Infrastructure Agencies Research Articles

Cycle route uptake and scenario estimation (CRUSE): an approach for developing strategic cycle network planning tools

This paper describes an approach for developing strategic cycle network planning tools. Based on our experience developing and deploying the Cycle Route Uptake and Scenario Estimation (CRUSE) Tool for Ireland, we outline the underlying methods, including disaggregation of origin–destination data with the open source ‘odjitter’ software, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that is tested and used by practitioners. Commissioned by the national infrastructure agency Transport Infrastructure Ireland, CRUSE provides estimates of current and potential future cycling levels under ‘snapshot’ scenarios to inform investment decisions. The publicly available results at https://cruse.bike/ enable planners, engineers, and other stakeholders to make more evidence-based decisions. CRUSE goes beyond previous work by: modeling networks at high spatial resolution; simulating multiple trip purposes (social, shopping, personal utility, recreational, and cycle touring), supplementing official origin–destination datasets on travel for work and education; and providing estimates of ‘quietness’ (a proxy for cyclist comfort and route preference) at the route segment level. Three network types—‘Fastest’, ‘Balanced’, and ‘Quietest’—help plan both arterial and residential cycle networks. Workshops with stakeholders were used to inform the development of the tool. Feedback shows that the tool has a wide range of uses and is already being used in practice to inform urban, inter-urban, and rural cycle network designs. The approach is flexible and open source, allowing the underlying ideas and code to be adapted, supporting more evidence-based and effective cycling policies and interventions internationally.

Rapid jail-based implementation of overdose education and naloxone distribution in response to the COVID-19 pandemic

BackgroundPeople incarcerated in jails are highly impacted by the opioid epidemic, and overdose education and naloxone distribution (OEND) is an effective strategy to reduce opioid overdose deaths. This study examines barriers and facilitators of fast-track OEND implementation within the jails in the Wave 1 Kentucky counties of the HEALing Communities Study during the COVID-19 pandemic.MethodsMeeting minutes with jail stakeholders were qualitatively coded using the Practical, Robust Implementation and Sustainability Model (PRISM) as the coding framework. The analysis highlighted the top barriers and facilitators to fast-track OEND implementation within the PRISM framework.ResultsSpace and staffing shortages related to the COVID-19 pandemic, disruptions in interorganizational programming from pandemic-related service suspensions, and a lack of technological solutions (e.g., reliable Internet access) for socially distanced delivery were the top barriers to fast-track OEND implementation. In addition, there were limitations on non-jail staff access to jails during COVID-19. Top facilitators included jail leadership support, the option to prioritize high-risk groups, and the incorporation of OEND processes into existing communications and management software. While the COVID-19 pandemic strained jail infrastructure, jail and partner agency collaboration led to creative implementation strategies for the successful integration of OEND into jail operations. Urban jails were more likely than rural jails to be early adopters of OEND during the public health emergency.ConclusionsUnderstanding the barriers to and facilitators of OEND within jails will improve implementation efforts seeking to curb opioid overdose deaths. Jail leadership support and interorganizational efforts were key facilitators to implementation; therefore, it is recommended to increase buy-in with multiple agencies to promote success. Challenges brought on by COVID-19 have resulted in a need for innovative solutions for implementation.Clinical trial informationClinicalTrials.gov, NCT04111939, Submitted 30 September 2019, https://clinicaltrials.gov/study/NCT04111939?titles=HEALing%20Communities%20Study&rank=1.

Depth profile of Eurocode LM1 Load and its influence on geotechnical structures

This study concerns the impact of the moving loads LM1 on geotechnical structures like embankments and retaining structures related to cut and fill slope problem for road construction and maintenance. In many national standards or recommendations there is a depth dependant reduction factor for live road loads. Bulgarian road infrastructure agency and other institutions do not account for the load reduction with depth, which corresponds to higher cost of the infrastructure itself. This problem appears mainly when calculating the most common 2D tasks, while LM1 and the soil are 3D in nature. This paper presents two geotechnical structures an embankment and a retaining wall, where 3D FEM model is used. Using higher level soil model as hardening soil model with small strain stiffness, the study obtains the reduction of the tandem systems of LM1 and its influence on the slope surface or the structure itself.

Automated potholes detection using vibration and vision-based techniques

Roads serve as vital parts of our infrastructure, providing as crucial conduits for people's mobility and connectivity. However, the growing number of vehicles on the road has resulted in an increase in pavement strain and degradation, which has a substantial impact on the entire riding experience. To achieve a high-quality surface, roadways must be consistently monitored and maintained. In recent years, transportation infrastructure agencies and governments have shown a rising interest in leveraging new technologies to monitor road pavements. This interest derives from the difficult and time-consuming nature of manual and instrumented techniques. Automated technologies have arisen as a response to these issues, notably in recognizing pavement deterioration, such as the common problem of potholes. The objective of this research is to identify potholes using two low-cost automated techniques: a vibration-based method that uses the G-Sensor Logger application and a vision-based way that uses image processing. On the same roads, both approaches were employed and compared, with manual surveying utilized to validate the results. The results showed that vision-based strategies were more effective than vibration-based methods. Finally, although vibration-based analysis is appropriate for routine monitoring, vision-based analysis provides a more comprehensive and in-depth examination of road conditions. These discoveries will help future efforts to better monitor and maintain road surfaces, ensuring a smooth and safe travel experience for everybody.

The role of early childhood development and education (ECDE) in supporting learning and well-being in rural early childhood and primary schools in South Africa

ABSTRACT This paper examines how early childhood and primary schools can be constructed as enabling spaces to improve the learning and well-being of children aged six to nine who live in multidimensionally poor, low-resourced rural communities in South Africa. Quality early childhood development and education (ECDE) can be the catalyst to break the cycle of poverty for many young children in rural areas. A systematic review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart. A comprehensive search strategy using electronic databases and hand searches systematically whittled down an initial database of 30,080 articles to 16 articles for this study. A thematic analysis identified enablers and constraints for supporting children’s learning and well-being across three themes: (1) infrastructure, educational resources and child agency (2) initial teacher education (ITE) and (3) socioeconomic status. The findings and discussion highlight child agency as an enabler to learning and well-being and the structural and pedagogical challenges of implementing ITE curricula specific to rural educational contexts.

Analysis of The Effect of Work Environment and Knowledge Sharing on Employee Performance in Innovative Behavior Mediation

Purpose - This study aims to analyze the effect of the work environment and Knowledge sharing on employee performance by mediating innovative behavior.Design/methodology/approach - The sampling method used was the census method. The research subjects were the Settlement Infrastructure Agency for DI Yogyakarta Region employees, while data retrieval employed a questionnaire for 146 respondents. However, questionnaires only processed data for 100 respondents. Data analysis used Partial Least Square (PLS) inferential, variance-based SEM with SmartPLS Version 3.0 software.Findings - The results showed that the work environment and knowledge sharing had a positive and significant effect on employee performance, the work environment had no effect on innovative behavior or was not proven, knowledge sharing had a positive and significant effect on innovative behavior, innovative behavior had a positive and significant effect on employee performance. The mediation results showed that innovative behavior could partially mediate the influence of the work environment and Knowledge sharing on employee performance. The role of innovative behavior in mediating the work environment and Knowledge sharing had a positive and significant effect on employee performance, so, in this study, innovative behavior could mediate the work environment and Knowledge sharing on employee performance.Research limitations/implications – Respondents who returned the questionnaires to the researchers were not 100% of the total sample population, so the analysis results were not the same as the hypothesis.Originality/value - The novelty of this research is to examine the role of mediating innovative behavior in the influence of KS and the work environment on employee performance in public service employees who have different characteristics when compared to employees of non-public organizations.

Modelling two-dimensional chloride diffusion in repaired RC structures for sustainable maintenance management

Both public and private infrastructure management agencies are responsible for chloride-related corrosion damage to coastal reinforced concrete (RC) structures, which often requires extensive repairs. These repairs are intended to provide serviceability and safety while reducing costs and environmental impact. While there are many repair methods, techniques, and materials available, little is known about their long-term performance and durability. This study examines two-dimensional chloride ingress into square cross section RC columns and their durability using cover replacement techniques with several shapes, thicknesses, locations, and repair times. First, a two-dimensional repair model is developed to simulate these repair strategies and predict their serviceability performance. Two orthogonal concrete replacement strategies (OCR1 and OCR2) and one circular concrete replacement strategy (CCR3) are studied. Next, a method to evaluate and compare maintenance strategies in terms of durability, cost, and environmental impact is also considered. The results of this study reveal that the corners of a column are the most critical areas to evaluate chloride concentration when predicting the time of corrosion initiation and estimating repair time. For long-term maintenance management, the circular concrete replacement strategy is recommended over orthogonal concrete replacement for repair of RC columns exposed to chloride-induced corrosion. The CCR3 strategy requires fewer repairs and achieves higher cost-effectiveness and sustainability compared to the other strategies.

Employees’ BYOD Security Policy Compliance in the Public Sector

ABSTRACT The proliferation of the Bring Your Own Device (BYOD) policy has instigated a widespread change across organizations. However, employees’ compliance toward BYOD security policy remains a challenge. Building on the organizational control, security culture, and social cognitive theory, a research framework for analyzing BYOD security policy compliance factors was developed in this study. To validate the framework, 346 responses were obtained from three Critical National Information Infrastructure (CNII) agencies. Using Partial Least Square-Sequential Equation Modelling (PLS-SEM), the study confirmed that perceived mandatoriness, self-efficacy, and psychological ownership are influential in predicting BYOD security policy compliance. Specification of policy is associated with perceived mandatoriness. Self-efficacy is associated with both BYOD IT support and SETA. Further, security culture was found to have no significant relationship with BYOD security policy compliance.

Resource Allocation Framework for Optimizing Long-Term Infrastructure Network Resilience

With the increase in frequency and severity of extreme weather events, it is essential to incorporate the resilience of infrastructure networks into the decision-making process of resource allocation for maintenance planning. Considering that infrastructure systems are interdependent in nature, the impact of both extreme events and maintenance treatments on infrastructure resilience could be further amplified. Consequently, infrastructure interdependencies should be considered when analyzing the impact of extreme events and maintenance treatments. Additionally, uncertainties (such as uncertainties associated with the occurrence of extreme events and maintenance treatment effects) should also be into consideration. This paper proposes a resource allocation framework that incorporates these factors to optimize long-term resilience of infrastructure networks. The proposed framework capitalizes on integrating agent-based modeling with a double deep Q-network model to support decision-making in resource allocations; it allows infrastructure management agencies to maximize the long-term resilience of infrastructure networks while keeping their physical condition at an acceptable level. The results obtained from the case study show that the proposed framework is effective and can be customized to various local conditions.

Infrastructure project selection automation using non-structural fuzzy decision support system II

In this study, we develop a web-based Decision-Making Tool (DMT) based on a four-year research project in building the proper multiple criteria Decision-Making Framework (DMF) for infrastructure project selection automation. Several challenges in selecting and prioritizing infrastructure projects include poor front-end planning, lack of project funding, improper investment, unsustainable development, regulatory barriers, and poor coordination among stakeholders. The Non-Structural Fuzzy Decision Support System II (NSFDSS-II) is chosen as the main method applied in the proposed DMF since it could resolve complex multi-criteria problems, even without sufficient information provided. When developing the DMT, Agile software development method is used since the development cycle can be run in a light and fast manner with iterative and incremental processes. The DMT is successfully developed by using PHP, HTML, and JavaScript which implement the proposed NSFDSS-II method. We further tested the decision results from the DMT by using eight real past infrastructure projects from relevant infrastructure agencies in Indonesia, such as the Ministry of Public Works and Housing (MPWH), the Ministry of Transportation, and the Local Government. The DMT outcomes were compared with the actual implementation status and evaluated by an independent expert. It was found that the decision results from the developed DMT are in accordance with the real implementation status of evaluated projects. The DMT is recommended to be used for infrastructure project selection automation. However, despite of its fast and accurate result, the DMT should be tested on larger number of infrastructure projects in the future

Cost overruns of Belgian transport infrastructure projects: Analyzing variations over three land transport modes and two project phases

Transport infrastructure agencies are increasingly coping with strong budget constraints, while being highly under pressure to manage and upgrade an infrastructure network that meets the increasing service level expectations of all its stakeholders. Sound infrastructure management therefore includes tight cost control, a long-term vision and budget planning. Belgium has long been structurally underinvesting in infrastructure, but is in recent years trying to clear the backlog. However, it seems that cost overruns for transport investment projects – paid by the same budget as structural maintenance projects – may seriously reduce the number of critical projects to be carried out in the next years, delaying the necessary catching up process as compared to neighboring countries’ state of infrastructure (in the Netherlands, the UK, and Germany). This study analyzes quantitatively the cost developments, from the first publicly released estimates to the final execution costs, of 36 Belgian railway, road and inland waterway projects, representing a total final value of € 1,059,754,416.37 in 2020 prices, or approximately almost 10% of all transport infrastructure investments (in % of CAPEX) in Belgium during the last two decades is captured in our sample. We obtain results on the cost variation itself, and on the phase of the project in which the deviation is higher. We also investigate the transport mode as the independent variable. We find that overruns are higher in the project stage before contract awarding, and that cost overruns for road projects exceed those of rail or inland navigation projects. This case-based quantitative analysis, together with the variables researched in the case analysis, will enable Belgian governing bodies and transport agencies, separately responsible for one mode per region, to learn from these deviations, and to prioritize the need to further explore causes and develop solutions.

Sustainable development goals as accountability mechanism? A case study of Dutch infrastructure agencies

The UN sustainable development goals (SDGs) were adopted by the United Nations as a “universal call to action to end poverty, protect the planet, and ensure that by 2030 all people enjoy peace and prosperity.” These goals prove to have a strong appeal to managers in both public and private sectors. Despite the popularity of the goals, little is known about the consequences (intended and unintended, desired and undesired) of organisations adopting SDGs in their management practices. Therefore, our research question is: “What is the potential role of SDGs as an accountability mechanism?” The following article will study how organisations responsible for technological infrastructures in the Netherlands use the SDGs as an accountability mechanism. To do this, the authors will first provide an overview of the SDGs and how we conceptualize accountability. We will then present our case study methodology before looking at a single case study based on interviews with employees from three organizations running infrastructure in the Netherlands. Based on this case study, we will provide a broader analysis of the key tensions that are becoming apparent when using the SDGs as an accountability mechanism. In conclusion, we will argue that the SDGs may provide a valuable tool to make organizations more accountable to societal needs, however further shifts are needed in the way the accountability mechanisms are designed in order to ensure meaningful accountability.

Infrastructure Financing for Climate Change Adaptation in Australia: Practitioners’ Perspectives

With increased climate-related risks and natural disasters, impacts on infrastructure assets are intensifying. As the need for adaptation actions increase, how finance is used to enable adaptation plays a vital role in the resilience of infrastructure. This research aims to understand how infrastructure adaptation measures are carried out, focusing on how financing is used to aid such efforts. Exploratory interviews with infrastructure and finance practitioners from a broad range of organisations were conducted to understand the dynamics of how infrastructure adaptation occurs. The findings reveal that infrastructure agencies conduct adaptation activities to maintain the serviceability of assets under climate change risks, with most climate financing targeting mitigation rather than adaptation. Most actions are taken at individual asset or agency level with little collaboration across agencies and sectors. The results illustrate a need for a more holistic, systems-level approach to adaptation across the infrastructure sector in Australia.

Investigating pedestrian safety-related behavior in developing countries: Egypt as a case study

Understanding pedestrian behavior and road safety culture is essential for improving traffic safety in developing countries. The primary aim of this study was to investigate the validity for applying the Pedestrian Behavior Scale (PBS) in Egypt to explore the pedestrian behaviors in developing countries and to investigate the relationship of these behaviors across demographic variables. A Pedestrian Behavior Questionnaire (PBQ) was conducted in Egypt containing behavioral items and demographic questions with a total of 567 participants. Exploratory factor analysis (EFA) was applied to assess the number of behavioral factors that express the pedestrian behaviors. The analysis showed that the Egyptian pedestrian behaviors consist of four factors, including transgressions (violations and errors), lapses, aggressive behaviors, and positive behaviors. T-test and ANOVA were conducted to explore the significant difference across gender, age groups and education level. Furthermore, linear regression analysis was conducted to investigate how the examined variables influence the behavioral factors. The current study showed that the Pedestrian Behavior Scale (PBS) is an effective tool for investigating Egyptian pedestrian’s behaviors. This study added a validation for applying the PBS to explore the pedestrian behaviors in developing countries such as Egypt and to understand the variables affecting the pedestrian behaviors. The findings can be used by infrastructure agencies to enhance educational road safety programs and enact appropriate laws, which could reduce the number of pedestrian-related crashes.

Hurricane María and Public Health in Puerto Rico: Lessons Learned to Increase Resiliency and Prepare for Future Disasters.

Background:On September 20, 2017, Hurricane Maria, a devastating Category 5 storm struck the Caribbean Island of Puerto Rico and officially took the lives of 2 975 people although the Harvard University survey in 2018 placed that number much higher at 4 645 [12]. The island’s infrastructure was devastated. Eight months later in May 2020, many vital services including telecommunications, utilities, and health care systems had not yet been repaired.Objectives:To (1) review the immediate public health problems and the longer-term repercussions of Hurricane Maria; (2) identify pre-existing infrastructural deficiencies, health disparities, and problems in governance that may have increased vulnerability and delayed recovery; and (3) offer proposals for preventive measures to increase resiliency and adequately prepare Puerto Rico for future disasters.Methods:Data from the CDC and the Puerto Rico’s Health Department were collected and analyzed. Government publications, news articles, scholarly journal entries and previous research were examined. Interviews were conducted with local citizens and public health professionals. The author’s personal experience is referenced.Findings:The Puerto Rican Electric Power Authority (PREPA) and the Puerto Rico Aqueduct and Sewer Authority (PRASA) both had severely weakened infrastructures before the hurricane as a result of a massive financial crisis that had begun in 2006. These pre-existing weaknesses increased vulnerability and made reconstruction more challenging. Approximately 95% of the cell towers in Puerto Rico sustained significant damage during the hurricane and resulted in almost total loss of cell phone communication [3]. Subpar management of relief efforts by both federal agencies and the local government further hindered recovery, resulting in mass emigration of Puerto Ricans. The public health problems of Hurricane Maria continue to plague Puerto Rico’s citizens and will have long-term consequences.Conclusion:Lack of resilience in Puerto Rico’s infrastructure and government agencies rendered the island highly vulnerable to the detrimental effects of Hurricane María. Improvements to infrastructures and a transition towards a more sustainable way of life could improve Puerto Rico’s preparation and response to future disasters – natural and human-made.

Limited Diversity in risk treatment selection in public infrastructure projects

In public infrastructure projects, risks can emerge quickly due to its external uncertainties and interdependencies among a large number of stakeholders. Scholars still debate whether the current approach of risk management is dynamic enough to safeguard project objectives in such public environments. Because of little empirical evidence that explains how and why Project Management Teams (PMTs) select a specific risk treatment, we aim to characterize risk treatment selection by PMTs in public infrastructure projects. Based on document reviews and semi-structured interviews with PMT members and their executives of a Dutch project-oriented public infrastructure agency, it was found that the diversity in risk treatment selection is limited and risk treatment in public infrastructure projects focuses on controlling risk predominantly through preventive control measures. Although PMTs also intentionally control risk through preventive measures, the decision to do so is often implicitly taken and constitutes an unwitting routine that PMTs seem to have developed due to a risk-averse organizational culture. We conclude with providing directions to improve risk management practices and enable more diversity in risk treatment selection by PMTs in public infrastructure projects.

A methodology for scheduling within‐day roadway work zones using deep neural networks and active learning

AbstractCity infrastructure agencies routinely implement road projects that address various elements of urban infrastructure. The majority of these projects are short‐term in nature (e.g., utility repair), as they are completed in a few hours within 8:00 a.m. to 5:00 p.m. of a workday. The implementation of these projects during working hours, in spite of the inconvenience imposed on road users, helps the agency avoid extra labor costs associated with nonregular working hours. Careful scheduling of these projects can prevent unduly increased travel delays (road users’ interest) while keeping project costs low (the agency's interest). This study presents a bi‐level framework for scheduling short‐term urban road projects that analyzes the implicit tradeoffs between the two stakeholders’ interests. The upper‐level model establishes the optimal schedule considering the project characteristics, such as cost and duration. The lower‐level model captures the dynamic user equilibrium conditions that yield the road users’ path and departure time choices. The bi‐level model is a mixed‐integer program with nonlinear constraints. Recognizing the relatively low efficiency of traditional solution methods, this paper proposes a deep‐neural‐network‐ensemble‐assisted active learning (DN2EA2L) algorithm and adopts a fixed‐point algorithm for solving the bi‐level model. The numerical experiment uses the Sioux Falls network to demonstrate the efficiency of the DN2EA2L, compared to conventional metaheuristic methods. It is shown that travel time increases due to the project implementation during the peak hours can outweigh the agency's saving in wage costs. Further, it is shown that a significant reduction in the road users’ value of time enables the agency to schedule more projects during regular working hours.

Challenges, drivers, and benefits to integrated infrastructure management of water, wastewater, stormwater and transportation systems

Infrastructure systems are known to be interdependent systems; however, infrastructure systems are typically managed individually by agencies in charge of these systems. The existing literature has proposed the concept of an integrated infrastructure management approach, yet this literature has focused on managing infrastructure systems in short-term contexts (e.g., response to natural and human-made disasters). As such, limited understanding exists about implementing an integrated infrastructure management approach in the long-term (i.e., maintenance and rehabilitation). This study aims to explore the challenges, drivers, and benefits of implementing an integrated urban infrastructure management approach by agencies managing urban water, wastewater, stormwater, and transportation infrastructure systems in the long-term. This study qualitatively analyzed 15 semi-structured interviews with stakeholders in the management of infrastructure systems in Chile. It was found that the implementation of an integrated infrastructure management approach is challenged and driven by organizational instead of technical aspects. It was found that the local context where agencies operate represents a challenge for the successful implementation, the willingness to collaborate of infrastructure agencies’ workers represents a driver to implementation, and that benefits encompass agencies and users. Infrastructure agencies can use our findings to account for contextual conditions to successfully implement an integrated infrastructure management approach.

THE ROLE OF DIGITAL TOURISM DESTINATION IN ACHIEVING DIGITAL TOURISM DESTINATION PERFORMANCE THROUGH DIGITAL'S ROLE AS INTERVENING VARIABLES

ABSTRACT
 
 The purpose of this study is to determine and analyze the role of digital tourism destinations in realizing the performance of digital tourism destinations through the role of digital as an intervening variable. This research approach is quantitative with the type of explanatory research. Sources of primary data were obtained using the survey method. This research was conducted in the Thousand Islands Regency, Jakarta before the Covid-19 period. Researchers have surveyed as many as 140 people to tourism actors, but from 140 people who meet the requirements 100 samples. To test the hypothesis using path analysis.
 The research findings show that: (1) digital tourism destination variables (destination image, accessibility, infrastructure, and travel agency) affect the digital role; (2) digital tourism destination variables (destination image, accessibility, infrastructure, and travel agency) do not directly affect digital tourism destination performance; (3) Digital tourism destination variables (destination image, accessibility, infrastructure, and travel agency) through digital roles affect digital tourism destination performance.
 The results of the analysis show that; (1) The success of digital technology that plays a role in providing tourism information contributes to providing a platform on digital technology as a form of providing information for potential tourists, this is effective because the millennial generation relies on various popular platforms that are commonly used in finding tourism information, and have met the criteria basic needs of life before tourism activities are carried out. The ability to share and exchange information between tourism providers and prospective tourists freely has an impact on increasing the number of tourists who; (2) The role of digital is used as a promotion in attracting tourists to visit using; formation of a positive destination image opinion, the availability of good accessibility including modes of transportation; infrastructure, tourist attraction areas that have added value, good travel agency services, so that the final impact can contribute to increasing the number of tourists. The ability to share and exchange information between tourism providers and potential tourists freely has an impact on digital tourism destination performance.
 
 Keywords: Digital tourism destination, Digital tourism destination Performance, and Digital Role.

Predicting Resilience of Interdependent Urban Infrastructure Systems

Climate change is increasing the frequency and the intensity of weather events, leading to large-scale disruptions to critical infrastructure systems. The high level of interdependence among these systems further aggravates the extent of disruptions. To mitigate these impacts, models and methods are needed to support rapid decision-making for optimal resource allocation in the aftermath of a disruption and to substantiate investment decisions for the structural reconfiguration of these systems. In this paper, we leverage infrastructure simulation models and Machine Learning (ML) algorithms to develop resilience prediction models. First, we employ an interdependent infrastructure simulation model to generate infrastructure disruption and recovery scenarios and compute the resilience value for each scenario. The infrastructure-, disruption-, and recovery-related attributes are recorded for each scenario and ML algorithms are employed on the synthetic dataset to develop accurate resilience prediction models. The results of the prediction models are analyzed and possible design strategies suggested based on the resilience enhancement attributes. The proposed methodology can support infrastructure agencies in the resource-allocation process for pre- and post-disaster interventions.