The Internet of Things (IoT) is the next generation of internet-connected information communication technologies (ICT). IoT typically integrates supply chain activities to enhance green supply chain performance (GSCP). Since every organization has different IoT capabilities in comparison with other organizations, GSCP can enable supply chain integration activities for enhanced performance. The implementation of an IoT system can reduce the consumption of organizational resources like energy, electricity, and time and can increase the operational speed to gain better logistics and, ultimately, improved supply chain performance. This study has developed and empirically tested the relationship between IoT capabilities, energy consumption behavior (ECB), supply chain integration, green training (GT), and supply chain practices. Such a multidisciplinary relationship has not previously been established in the literature. The proposed study can fulfill the literature gap and opens new horizons for interdisciplinary research. Data used in this study are collected through offline and online survey methods. A total number of 250 out of 400 respondents participated in the survey. Data has been analyzed through partial least square—structure equation modeling (PLS—SEM) technique. The results of this study empirically test the developed model. IoT has a positive effect on supplier integration (SI), and customer integration (CI). Furthermore, SI and CI have a mediating role between IoT and GSCP, and GT has a positive impact on GSCP. It is concluded that the implementation of IoT can integrate CI and SI to increase GSCP. GT and ECB can ultimately improve GSCP. Additionally, the use of technology and GT can motivate employees to save energy and protect the environment to increase GSCP.

Open government data (OGD) has gained much attention worldwide; however, there is still an increasing demand for exploring research from the perspective of its adoption and diffusion. Policymakers expect that OGD will be used on a large scale by the public, which will result in a range of benefits, such as: faith and trust in governments, innovation and development, and participatory governance. However, not much is known about which factors influence the citizens’ intention to use OGD. Therefore, this research aims at empirically investigating the factors that influence citizens’ intention to use OGD in a developing country using information systems theory. Improved knowledge and understanding of the influencing factors can assist policymakers in determining which policy initiatives they can take to increase the intention to widely use OGD. Upon conducting a survey and performing analysis, findings reveal that perceived usefulness, social approval, and enjoyment positively influences intention, whereas voluntariness of use negatively influences OGD use. Further, perceived usefulness is significantly affected by perceived ease of use, and OGD use is significantly affected by OGD use intention. However, surprisingly, the intention to use OGD is not significantly affected by perceived ease of use. The policymakers suggest increasing the intention to use OGD by considering significant factors.

Open government data (OGD) has huge potential to increase transparency, accountability, and participation while improving efficiency in operations, data-driven and evidence-based policymaking, and trust in government institutions. Despite its potential benefits, OGD has not been widely and successfully adopted in public sector organizations, particularly in developing countries. Therefore, the purpose of this study is to explore the theories/frameworks and potential determinants that influence the OGD adoption in public sector organizations. To ascertain the various determinants of OGD adoption in public sector organizations, this study involved a systematic review of already established theories and determinants addressed in the public sector open data domain. The review revealed that the TOE (technology, organization, environment) framework was dominantly employed over theories in the earlier studies to understand organizational adoption to OGD followed by institutional theory. The results, concerning potential determinants, revealed that some of the most frequently addressed determinants are an organization’s digitization/digitalization capacity, compliance pressure, financial resources, legislation, policy, regulations, organizational culture, political leadership commitment, top-management support, and data quality. The findings will enrich researchers to empirically investigate the exposed determinants and improve the understanding of decision-makers to leverage OGD adoption by taking relevant measures.

The adoption of solar photovoltaic (PV) systems is seen as an important part of the sustainable energy transition. In this regard, it is crucial to identify the determinants of solar (PV) systems’ adoption to facilitate this process. Therefore, this article aims to examine the determinants of SPVS adoption by contrasting the relationships in a cross-cultural environment. For the accomplishment of the purpose, this paper follows a quantitative method in which data is analysed by adopting the PLS-SEM approach using SmartPLS 3.3.9. After analysing the collected data of 464 consumers from Somalia and Pakistan, it is found that perceived usefulness, perceived ease-of-use, compatibility, observability, and perceived trust are significant predictors. However, no significant difference in influencing determinants has been observed between the two cultures using multi-group analysis. Further, perceived trust is not revealed as a significant determinant of behavioural intention in the Somalian context. The strongest relationship is found between attitude and behavioural intention in both cultures. In Somalia, the results reveal a variance of 49% in attitudes and 51% in intention to adopt SPVSs. In Pakistan, a variance of 60.1% in attitudes and 76.8% in intention to adopt SPVSs is found. Implications for both academics and managers to scale-up the adoption of SPVSs are made.

The industrial shift from Industry 4.0 to Industry 5.0 has transformed organizational thinking, moving the focus from purely technological implementation to a more human-centered approach. The current study has focused on the Industry 5.0 technological capabilities to bring into circular economy practices aligned with sustainable development goals, aiming to enhance sustainable performance. Moreover, the resource-based theory has grounded the development of the comprehensive framework on Industry 5.0 technological capabilities (artificial intelligence capabilities, big data analytical capabilities, Internet of Things capabilities, machine learning capabilities, and blockchain technology capabilities) and circular economy practices (eco-design, management system, and investment recovery) to achieve sustainable performance (environmental performance, social performance, and economic performance). Data have been collected from 179 respondents from the Chinese manufacturing industry. Additionally, data have been analyzed using the structural equation modeling technique. The results showed that Industry 5.0 technological capabilities directly affect sustainable performance. Moreover, circular economy practices played a dual, moderating, and mediating role between Industry 5.0 technological capabilities and sustainable performance. The current study has contributed to filling a gap in the literature on Industry 5.0 capabilities, especially in the circular economy and sustainable performance perspective. The practical contribution recommended is that if organizations focused on their Industry 5.0 technological capabilities, it would boost circular economy practices and sustainable performance to achieve sustainable development goals.

Objective: The global challenge of climate change and the need for energy conservation have prompted a reevaluation of energy sources and policies worldwide. This study aims to investigate the societal acceptability of solar photovoltaic (PV) systems among citizens of smart cities, an aspect crucial yet underexplored in the context of renewable energy technologies. Methods/Analysis: A comprehensive survey was conducted involving 560 respondents to assess public perceptions, attitudes, and behaviors toward solar PV systems. The study also examined the moderating effects of area (urban/rural), gender, trust, and duration of use (experience) on societal acceptability. Findings: The results show that both independent and moderating variables significantly influence the social acceptability of solar innovations in smart cities. Key factors identified include the user-friendly design of solar systems, effective awareness campaigns highlighting their benefits, and compatibility with existing technologies. These elements are crucial in fostering positive attitudes and intentions towards the adoption of solar energy. Novelty/Improvement:This research provides valuable insights for policymakers, energy planners, and researchers, emphasizing the importance of considering demographic and experiential factors in policy-making. The findings suggest that societal acceptance of solar PV systems can be enhanced by targeting area-specific needs, leveraging trust, and promoting the benefits of prolonged usage experience. Doi: 10.28991/CEJ-2025-011-02-016 Full Text: PDF