Browsing by Author "Jelodar MB"

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A guideline for BIM and lean integrated construction practice
(Emerald Publishing Limited, 2025-04-09) Likita AJ; Jelodar MB; Vishnupriya V; Rotimi JOB
Purpose This study proposes a guideline for integrating Building Information Modelling (BIM) technology and lean construction practices to address the construction industry’s challenges in transitioning to environmentally friendly developments. Design/methodology/approach This study employs a qualitative research method, integrating and validating lean principles with BIM tools by extensively analysing previous studies. Subject matter expert interviews were conducted to validate the findings and create conceptual maps. Thematic and content analyses were performed to develop the proposed guidelines and recommendations. Findings The study highlights the potential of integrating BIM and lean construction practices to enhance productivity and reduce waste. The proposed guidelines provide practical recommendations for improving the implementation of BIM and lean practices, offering a structured approach for stakeholders to address critical challenges. Research limitations/implications While this study provides valuable insights, it primarily focuses on the New Zealand (NZ) context. Future research could explore the applicability of the proposed guidelines in different regions and consider quantitative validation methods to strengthen the findings. Originality/value This research contributes to the field by providing a novel guideline for integrating BIM and lean construction practices, addressing critical implementation challenges. The study offers valuable insights for global construction practices aiming to adopt advanced management approaches.
A review of climate change impact assessment and methodologies for urban sewer networks
(Elsevier B V, 2025-06) Karimi AM; Jelodar MB; Susnjak T; Sutrisna M
Understanding how climate change affects urban sewer networks is essential for the sustainable management of these infrastructures. This research uses a systematic literature review (PRISMA) to critically review methodologies to assess the effects of climate change on these systems. A scientometric analysis traced the evolution of research patterns, while content analysis identified three primary research clusters: Climate Modelling, Flow Modelling, and Risk and Vulnerability Assessment. These clusters, although rooted in distinct disciplines, form an interconnected framework, where outputs of climate models inform flow models, and overflow data from flow models contribute to risk assessments, which are gaining increasing attention in recent studies. To enhance risk assessments, methods like Gumbel Copula, Monte Carlo simulations, and fuzzy logic help quantify uncertainties. By integrating these uncertainties with a Bayesian Network, which can incorporate expert opinion, failure probabilities are modelled based on variable interactions, improving prediction. The study also emphasises the importance of factors, such as urbanisation, asset deterioration, and adaptation programs in order to improve predictive accuracy. Additionally, the findings reveal the need to consider cascading effects from landslides and climate hazards in future risk assessments. This research provides a reference for methodology selection, promoting innovative and sustainable urban sewer management.
A Study of the Soft Skills Possessed and Required in the Construction Sector
(MDPI (Basel, Switzerland), 2023-02-14) van Heerden AH; Jelodar MB; Chawynski G; Ellison S; Tummalapudi M; Harper C
Soft skills are essential to employability and retention; therefore, if obtained and observed, they can significantly reduce sector-wide turnover. This study aims to investigate and compare soft skills that industry professionals currently possess and soft skills the industry requires and needs to attain. A questionnaire was administered using the RICS database, and 741 respondents participated in this study. Initially, the soft skills possessed and the soft skills required were analysed and compared via descriptive statistics. Furthermore, principal component factor analysis was used to identify the underlying factors and classify the identified soft skills. It was found that there are alignments and evident discrepancies between the actual skills currently possessed and the skills required by these professionals. The soft skills currently possessed by the industry were classified into three groups: (a) Ethics and Professionalism Cluster; (b) Self-Effort Management Cluster; and (c) Management—Leadership and Power Cluster. This was different to the two clusters identified for the soft skills requirements, which were: (a) trait-based cluster—less controllable; (b) training-based cluster—more controllable. The study concludes that there are controllable and less-controllable skills, which need to be possessed and managed in building professionals. Controllable soft skills are easier to train, whereas trait-based soft skills are more difficult to train and possess. The findings of this research are significant as their understanding can be used to help mitigate turnover and guide construction sector professionals to plan for the appropriate skills they require.
A taxonomy of pedestrian evacuation infrastructure for urban areas; An assessment of resilience towards natural hazards
(IOP Publishing Ltd, 2022-01-01) Fathianpour A; Jelodar MB; Wilkinson S; Evans B
Many people in the world live in hazardous environments and are susceptible to disasters. In the time of a destructive event, a resilient community must be prepared to mitigate the event and quickly respond. An effective mitigation plan can lead to fewer fatalities and damages. One of the most critical tasks for mitigation is the evacuation process. Wherein short notice time, overcrowding, bottlenecks in infrastructure and challenging terrain and topography may worsen the situation. Amongst other things, the evacuation process encompasses transportation infrastructures referred to as corridors, signs, pedestrian footpaths, and/or shelter infrastructures for keeping people safe. Evacuation infrastructure can also become damaged after the event; therefore, it's imperative to have a robust assessment of different evacuation infrastructures. This study will investigate the characteristics of the available evacuation infrastructure and outline the general drawbacks. A systematic methodology for reviewing articles has been implemented to understand how vulnerable cities can be more prepared, especially for pedestrian evacuation. An evacuation scoring system for pedestrians will be developed to investigate evacuation infrastructure in terms of different resilience features, such as redundancy, safe to fail, readiness, capacity. The most practical evacuation system will be estimated, with a final output being to provide the features of a successful pedestrian evacuation system for future policy use.
Artificial Neural Network (ANN) model for predicting blast-induced tunnel response in Steel Fiber Reinforced Concrete (SFRC) structures
(Elsevier Ltd, 2025-12-01) Ali M; Chen L; Feng B; Rusho MA; Jelodar MB; Tasán Cruz DM; Samandari N
This study presents an Artificial Neural Network (ANN)-based predictive framework for evaluating the blast-induced response of Steel Fiber Reinforced Concrete (SFRC) tunnel structures. As underground infrastructure is increasingly exposed to dynamic and extreme loading conditions, particularly from accidental or intentional explosions, accurate and efficient prediction tools are essential. In this research, a comprehensive dataset comprising 299 data points was developed, including approximately 120 experimental results from published blast and structural tests, and 179 high-fidelity numerical simulations. This combined dataset ensured both physical reliability and broad coverage of loading scenarios. The model incorporates nine critical input parameters: Peak Overpressure (MPa), Impulse (kPa·ms), Tunnel Diameter (m), Wall Thickness (m), Compressive Strength (MPa), Tensile Strength (MPa), Fiber Volume Fraction (%), Soil Stiffness (MPa/m), and Standoff Distance (m). The target output variable is the tunnel's Maximum Displacement (mm) under blast loading. A three-hidden-layer ANN architecture was optimized through rigorous hyperparameter tuning. The best-performing model, with 16 neurons in each hidden layer, achieved high predictive accuracy, with R² values of 0.983 (training), 0.956 (validation), and 0.948 (testing). Error metrics including RMSE (2.12–3.14 mm), MAE (1.92–3.52 mm), and MAPE (1.95 %–3.12 %) further confirmed the model’s robustness. Validation against experimental data from literature demonstrated excellent agreement, verifying the model's practical applicability. Additionally, sensitivity analysis identified Peak Overpressure and Standoff Distance as the most influential factors affecting displacement. The proposed ANN framework offers a computationally efficient and accurate tool for assessing SFRC tunnel performance under blast loading, supporting the design of safer and more resilient underground structures.
Building Urban Resilience for Coastal Urban Communities: The Surprise of Tsunamis with Consideration of Human Factors
(Routledge, 2024-05-31) Fathianpour A; Jelodar MB; Evans B; Wilkinson S; Toivonen S; Heinonen S; Verma I; Castaño-Rosa R; Wilkinson S
Frequent and intense multi-hazard events are occurring more frequently, making it crucial to prepare in advance and build resilience. Tsunamis, which are massive waves triggered by earthquakes or volcanic eruptions, are particularly devastating and pose significant risks to coastal areas and human life. Therefore, it is essential to be well-prepared for such events. Once the appropriate response to tsunamis is determined, it becomes important to anticipate different scenarios and take proactive measures. The study of evacuation process resilience is considered vital for effective disaster management, with current research and practice placing significant emphasis on the use of simulation models to evaluate tsunami responses. This chapter focuses on the development of an evacuation simulation tool known as MSEM (Micro-Simulation Evacuation Model), which aims to assess the resilience of the evacuation process by considering different evacuation scenarios in the case of tsunami risk. The tool provides insights into long-term planning and suggests improvements for infrastructure and land use. By analysing the simulation outputs, such as survival rates, indicating the number of people who would be safe when the tsunami reaches the shore, the tool helps identify the resiliency level of a city in the face of tsunamis. Napier City, New Zealand, which is vulnerable to various natural hazards, including liquefaction, earthquakes, flooding, volcanoes, and tsunamis, has been chosen as the case study. Based on the city's spatial characteristics and built environment, recommendations are made regarding land use planning and infrastructure upgrades to boost the resiliency level. MSEM can assist decision-makers underscore the need to enhance the transportation system to accommodate mass evacuations effectively. Additionally, it emphasises the importance of educating individuals on the optimal course of action to take during such situations.
Comparing two AI methods for predicting the future trend of New Zealand building projects: Decision Tree and Artificial Neural Network
(IOP Publishing Ltd, 2022-01-01) Zavvari A; Jelodar MB; Sutrisna M
The rise of Artificial Intelligence and Machine Learning in many aspects of construction management has helped this industry to further improve the management, design, and planning of construction projects. This trend happens in many construction sectors, including in New Zealand. Whilst relatively smaller compared to construction sectors in other OECD countries, the construction sector in New Zealand carries a similar degree of complexity and with its own unique characteristics. Various studies showed that AI and ML can be used for analysis of construction data to generate further insights and to predict future trends in construction sectors. However, the AI approaches have their own set of challenges such as complexity, high cost of training, failure, and change. Aiming to better understand the trends and requirements of New Zealand building projects, this study started with a review of the existing AI methods that are currently being applied. Accordingly, compare and evaluate the accuracy of two AI prediction methods. The two methods of Decision Tree and Artificial Neural Network are selected based on their predictive power and accuracy. These methods are conducted by using available historical building data which is available on StatsNZ website. A portion of the data is used for testing and evaluation purposes, and the rest of the data is used for training the AI methods. It was identified that the Decision Tree method did not show suitable accuracy for prediction building consents issued data. In comparison, Artificial Neural Network shows a reasonable range with 95% of confidence level. Therefore, this method is applied for building consents issued in New Zealand.
Digital technologies and data-driven delay management process for construction projects
(Frontiers Media S.A, 2022-12-21) Radman K; Jelodar MB; Lovreglio R; Ghazizadeh E; Wilkinson S
One of the main challenges of construction projects is managing delays; there is still a lot to overcome to reach near-zero delays (mitigation of delays) in all construction projects. Technology and different platforms are applied to support a high volume of data flow acquired from multiple resources during the construction project life cycle; how can these automated and digital progress tracking systems be considered for more effective construction delay management? The aim is to investigate the current state of real-time technologies and their applications and assess how specific attributes of these disruptive technologies can significantly alter delay management in construction industries. Therefore, this study presents a new process-based framework for using technologies with a data lifecycle viewpoint. This research uses a four-step systematic literature review involving identification, screening, extortion-eligibility check, and selection-inclusion. Furthermore, it is followed up by a thematic content analysis on using new technologies to mitigate delays in construction projects. Key trends, themes, areas of concern for research, and limitations identified in previous literature as research gaps and future needs were documented and structured. This work presents a novel process of comprehensive classification of real-time technologies that are being used in the construction industry to acquire data, screen/analyses data, and present information through an Industry 4.0 application: IoT technologies such as sensors, RFID etc., smartphones, planning/scheduling tools (Ms Project, Primavera), and Building Information Modelling (BIM). The developed process-based framework is served as a roadmap to 1) centralise real-time communication between technologies to collect, analysis and presentation data in construction phase, 2) prepare timely reports for project managers to take proper action against those problems delaying project.
Exploring Off-site Construction and Building Information Modelling Integration Challenges; Enhancing Capabilities within New Zealand Construction Sector
(IOP Publishing Ltd, 2022-01-01) Ghalenoei NK; Jelodar MB; Paes D; Sutrisna M
Over the last few years off-site construction (OSC); which is essentially manufacturing different components in a controlled environment, has become popular in the construction industry. This method has the advantages of simplicity, speed, reducing project duration, and minimising construction waste. Therefore, a growing body of literature recognises the importance of OSC to gain better project performance. While OSC has received considerable critical attention, to enhance OSC applications, integrating advanced technologies such as building information modelling (BIM) is essential. There is a lack of research addressing the integration of BIM and OSC, particularly in New Zealand, and few studies investigated the current subject. Therefore, this study focuses on finding the existing OSC and BIM integration challenges within the New Zealand construction sector. The objective of this study has been investigated through literature review and interviews with experts. The common challenges of OSC and BIM integration were identified and classified. Human resources, documentation, managerial, and organisational are the main challenges. This paper is dedicated to exploring OSC and BIM integration in New Zealand, an essential step for the OSC application strategies within the construction sector. This study findings will lend to the construction sector expanding capabilities to improve the status quo and optimise OSC applications through advanced technologies.
Generative AI, Large Language Models, and ChatGPT in Construction Education, Training, and Practice
(MDPI (Basel, Switzerland), 2025-03-15) Jelodar MB; Senouci A
The rapid advancement of generative AI, large language models (LLMs), and ChatGPT presents transformative opportunities for the construction industry. This study investigates their integration across education, training, and professional practice to address skill gaps and inefficiencies. While AI’s potential in construction has been highlighted, limited attention has been given to synchronising academic curricula, workforce development, and industry practices. This research seeks to fill that gap by evaluating AI adoption through a mixed and multi-stage methodology, including theoretical conceptualisation, case studies, content analysis and application of strategic frameworks such as scenario planning, SWOT analysis, and PESTEL frameworks. The findings show AI tools enhance foundational learning and critical thinking in education but often fail to develop job-ready skills. Training programmes improve task-specific competencies with immersive simulations and predictive analytics but neglect strategic leadership skills. Professional practice benefits from AI-driven resource optimisation and collaboration tools but faces barriers like regulatory and interoperability challenges. By aligning theoretical education with practical training and strategic professional development, this research highlights the potential to create a future-ready workforce. The study provides actionable recommendations for integrating AI across domains. These findings contribute to understanding AI’s transformative role in construction, offering a baseline for effective and responsible adoption.
Human-centric integrated change management framework for digital transformation in construction
(Emerald Publishing Limited, 2025-09-08) Bidhendi A; Poshdar M; Jelodar MB; Rahimian F; González VA
Purpose – This study develops a human-centric change management framework to address the gap between building information modelling (BIM) potential and its practical implementation and adoption in the construction industry by focusing on human factors influencing digital transformation success. Design/methodology/approach – A multi-phased methodology was employed, combining systematic literature reviews with advanced network analysis techniques. Two literature review rounds extracted key change management activities and human-centric principles. Social network analysis (SNA) was utilised to quantify relationships and significance within the construction industry context, identifying high-centrality nodes in the network. Findings – The analysis identified training, organisational competency assessment and resource allocation as the most critical change management activities for successful digital transformation, which emerged as central nodes. The study developed a tailored three-phase framework (Strategic initialisation, Operational transformation and Sustainable integration) that enables construction organisations to implement BIM and digital technologies while maintaining focus on human factors. Practical implications include improved employee engagement, reduced resistance to technological change, enhanced organisational readiness for digital transformation and a structured pathway for construction organisations to move beyond current BIM implementation barriers. The framework provides actionable guidance for construction leaders to balance technological advancement with human-centric values, ultimately supporting sustainable digital transformation in the industry. Originality/value – This study offers a novel data-driven approach to digital transformation in construction by quantitatively analysing relationships between change management activities and human-centric principles. The research addresses a critical gap in BIM and digital transformation implementation literature by developing an integrated framework that balances technological advancement with human considerations, helping organisations move beyond current adoption barriers in the AECO industry’s transformative journey.
Information and Communication Technology (ICT) Utilization and Infrastructure Alignment in Construction Organizations
(MDPI (Basel, Switzerland), 2022-03-01) Eliwa HK; Jelodar MB; Poshdar M; Xia B
Information and communication technology (ICT) is one of the important factors that support construction project performance. Various studies have concluded that by aligning the ICT utilization with organizational ICT infrastructure, better performance outcomes can be achieved from the project to organization level. A positive connection between utilization of ICT and project performance has been established. However, the effects of ICT utilization strategy alignment with the organizational ICT infrastructure on construction project performance have not been investigated. This research evaluates and analyzes the importance of organizational ICT infrastructure to improve ICT utilization not just at the project level but also at the level of construction organizations. The main objective of this research is to investigate whether the effect of ICT utilization on project performance may be restricted and affected by its alignment with the ICT infrastructure level in the organization. The analyses of ICT infrastructure, ICT usage, and their associations with project performance are based on case studies of projects and organizations from the New Zealand construction sector. A method of evaluating ICT utilization and ICT infrastructure is proposed. This allows for further detailed examination of the strategic alignment between ICT utilization and organizational infrastructure. The effects of this strategic alignment on project performance are discussed and recommendations for the optimal strategic utilization are provided.
INFORMATION AND COMMUNICATION TECHNOLOGY APPLICATIONS IN CONSTRUCTION ORGANIZATIONS: A SCIENTOMETRIC REVIEW
(ITcon, 2023-04) Eliwa HK; Jelodar MB; Poshdar M; Yi W; Kumar B
The application and research of Information and Communication Technology has exponentially grown in construction and is of a multidiscipline nature. However, there is a lack of investigation into progression of ICT research topics within the construction disciplines and the knowledge domain has not been deeply explored. This research fills this gap using a scientometric review of construction ICT research. Relevant literature from reputable sources are reviewed and classified to create a comprehensive framework for ICT application in construction. Accordingly, a manual review of research titles, as well as abstracts, was conducted. Accordingly, five analysis steps were performed including “Journals Selection, Publication Type and Name” “Citation Analysis”, “Keywords Co-Occurrence Network”, “Cluster Analysis”, and “Keyword time analysis”. A total of 376 research selected for burst detection, co-citation analysis, cluster analysis, keyword co-releases, and ICT application analysis in order to provide a comprehensive knowledge summary of the ICT application in the construction industry. Automation in Construction and Journal of Management in Engineering were identified as the major journals associated with research on the ICT application in the construction industry. Based on the research method, the articles used for scientometric analysis were only selected from Scopus and Web of Science database. Moreover, the study mainly concentrated on the quantitative analysis in regard to articles emerging frequently the knowledge domain, and were used to indicate the trends, timelines and hot topics. This research explores the construction industry body of knowledge by classifying the existing ICT related research, evolutionary trend, providing current status, a comprehensive knowledge framework, and future directions.
Innovative use of low-cost digitisation for smart information systems in construction projects
(MDPI (Basel, Switzerland), 2021-06-24) Jelodar MB; Shu F; Edwards DJ; Aigbavboa C; Ejohwomu O
The low-level application of digital tools and information systems in construction implies that many projects cannot meet modern requirements and standard of work of advanced industries. This study adopts a practical and diagnostic approach to identify key attributes and implementation processes of information systems in construction and logistics. To have triangulation of knowledge, a three-step methodology is adopted. Initially an exploratory analysis of previous literature is per-formed. Secondly a diagnostic analysis of IS applications in construction is achieved by case studies. Finally, expert interviews are performed to examine and consolidate the findings. The study illus-trated practical and innovative applications of low-cost digital tools in IS development and created a framework for documentation of these discrete and mostly unshared practices. It is recommended that the construction sector should embrace more advance technologies to minimise human inter-vention and enhance real-time capabilities. The practicality of how different low-cost and off-the-shelf tools and digital platforms can be combined is discussed and demonstrated. The study provides a clear distinction for practitioners and academics as to what is being practiced in comparison to the dominant theories.
Lean and BIM Implementation Barriers in New Zealand Construction Practice
(MDPI AG, 2022) Likita AJ; Jelodar MB; Vishnupriya V; Rotimi JOB; Vilasini N
The construction sector is lagging behind other industries in terms of efficiency and value achievement. Several building sector initiatives are introduced to improve productivity and project value enhancement. Significant developments such as Lean principles and BIM tools have been applied in the construction sector to achieve efficiency and enhanced productivity while minimizing waste. Lean principles in construction practice are a developing research area, and BIM tools have been widely used in construction project delivery and communications. Although these concepts are beneficial, barriers to their integration and joint implementation have not previously been explored. The paper investigates barriers to implementing Lean and BIM and their interrelationships in the New Zealand construction industry. A three-step triangulation methodology was used in the study to validate the findings. The study used an extensive literature review process, case studies, and expert interviews to consolidate the findings. Barriers to Lean and BIM implementation in construction practice were identified, which include strong cultural resistance, lack of Lean-BIM understanding, resistance to change, lack of knowledge of the Lean-BIM method, and lack of support from senior staff in New Zealand organizations. The effect of implementing Lean-BIM principles is discussed, as are recommendations for implementing the method in construction practice.
Real-time Employee Monitoring Technologies in the Construction Sector - Effect, Readiness and Theoretical Perspectives: The case of New Zealand
(IOP Publishing Ltd, 2022-01-01) Wu RW; Yiu TW; Jelodar MB
Varieties of Real-time Employee monitoring Technology (REMT) are becoming popular and have aroused significant interest in recent years from the construction sector, where the industry explores the use of advanced monitoring technologies to reduce unsafe work behaviours and improve productivity. However, studies identified some concerns about applying these monitoring technologies at construction sites. Consequently, REMT devices and applications have not been well-received for tracking frontline workers. Lack of understanding of REMT, monitoring data protection and privacy management strategy set a barrier for the monitoring technologies to implement in the construction industry. Privacy has become a critical issue for the future digital construction site. This study adopts the literature review and a questionnaire survey, examined the readiness, summarised effects of REMT applied at the New Zealand construction sites, identified the influence factors, and discovered the theories that will potentially explain the factors and address the potential impact. Communication Privacy Management theory (CPM), Equity Theory (ET) and Control Theory of Privacy (CTP) are reviewed, and a theoretical framework is built upon REMT adoption in the construction sector. In conclusion, future studies are recommended for the international construction entities to get ready to adopt the real-time monitoring tools.
Real-Time tracking and analysis in construction projects: A RealCONs framework
(Elsevier Ltd, 2025-09-01) Radman K; Jelodar MB; Lovreglio R; Ghazizadeh E; Wilkinson S
Construction projects increasingly rely on processing vast amounts of data from multiple sources, including consultants (BIM), cloud-based project management platforms (e.g., Aconex), planning departments, construction sites, main contractors, and subcontractors. However, inefficiencies in data acquisition and reliance on manual data entry hinder real-time project analysis, delay notifications, and decision-making. This study introduces the Real-Time Data-Driven Construction Project Analysis Framework (RealCONs) to address these challenges by streamlining data flow and enhancing project performance. A comparative analysis used eight case studies four employing the existing approach and four utilising RealCONs—to assess improvements in data integration, early delay identification, and decision-making efficiency. The results, validated through Earned Value Management (EVM) and Earned Schedule Management (ESM) metrics, demonstrate that RealCONs significantly enhance project forecasting accuracy, schedule adherence, and cost management. Additionally, statistical analyses, including the Shapiro-Wilk test and the Wilcoxon Signed-Rank analysis, confirm that RealCONs outperform the existing approach by reducing data collection and decision-making delays, enabling project managers to implement proactive mitigation strategies. These findings highlight RealCONs’ potential to improve project efficiency, reduce costs, and optimise real-time construction management.
Reducing the vulnerability of tourists to tsunami: challenges for decision-makers
(Springer Nature, 2023-06-17) Fathianpour A; Wilkinson S; Jelodar MB; Evans B
A near source or local tsunami, because of its close proximity to an affected area, cannot usually be predicted soon enough to mitigate many of the risks posed. The limited notice time in local tsunamis poses greater challenges for decision-makers than distant source tsunamis. Tsunamis affect coastal regions, where many of these areas are visited by tourists who often lack adequate knowledge of the hazards of the region. This study focuses on the risks tourists face during a local tsunami and discusses how to best protect tourists. Initially, a thematic literature analysis was performed to identify research gaps. Then, a case study methodology was adopted to obtain an in-depth understanding of how emergency management officials consider the management of tourists in evacuation planning. Napier, New Zealand, was used as a case study because it is a tourist town and vulnerable to tsunamis. Key decision-makers in the disaster management and tourist management sector were interviewed. The results outline three major initiatives that could lead to better tourist management and create better tsunami awareness for tourists. First, the risks posed to tourists can be reduced if emergency management officials collaborate with tourism agencies. Second, developing accurate evacuation simulations can show what would happen to tourists in a tsunami so that emergency management officials can be better prepared, and councils can improve evacuation planning and infrastructure to evacuate tourists and local communities safely. Third, educating tourists about evacuation plans will increase their readiness and enhance their safety.
Systematic representation of relationship quality in conflict and dispute: For construction projects
(2015) Jelodar MB; Yiu TW; Wilkinson S
The construction industry needs to move towards more relational procurement procedures to reduce extensive losses of value and avoid conflicts and disputes. Despite this, the actual conceptualization and assessment of relationships during conflict and dispute incidents seem to be neglected. Via a review of literature, relationship quality is suggested as a systematic framework for construction projects. General system theory is applied and a framework consistent of four layers respectively labelled as triggering, antecedent, moderation and outcome is suggested. Two different case studies are undertaken to represent the systematic framework; which verifies that changes in contracting circumstances and built environment culture can affect the identified layers. Through system reliability theories a fault tree is derived to represent a systematic framework of relationship quality. The combinations of components, causes, and events for two case studies are mapped out through fault tree. By analysing the fault tree the combination of events that lead to relationship deterioration may be identified. Consequently the progression of simple events into failure is formulized and probabilities allocated. Accordingly the importance and the contribution of these events to failure become accessible. The ability to have such indications about relationship quality may help increase performance as well as sustainable procurement.
Tsunami evacuation modelling via micro-simulation model
(Elsevier B.V., 2023-02-15) Fathianpour A; Evans B; Jelodar MB; Wilkinson S
The associated tsunami risks posed to coastal regions in earthquake-prone areas highlight the importance of an effective emergency evacuation plan for these regions. Evacuation simulations have shown to be a valuable tool in assessing the effectiveness of existing evacuation plans and providing solutions for risk reduction, and improving community readiness. This paper describes the development of a micro-simulation evacuation model (MSEM) to assess the effectiveness of local tsunami evacuation processes and test the results with a velocity-based theoretical model. As an agent-based model, the MSEM considers both pedestrian and vehicle interactions and their interactions with each other. The models were used to assess the evacuation scenarios for a tsunami-prone city Napier, in New Zealand. The evacuation process was evaluated based on a local 8.4 Mw earthquake that would trigger a tsunami event, with an evacuation time of 50 min between feeling the initial shake in Napier City and the time of arrival of the tsunami wave. The study outlined within this paper assumes two scenarios: (1) effected population would evacuate by foot, and (2) affected population would evacuate by car, considered to take place during the afternoon at the traffic peak time. The results of the MSEM show factors such as evacuation method, lane and sidewalk capacities, and interactions between individuals affect the individuals' ability to safely evacuate. The MSEM model based on scenario 1 and 2 for Napier City, demonstrated around 85% of residents would reach designated safe area when all evacuating by foot, whilst, only 45% of evacuees will reach their designated safe zone if all individuals attempted to use vehicles as their means of evacuation.