This systematic review synthesizes literature on project performance, which investigates the roles of corporate governance, finance, and operations. This study supports Sustainable Development Goals (SDGs) by synthesizing firm-level studies supporting sustainable financing. The literature signifies that effective corporate governance improves decision-making, risk allocation, and organizational resilience. On the other hand, social networks enhance collaboration and project performance. In addition, technological adoption in financing and project management improves cost control and resource optimization. It also supports effective decision-making, which links operational and financial objectives with corporate sustainability objectives. Moreover, rational capital allocation optimizes risk-sharing with institutional support. Operational management also improves quality assurance and safety. Thus, managerial decision-making helps attain strategic, financial, and sustainability goals. Furthermore, delivery methods and contractual structures help optimize performance through technology adoption and effective operations. The study suggests an adaptive approach with technology support to improve efficiency in project management.

This paper finds that in ASEAN-4, the micro loan characteristics: loan amount and LIBOR whilst the macro characteristics: inflation, net export and GDP growth influence the loan spread in the project finance. However, simultaneously at the country level, the determinants of the loan spread are distinctive to each country’s infrastructure industry characteristic. The paper’s main contribution relates to the determinants of the project finance loan spread at the country level and regional level, ASEAN-4. The purpose of this paper is to fathom the critical risk factors behind the project finance loan pricing differential across the ASEAN-4 countries. Hence, the policy makers, project developers and lenders can have a better understanding of the drivers behind the project finance loan spread pricing. The study adopted an ordinary least square (OLS) regression methodology and collected data from ASEAN-4 countries consisting of Indonesia, Malaysia, Philippines, and Thailand.