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 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.

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Increasing supply chain performance (SCP) has always been a common phenomenon in the history of organizations. Recent technological advancements [including, radio frequency identification (RFID) in combination with big data predictive analytics (BDPA)] have been able to significantly leverage SCP. In this respect, there is an urgent need for acceptance of RFID technology as well as BDPA to be empirically investigated in order to better understand the enhancement of SCP. Therefore, this paper aims at establishing and empirically investigating the relationship between BDPA acceptance, RFID acceptance, and SCP, respectively. The population of this paper comprises the pharmaceutical logistics industry in China. The sample was obtained from employees through the use of a simple random sampling method. Data were collected through an adapted questionnaire. SmartPLS 3.0 software was used for structural equation modeling analysis. Partial least square-structural equation modeling (PLS-SEM), the value of path coefficient, was found to be 0.700. This showed a direct positive effect of BDPA acceptance on SCP. Moreover, RFID acceptance was also tested through the ''variance accounted for'' method of mediation. Results showed a partial mediation of 57% between BDPA and SCP. Theoretically, this paper fills the knowledge gap by finding relationships between BDPA and SCP via a mediation role of RFID technology. Practically, it would be beneficial for supply chain managers in the pharmaceutical industry to adopt and implement BDPA and RFID technology so as to enhance SCP.INDEX TERMS Big data predictive analytics, Internet of medical Things (IoMT), radio frequency identification, pharmaceutical logistic, supply chain management, supply chain performance.

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.

This article examines factors that can be argued to influence the academician's behavioral intentions in using open government data (OGD). Policy-makers and practitioners will determine policy instruments in increasing acceptance and use of OGD by maintaining a good understanding of these factors. In this article, Rogers' Diffusion of Innovations (DOI) theory has been proposed and used in order to empirically examine these factors taking perceived characteristics of innovations. Relevant hypotheses have been developed through the literature review, forming a preliminary research model, while respective influences of the factors on the behavioral intention to use open government data have been statistically tested. Results have shown that compatibility and voluntariness have had a strong influence on behavioral intention, whereas a 66.2% variance has been found in academicians' behavioral intentions to use open government data.

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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.