Purpose The purpose of this study is to discuss how knowledge management (KM) practices can help in sustainable infrastructure growth in various regions with specific reference to energy consumption and economic development. Design/methodology/approach The study employs the panel data of 65 Belt and Road Initiative (BRI) countries across the period between 1981 and 2016 to analyze using the econometric modeling techniques. Energy consumption, financial development, utilization of renewable energy and technological advancement are key variables. A theoretical lens of KM is incorporated in comprehending the data-driven decision-making and knowledge-based policy implementation. To ensure robust results, advanced econometric techniques are applied, including cross-sectional dependence tests (LM Breusch–Pagan and CD test of Pesaran), unit root tests (ADF Fisher Chi-square and CIPS CADF) to capture long-run relationships. Findings The findings indicate that energy consumption and economic expansion have significant implications to the quality of the environment whereas use of renewable energy and economic development have positive environmental consequences within the chosen regions. The research reveals that the regional differences influence the manner in which the KM mediates the interrelation of development and sustainability. Research limitations/implications The research depends on secondary sources of KM inferences and is restricted to the chosen BRI countries. Practical implications The study also gives policymakers, planners of infrastructure and development institutions recommendations of how to incorporate KM in infrastructure policy in line with the sustainability objectives. Social implications International organizations and development partners should fund capacity-building programs and knowledge-sharing platforms to enable BRI nations to execute sustainable development objectives. Originality/value The research examines how KM is linked to sustainable development in 65 BRI countries, taking into account differences among areas and difficulties in using cross-sectional information.
Murtaza et al. (Tue,) studied this question.