Solar PV (photovoltaic) technology has gained considerable attention worldwide, as it can help reduce the adverse effects of CO₂ emissions. Though the government of Pakistan is adopting solar PV technology due to its environmental friendliness nature, studies focusing on consumer’s acceptance of solar PV are limited in the country. This research aims to close this knowledge gap by looking into the various considerations that may influence consumers’ willingness to adopt (WTA) solar PV for household purposes. The study further contributes by expanding the conceptual framework of the theory of planned behavior by including three novel factors (perceived risk, perception of self-efficacy, and openness to technology). The analysis is based on questionnaire data collected from 683 households in Pakistan’s provincial capitals, including Lahore, Peshawar, Quetta, Gilgit, and Karachi. The proposed hypotheses are investigated using the state-of-the-art structural equation modeling approach. The empirical results reveal that social norms, perception of self-efficacy, and belief about solar PV benefits positively influence consumers’ WTA solar PV. On the contrary, the perceived risk and solar PV cost have negative effects. Notably, the openness to technology has an insignificant effect. This study can help government officials and policymakers explore cost-effective, risk-free technologies to lessen the environmental burden and make the country more sustainable. Based on research results, study limitations, as well as prospective research directions, are also addressed.

Universities can contribute to economic and sustainable development (SD) in a variety of ways, such as mediating social debates, educating citizens on scientific and technical issues, fostering communication among various agents (politicians, businesspeople, higher education institutions’ managers, and citizens), and advancing socioeconomic progress. By teaching the current and next generations of decision-makers, universities have a role in “shaping the ideals of society”. Numerous publications address the topic of sustainable development, but they do so from the standpoint of how its responsibilities are implemented and how students are prepared and aware of it. This manuscript addresses this vacuum by looking at how students assess university activities and specific pillars of sustainable development, which is an unique approach. The investigation used the CAWI questionnaire. The sample consists of 115 Pakistani respondents, and information was gathered between February and August of 2022. The research built a logistic regression model. Our research’s findings and their analysis revealed that University 4.0s should take initiatives for sustainable development, and that these issues are top priorities for them. The analysis revealed that Society 5.0 is active in University 4.0s’ sustainable development initiatives, and that these initiatives are vital for Society 5.0.

The aim of this study is to investigate the relationship between green technology R&D investment and corporate performance (ROA) of 44 Beijing-listed energy companies from 2016 to 2021 using a threshold regression model. The results show that there is an inverse W-shaped nonlinear relationship between green technology R&D investment and firm performance. This means that green technology R&D investments only have a positive effect on firm performance within an appropriate green technology R&D investment interval, and a negative effect occurs outside this interval. Additionally, the study analyses the influence of three threshold variables (firm size, capital structure and capital density) on the relationship between green technology R&D investment and firm performance. The results show that firm size has an inversely- U-shaped relationship, the capital structure has a negative nonlinear relationship and the capital density has an inversely N-shaped relationship. Optimal intervals are observed for all three threshold variables. Moreover, the study shows that the green technology R&D investment intensity has a lagged effect on firm performance. The positive influence weakens over time, and the negative influence becomes more pronounced. The findings of the study can help energy companies to develop green technology R&D innovation strategies, such as differentiating green technology R&D expenditures for companies in different development situations. It can also exploit the driving effect of green technology R&D investment on firm performance in the context of China’s energy sector restructuring.

The social distancing due to the Covid-19 epidemic has disturbed all sectors of society, including education. To maintain normal operations, it is necessary to adapt quickly to this situation. Many technologies and platforms have rushed to offer their support to users. This article adopts a critical perspective to reflect on the factors that may cause the hasty adoption of 5G smart learning technology. To investigate students' intentions toward smart learning, this article provides a theoretical framework premised on the technology acceptance model (TAM) by adding components from the social practise theory (SPT). Based on data analysis through Structural equation Modeling (SEM) of a survey (n = 375) conducted in China, we found that the choice of 5G smart-learning technology depends on the combined effect of Material (MAA), Meanings (MEA), and Competency access (COA) factors. The results illustrate that these are the effective factors for student’s intentions to adopt 5G smart-learning technology. These outcomes are intended to aid service providers and decision-makers in developing effective ways to increase smart learning use. These findings can also enable us to identify challenges affecting smart learning adoption and to contribute to the design and proper supply of smart learning programs in other countries.