DIGITALIZATION AS A TOOL TO REDUCE CORRUPTION IN PAKISTAN’S CONSTRUCTION INDUSTRY

Abstract

In Pakistan's construction sector, corruption has long been a major problem that negatively impacts public trust, project quality, and cost effectiveness. Sectoral performance and sustainable development are nevertheless threatened by practices including bribery in procurement, manipulation of tendering procedures, fabrication of documents, and inadequate monitoring systems. By improving accountability, traceability, and transparency in construction-related procedures, digitalization has become a viable solution in recent years to address these governance shortcomings. In order to reduce corruption in Pakistan's construction industry, this study looks at digital technologies such e-procurement systems, Building Information Modeling (BIM), Geographic Information Systems (GIS), digital payment platforms, and real-time project monitoring tools. The study examines how digital interventions can reduce human involvement, enhance regulatory supervision, and limit discretionary power through a qualitative assessment of policy texts, institutional reports, and pertinent academic literature. The results indicate that by standardizing processes, enhancing data accessibility, and fortifying audit systems, digitization considerably lowers the likelihood of rent-seeking. The full potential of digital solutions is, however, hampered by issues including uneven implementation, reluctance to change, limited technical competence, and insufficient legal frameworks. The study comes to the conclusion that although digitalization cannot completely eradicate corruption, technology can significantly enhance governance in Pakistan's construction sector when strategically combined with institutional changes, capacity building, and a strong political commitment. By emphasizing digital governance as a workable route toward transparency and sustainable infrastructure development in Pakistan, the article adds to current policy and scholarly conversations.