Next-generation wide-body aircraft, such as the Boeing 787 and Airbus A350, incorporate advanced composite structures and predictive maintenance systems; however, limited research has examined how these innovations affect maintenance costs and reliability throughout the aircraft lifecycle. This study employs a mixed-methods comparative approach, combining published cost and reliability data from ICAO, IATA, FAA, EASA, and airline reports with insights from six semi-structured interviews with maintenance professionals in the Philippines. The quantitative analysis focused on the Maintenance Cost Index (MCI), Cost per Flight Hour (CPFH), and Mean Time Between Failures (MTBF), applying a cost–reliability benchmarking equation adapted from established maintenance economics models. Qualitative data were thematically analysed using NVivo 14 to capture practitioners’ perspectives on repair complexity, maintenance procedures, and predictive system utilisation. The findings show that the Airbus A350 achieves a lower CPFH, higher dispatch reliability, and shorter repair times, which are attributed to its modular Glass Laminate Aluminium Reinforced Epoxy (GLARE) design and Skywise predictive platform. In contrast, the Boeing 787 exhibits greater maintenance complexity and higher costs owing to its monolithic carbon fibre structure and specialised repair requirements. This study introduces a novel cost–reliability synthesis framework, offering context-specific insights for fleet planning, MRO procurement, and technician training, while outlining future research directions using primary operator data sets and AI-driven predictive maintenance models.
Multimodal integration enhances public transport usage, thereby reducing traffic congestion, which is particularly suitable in Sri Lanka. However, the fragmented ownership of public transport and the lack of coordination between different transport service providers make it difficult to implement this concept. This study aims to identify the best global practices and prioritise them for the Sri Lankan context, focusing on the Kandy Multimodal Transit Terminal (KMTT) as a case study for implementing multimodal integration. A qualitative and quantitative mixed-methods approach is used, including a literature review, case study analysis, and structured expert interviews, to identify the best global practices that other countries have used to implement multimodal integration and rank them according to importance and urgency based on their suitability to Sri Lanka's unique transport system. The mixed-method approach increases the accuracy of the provided practices. The analysis provided a model of the integration ladder based on the Important–Urgent matrix to implement multimodal integration step-by-step to achieve seamless transport and ensure better connectivity, accessibility, and efficiency.
This study examines the transformative role of Technical and Vocational Education and Training (TVET) in promoting non-motorised transportation (NMT) as a pathway to sustainable mobility in Africa. A structured literature review was conducted, synthesising 68 peer-reviewed publications from 2010 to 2023 using Scopus and Web of Science databases. Thematic analysis was employed to identify and categorise core trends linking TVET innovations to sustainable transport outcomes. The findings reveal that TVET institutions contribute significantly to the development of context-specific frugal innovations, such as solar-powered bicycles, cargo tricycles, and modular repair kits designed for informal and peri-urban African settings. Despite this potential, TVET-driven innovations remain underrepresented in national transportation policies and urban planning frameworks. This study argues for a stronger alignment between TVET curricula and green mobility policy, supported by skills development in digital fabrication, green energy systems, and local-material engineering. This study also critiques the fragmented application of Industry 4.0/5.0 concepts in the literature and calls for clearer integration frameworks that reflect Africa’s technological realities. This review advances a conceptual agenda for leveraging TVET as a catalyst for inclusive low-carbon transport in Africa.
This study examines the digital transformation of Sri Lanka's maritime industry, focusing on identifying key barriers, analysing their interconnections, and assessing the digitalisation potential in import, export, and freight forwarding operations. Through a systematic review, this study identifies five primary categories of barriers to digitalisation: organisational and management-related, operational, resource-related, market-related, and technological barriers. A structured questionnaire was distributed to 148 professionals in the maritime sector, including stakeholders from shipping agencies, freight forwarders, and port authorities, who were selected using the snowball sampling method. The collected data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) to assess the influence of each barrier on the digitalisation level of Sri Lanka’s maritime industry. The findings confirm that all five barrier types significantly hinder digitalisation, with organisational and management-related barriers having the strongest and most negative impact. Additionally, ordinal data analysis was used to evaluate the current and potential digitalisation levels in imports, exports, and freight forwarding. The results reveal significant gaps between the existing and potential states, particularly in critical operations. These insights can help stakeholders address key barriers and implement targeted actions to boost digital adoption, improve efficiency, and enhance global competitiveness in the industry. The findings contribute not only to the academic discourse on maritime digitalisation but also serve as a practical guide for policymakers, industry leaders, and practitioners navigating the complexities of digital transformation in Sri Lanka’s maritime sector.
The Port of Hambantota is strategically located along the East-West main sea route, with an approximate deviation of ten nautical miles. Most current business at the Port of Hambantota relies on automobile roll-on/roll-off, breakbulk, bulk, and project cargo operations. Furthermore, container ship handling operations are expected to commence at the Port of Hambantota. Therefore, this study evaluates the competitiveness of the Port of Hambantota as a container transshipment hub compared to six existing transshipment hub ports: the Port of Jebel Ali and Port of Salalah in Southwest Asia, the Port of Colombo in South Asia, and the Port of Singapore, Port of Tanjung Pelepas, and Port Klang in Southeast Asia. This study considers the mainline-to-feeder transshipment operation. The competitiveness analysis is based on market share using an extended version of the generalised cost approach combined with a discrete choice model. Senior managers attached to the main container line agencies in Sri Lanka evaluated the selection criteria for transshipment hub ports and the performance of the competing hubs. Further scenario analysis was conducted to understand the potential implications for the transshipment business at the Port of Hambantota. The results indicate that the Port of Singapore has the highest potential to become a market leader in transshipment operations despite the presence of the Port of Hambantota. However, the findings also suggest that the Port of Hambantota possesses significant potential for transshipment operations, provided that there are continuous improvements in port performance.
Carpooling, as a shared mobility option, offers a means to reduce single-occupancy vehicle use and promote sustainable travel behaviour. While many studies have explored carpooling in developed countries, there is a growing need to consider context-specific factors influencing the participation of vehicle users in lower- and middle-income countries (LMIC). This study employed a mixed-methods approach, combining interviews and surveys, to examine carpooling behaviour in Sri Lanka. The interview data were analysed thematically, while the survey data were examined using descriptive analysis and hypothesis testing to identify the key factors influencing the willingness to carpool. This study explores the willingness of private vehicle owners in Sri Lanka, particularly work commuters, to share empty vehicle spaces as potential carpooling facility suppliers. While carpooling remains unfamiliar to many, the participants expressed optimism regarding its potential to reduce traffic congestion. The ranking results indicated that the participants prioritised vehicle efficiency, comfort, cost savings, and personal security. Age was a stronger determinant of willingness than gender or education, with 25–35-year-olds most receptive, mainly for commuting to work, and valuing features like assured matches and safety protocols. These findings support the development of targeted policies and digital solutions that align with user needs and mobility patterns in emerging urban contexts.
The adoption of Industry 4.0 technologies has transformed warehouse management, enhancing its efficiency, accuracy, and profitability. However, optimising warehouse layouts, particularly fishbone designs, remains complex and often relies on intricate mathematical models that are impractical for workers to implement. Addressing this gap, this study proposes a straightforward methodology for generating optimised fishbone layouts adaptable to various warehouse sizes. The framework integrates warehouse, product, and forklift dimensions, leveraging Prolog to calculate aisle widths, row numbers, and forklift turning capabilities. This dynamic approach optimises safety and operational efficiency while simplifying decision-making processes. Validation through real-world scenarios demonstrates the model's adaptability and effectiveness across diverse setups, ensuring safe forklift navigation and efficient space utilization. By bridging the divide between theoretical models and practical application, this methodology offers warehouse operators an accessible tool for layout design. The findings contribute to warehouse optimization research, providing a scalable and efficient solution for optimising space and operations in warehouse management systems.
Transition to electric bike-sharing systems (EBSS) offers a sustainable and efficient solution for urban mobility, reducing emissions and enhancing accessibility. This study used data from New York City's bike-sharing program, combining socio-demographic factors, built environment indicators, and bike station placement insights to assess EBSS adoption. Using participatory system dynamics modelling, we developed causal loop diagrams to compare the dynamics of cycling adoption in two contrasting contexts: New York, USA, where EBSS is well-integrated as a last-mile and supplementary transportation mode, and Colombo, Sri Lanka, where e-bike adoption remains limited. Key feedback loops identified in New York emphasise the role of infrastructure investments, public transit integration, and safety measures in driving EBSS demand. These insights were adapted to Colombo, revealing potential strategies such as improving cycling infrastructure, integrating EBSS with transit systems, and launching awareness campaigns to overcome cultural and behavioural barriers. The findings provide a systematic framework for policymakers, urban planners, and stakeholders to accelerate EBSS adoption in diverse urban settings. By applying lessons from New York to Colombo, this study highlights actionable pathways to foster e-bike culture and sustainable urban mobility.
An adequate supply of rail services in the Colombo suburban network is critical to meeting the needs of the current passenger clientele. Despite the increasing demand due to urbanisation and population growth, limited research has hitherto been undertaken on whether train services align with commuter needs, especially during peak hours. Using the Gap Analysis approach, this study examined the extent to which the provision of rail services met the demand of the current clientele in the Colombo suburban network. It focused specifically on the Main Line between Colombo Fort and Polgahawela, and on the Puttalam Line between Ragama and Chilaw. In this study, demand was estimated as revealed from ticket sales using the Origin-Destination (OD) Matrix, and supply was estimated based on the seating capacity of trains operated during peak hours. The stations with high and low demand were thereby identified analysing the patterns of passenger flows and sectional load factors. Even though the socio-economic benefits associated with increased railway mode share were found to be substantial, the outcomes of the study suggest that the potential to attract more passengers to the railway mode, especially on the Main Line, may be limited due to existing high load pressures. Alleviation of such pressures requires strategic interventions to reform the operating schedules and structures providing more express trains to stations with substantial demand and sections with high load factors while selectively removing stops at stations fetching lower demand. The alternative would be to augment the supply capacity, which will be highly capital-intensive.
This study aims to identify traffic accident hotspots and establish the correlation between road features and accidents. Network-based Kernel Density Estimators (NKDE) were computed using traffic accident data from 2009 to 2013 for each year for road segments termed lixels. These yearly NKDEs were aggregated to formulate a traffic accident intensity index (AII), serving as the foundation for hotspot identification. A Gamma regression model with a logarithmic link was constructed to relate the AII values of lixels in the A2 highway with macro-level parameters. Population, Junction density (number of junctions in a section), Bendiness, and Urbanisation. The study determined that a cell size of 250 m with a 500 m bandwidth is optimal for NKDE calculations for the road network of the Galle district. Lixels having extreme AII values were defined as the traffic accident hotspots and subdivided into yellow, orange, and red zones. Additionally, the Gamma regression model highlighted significant correlations between road attributes and accident intensity, indicating a 131% increase in AII values in urban areas compared to rural ones. Areas with junctions and bends had a decreasing effect on the AII values. With the increase of a junction, AII decreased significantly by 29 %, and if a bend is present in the lixel, AII decreases significantly by 12%.
International trade documentation in South Asia are complex and time-consuming to process, and they are often hindered by delays and inefficiencies. This study investigates the potential of Blockchain (BC) and Machine Learning (ML) to reduce trade document processing time and improve trade efficiency. Using an explanatory sequence design, the research combines quantitative analysis of survey data with qualitative insights from case studies. The quantitative phase revealed that BC, ML, and trade facilitation regulations are significant in reducing trade documentation processing time. Consequently, reducing trade documentation processing time requires the implementation of BC and ML with supporting new trade facilitation regulations. The qualitative phase identifies key challenges to the adoption of BC and ML, including legal and regulatory hurdles (e.g., legal recognition of smart contracts, unclear data ownership, and unclear data privacy regulations), organisational barriers (e.g., Resistance to change, lack of awareness, and lack of skilled personnel), and technological limitations (e.g., scalability issues, integration challenges, and security concerns). The study underscores the importance of addressing these challenges through collaborative efforts between governments, financial institutions, and technology companies. This research contributes to the growing body of knowledge on BC and ML applications in international trade, providing valuable information for policy makers and practitioners seeking to modernise trade processes in South Asia.
Road crashes are a global concern, and they disproportionately affect younger drivers due to their inexperience and risk-taking behaviour. In Sri Lanka, the higher risk of traffic crashes among younger drivers underscores the need for researchers to study their driving confidence and behaviour. Such research could help mitigate the risks of future crashes. This research surveyed 400 young adults using a paper-based questionnaire to assess their confidence in various driving conditions: daytime, peak hours, nighttime, rainy weather, and hilly roads. It also examined risky behaviour such as smoking while driving, driving under the influence of alcohol, using a phone, and making illegal U-turns. The analysis employed Cronbach's Alpha reliability statistics, inter-item correlation, and Binary Logistic Regression (BLR) modelling. Participants' opinions on the Sri Lankan driving license process revealed that 16% rated it as good, 25% as average, and 59% as bad. Findings highlighted that increasing young drivers' confidence during nighttime and high-traffic congestion conditions reduces the likelihood of crashes. Confidence during nighttime and rainy conditions, along with perceptions of the licensing process, significantly influence crash involvement. Furthermore, risky manoeuvres, like overtaking in restricted areas, increase crash risk. The study highlights the importance of improving driver education and fostering safer behaviour to enhance road safety among young drivers in Sri Lanka.
The critical gap/lag value for an uncontrolled intersection is an important parameter in estimating highway traffic capacity and developing micro stimulations of traffic movements. In manoeuvring an intersection, drivers decide to accept or reject the gap, based on several considerations. However, only a few studies have been carried out to estimate the critical gap on Sri Lankan roads; meanwhile, estimates of external factors are rare. This study found the influence of external factors on drivers’ gap acceptance decision and estimated the critical gap/ lag values using the Binary Logistic model. Analysis considered 4,233 gap acceptance decisions taken by drivers on minor roads. These were collected at three four-way and two three-way intersections and analysed across three vehicle categories: Motorcycle, Threewheeler, and Car/Van. Among the external factors studied, vehicle type, intersection type, size of the available gap, and type of traffic manoeuvre were found to have a significant influence on gap acceptance. Critical gap/lag values found in this study can be used for capacity estimation of three-way and four-way intersections in Sri Lanka.
Rail freight in Sri Lanka is declining substantially in all respects of volume, mode share, financial performance, and service quality, which are severely lag far behind international standards. This dire situation calls for a complete reformation of the rail freight system from its inception. Moreover, the issue of overcrowded roads increases the urgency for an improved alternate mode of freight transportation. Accordingly, this research investigates a rail freight strategy for Sri Lanka, using a global strategic model to align the Sri Lankan railway with international standards. The strategy formulation model is a pre-designed multiplicative regression framework, crafted through insights gleaned from a comprehensive global analysis of strategies employed by different nations for revitalising the sector. This model was selected following a rigorous examination of available frameworks identified through a thorough literature survey. Finally, our application of the model to the Sri Lankan context suggests various strategic measures that could be taken to optimise the performance of the Sri Lanka Rail freight industry and its ability to conform to global standards. These measures span policy, business operating structure and operations of Sri Lanka rail.
This study aims to identify the attributes of public transportation buses (PTB) preferred by passengers, which will be perceived as the buses’ quality of service. PTB of Sri Lanka faces several issues impacting its quality, efficiency, and modal share. Understanding user perceptions is essential to enhancing service quality and addressing the challenges that deter bus usage. Thirteen shortlisted attributes were rated by 84 (61 Male and 23 Female) respondents, and the top five attributes were selected. The study gathered user preferences towards PTB using Stated Preference (SP) and Revealed Preference (RP) methods for the five chosen attributes. RP data were modelled using a multiple linear regression model with R language. The data set comprised 192 (127 Male and 65 Female) valid responses. SP data showed that the respondents favoured medium-speed buses (51.2%) that were clean and reliable. Time of arrival was the most crucial attribute (30.3%), followed by vehicle condition (24.3%). Segment analysis revealed that gender and vehicle ownership significantly impacted preferences. Both gender and vehicle ownership segments prioritised arrival time and least valued seat comfort. The study emphasises the importance of prioritising punctuality over comfort. The findings of this study could provide valuable insights for policymakers to design more user-centric strategies, potentially enhancing the efficiency and attractiveness of bus services in Sri Lanka.
The transportation sector plays a vital role in fostering economic growth, societal connectivity, and individual mobility. Long-distance bus services have emerged as a prominent mode of transportation, offering an efficient and cost-effective means of travel for both urban and intercity commuters. This study aims to comprehensively assess and elucidate the supply-side determinants that significantly impact passenger satisfaction with long-distance expressway bus service in Sri Lanka. To ensure the collection of detailed and relevant insights from frequent users of the Southern Expressway's long-distance bus services, a purposive sampling technique was employed. Data collection was guided by variables identified in the literature review, and exploratory factor analysis was used to analyse the sample data. The study identified six salient supply-side factors affecting passenger satisfaction: service quality, comfort, accessibility and convenience, safety and security, cost, and customer service. These factors explained 74% of the total variance, with service quality being the most influential, accounting for 18% of the total variance. The findings recommend upgrading the bus fleet, maintaining cleanliness, optimizing scheduling, enhancing reservation systems, implementing staff training, improving safety measures, ensuring fair pricing, enhancing customer service, raising passenger awareness, and encouraging innovation to improve expressway bus services, attract more passengers, and build a reliable public transport system.
Although Sri Lanka has significant traffic-related fatalities and injuries, only a limited number of studies have focused on the road safety challenge. This study applies the random parameters logit model to police reported crash data to identify the factors contributing to the severity of crashes in Sri Lanka. We find that severe crashes are associated with roadways that are unlit, in rural areas and have traffic controls, dual purpose vehicles, heavy vehicles, head-on and hit pedestrian crashes, drivers who are unlicensed, and casualties who are older (65 years and older) and do not use safety equipment, while minor crashes are associated with rear-end crashes, and female or younger (aged 25 years or younger) casualties. Several engineering, enforcement, and education measures are recommended based on the risk factors identified.
Inventory management is a crucial component of sustainability, enabling companies to reduce expenses, enhance cash flow, and increase profitability. Inventory makes up a majority of current assets in the wholesale sector, where inefficiencies are bound to happen, given the large-scale inventory. This research focuses on identifying the factors and performance measures of inventory management and evaluating their interrelationships focusing on the Sri Lankan wholesale sector. The factors identified through a systematic review and industry experts’ interviews were then categorized into key areas with a thematic analysis. The 22 factors identified were grouped into the categories of organization, facilities and equipment, and processes and practices. The 24 performance measures were grouped into operational, customer satisfaction, and environmental categories. A questionnaire survey was conducted with 126 managerial-level employees of wholesale organisations. The partial least squares structural equation modelling (PLS-SEM) method is used to validate the relationship between the variables and the moderation effect of firm size on these relationships. The findings reflect that factors of organisation and facilities and equipment, influence the performance measures. Organisational factors were the most significant in influencing all three performance categories. For most relationships, the firm size did not have a moderation effect. This research assists wholesale businesses in achieving excellence and a competitive edge in the Sri Lankan market while finding answers to the ongoing business issues in the wholesale sector.
This agent-based simulation study investigates pedestrian dynamics with a focus on the impacts of behaviour idling on pedestrian flows. It also examines the influence of psychological, social, and environmental factors on pedestrian flows. Our research categorises pedestrian behaviour into three types: time-sensitive (Type A), mobility-constrained (Type B), and 'wandering' type (Type C), defined as pedestrians moving without a specific destination, which includes tourists, shoppers, and leisure walkers. We demonstrate how behaviour heterogeneity influences flow and movement patterns through simulations in unidirectional, bi-directional, and multi-directional pedestrian facilities. We find that Type C pedestrians significantly slow down Type A pedestrians, leading to a speed reduction of up to 30% in high-density tourist scenarios, and cause prolonged stationary periods for Type B pedestrians, particularly in less crowded settings where Type C's tendency to idle is more pronounced. Our results show a linear relationship between density and speed reduction, with tourist behaviour notably exacerbating congestion in high-density environments. Key insights highlight the critical role of wandering (Type C) behaviours in affecting pedestrian flow, emphasising the necessity for urban planning and infrastructure design to accommodate this variability. Future research aims to apply these findings to real-world contexts, further refining urban design strategies to accommodate the full spectrum of pedestrian behaviours.
In the 1960s, a counter-cultural movement promoting utilitarian bicycle usage emerged in Europe and North America, challenging the dominance of cars, and advocating for sustainable urban mobility. despite the emergence of this movement, many developing cities have low cycling modal share and encounter obstacles in promoting utilitarian cycling. This study delves into workers attitudes toward using bicycles as an alternative mode of transportation. Employing a Binary logistic regression model and incorporating the Relative Importance Index (RII), the research identifies key determinants of utilitarian cycling. The findings highlight significant community willingness (71%) to bike to work, despite perceived barriers. Safety concerns (RII - 0.88) and environmental factors (RII = 0.60), such as rain and heat, emerge as prominent deterrents. Societal perceptions linking cycling to lower social status (vanity) (RII = 0.35), bicycle affordability (RII = 0.35), and work-related factors (RII = 0.48), such as non-cycle-friendly work attire and insufficient office parking safety, play relatively minor roles in discouraging bicycle use. Using the logistic regression model, the study predicts factors influencing the willingness to use bicycles for utilitarian transportation, revealing negative impacts from the absence of cycling infrastructure, motor traffic, rainy weather, and a lack of a cycling community.
