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    PublicationOpen Access
    Strategic implementation of PPP for small-scale infrastructure in Sri Lanka: a comparative analysis of alternative PPP models
    (Ceylon Institute of Builders - Sri Lanka, 2023-07-21) Guruge, K; Coomasaru, P; Weeraman, C
    This study aims to provide a thorough comparison of Private Finance Initiative (PFI), Build-Operate-Transfer (BOT), and Joint Venture (JV) models for Small-Scale Infrastructure Development (SSID) in Sri Lanka and devise innovative, tailored recommendations to maximise efficiency, effectiveness, and compatibility. Employing a mixed-methods approach, the research systematically examines the key features, benefits, and limitations of PFI, BOT, and JV models in the context of SSID. A compatibility assessment is conducted, focusing on financing approaches, stakeholder engagement, and other critical success factors. The findings reveal that the BOT and JV models are superior to the PFI model due to their balanced stakeholder engagement, risk sharing, and alignment with critical success factors. Based on these insights, the study formulates novel, customised recommendations for optimising the selected model's efficiency, effectiveness, and compatibility with SSID in Sri Lanka, with the aim of informing policy and practice. Furthermore, the study highlights the need for future research exploring alternative financing models and emerging technologies in SSID, opening new avenues for innovative approaches to infrastructure development in Sri Lanka. In conclusion, this comprehensive comparison offers valuable guidance for academics, industry professionals, and policymakers seeking to enhance small-scale infrastructure development in Sri Lanka, emphasising the importance of selecting the most suitable financing model.
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    PublicationOpen Access
    POTENTIAL IMPACTS OF BLOCKCHAIN TECHNOLOGY IMPLEMENTATION ON CONSTRUCTION CONTRACT MANAGEMENT IN SRI LANKA
    (Construction Contract Management, 2023-07-21) Karunaratne, B.C.T.M.; Abeynayake, D.N.
    The construction contract is the mainstay for the ascendancy of the construction project requiring proper contract management. The Sri Lankan construction industry has many complications associated with contract management. Blockchain, as a decentralised transaction and data management technology, can potentially address the issues related to contract management amidst the impediments to effective implementation. However, blockchain technology adaptation in the Sri Lankan construction industry lacks evidence, even though other sectors, for example, banking and agriculture, are with the initial implementation. Hence, this research aimed to identify the potential impacts of implementing blockchain technology in construction contract management in Sri Lanka. A literature review was conducted to identify the concept of blockchain technology, its applications and its benefits. A qualitative survey strategy was adopted, and data were collected via semi-structured interviews in two phases; Phase I with ICT and finance industry experts and Phase II with construction contract experts. Samples were selected purposively through snowball sampling. The data analysis revealed that the awareness and use of blockchain technology in Sri Lanka are relatively low. However, Sri Lanka has the potential to adopt Blockchain in different fields, depending on their capabilities. Furthermore, the study found associated positive impacts of Blockchain, e.g., avoiding complex procedures, providing transparency, no ambiguities, no human errors and reducing political influence to mitigate contract management issues. Besides, Blockchain may negatively impact due to, e.g., high initial and maintenance costs, lack of knowledge and expertise, unavailability of rules and regulations, and reluctance to change those need mitigations.
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    PublicationOpen Access
    A STUDY ON THE PHYSICAL AND MENTAL HEALTH ISSUES TO THE NEIGHBOURING RESIDENCES DUE TO THE CONSTRUCTION PROJECTS IN SRI LANKA
    (Ceylon Institute of Builders - Sri Lanka, 2023-07-21) Arjuna, M.P.; Edirisinghe, V.; Manoharan, K.; Herath, S.S.
    This study investigates the physical and mental health issues experienced by neighbouring residences as a result of construction projects in Sri Lanka. Specifically, it examines the impact of these projects on respiratory distress, hearing impairments, traffic congestion, lack of landscape, and flooding conditions. Additionally, the study explores the psychological effects on residents and emphasises the importance of health and safety measures in project management. Data collection involved conducting interviews with project managers, site safety officers, and a male nurse from three selected construction sites, followed by a questionnaire survey administered to 30 neighbouring residents. The study provides recommendations to mitigate adverse impacts, raise community awareness, and promote environmentally friendly practices in the construction industry. The findings enhance understanding of the health challenges faced by neighbouring residents and offer insights to policymakers and project managers to improve the well-being of affected communities.
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    PublicationOpen Access
    Projected Water Levels and Identified Future Floods: A Comparative Analysis for Mahaweli River, Sri Lanka
    (IEEE, 2023-01) Rathnayake, N; Rathnayake, U; Chathuranika, I; Dang, T. L; Hoshino, Y
    The Rainfall-Runoff (R-R) relationship is essential to the hydrological cycle. Sophisticated hydrological models can accurately investigate R-R relationships; however, they require many data. Therefore, machine learning and soft computing techniques have taken the attention in the environment of limited hydrological, meteorological, and geological data. The accuracy of such models depends on the various parameters, including the quality of inputs and outputs and the used algorithms. However, identifying a perfect algorithm is still challenging. This study develops a fuzzy logic-based algorithm called Cascaded-ANFIS to accurately predict runoff based on rainfall. The model was compared against three regression algorithms: Long Short-Term Memory, Grated Recurrent Unit, and Recurrent Neural Networks. These algorithms have been selected due to their outstanding performances in similar studies. The models were tested on the Mahaweli River, the longest in Sri Lanka. The results showcase that the Cascaded-ANFIS-based model outperforms the other algorithms. The correlation coefficient of each algorithm’s predictions was 0.9330, 0.9120, 0.9133, 0.8915, 0.6811, 0.6811, and 0.6734 for the Cascaded-ANFIS, LSTM, GRU, RNN, Linear, Ridge, and Lasso regression models respectively. Hence, this study concludes that the proposed algorithm is 21% more accurate than the second-best LSTM algorithm. In addition, Shared Socio-economic Pathways (SSP2-4.5 and SSP5-8.5 scenarios) were used to generate future rainfalls, forecast the near-future and mid-future water levels, and identify potential flood events. The future forecasting results indicate a decrease in flood events and magnitudes in both SSP2-4.5 and SSP5-8.5 scenarios. Furthermore, the SSP5-8.5 scenario shows drought weather from May to August yearly. The results of this study can effectively be used to manage and control water resources and mitigate flood damages.