Harnessing AI and Circular Frameworks to Address Socio-Economic and Environmental Impacts of Mega-Project Delays: A Case Study of the Padma Multipurpose Bridge.

 Harnessing AI and Circular Frameworks to Address Socio-Economic and Environmental Impacts of Mega-Project Delays: A Case Study of the Padma Multipurpose Bridge.
Husain S.M.
Department of MBA Programme (Bangladesh), Faculty of Graduate Studies, University of Kelaniya (UoK), Sri lanka
Department of Computer Science & Engineering, Associate Professor, State University of Bangladesh (SUB)

DOI: https://dx.doi.org/10.47772/IJRISS.2025.9020067

Received: 30 January 2025; Revised: 06 February 2025; Accepted: 08 February 2025; Published: 03 March 2025

ABSTRACT

The Padma Multipurpose Bridge (PMB) represents a transformative mega-project aimed at fostering regional economic growth, enhancing connectivity, and improving socio-economic conditions in southern Bangladesh. This study explores the interconnected socio-economic and environmental consequences arising from construction delays in large-scale infrastructure projects. Data were sourced from prior research, media sentiment analysis, and household surveys, complemented by AI-based thematic analysis. This research leverages AI-driven thematic analysis to identify underlying patterns and generate insights that traditional qualitative methods may overlook.

A robust conceptual framework is introduced, integrating Stakeholder Theory and Circular Economy principles to analyze project impacts. The findings emphasize the role of AI-powered monitoring systems, sustainable construction practices, and stakeholder engagement in mitigating delays. Comparative case studies, including WestConnex (Australia) and China’s Belt & Road Initiative, provide insights into global best practices. The study offers a policy framework for integrating predictive analytics in project execution, ensuring timely completion and enhanced sustainability.

Keywords: Padma Bridge, AI-driven thematic analysis, socio-economic impact, environmental sustainability, project delays, circular economy.

INTRODUCTION

Background and Research Problem

Mega-projects like the Padma Multipurpose Bridge (PMB) play a pivotal role in fostering economic development and addressing regional disparities. However, prolonged delays create a cascade of socio-economic and environmental challenges. The nine-year delay in PMB’s completion underscores the need for more adaptive project management strategies, particularly in developing nations.

This study explores the circular effects of project delays, analyzing how disruptions in infrastructure projects reinforce socio-economic inequalities and environmental degradation, creating self-sustaining feedback loops.

Conceptual Framework

A new theoretical framework has been introduced, integrating:

• Stakeholder Theory – Emphasizes the role of governments, private entities, and local communities in mitigating mega-project delays.
• Circular Economy Model – Analyzes how project delays escalate socio-economic and environmental costs while limiting sustainable development.

This framework illustrates the interconnected loops between delays, economic instability, environmental degradation, and further project setbacks, providing a foundation for predictive modeling and AI-driven interventions.

Australian Relevance and Comparisons

The challenges faced by the Padma Multipurpose Bridge (PMB) align with experiences from major Australian infrastructure projects like the Snowy Mountains Scheme and West Connex. Infrastructure initiatives such as WestConnex in Australia underscore the importance of dynamic risk management strategies, stakeholder engagement, and AI-driven project monitoring in mitigating delays and optimizing project outcomes. (Choi et al., 2019). These lessons are applied to the Padma Bridge project to bridge execution gaps. Both countries contend with delays caused by stakeholder coordination issues, environmental compliance, and financial overruns. Analyzing these parallels offers lessons for improving future infrastructure planning and execution in Bangladesh.

LITERATURE REVIEW

Global Insights

Infrastructure projects worldwide have demonstrated mixed outcomes in promoting socio-economic growth. Recent studies (Chen et al., 2023) highlight the role of transportation infrastructure in economic inclusion, while others (Shoulin et al., 2024) reveal how poor project execution can worsen inequalities.

Comparative Case Studies

Studies by Jalil and Mia (2021) and Shoulin et al. (2024) emphasized Padma Multipurpose Bridge (PMB)’s role in regional economic integration and agricultural trade. However, challenges like displacement, land-use changes, and livelihood disruptions persist, highlighting gaps in stakeholder engagement and environmental planning.

China’s Belt & Road Initiative and WestConnex (Australia) provide critical lessons in AI-driven risk management and stakeholder collaboration to mitigate project delays.

Research Gaps

• Lack of AI integration in mega-project management.
• Absence of real-time monitoring frameworks for reducing socio-economic disruptions.
• Limited empirical studies on circular effects of infrastructure delays.

Figure 1 illustrates the circular effects of socio-economic and environmental impacts caused by project delays. The feedback loops demonstrate how disruptions in socio-economic domains exacerbate environmental challenges, which, in turn, create further delays. This framework underscores the necessity for integrated solutions that address both dimensions simultaneously.

Existing research often overlooks the cumulative impacts of delays on marginalized communities and the potential of AI-driven analytics to mitigate such challenges. This study aims to fill these gaps by integrating qualitative insights with ML/AI tools for a holistic analysis.

The following conceptual framework visualizes the circular effects between socio-economic and environmental impacts. It highlights feedback loops where socio-economic disruptions exacerbate environmental challenges, leading to project delays.

Figure 1: Conceptual Framework of Circular Effects

While traditional methods have identified socio-economic and environmental impacts, they fall short in providing actionable insights. AI-based tools bridge this gap by enabling real-time data processing and predictive analytics.

Comparative Case Studies

Australian projects like WestConnex have demonstrated the importance of integrating climate-resilient infrastructure designs to address environmental challenges (Choi et al., 2019). Similarly, the Sydney Metro project highlights the critical role of effective stakeholder engagement in minimizing project delays. Lessons from these cases could inform strategies to enhance the efficiency and sustainability of the Padma Bridge project.

METHODOLOGY

Data Collection Methods

This study employs a mixed-method approach, utilizing:

• Primary Data – Surveys of 5,076 households assessing income, accessibility, and perception of Padma Multipurpose Bridge (PMB)’s  delays.
• Secondary Data – Media reports, government publications, and academic sources.
• AI-Driven Thematic Analysis – NVivo and TextBlob were used to identify recurring themes from qualitative data.

Analytical Framework

• Sentiment Analysis – TextBlob & VADER were applied to measure public sentiment shifts over time.
• AI-Based Topic Modeling – Latent Dirichlet Allocation (LDA) was used to uncover hidden themes from project-related discourse.

Ethical Considerations

All data collection adhered to confidentiality and informed consent guidelines, ensuring ethical integrity.

Advanced AI Applications

To better understand project impacts, predictive AI tools such as machine learning algorithms were employed. These tools analyzed trends in media sentiment and forecasted long-term economic impacts. Techniques included predictive maintenance models to anticipate infrastructure needs and thematic clustering to extract actionable insights from qualitative data.

ANALYSIS AND FINDINGS

Socio-Economic Impacts

Figure 2 provides a quantitative summary of the socio-economic benefits derived from the Padma Multipurpose Bridge (PMB). Metrics such as average income changes, employment generation, and an increase in educational enrollment illustrate the significant regional development impacts.

• Employment Generation: The PMB created 743,000 man-years of employment.
• Educational Access: 25% increase in school enrollment due to improved connectivity.
• Income Growth: Rural household earnings rose by 12% post-construction.

Figure 2 presents key socio-economic metrics following the completion of the Padma Multipurpose Bridge. The project has significantly contributed to regional employment, generating approximately 743,000 man-years of work, benefiting marginalized communities. Additionally, the average household income increased, reflecting economic stimulation in the surrounding areas. Furthermore, the improved infrastructure has facilitated a 25% rise in school enrollment, indicating enhanced access to education. These findings highlight the broader socio-economic benefits associated with large-scale infrastructure development.

Figure 2: Descriptive Statistics of Socio-Economic Metrics

Environmental Impacts

• Land Displacement: 14,000+ families were relocated due to construction.
• Green Technology: The adoption of eco-friendly materials reduced environmental degradation by 60%.

AI-Driven Insights on Public Perception

AI-based sentiment analysis showed positive public sentiment increased by 40% after proactive sustainability measures were implemented.

Figure 3 depicts sentiment analysis trends extracted from media reports over six months. Positive sentiment grew steadily, reflecting public optimism about the economic benefits of the Padma Multipurpose Bridge (PMB), while negative sentiment declined, suggesting reduced concerns over environmental degradation as mitigation measures gained visibility.

Media sentiment analysis revealed public optimism regarding economic benefits but concerns over environmental degradation.

The sentiment analysis trends below, derived from media sources, show public optimism regarding economic benefits juxtaposed with concerns about environmental degradation.

AI analysis revealed that public sentiment about economic benefits peaked after the project’s halfway point (Zhou et al., 2019). Negative sentiment concerning environmental impacts declined following the announcement of climate-resilient measures.

Figure 3: Media Sentiment Trends Over Time

Climate Resilience and Sustainability Measures

Figure 4 compares the environmental impact reduction achieved before and after adopting climate-resilient measures in the Padma Multipurpose Bridge (PMB) project. Post-adoption strategies led to a 60% reduction in predicted environmental degradation, demonstrating the value of integrating adaptive infrastructure designs.

The analysis revealed that incorporating climate-resilient measures into PMB’s design could significantly reduce the impact of extreme weather events. Adopting these measures, such as elevated structures and adaptive materials, aligns with best practices observed in Australian mega-projects.

The simulation results below illustrate the predicted reduction in environmental degradation post-adoption of climate resilience measures for the PMB project.

Figure 4: Climate Resilience Impact Simulation

Figure 4 shows a significant 60% reduction in environmental degradation after integrating adaptive designs and green technologies.

DISCUSSION AND POLICY RECOMMENDATIONS

Addressing the circular effects of project delays requires integrating advanced technologies, sustainable practices, and proactive stakeholder engagement. By leveraging AI tools and fostering community participation, future projects can minimize delays and enhance their socio-economic and environmental sustainability. These strategies provide a blueprint for achieving efficient timelines and maximizing the developmental impact of mega-projects in developing nations.

Integrating AI and adopting global best practices can mitigate delays and enhance the sustainability footprint of mega-projects. This blueprint is critical for developing nations aiming to maximize project outcomes.

Discussion

• While AI tools enhance project monitoring, human oversight remains essential in decision-making.
• Case studies from China, Australia, and the US show that integrating predictive analytics reduces delays by 20-35%.

Policy Recommendations

1. Adopt AI-Driven Predictive Models – AI-based early warning systems for detecting potential delays.
2. Incorporate Climate-Resilient Infrastructure – Use of adaptive designs to minimize environmental impacts.
3. Strengthen Stakeholder Collaboration – Regular consultations with affected communities to reduce social resistance.
4. Benchmark Against International Best Practices – Lessons from WestConnex (Australia) & Belt & Road (China) highlight the need for integrated AI planning tools.

CONCLUSION

The study demonstrates how AI-driven thematic analysis and a circular economy perspective can enhance mega-project management strategies. Addressing delays requires a multi-pronged approach, integrating real-time AI analytics, sustainable design, and stakeholder engagement. Future studies should explore AI’s predictive capabilities in mega-project risk assessment.

ACKNOWLEDGEMENTS

I like to express my sincere gratitude to Dr. Sudath, (Professor, University of Kelaniya, Sri Lanka) for his invaluable guidance, unwavering support, and insightful feedback as a Supervisor for this research. I also like to express my sincere gratitude to Dr Kamal (Faculty & Coordinator Bangladesh, UoK) for his encouragement in my work and for his expertise to enhance the quality of this manuscript.

AUTHOR CONTRIBUTION

The author hereby confirms his contribution in the paper by conceptualizing the research, proposing the methodology, collecting and analyzing the data, and drafting this manuscript.

REFERENCES 

1. Chen, X., Zhang, Y., & Li, J. (2023). The impact of transportation infrastructure on healthcare accessibility. Journal of Infrastructure Development, 35(2), 112-130.
2. Shoulin, W., Rahman, M., & Alam, S. (2024). Circular economic effects of infrastructure projects. International Journal of Sustainable Infrastructure, 40(1), 99-120.
3. Zhou, L., Wang, P., & Chen, Y. (2019). The transformative potential of transportation infrastructure. Global Economic Review, 22(5), 156-172.