Search Results (65)

This study explores the application potential of a lean–Agile hybrid method in complex construction project management. By integrating Scrum iterative development, the Last Planner System, and a BIM collaboration platform, a dual-engine model is established to optimize the dynamic priority mechanism (MoSCoW 2.0) and interface conflict entropy algorithm (ICE model). Through a combination of theoretical and practical approaches, the study elucidates the implementation pathway of this hybrid method and evaluates its benefits in enhancing project efficiency, reducing waste, and accelerating digital transformation. The study provides a replicable management framework for the construction industry and proposes a blockchain-based decentralized knowledge management framework based on blockchain technology. Full article

Island communities that depend on mainland grid connections face substantial risks when natural disasters sever undersea or overhead cables, often resulting in long-lasting outages. This paper presents a comprehensive and novel two-part methodological framework for enhancing the resilience of these communities through networked microgrids that interconnect local renewable energy resources and battery storage. The framework integrates techno-economic capacity optimization using HOMER Pro with agent-based simulation in AnyLogic to determine cost-effective solar and storage capacities and to model dynamic real-time dispatch under varying conditions. Six island communities across three Indonesian provinces serve as illustrative case studies, tested under best-case and worst-case disruption scenarios that reflect seasonal extremes of solar availability. Simulation results reveal that isolated expansions of PV and battery storage can ensure critical residential loads, though certain islands with limited resources continue to experience shortfalls. By contrast, networked microgrids enable surplus power transfers between islands, significantly reducing unmet demand and alleviating the need for large-scale, individual storage. These findings demonstrate the significant potential of clustered microgrid designs to improve reliability, lower operational costs, and facilitate secure energy supply even during prolonged cable outages. The proposed framework offers a scalable roadmap for deploying resilient microgrid clusters in remote regions, with direct policy implications for system planners and local stakeholders seeking to leverage renewable energy in high-risk environments. Full article

Integrating passenger and parcel transportation via transit (also known as transit co-modality) has been regarded as a potential solution to sustainable transportation, in which well-planned locations for parcel lockers are crucial for transferring parcels from transit to last-mile delivery vehicles. This paper proposes a data-driven optimization framework on parcel locker locations in a transit co-modal system, where last-mile delivery is realized via a ride-pooling service that pools passengers and parcels using the same fleet of vehicles. A p-median model is proposed to solve the problem of optimal parcel locker locations and matching between passengers and parcel lockers. We use the taxi trip data and the candidate parcel locker location data from Shenzhen, China, as inputs to the proposed p-median model. Given the size of the dataset, an optimization framework based on random sampling is then developed to determine the optimal parcel locker locations according to each candidate’s frequency of being selected in the sample. The numerical results are given to show the effectiveness of the proposed optimization framework, explore its properties, and perform sensitivity analyses on the key model parameters. Notably, we identify five types of optimal parcel location based on their ranking changes according to the maximum number of planned parcel locker locations, which suggests that planners should carefully determine the optimal number of candidate locations for parcel locker deployment. Moreover, the results of sensitivity analyses reveal that the average passenger detour distance is positively related to the density of passenger demand and is negatively impacted by the number of selected locations. We also identify the minimum distance between any pair of selected locations as an important factor in location planning, as it may significantly affect the candidates’ rankings. Full article

The design phase is critical in construction projects, as it directly impacts cost, quality, and execution efficiency. However, it suffers from structural deficiencies in communication, coordination, and early problem detection, leading to delays, cost overruns, and inefficiencies. While Lean Construction has been widely applied in execution phases, its adoption in design remains fragmented, lacking a clear framework for identifying and evaluating Lean tools in this context. This study aims to identify, classify, and evaluate Lean tools applicable to the building design phase, emphasizing their functionalities, benefits, and limitations. A systematic literature review and expert validation process led to the identification of 16 Lean tools and 26 design-related functionalities. Among these tools, Building Information Modeling (BIM), Last Planner System (LPS), and Agile Design Management (ADM) were identified as the most impactful, collectively addressing 88% of design functionalities. Expert insights revealed that ADM improves task control and decision-making clarity, LPS reduces uncertainty and enhances workflow reliability, and BIM strengthens coordination and early conflict detection. This study provides a structured perspective on Lean tool integration during design, highlighting their benefits and limitations and offering guidance for their implementation. The findings contribute to improving design efficiency, minimizing waste, and fostering collaboration in construction projects. Full article

The lack of access to centralized technologies and economic resources in rural communities makes wastewater management a critical challenge. Decentralized systems such as constructed wetlands offer sustainable solutions by leveraging natural processes for effluent treatment. However, their success and sustainability require active community participation. Currently, there is little evidence of community involvement in the implementation, maintenance, and management of constructed wetlands. Existing strategies for community collaboration in environmental and sanitation projects were analyzed through a literature review covering research conducted in the last 20 years. Only peer-reviewed research in English and Spanish was considered. Based on the findings, a triple helix model integrating academia, government, and society is proposed, compiling the most functional strategies from initial awareness raising to maintenance and dissemination. A case study of community participation is presented under this approach in the Salvador Díaz Mirón rural community, Veracruz, Mexico. The results of this study provide key information for effective strategies designed to manage constructed wetlands, emphasizing that their success depends on both the technology and the genuine commitment of communities to their operation and long-term sustainability. Furthermore, these findings can serve as a reference for decision-makers and project planners seeking to integrate participatory models into decentralized sanitation and water resource conservation. Full article

The increasing complexity of urban logistics in smart cities requires innovative solutions that leverage real-time data, predictive analytics, and adaptive learning to enhance efficiency. This study presents a predictive analytics framework integrating digital twin technology, IoT-enabled logistics data, and cybernetic feedback loops to improve last-mile delivery accuracy, congestion management, and sustainability in smart cities. Grounded in Systems Theory and Cybernetic Theory, the framework models urban logistics as an interconnected network, where real-time IoT data enable dynamic routing, demand forecasting, and self-regulating logistics operations. By incorporating machine learning-driven predictive analytics, the study demonstrates how AI-powered logistics optimization can enhance urban freight mobility. The cybernetic feedback mechanism further improves adaptive decision-making and operational resilience, allowing logistics networks to respond dynamically to changing urban conditions. The findings provide valuable insights for logistics managers, smart city policymakers, and urban planners, highlighting how AI-driven logistics strategies can reduce congestion, enhance sustainability, and optimize delivery performance. The study also contributes to logistics and smart city research by integrating digital twins with adaptive analytics, addressing gaps in dynamic, feedback-driven logistics models. Full article

Natural and man-made disasters threaten humans. Effective emergency management is essential to minimize disasters and their harmful effects. Prevention, preparation, response, and recovery are the basic phases of emergency management. Emergency assembly places are very important in emergency management during the preparation phase, as these are the first places to be reached during and after the disaster. This study aims to identify the most suitable locations for emergency assembly points, which play a critical role in sustainable disaster management. The location of emergency assembly points is influenced by many criteria. In this study, suitable locations for emergency places were investigated on the basis of criteria. The Best–Worst Method (BWM), a relatively new multi-criteria decision-making (MCDM) method that requires fewer pairwise comparisons and yet provides consistent results, is used to calculate the weights of the criteria after comparing results with the Analytical Hierarchy Process (AHP). The weighted criteria were then used to perform spatial analyses using Geographic Information Systems (GIS). In this study, a two-phase approach was used to determine suitable locations for assembly points: In the first phase, suitable areas were identified by applying raster-based analyses, and in the second phase, vector-based analyses were performed. The results of the two phases were evaluated together, and suitable locations for disaster assembly places were determined. In Atakum District, which is the study area, 41 emergency assembly places were identified, and suitable assembly places were ranked by the Preference Ranking Technique with Similarity to Ideal Solution (TOPSIS) method. Results showed that the first three highest-ranked assembly points (AP) were AP20, AP15, and AP25, while the last three lowest-ranked assembly points were AP2, AP7, and AP6. The identification of these locations will provide crucial decision support for local governments, disaster management authorities, urban planners, etc. in ensuring a more sustainable city. Full article

The construction industry faces persistent inefficiencies, with projects often failing to meet time, cost, quality, and other conditions of satisfaction. This study investigated real estate owners’ early perceptions of Lean Integrated Project Delivery (Lean IPD) as a potential solution, analyzing the acceptance of principles such as early stakeholder involvement, risk–reward compensation, and open-book accounting, among other key features in Lean IPD. A survey of 62 professionals in real estate development companies in Spain was conducted, analyzing their experience with collaborative contracts and Lean techniques, including Last Planner System and Target Value Design. Statistical methods such as hierarchical clustering and PLS-SEM modeling revealed two distinct groups: those receptive to Lean IPD’s economic mechanisms and those less inclined. While governance principles like early collaboration and team co-responsibility received widespread support, skepticism was noted toward economic transparency practices due to cultural and structural barriers. Additionally, the findings indicate a significant gap in formal training for Lean IPD. Despite challenges, there is strong interest in adopting Lean IPD, driven by its potential to address critical project inefficiencies. This study concludes that successful Lean IPD implementation requires strategic leadership from owners, targeted training programs, and a cultural shift within the industry to embrace collaborative and transparent practices. Full article

This research develops and applies a tool that allows the breakdown of time objectives to the same level of detail traditionally applied to cost, while also providing a favorable production scheme to ensure the project quality. This tool introduces an innovative approach to planning and execution monitoring through cascading dashboards, representing production packages and activities across designated project zones. This approach reinterprets the Last Planner System for jobs on-site in conjunction with the Location-Based Management System. The primary dashboard facilitates the management of complex work structures—typically involving hundreds of rows in Gantt chart representations or numerous lines in Line of Balance diagrams—while enabling the easy identification of activity cycles and gaps between activities in each zone. The tool offers a four-dimensional planning visualization—what, where, when, and who—enhancing the understanding of activity sequences and workflows across project zones, while also contributing to product quality improvement. Furthermore, it has been demonstrated through its application that the tool provides reliable, real-time information that supports decision-making, optimizes resource allocation, and improves overall project competitiveness. Full article

Bike-sharing (BS) systems provide a widely used and convenient feeder mode for connecting to public transportation (PT) and is seen as an effective solution to the first- and last-mile problem. Amidst the critical challenges posed by global climate change and rising temperatures, enhancing the resilience of the BS and PT integration is essential to ensure sustainable urban mobility and adapt to increasing climate variability, yet empirical studies in this area remain limited. This study analyzes BS-PT integration usage under extreme heats events, focusing on a Chinese mega city’s bike-sharing system. By defining extreme heat using the heat index, a more accurate measure of heat perception is established. We carefully categorize heatwaves based on the duration and temperature context of extreme heat to account for their potential impact on the integration’s response. Then, integrating multi-source big data and applying geographically weighted regression (GWR), we explore the spatial–temporal variations in the response of BS-PT integration ridership during different temperatures, and further identify key factors that contribute to the response of BS-PT integrated travel. Results show that extreme heat significantly influences BS-PT integration, with users showing a greater willingness to shift towards more integrated uses under extreme heat during non-summer seasons, compared to solely using bike-sharing, to avoid outdoor heat exposure. The temporal heterogeneity of the integrated trips is highest during extreme heat in non-summer and lowest under continuous extreme-heat periods. GWR spatial regression reveals that land-use characteristics significantly affect BS-PT integration resilience, with notable spatial differences in the influence of various factors, such as office density and entropy. These findings enhance our understanding of how climate change affects public transportation, providing urban planners and policymakers with valuable insights for improving the adaptability of urban mobility systems to climate change. Full article

Urbanization is a multifaceted process characterized by changes in urban areas through various means, such as sprawl, ribbon development, or infill and compact growth. This phenomenon changes the pattern of the local climate zone (LCZ) and significantly affects the climate, vegetation dynamics, energy consumption, water resources, and public health. This study aims to discern the impacts of changes in urban growth on the LCZ and land surface temperature (LST) over a two-decade period. A comprehensive methodology that integrates statistical analysis, data visualization, machine learning, and advanced techniques, such as remote sensing technology and geospatial analysis systems, is employed. ENVI, GEE, and GIS tools are utilized to collect, process, and monitor satellite data and imagery of temporal and spatial variations in intensive or diffuse urbanization processes from 2003 to 2023 to analyze and simulate land use and land cover (LULC) changes, urbanization index (UI), LCZ patterns, and LST changes over the years and to make overlapping maps of changes to recognize the relation between LULC, LCZ, and LST. This study focuses on Seville’s urban area, which has experienced rapid urbanization and a significant increase in average temperature during the last few decades. The findings of this study will provide actionable recommendations into the interplay between urban growth and climate and highlight the pivotal role of urban growth in shaping resilience and vulnerable areas based on microclimate changes. Urban planners can leverage these insights to predict alternatives for the future development of urban areas and define practical climate mitigation strategies. Full article

The urban landscape of Kinshasa, Democratic Republic of Congo, faces significant mobility challenges, primarily stemming from rapid urbanization, overpopulation, and outdated infrastructure. These challenges necessitate the exploration of modern smart mobility concepts to improve traffic flow, road safety, and sustainability. This study investigates the potential of solutions such as Mobility-as-a-Service, car sharing, micro-mobility, Vehicle-as-a-Service, and electric vehicles in addressing these challenges. Through a comparative analysis of global implementations, this research identifies key success factors and barriers that inform the feasibility of integrating these solutions into Kinshasa’s unique socio-political and infrastructural context. The study presents a conceptual framework, supported by stakeholder analysis, for adapting these solutions locally. A detailed feasibility analysis considers technological, economic, social, environmental, and regulatory factors, offering a clear roadmap for implementation. Drawing on lessons from cities facing similar urban mobility challenges, the paper concludes with actionable recommendations and insights for policymakers and urban planners in Kinshasa. This research not only highlights the viability of smart mobility solutions in Kinshasa but also contributes to the broader discourse on sustainable urban development in rapidly growing cities. While smart mobility studies have largely focused on cities with developed infrastructure, there is a gap in understanding how these solutions apply to cities like Kinshasa with different infrastructural and socio-political contexts. Previous research has often overlooked the challenges of integrating smart mobility in rapidly urbanizing cities with underdeveloped transportation systems and financial constraints. This study fills that gap by offering a feasibility analysis tailored to Kinshasa, assessing smart mobility solutions for its traffic congestion and road safety issues. The smart mobility solutions studied—Mobility-as-a-Service (MaaS), car sharing, electric vehicles (EVs), and micro-mobility—were chosen for their ability to address Kinshasa’s key mobility challenges. MaaS reduces reliance on private vehicles, easing congestion and improving public transport. Car sharing offers affordable alternatives to vehicle ownership, essential in a city with income inequality. EVs align with sustainability goals by reducing emissions, while micro-mobility (bikes and e-scooters) improves last-mile connectivity, addressing public transit gaps. These solutions are adaptable to Kinshasa’s context and offer scalable, sustainable improvements for urban mobility. Full article

Saudi Arabian cities have rapidly expanded their urban areas, especially their city centers, over the last four decades. This growth has led to increased vehicular usage. As a result, the daily walking experience for residents has been adversely affected. Walkability has several positive effects on people’s health and the urban environment. It serves as a means of transportation and helps create a sense of place. This enhances the legibility of urban structures and deepens emotional bonds with the city. This study uses the medium-sized Saudi Arabian city of Onaizah as a case study. It explores the feasibility of creating urban walking corridors to encourage more walking. According to Saudi Arabia’s Vision 2030, sustainable urban development and improved quality of life are key priorities. The study addresses walkability as a way to enhance the urban landscape of the city center. Geographic Information Systems (GISs) were used to analyze data and generate urban corridors in the city center. The results indicate that walking in Onaizah can be improved through three urban corridors. These corridors measure 1335 m, 1624 m, and 1937 m, respectively. They represent urban, commercial, and heritage corridors. This provides planners and decision makers an opportunity to prioritize pedestrian connectivity and improve the physical environment. Such efforts contribute to sustainable urban development. Various criteria-analysis methods were employed to assess the factors that led to the conclusion of these urban corridors. This includes evaluations of land use, transportation, and environmental considerations. The study aligns with Saudi Arabia’s Vision 2030 by promoting walking and enhancing overall walkability. It also aims to create a sustainable and livable urban environment for the community in Onaizah. Full article

Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies. Full article

Lean practice is recognised for having a great potential in promoting safety risk management in off-site construction (OSC). This paper presents results of a study conducted to assess the impact of lean practice on safety risk management in OSC in a developing country. A quantitative approach using a survey-based questionnaire was adopted. Lean management practices (LMPs) identified from a literature review were empirically tested using a sample survey of 103 OSC contractors. The survey responses were subjected to descriptive and inferential statistics. The top ranked LMPs for safety risk management in OSC included two mistake-proofing practices, i.e., use of personal protective equipment (PPE) and use of hazard warning equipment; two last planner system (LPS) practices, i.e., involvement of workers in safety planning and providing necessary working equipment; and one first run studies (FRS) practice, i.e., critical analysis of work methods. These LMPs are useful in controlling high-consequence safety risks in OSC. Based on evidence found in this study, the paper argues that lean practice can bring great value to safety risk management in OSC in countries where OSC is transitioning. Full article