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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