Project Politics in Public Housing in Small Island Developing States: A Case Study of Cost and Revenue
DOI:
https://doi.org/10.47941/jbsm.1998Keywords:
Project Politics, Public Housing, Small Island, Developing States (SIDS), Cost, RevenueAbstract
Purpose: This research aims to explore the intricate dynamics of project politics in public housing development within Small Island Developing States (SIDS), with a particular focus on the interplay between costs and revenue.
Methodology: Utilizing a detailed case study approach, this paper investigates a specific public housing project in a SIDS, analyzing the political dynamics surrounding its cost and revenue aspects.
Findings: The study reveals that political factors significantly influence decision-making processes, resource allocation, and the financial viability of public housing projects in SIDS. Political interference often results in resource misallocation, cost overruns, and inefficiencies in revenue generation. Additionally, patronage and nepotism lead to housing resource distribution based on political favoritism rather than genuine need, undermining the effectiveness and fairness of public housing initiatives.
Contribution to Theory, Policy, and Practice: This research underscores the critical importance of addressing project politics to ensure sustainable and effective housing solutions in SIDS. By highlighting the need for enhanced financial viability, transparency, and accountability in public housing projects, this study contributes valuable insights to the theoretical understanding of development politics. It also offers practical recommendations for policymakers to mitigate political interference, thereby fostering equitable and sustainable public housing solutions in SIDS.
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Chadee, A. A., Martin, H. H., Gallage, S., Banerjee, K. S., Roopan, R., Rathnayake, U., & Ray, I. (2023). Risk Evaluation of Cost Overruns (COs) in Public Sector Construction Projects: A Fuzzy Synthetic Evaluation. Buildings, 13(5), 1116.
Allam, Z., & Jones, D. (2019). Climate change and economic resilience through urban and cultural heritage: The case of emerging Small Island developing states economies. Economies, 7(2), 62.
Dornan, M. (2014). Access to electricity in Small Island Developing States of the Pacific: Issues and challenges. Renewable and Sustainable Energy Reviews, 31, 726-735.
Allam, Z., & Jones, D. (2019). Climate change and economic resilience through urban and cultural heritage: The case of emerging Small Island developing states economies. Economies, 7(2), 62.
Pelling, M., & Uitto, J. I. (2001). Small island developing states: natural disaster vulnerability and global change. Global Environmental Change Part B: Environmental Hazards, 3(2), 49-62.
Chittoo, H. B. (2011). Public administration in “Small and island developing states”: A debate about implications of smallness. Global Journal of Management and Business Research, 11(9), 23-34.
Rehan, H. (2024). The Future of Electric Vehicles: Navigating the Intersection of AI, Cloud Technology, and Cybersecurity. Valley International Journal Digital Library, 1127-1143.
Chadee, A. A., Martin, H. H., Mwasha, A., & Otuloge, F. (2022). Rationalizing critical cost overrun factors on public sector housing programmes. Emerging Science Journal, 6(3), 647-666.
Pulicharla, M. R. (2023). Hybrid Quantum-Classical Machine Learning Models: Powering the Future of AI. Journal of Science & Technology, 4(1), 40-65.
Jiang, B., Seif, M., Tandon, R., & Li, M. (2021). Context-aware local information privacy. IEEE Transactions on Information Forensics and Security, 16, 3694-3708.
Chadee, A. A., Chadee, X. T., Ray, I., Mwasha, A., & Martin, H. H. (2021). When parallel schools of thought fail to converge: The case of cost overruns in project management. Buildings, 11(8), 321.
Pulicharla, M. R. (2024). Data Versioning and Its Impact on Machine Learning Models. Journal of Science & Technology, 5(1), 22-37.
Asaju, B. J. (2024). Privacy Preservation Techniques in V2X Ecosystems: Safeguarding Individual Privacy in Connected Vehicle Environments. Journal of Artificial Intelligence Research, 4(1), 58-72.
Pinto, J. K. (2000). Understanding the role of politics in successful project management. International Journal of Project Management, 18(2), 85-91.
Bang, H. P. (2009). ‘Yes we can’: identity politics and project politics for a late-modern world. Urban Research & Practice, 2(2), 117-137.
Hodgson, D., & Cicmil, S. (2007). The politics of standards in modern management: Making ‘the project’a reality. Journal of Management Studies, 44(3), 431-450.
Adeyeri, T. B. (2024). Enhancing Financial Analysis Through Artificial Intelligence: A Comprehensive Review. Journal of Science & Technology, 5(2), 102-120.
Altshuler, A. A., & Luberoff, D. E. (2004). Mega-projects: The changing politics of urban public investment. Rowman & Littlefield.
Aureli, P. V. (2008). The project of autonomy: politics and architecture within and against capitalism (Vol. 4). Princeton Architectural Press.
Asaju, B. J. (2024). Advancements in Intrusion Detection Systems for V2X: Leveraging AI and ML for Real-Time Cyber Threat Mitigation. Journal of Computational Intelligence and Robotics, 4(1), 33-50.
Singh, M. Machine Learning in Marketing Analytics.
Heston, T. F., & Pahang, J. A. (2019). Moral injury and the four pillars of bioethics. F1000Research, 8.
Zhang, W., Jiang, B., Li, M., & Lin, X. (2022). Privacy-preserving aggregate mobility data release: An information-theoretic deep reinforcement learning approach. IEEE Transactions on Information Forensics and Security, 17, 849-864.
Wong, P. P. (2011). Small island developing states. Wiley Interdisciplinary Reviews: Climate Change, 2(1), 1-6.
Briguglio, Lino. "Small island developing states and their economic vulnerabilities." World development 23.9 (1995): 1615-1632.
Ghina, F. (2003). Sustainable development in small island developing states. Environment, development and sustainability, 5, 139-165.
Heston, T. F., & Pahang, J. A. (2023). Moral injury and the four pillars of bioethics [version 4.
Weng, Y., & Wu, J. (2024). Fortifying the global data fortress: a multidimensional examination of cyber security indexes and data protection measures across 193 nations. International Journal of Frontiers in Engineering Technology, 6(2), 13-28.
Kelman, I., & West, J. J. (2009). Climate change and Small Island developing states: a critical review. Ecological and Environmental Anthropology, 5(1), 1-16.
Eastin, J. (2018). Climate change and gender equality in developing states. World Development, 107, 289-305.
Betzold, C. (2015). Adapting to climate change in small island developing states. Climatic change, 133(3), 481-489.
Weng, Y. (2024). BIG DATA AND MACHINE LEARNING IN DEFENCE. International Journal of Computer Science and Information Technology, 16(2), 25-35.
Pelling, M., & Uitto, J. I. (2001). Small island developing states: natural disaster vulnerability and global change. Global Environmental Change Part B: Environmental Hazards, 3(2), 49-62.
Liang, Y., Wang, X., Wu, Y. C., Fu, H., & Zhou, M. (2023). A Study on Blockchain Sandwich Attack Strategies Based on Mechanism Design Game Theory. Electronics, 12(21), 4417.
Adeyeri, T. B. (2024). Automating Accounting Processes: How AI is Streamlining Financial Reporting. Journal of Artificial Intelligence Research, 4(1), 72-90.
Turvey, R. (2007). Vulnerability assessment of developing countries: the case of small‐island developing states. Development Policy Review, 25(2), 243-264.
Barton, D. M., & Sherman, R. (1984). The price and profit effects of horizontal merger: a case study. The Journal of Industrial Economics, 33(2), 165-177.
Li, X., Wang, X., Chen, X., Lu, Y., Fu, H., & Wu, Y. C. (2024). Unlabeled data selection for active learning in image classification. Scientific Reports, 14(1), 424.
Ojo, L. O. (2020). Impact of tax administration on government revenue in developing economy: A case study of Nigeria. Advance Journal of Financial Innovation and Reporting, 4(4).
Lee, Z., Wu, Y. C., & Wang, X. (2023, October). Automated Machine Learning in Waste Classification: A Revolutionary Approach to Efficiency and Accuracy. In Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition (pp. 299-303).
Jiang, B., Li, M., & Tandon, R. (2019, May). Local information privacy with bounded prior. In ICC 2019-2019 IEEE International Conference on Communications (ICC) (pp. 1-7). IEEE.
Adeyeri, T. B. (2024). Blockchain and AI Synergy: Transforming Financial Transactions and Auditing. Blockchain Technology and Distributed Systems, 4(1), 24-44.
rnest Adu-Gyamfi, E. (2014). E ffective Revenue Mobilisation by Districts Assemblies: A Case Study of Upper Denkyira E ast Municipal Assembly of Ghana. Public Policy and Administration, 2(1), 97-122.
Guo, H., Ma, Z., Chen, X., Wang, X., Xu, J., & Zheng, Y. (2024). Generating Artistic Portraits from Face Photos with Feature Disentanglement and Reconstruction. Electronics, 13(5), 955.
Wang, X., Wu, Y. C., & Ma, Z. (2024). Blockchain in the courtroom: exploring its evidentiary significance and procedural implications in US judicial processes. Frontiers in Blockchain, 7, 1306058.
Marn, M. V., & Rosiello, R. L. (1992). Managing price, gaining profit. McKinsey Quarterly, 18-18.
Liu, Y., Wu, Y. C., Fu, H., Guo, W. Y., & Wang, X. (2023). Digital intervention in improving the outcomes of mental health among LGBTQ+ youth: a systematic review. Frontiers in psychology, 14, 1242928.
Chandra, A. Privacy-Preserving Data Sharing in Cloud Computing Environments.
Manukondakrupa, Ajay Chandra. (2024). ENHANCED THREAT INTELLIGENCE NETWORK (EETIN): A UNIFIED APPROACH FOR IOT ATTACK DETECTION.
Jiang, B., Li, M., & Tandon, R. (2024). Online Context-aware Streaming Data Release with Sequence Information Privacy. IEEE Transactions on Information Forensics and Security.
Manukondakrupa, Ajay Chandra. (2024). Fortifying Patient Privacy: A Cloud-Based IoT Data Security Architecture in Healthcare.
Alizamir, S., Iravani, F., & Mamani, H. (2019). An analysis of price vs. revenue protection: Government subsidies in the agriculture industry. Management Science, 65(1), 32-49.
Effendi, A. (2020). Sales volume and production costs against company revenue: a case study in the indonesia stock exchange 2014-2018. International Journal on Social Science, Economics and Art, 10(3), 144-152.
El Haddad, R., Roper, A., & Jones, P. (2008, October). The impact of revenue management decisions on customers attitudes and behaviours: A case study of a leading UK budget hotel chain. In EuroCHRIE 2008 Congress, Emirates Hotel School, Dubai, UAE, 11th-14th October. Retrieved April (Vol. 6, p. 2011).
Manukondakrupa, Ajay Chandra. (2024). A GREY WOLF OPTIMIZATION-BASED FEED-FORWARD NEURAL NETWORK FOR DETECTING INTRUSIONS IN INDUSTRIAL IOT. International Journal of Management IT and Engineering. 14. 65-91.
Xu, H., & Li, B. (2013). Dynamic cloud pricing for revenue maximization. IEEE Transactions on Cloud Computing, 1(2), 158-171.
Manukondakrupa, Ajay Chandra & Technical, M & Manager, Erp. (2024). A COMBINATION OF OPTIMIZATION-BASED MACHINE LEARNING AND BLOCKCHAIN MODEL FOR ENHANCING SECURITY AND PRIVACY IN THE MEDICAL SYSTEM. 12. 21-49.
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Copyright (c) 2024 Aaron Anil Chadee , Gunness Sudama , Ryan Rampair
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