, the remaining independent variables had the most significant impact on adopting AR technologies. Considering the limitations of this study, the paper concludes by discussing the significant implications and insinuating avenues for future research.

To better investigate mobile AR app adoption in Pakistan’s shopping malls, the researchers modified the newly proposed MTAM model by incorporating mobile self-efficacy theory, social influence, rewards and perceived enjoyment. However, the extended model has not been extensively studied in previous research. This study is the first to examine the variables that affect an individual’s intention to accept mobile AR apps by using a novel extended MTAM.

This study aims to explore the consumers’ choices of mobile payments (m-payments) using a comprehensive unified model. The financial technology for digital m-payment has been increasingly introduced in the market, yet their acceptance has remained low.

This study uses the unified theory of acceptance and use of technology (UTAUT) with additional constructs of social influence, trust, anxiety, personal innovativeness and grievance redressal (GR). Structural equation modeling is used to evaluate the predictive model of attitudes toward m-payment. Individuals’ responses to questions regarding their attitude and intention to accept m-payment were gathered and examined through the lens of extended UTAUT model.

While the model supports TAM classical role, empirical examination of the model revealed that users’ attitudes and intentions are influenced by trust, personal innovativeness and social influence. Moreover, intention to use and GR are significant positive predictors of m-payment usage behavior.

M-payment provides customers with new digital payment platforms while providing businesses and marketing agents with more alternatives for online marketing. However, there is not much reported about m-payment adoption in Pakistan. This research introduces and evaluates new constructs that were not included in the original model. In Pakistan, to the best of the authors’ knowledge, this is a first of its kind of research which is purely based on the customers’ perspective of m-payment adoption.

Edible food packaging provides a solution to the solid waste problem caused by traditional packaging. However, tourists’ readiness to adopt this novel technology is unclear.

An online survey was conducted to examine how motivated consumer innovativeness (CI), environmental awareness, perceived behavioral control, subjective norms and attitudes influence tourists' purchase behaviors in the context of edible food packaging in the tourism industry. The collected data were analyzed using structural equation modeling (SEM) with SmartPLS 3.2.8.

The results of the structural equation analysis indicate that each sub-factor of motivated consumer innovativeness positively influences attitudes. Additionally, attitudes, subjective norms, perceived behavioral control and personal norms were found to significantly impact purchase intentions. Environmental awareness was found to moderate the relationships between (1) perceived behavioral control and purchase intention, (2) subjective norms and purchase intention and (3) attitude and purchase intention. These findings expand the applicability of the diffusion of innovation, planned behavior and environmental awareness theories, offering useful insights for foodservice professionals.

This study emphasizes key implications for the tourism and foodservice industries, as consumers with an innovative attitude and higher environmental awareness are more likely to adopt edible food packaging. Identifying these factors will help stakeholders establish effective strategies for waste reduction through innovative packaging solutions.

This research uniquely investigates tourists' adoption of edible food packaging by integrating theories of innovation diffusion, planned behavior and environmental awareness. It offers novel insights into how various psychological and social factors influence purchase behaviors within the tourism industry.

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.

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.

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.

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.

As smart technologies rapidly permeate the hospitality industry, understanding their impact on guest experiences is crucial. Existing research often treats smart technology as a peripheral factor, without fully exploring the essence of “smartness.” This study addresses that gap by leveraging the Hedonic Information Systems Acceptance Model (HISAM) to differentiate between the utilitarian and hedonic motivations that influence tourists' intentions to stay in smart hotels. Additionally, we introduce technology readiness as a moderating factor, examining how individual traits affect behavior in smart hospitality environments.

Using SmartPLS 3.2.8, we conducted structural equation modeling (SEM) on 311 valid samples to empirically test our hypotheses.

Our results reveal that HISAM factors significantly influence tourists’ intentions to engage with smart hotel services. Notably, the perception of smartness emerges as a key driver of perceived ease of use, usefulness and enjoyment. These insights pave the way for both theoretical advancements and practical applications, with recommendations for future research outlined.

This study not only advances theoretical understanding but also provides actionable insights for the hospitality industry. By identifying the factors that enhance user experience in smart hotels, industry professionals can better meet evolving guest expectations and preferences, thereby improving service quality and customer satisfaction.

This pioneering study is the first to integrate the concept of smartness within the HISAM framework, establishing a robust foundation for future research in the tourism and hospitality sectors. Furthermore, the introduction of technology readiness as a moderating variable offers a fresh perspective on individual differences in the adoption of smart technologies.

This study aims to inspect the impact of US climate policy uncertainty (CPU) on the economic growth of Asian countries with the moderating role of crude oil price (COP) changes.

The Im-Pesaran Sin and Fisher-type tests are used for stationarity check, while Kao and Pedroni tests are used for cointegration analysis. The Hausman test is applied for model selection, where pooled mean group autoregressive distributed lag (PMG/ARDL) has been selected and applied. Besides, the fully modified ordinary least squares is also used for robustness analysis. Additionally, the literature review and descriptive statistics have been used.

The main findings disclosed that US CPU negatively impacted the economic growth of Asian economies with high significance in the long run whereas insignificant in the short run. The results further concluded that COP positively affected economic growth both in the short and long run. Furthermore, the results also revealed that COP significantly and positively moderates the relationship between CPU and COP in the long and short run.

The study is the first of its kind to examine the impact of the US CPU on the economic growth of Asian economies. Second, it further revealed the moderating role of COP between US CPU and economic growth. Third, a large panel of data from Asian countries has been considered. Fourth, the study adds to the current literature by using the PMG/ARDL model to determine the impact of US CPU on economic growth. Additionally, this study focuses on the US CPU because it is a developed country playing a significant role in energy and climate issues, and has been very uncertain.

This study aims to investigate technology-based health and safety (H&S) management to control the spread of disease on construction sites using a partial least squares structural equation modelling (PLS-SEM) approach.

An extensive literature review is conducted to develop a conceptual framework. The variables identified from the literature review are included in a cross-sectional survey which gathered a total of 203 valid feedback. The variables for challenges are grouped under their relevant construct using exploratory factor analysis. Then, a hypothesized model is developed for PLS-SEM analysis using Smart PLS software. Later, the outcome of the model is further validated by nine construction experts using a semi-structured questionnaire survey.

The results rationalized the relationships between the COVID-19 H&S measures, challenges in implementing COVID-19 H&S measures on construction sites and the innovative technologies in transforming construction H&S management during the COVID-19 pandemic. The possible challenges that obstruct the implementation of H&S measures are highlighted. The potential technologies which can significantly transform H&S management by reducing the impact of challenges are presented.

The findings benefited the industry practitioners who are suffering disruption in construction operations due to the pneumonic plague.

By developing a conceptual model, this study reveals the contribution of technology-based H&S management for construction projects during the COVID-19 pandemic, which remains under-studied, especially in the context of the developing world.

This study aims to explore the determinants of green electronics purchase intention in Malaysia by extending existing knowledge on green consumer behavior and contributing to the field of sustainable consumption.

A quantitative research approach was adopted, with data collected from 250 Malaysian consumers. The proposed model was tested using partial least squares structural equation modeling to assess the relationships between various determinants and green purchase intention.

The results demonstrate that perceived consumer effectiveness, green advertising and monetary cost positively affect environmental attitudes, which subsequently influence green purchase intention. The study also identifies that brand image and information quality significantly enhance green brand trust (GBT), leading to stronger intentions to engage in green purchasing. Additionally, it finds that environmental knowledge and environmental concern shape perceived behavioral control, which further impacts green purchasing intention.

The study focuses on Malaysian consumers, which may limit the generalizability of the findings to other cultural contexts. Future research could expand the scope to include cross-cultural comparisons to validate the model in different settings.

By providing insights into the key factors driving consumers’ intention to purchase green electronics, the study offers valuable guidance for marketers and manufacturers to develop targeted strategies that promote sustainable consumption and capitalize on the growing demand for green products in Malaysia.

This study is unique in measuring the influence of green attitude, GBT and perceived behavioral control on green purchase intention specifically within the electronics sector, offering a novel contribution to the literature on sustainable consumer behavior.

This study aims to investigate the influence of corporate social responsibility (CSR) on corporate sustainable performance (CSP) of small- and medium-sized enterprises (SMEs) by looking into the significance of mediating factors, namely, brand image (BI) and brand loyalty (BL), within the context of an emerging economy.

The authors conduct an extensive literature study on the subjects of CSR, BI and BL to assess their influence on the sustainable performance of SMEs in an emerging market. The study adopts a quantitative methodology. A total of 438 answers were obtained from a sample size of 513. The data of the SMEs in Vietnam was analyzed using the smart partial least squares structural equation modeling software, specifically version 3.3.2.

The results of the authors demonstrate notable and favorable correlations between CSR and CSP, CSR and BI and CSR and BL. Importantly, the findings contribute to existing knowledge by looking into the mediating influence of BI and BL in the relationship between CSR and CSP.

According to the authors’ understanding, a number of research have investigated the correlation between CSR and CSP within the realm of SMEs. Nevertheless, there is a scarcity of scholarly research examining the mediating function of BI and BL in this association. The study’s findings have important implications for entrepreneurs and senior management in effectively guiding their enterprises and improving their business strategies with an emphasis on sustainability in emerging markets. The outcome of this study has the potential to significantly contribute to SMEs in Vietnam as well as other emerging countries.

This study aims to investigate the various systems in logistics industry of Pakistan through the lens of the World Bank's logistics performance indicators (LPI) and understand their impact on the China–Pakistan economic corridor (CPEC) that is a vital part of China's belt and road initiative (BRI).

In this study thematic analysis was performed on twenty-three semi-structured interviews with experts in Pakistan's logistics and supply chain sector to gain an in-depth insight into the logistics performance relative to CPEC.

A performance gap exists in the logistics systems in Pakistan, both for hard and soft infrastructure. The significant challenges are the inefficiencies of the government, minimal use of information and computing technology (ICT), and an incapable workforce. It is essential to be cognizant of the ground realities and amendments required in the existing policies and practices in light of the challenges faced and best practices adopted by developed and developing countries with good standing in logistics performance. This study will guide policymakers and practitioners for hard and soft logistics infrastructure improvement, which may benefit economic corridors in general and CPEC in particular.

This study contributes to the existing literature by highlighting the role of ICT in improving both soft and hard logistics infrastructure, which can lead to significant development of economic corridors. The study makes use of a case study of the CPEC to demonstrate the lack of ICT can hamper the growth of an economic corridor despite billions of dollars of investment in the hard infrastructure development projects.