Quantifying Sustainability in Transportation Asset Management: A Review of Environmental, Social, and Governance (ESG) Metrics

Abstract

Transportation asset management (TAM) has traditionally centered on technical performance and economic efficiency. In recent years, however, there has been increasing recognition of the environmental and social impacts of maintenance and rehabilitation (M&R) activities. This paper presents a systematic review of how Environmental, Social, and Governance (ESG) metrics are being incorporated into TAM. Using PRISMA 2020, four major databases were searched, identifying 75 studies since 2010. Environmental metrics were the most developed, especially those measuring emissions, energy use, and material consumption. Social metrics appeared less frequently and are typically used descriptively, including indicators of income inequality, user costs, and equity-focused metrics such as the Benefit Distribution Ratio and Social Return on Investment. Governance was the least explored pillar and is generally addressed through fiscal transparency, risk management, or institutional practices rather than explicit measurable indicators. Overall, the review shows growing interest in integrating ESG into TAM, but the adoption of social and governance metrics remains limited. In particular, governance indicators are rarely operationalized as measurable variables within TAM decision-making, highlighting a critical gap in the literature. This study synthesizes ESG-related indicators used in TAM and provides a structured foundation for future research and more comprehensive sustainability-oriented decision frameworks.

1. Introduction

Transportation assets such as roads, airports, railways, and ports are critical components of a nation’s social and economic development. Among these assets, roads are the most widespread worldwide, as they provide the highest level of flexibility for the movement of people and goods [1]. At the same time, the rapid expansion of transportation systems has placed growing pressure on the natural environment. The transport sector accounts for approximately 23% of global energy-related CO₂ emissions, and emissions in developing regions have grown more rapidly than in Europe and North America, with this trend expected to continue in the coming decades [2].

The sustainability of transportation systems depends not only on expansion but also on the effective maintenance of existing assets. Many countries face significant challenges in preserving aging infrastructure that has exceeded its design life, leading to deteriorating service levels, safety concerns, and increased maintenance costs. Studies emphasize that a proactive, life-cycle-based asset management approach is essential to optimize limited resources, improve resilience, and ensure that transportation networks continue to support economic activity and social well-being [3].

To support decision-making, TAM provides agencies with tools to determine which assets within a network should be preserved, maintained, or rehabilitated. Historically, these assessments have been conducted primarily in economic and technical terms, with transportation agencies relying on methods such as life-cycle cost analysis (LCCA) to compare the long-term efficiency of pavement designs and M&R strategies [4,5]. TAM programs, therefore, focus on the physical condition of the assets, primarily evaluating technical performance metrics in the assessment. However, dependence on purely technical factors in asset management decision-making can lead to significant challenges when transportation owners consider the impact of M&R activities across the user population. For example, agricultural states like Iowa struggle to justify investments in low-volume rural road assets [6].

Given the critical role of transportation infrastructure in sustainable development, it is essential to move beyond purely technical and economic considerations and adopt a more holistic approach to asset maintenance, one that ensures solutions are not only technically sound and economically viable but also environmentally and socially sustainable [7,8]. Early studies aimed to integrate sustainability into decision-making, often beginning with the cost-effectiveness (CE) method, which combines technical and economic aspects. However, the traditional CE approach did not consider environmental consequences. Including environmental costs in the CE analysis has been suggested as a way to overcome this limitation. For instance, Delucchi [9] developed one of the first models for evaluating the social costs generated by vehicles, incorporating environmental considerations into economic assessments. Yet, even this model did not fully capture the environmental impacts of maintenance operations, nor the complexity of related economic estimations.

To address such limitations, researchers have increasingly turned to multicriteria and multi-objective decision-making methods. These approaches compare a set of alternatives based on multiple criteria, assign weights to reflect their relative importance, and then rank them according to how well they satisfy the chosen objectives. Within the TAM field, several applications of these methods have emerged. For example, Wu and Flintsch [10] used a weighted-sum approach to define optimal preservation treatments, and subsequent studies extended this framework by incorporating sustainability metrics alongside traditional technical and economic criteria. In this context, researchers have increasingly used multi-objective optimization approaches that incorporate sustainability, taking into account factors such as agency costs, user costs, greenhouse gas emissions, and various environmental indicators to better support sustainable decision-making [5,10,11,12].

Sustainability has traditionally been defined as development that meets the needs of the present without compromising the ability of future generations to meet their own. This concept emphasizes a balance between social, economic, and environmental dimensions [13,14]. Since then, numerous efforts have been made to expand this concept, resulting in the development of tools and frameworks that aid in measuring and enhancing sustainability in practice. Zuluaga, Karney [15] emphasized that infrastructure decision-making should account for multiple forms of value beyond purely monetary measures, including environmental and social impacts associated with infrastructure systems. One of the most influential is the Environmental, Social, and Governance (ESG) framework, introduced by the United Nations Global Compact (UNGC) to encourage more responsible business and investment practices. Today, ESG is widely recognized as a way to assess not only the long-term sustainability of investments but also their broader social and ethical impact. More recently, researchers have begun applying ESG principles to infrastructure, demonstrating how they can enhance public welfare, foster social responsibility, and promote regional economic development [16]. More specifically, in the context of transportation infrastructure, environmental aspects generally relate to life-cycle impacts such as emissions and resource use, social aspects address accessibility, equity, and user impacts, while governance is reflected in decision-making processes, transparency, and risk management within TAM.

Over the past decade, the enhancement of sustainability in transportation infrastructure has drawn increasing attention from researchers and practitioners alike. Many studies have explored ways to incorporate sustainability metrics into TAM, reflecting a shift toward more balanced and forward-looking decision-making. Leveraging existing works, this paper presents a comprehensive review of the metrics and frameworks applied within the three ESG dimensions—environmental, social, and governance. By examining both quantitative measures and broader rating tools, the review aims to highlight current practices, identify gaps in the literature, and offer insights into how ESG can strengthen the role of TAM in promoting long-term sustainability. To systematically examine the integration of ESG considerations within TAM, this study addresses the following research questions:

RQ1: What ESG indicators have been proposed in the literature related to TAM?

RQ2: To what extent have ESG indicators been quantitatively integrated into TAM decision-making frameworks?

RQ3: Which ESG dimensions are most represented in the existing TAM literature, and which areas remain underdeveloped?

2. Methods

2.1. Paper Selection Methodology

In this study, we conduct a systematic literature review on sustainability metrics with a particular emphasis on Environmental, Social, and Governance (ESG) dimensions. Following the PRISMA 2020 guideline [17], a seven-step search strategy was applied. The process began with the formulation of research questions and the selection of relevant databases and websites. Next, appropriate keywords were identified to ensure a balance between precision and breadth. The third and fourth steps involved defining the inclusion and exclusion criteria for screening titles and abstracts. In the fifth step, the full texts of the selected papers were reviewed. Finally, the last two steps consisted of performing backward and forward searches, examining the references cited in the retrieved papers, and identifying newer studies that have cited them to ensure comprehensive coverage of the literature.

To capture a wide range of academic journal articles, we searched established databases, including Web of Science, ScienceDirect, and Scopus. At the same time, Google Scholar was included to ensure broader coverage of relevant studies. During the keyword selection process, we observed that combining broad terms such as “sustainability,” “environmental,” or “ESG” with TAM resulted in an extremely large and unfocused set of results that would have been impossible to systematically review. Since our objective was to conduct a focused review on sustainability metrics integrated into TAM, we refined our search strategy using the following keyword set:

(“ESG metrics” OR “sustainability metrics” OR “governance metrics” OR “social metrics” OR “environmental metrics”) AND (“Transportation Asset Management” OR “Pavement Management” OR “Infrastructure Asset Management”). The search was then carried out using all possible combinations of these terms, with the search fields limited to titles, abstracts, and keywords to ensure relevance and precision. The same keyword structure was applied across all four databases, and the final literature search was conducted on 18 August 2025.

The next step was to establish inclusion and exclusion criteria. We limited the results to peer-reviewed journal articles and conference papers, including both research and review studies, while excluding books, book chapters, and encyclopedia entries. To ensure the review reflected more recent developments, only studies published after 2010 were considered, as this period marks the growing integration of sustainability frameworks and ESG-related considerations in infrastructure management research and policy discussions, consistent with prior systematic reviews adopting a similar study period [16]. For consistency, we restricted the search to English-language publications. Finally, we did not filter articles based on journal rankings or citation indicators such as the h-index in order to avoid favoring certain outlets or overlooking potentially valuable studies. After gathering the results from all four databases, the next step was to remove duplicate records. Because Google Scholar does not allow filtering by document type during the search, all retrieved records were exported to Zotero (version 7.0.24) reference management software. In total, approximately 238 records were collected and screened using the predefined inclusion and exclusion criteria. We then screened the abstracts to exclude studies that were not relevant to the research scope. The screening process was conducted independently by the first and corresponding authors, and any disagreements regarding study inclusion were resolved through discussion and consensus. Finally, the remaining articles were subjected to a full-text review to ensure their suitability for inclusion in the study.

2.2. Summary of Results

The search process and exclusion steps are illustrated in Figure 1. Since Google Scholar does not provide filtering options to exclude research types, the initial results were limited only by publication year (excluding works published before 2010). After exporting the search results, this database yielded 142 papers. For the other three databases, the results were 28 from Web of Science, 14 from ScienceDirect, and 2 from Scopus. After removing duplicates across all sources, the total number of unique papers was 175. In the next stage, the abstracts were reviewed to determine their relevance, resulting in a total of 101 papers. A full-text review of these 101 papers identified additional exclusions, as some were not aligned with the research focus. This final step resulted in 75 papers being included in the review.

The publication trend can be divided into three phases. Prior to 2014, the field experienced low activity, with only a few papers published annually and minimal fluctuations. In 2015, output increased sharply to eight publications, marking the beginning of a more active period. From 2015 to 2021, the annual number of papers generally remained within this higher range, except for a dip in 2016, indicating a sustained but moderate level of research engagement. The final phase, beginning in 2022, exhibits a notable surge, reaching a peak of 13 publications. In the following years, publication levels stabilize around ten papers annually, aside from a temporary drop in 2023. This trend can be attributed to several global developments, including the adoption of the Sustainable Development Goals (SDGs) in 2015 [18] and the growing integration of sustainability considerations into infrastructure planning and asset management. Overall, Figure 2 illustrates a clear long-term growth in scholarly interest, with particularly rapid expansion more recently.

2.3. Study Coding and Classification

To enable systematic analysis of the selected studies, each paper was coded according to several attributes. Studies were first classified based on the environmental, social, and governance dimensions addressed. The analysis also distinguished between qualitative and quantitative integration of ESG metrics. Qualitative integration refers to studies that discuss sustainability considerations conceptually or propose ESG-related indicators without directly embedding them in analytical models. Quantitative integration refers to cases in which ESG indicators are explicitly incorporated into asset management models, prioritization frameworks, or performance evaluation metrics used to support TAM decisions.

The first part of the analysis focuses on sustainability metrics used in the prioritization and optimization of roads, pavements, materials, and other transportation assets across the three ESG dimensions. This section emphasizes metrics that can be measured and applied quantitatively to improve sustainability outcomes. By capturing these quantifiable aspects, the analysis highlights how researchers and practitioners attempt to embed sustainability directly into decision-making models and optimization processes. The second part of the analysis is a comprehensive examination of studies that primarily present frameworks to guide agencies toward sustainability. Within this body of work, sustainability rating tools play a central role, as they provide a structured set of criteria, performance indicators, and scoring systems that enable agencies to systematically assess the environmental, social, and economic impacts of infrastructure projects.

3. Findings and Discussion

3.1. Descriptive Characteristics of the Reviewed Studies

The analysis of the reviewed quantitative papers shows that there are about twice as many studies focusing on the environmental dimension as those addressing the social aspect. Specifically, 31 studies attempted to measure and incorporate environmental factors, compared with 14 that focused on social factors. This reflects a stronger emphasis on environmental sustainability in TAM, likely because environmental impacts such as emissions, energy use, and resource consumption are easier to quantify. In contrast, social factors are more difficult to measure and incorporate into analytical or optimization models. Another important observation is that only a few researchers have mentioned the governance dimension, indicating that aspects such as transparency, accountability, and institutional participation are rarely considered, even in frameworks intended to guide agencies toward more sustainable practices. Although the number of qualitative studies considering social aspects (21) is relatively close to that of those focusing on environmental aspects (25), this mainly occurs at the conceptual level. It suggests that while social sustainability is increasingly discussed in theory, it has not yet been effectively integrated into quantitative metrics or decision-making processes for M&R. Figure 3 shows the number of publications that focused on environmental and social aspects through both quantitative and qualitative approaches.

3.2. Quantitative Metrics for Optimization and Prioritization

3.2.1. Environmental Indicators

Environmental factors in ESG focus on protecting both human health and the world we live in for both current and future generations. These factors are usually grouped into seven main categories. Emissions and pollution prevention include reducing greenhouse gases, air and water pollution, and even noise. Energy involves how much we consume, how efficiently we use it, and how much comes from renewable sources. Water considers usage, conservation, and recycling. Waste management looks at how we handle everyday and hazardous waste, how much we produce, and how we dispose of it. Biodiversity and ecosystems reflect how our actions affect plants, animals, and microorganisms, especially protected species. Environmental hazards focus on threats like extreme heat, flooding, wildfires, and coastal erosion. Lastly, green innovation and education support the development of eco-friendly solutions and raise awareness about environmental protection [19].

Based on the review of studies that evaluated the environmental impacts of transportation infrastructure and incorporated quantitative metrics into the TAM process, these metrics can generally be categorized into three main groups: (i) emissions and consumption, (ii) material-related metrics, and (iii) index-based approaches. Although the reviewed metrics ultimately serve a common objective, which is to reduce environmental impacts, particularly emissions associated with construction and M&R activities, they differ in how this objective is operationalized. For example, the first category includes metrics that directly quantify emissions and energy consumption. The second category centers on material-related metrics, such as recycled materials and their contribution to lifecycle sustainability performance, and the third category includes composite indices that integrate multiple environmental dimensions into a single measure to support comparative evaluation. This categorization is intended to facilitate the organization and interpretation of the literature by grouping metrics with similar functional roles, rather than establishing strict or mutually exclusive boundaries between categories.

The first group focuses on emission-related indicators, which aim to reduce greenhouse gas (GHG) and carbon emissions or minimize fuel consumption during pavement M&R activities. The second group emphasizes pavement material-related metrics, examining how material selection, recycling, and lifecycle performance influence sustainability outcomes. The third group introduces composite or index-based approaches that capture a broader range of environmental parameters, such as emissions, water and noise pollution, and overall human well-being. It is also noteworthy that most of the reviewed studies concentrated on pavement M&R, as these activities tend to have a more significant environmental impact compared to other asset types such as bridges or ancillary structures.

GHG emissions have been widely adopted as a fundamental environmental metric in studies seeking to enhance the sustainability of pavement M&R programs. Within these frameworks, researchers have developed multi-objective optimization and budget allocation models that explicitly integrate GHG emissions to assess and minimize the environmental impacts of M&R decisions. Specifically, these studies evaluated emissions associated with material production, construction equipment operations, and traffic disruptions during maintenance activities [20,21,22]. In many of these studies, environmental and economic performance are evaluated through the combined application of Life Cycle Assessment (LCA) and LCCA. LCCA is used to assess the long-term economic performance of transportation infrastructure by accounting for agency and user costs, as well as maintenance expenditures over the asset’s service life. However, traditional LCCA approaches generally do not explicitly account for environmental impacts. In contrast, LCA is widely recognized as the primary method for evaluating environmental impacts, as it systematically quantifies emissions, energy use, and resource consumption across all stages of the infrastructure life cycle. While LCCA is more directly applicable in engineering practice and supports cost-effective decision-making, it does not inherently account for environmental externalities unless these impacts are monetized and incorporated into the analysis. As a result, several studies combine LCA and LCCA within multi-objective frameworks to balance economic efficiency and environmental performance in M&R decision-making [5,12].

In addition to GHG emissions, carbon emissions have been used as a key quantitative indicator to evaluate and mitigate the environmental impacts of pavement management strategies. Negishi, Fishcer [23] integrated carbon assessment within a life cycle framework for long-term road planning, combining material data, climate modelling, and digital simulation to evaluate the carbon footprint of various design and maintenance strategies. Torres-Machí, Chamorro [24] included carbon emissions as part of a broader sustainability evaluation framework that balanced technical, economic, and environmental objectives when comparing maintenance alternatives. Likewise, Li, Pitt [25] incorporated carbon emissions into a multi-objective optimization model, where emissions were minimized alongside life cycle agency cost and pavement performance indicators to develop sustainable pavement network maintenance plans.

Fuel and energy consumption were also used across the different studies as important indicators to evaluate the environmental performance of pavement M&R activities. Santos, Ferreira [22] used an LCA framework to calculate energy consumption during all pavement life cycle phases, including material production, transportation, construction, and traffic delays. Santos, Cerezo [11] incorporated cumulative energy demand (CED) from both renewable and non-renewable resources as a quantitative environmental metric within a combined life cycle cost–life cycle assessment (LCCA–LCA) model to identify energy-efficient M&R strategies. de Bortoli, Féraille [26] applied a holistic assessment method to evaluate pavement maintenance policies, using energy consumption and fuel use data to compare alternative maintenance strategies and identify those that achieve lower energy demand and higher resource efficiency throughout the pavement life cycle. Similarly, recent research has applied LCA methods to compare the environmental performance of asphalt and Portland cement concrete pavements, highlighting impacts such as greenhouse gas emissions and fossil fuel depletion across different life-cycle stages [27].

The second key environmental metric explored for enhancing pavement sustainability is the incorporation of recycled materials into pavement construction and rehabilitation [28]. In this regard, Zhao, Goulias [29] found that incorporating Recycled Asphalt Pavement (RAP) materials into highway projects significantly improves sustainability by lowering greenhouse gas emissions, conserving natural resources, and reducing life-cycle costs. Their analysis demonstrated that RAP-based strategies led to a 20.43% reduction in energy use and a 21.99% decrease in greenhouse gas emissions compared to conventional materials. Water consumption was reduced by 12.27%, and life-cycle costs dropped by 23.52%. In a related study, AKBAS and AKIN [30] investigated the use of Recycled Concrete Aggregate (RCA) in pavement base layers and found that mixes containing 50–75% RCA achieved substantial environmental gains. Notably, mixtures with 100% RCA yielded energy savings of up to 310 MJ/m² and a 9.5 kg CO₂/m² reduction in emissions. In addition to their environmental benefits, these RCA mixtures met technical standards, exhibiting strong bearing capacity and durability. Together, these findings highlight the effectiveness of recycled materials as a key component in sustainable pavement design [31].

Beyond material selection, the choice of surface treatments and technologies during the use phase plays a critical role in advancing pavement sustainability. Pulecio-Díaz [32] demonstrated that proper curing of concrete pavements can significantly reduce CO₂ emissions and energy consumption. Also Gilbert, Rosado [33] conducted a long-term assessment of cool pavement technologies, showing that high-albedo surfaces can reduce ambient air temperatures and, consequently, building energy demands. Their study demonstrated that replacing conventional overlays with reflective bonded concrete overlays containing supplementary cementitious materials (SCMs) resulted in measurable global warming potential (GWP) savings over a 50-year period, with SCMs substituting 21–50% of traditional cement. Importantly, the global cooling effect of increased albedo often outweighed the GWP penalties associated with material production. In the context of airport infrastructure, Pittenger [34] focused on optimizing pavement maintenance strategies to minimize environmental, economic, and social impacts. One of the core sustainability metrics employed was raw material consumption (RMC), measured using a life-cycle inventory (LCI) approach. Treatments were ranked by RMC, revealing that shotblasting consumed the least material among shotblasting, microsurfacing, and slurry seal, while asphalt-based treatments exhibited the highest consumption when compared to microsurfacing. This quantification of material intensity enabled more informed, sustainability-focused decision-making in pavement maintenance planning.

The third category of environmental metrics commonly used in pavement M&R focuses on indices that bring together multiple sustainability factors, such as emissions, energy use, and raw material consumption, into single, easy-to-compare scores. One example is the decision support system developed by Santos, Ferreira [12], which combined key environmental impacts across the pavement life cycle, such as greenhouse gas emissions and energy use. This system was later expanded in their 2019 study to include seven different impact categories, including global warming potential, acidification, eutrophication, human toxicity, and resource depletion [11]. These types of metrics make it easier for decision-makers to evaluate and prioritize pavement strategies based on environmental performance. Similarly, de Bortoli, Féraille [26] proposed an Environmental Burden (EB) index that estimates emissions from both construction equipment and vehicles used during maintenance, offering a more operational view of pavement sustainability.

Building on these efforts, Torres-Machi, Osorio [35] introduced the environmental coefficient (β_env,sn), a useful tool for assessing the environmental performance of individual road segments in urban areas. This coefficient was designed to reflect emissions generated during real traffic conditions, helping identify which roads have the greatest environmental impact and where improvements could make the biggest difference. In another approach, Zheng [29] proposed the Life-cycle Sustainability Evaluation Index (LSEI), which examines both emissions and resource use per maintenance strategy, providing a means to compare treatments based on overall environmental efficiency. Finally, Pittenger [34] used a broader scoring method called the Greenroads Score to evaluate sustainability in airport pavement M&R strategy. This score combined various factors, including material use, energy consumption, emissions, and even governance and social equity, providing a well-rounded view of what makes a pavement treatment sustainable.

Table 1. Summary of Environmental Indices Used in Transportation Asset Management.

Metric	Description	Unit	Application in TAM	References
Emissions and Consumption Category
GHG Emissions	Minimization of GHG emissions from materials and construction and traffic disruptions	kg	M&R Optimization/Prioritization, LCA, and LCCA	[5,12,20,36,37,38,39]
Carbon Emissions	Minimization of carbon emissions based on each treatment type due to materials, transportation, and on-site work.	kg	M&R Optimization/Prioritization, LCA, and LCCA	[23,24,25,40,41,42,43]
Energy Consumption	Minimizing total energy use across the lifecycle	MJ	M&R Optimization/Prioritization, LCA, and LCCA	[11,26,37,39,44]
Material Choice
Raw Material Consumption (RMC)	Measures total material mass used per treatment	kg	Material selection	[34]
RAP material usage	Energy and water consumption, life cycle cost, and global warming potential can be reduced significantly by increasing the percentage of RAP.	percentage	Material selection and LCA	[29,45,46,47,48,49]
Cool pavement	Changes in building energy use due to ambient temperature changes	-	Material selection and LCA	[33]
RCA material usage	Increasing the percentage of RCA usage leads to a reduction in CO2 emissions, lower energy consumption, and overall improvement in environmental impacts.	Percentage	Material selection and LCA and LCCA	[30,45,50]
Indices
The life cycle environmental burdens arising	Environmental impacts are obtained by employing the US-based impact assessment methodology, the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts.	Index	LCA	[12]
Roughness speed index (RSI)	The RSI model accounts for the additional rolling resistance of vehicles resulting from pavement surface properties measured in terms of smoothness as well as vehicle efficiency improvements over time.	Index	M&R Optimization/Prioritization	[22,51]
Environmental coefficient (βenv)	By using this environmental coefficient, maintenance alternatives producing lower GHG emissions will receive lower penalizations and thus better evaluations than those alternatives producing higher GHG emissions.	Score	M&R Optimization/Prioritization	[35]
Minimization of seven life cycle impact category indicators	They are as follows: (1) climate change (CC); (2) acidification (AC); (3) eutrophication (EU); (4) human toxicity (HT); (5) abiotic resources depletion (ARD); (6) terrestrial ecotoxicity (TE); and (7) particulate matter	Score	LCA	[11]
Environmental burden	Emissions from construction equipment and on-road vehicles in operating conditions	Index	M&R Optimization/Prioritization	[22,26]
Greenroads Score	Sustainability score combining material use, energy, emissions, equity, governance, etc.	Score	M&R Optimization/Prioritization	[34]
LSEI (life cycle environmental impacts)	Emissions or resource use per M&R strategy	Index	M&R Optimization/Prioritization	[52]

summarizes the environmental sustainability metrics applied in TAM, along with their corresponding definitions and sources.

3.2.2. Social Indicators

The social dimension of ESG is centered on fostering fairness, respect, and inclusivity within organizations and the communities they serve. It emphasizes turning values like diversity, equity, inclusion, and fairness into real, actionable practices rather than just policies on paper. The goal is to make sure that the voices and experiences of all people are considered in how organizations operate. Social factors are typically grouped into three major categories. The first is community and society, which includes protecting community rights, maintaining strong public relationships, promoting public health and safety, and preserving cultural and historical sites. The second is employee relationships and labor standards, which focus on fair workplace practices such as equal pay, diverse and inclusive hiring, safe working conditions, and opportunities for training and advancement. The third area is human rights, which addresses broader global issues, such as reducing poverty, preventing child and forced labor, and improving the overall quality of life. Together, these aspects aim to create more equitable and socially responsible transportation systems and infrastructure [19].

In the context of TAM, research has shown that residents in disadvantaged areas are almost twice as likely to live near poorly maintained roads and can consume up to twice as much excess fuel due to deteriorated pavement conditions [53]. Similarly, low-volume bridges are often overlooked in maintenance funding decisions because traditional asset management programs prioritize structures with higher average daily traffic, leaving smaller or rural communities at a disadvantage [54]. While environmental factors can be quantified through measurable indicators such as emissions or energy use, social equity is more complex to define and measure. Nevertheless, it remains essential to ensure a more equitable distribution of pavement conditions. Incorporating social indicators into TAM frameworks allows decision-makers to capture how infrastructure performance affects vulnerable populations and to promote fairer, more inclusive maintenance and investment strategies [55].

In this regard, several studies have developed quantitative measures to make bridge and pavement management within TAM frameworks more equitable. The Gini index, which is widely used to measure income inequality, has been adapted to evaluate disparities in infrastructure conditions, making it a useful tool for comparing inequality across different regions or populations [56]. Similarly, the Theil index has been applied as a complementary measure of inequality. Both indices have been used with the goal of achieving a fairer distribution of pavement conditions by minimizing the gap between disadvantaged and advantaged areas while maintaining overall network performance when prioritizing M&R projects [20,57]. Okte, Boakye [53] also applied the Gini index and found that travel on excellent roads is not evenly distributed. A relatively small share of the population benefits from a disproportionately large portion of travel on high-quality roads, suggesting inequality in access to well-maintained infrastructure.

In addition to inequality-based indices, user cost has also been employed as a key social metric to enhance social sustainability within TAM frameworks. Although user cost also has an economic dimension, it is considered a social metric in this study because it directly reflects impacts on user welfare, accessibility, and equity. This metric captures the direct and indirect impacts of pavement M&R activities on road users. Chen, Zheng [52] categorized these impacts into three main components: user comfort cost (UCC), travel delay cost (TDC), and traffic accident cost (TAC). Ref. [5], Santos, Ferreira [12] focused on minimizing the present value of total life-cycle road user costs (LCRUC), accounting for expenses incurred during both maintenance operations and regular traffic conditions. They defined these costs across five categories: fuel consumption, oil consumption, tire wear, vehicle maintenance and repair, and vehicle depreciation. Similarly, de Bortoli, Féraille [26] introduced a user time-saving indicator that considers the time lost in roadwork zones and trips to gas stations or garages, along with fuel consumption and wear on vehicle components. Together, these studies emphasize the importance of user cost as a social indicator, highlighting how road conditions and maintenance strategies affect the daily experience and economic burden of road users.

Alternatively, some researchers have focused on developing indices that can help promote social sustainability in TAM. For instance, Torres-Machi, Osorio [35] introduced the Sociopolitical Factor (SPF), which evaluates the importance of each road segment from a social and political perspective, helping agencies prioritize sections that play a vital role in community connectivity or public access. Li, Pitt [25] highlighted that well-maintained pavements not only improve user comfort and safety but also create wider benefits for society as a whole. Similarly, France-Mensah and O’brien [21] developed the Benefit Distribution Ratio (BDR) to assess whether maintenance resources are being distributed fairly, ensuring that investments support more equitable outcomes across regions and user groups.

In the context of bridge management, Gandy, Armanios [58] found that bridges located in disadvantaged communities identified using the Climate and Economic Justice Screening Tool (CEJST), as well as in low-income and Black-majority areas, are more likely to be in poor condition even when accounting for factors like bridge age, traffic volume, and environmental conditions. These findings underscore persistent inequities in how infrastructure is maintained. In a related effort to improve infrastructure decision-making, Miller and Gransberg [54] introduced the Social Return on Investment (SROI) framework to address the challenge of maintaining low-traffic rural bridges. This approach shifts the focus from traditional input and output indicators to measuring the actual social value created, supporting more equitable and impactful infrastructure investments.

Table 2. Summary of Social Indices Used in Transportation Asset Management.

Metric	Definition/Description	Unit	Application in TAM	References
GINI Index	It measures income inequality, and the goal is to minimize the difference between the disadvantaged group and the rest of the network.	Score	M&R Optimization/Prioritization	[20,53,57]
Theil index		Score	M&R Optimization/Prioritization	[53,57]
Benefit Distribution Ratio	Compares the benefits received vs. the needs in underserved communities	Ratio	M&R Optimization/Prioritization	[57]
User Costs	Includes delay, accident, and vehicle operating costs	USD	Budget allocation and LCCA	[52,59,60]
Long-term pavement performance (LTPP)	Pavements in better condition can provide road users with better service and produce more benefits to society. Therefore, given a maintenance plan, its social benefit can be evaluated by the LTPP	Index	M&R Optimization/Prioritization	[25]
Present value of the total life cycle road user costs (LCRUC)		USD	LCCA	[5,12]
Social Return on Investment (SROI)	The SROI is a framework based on ‘social generally accepted accounting principles’ that can be used to quantify and understand the social, economic, and environmental outcomes	Index	M&R Optimization/Prioritization	[54]
Sociopolitical Factor (SPF)	Assesses the relevance of the section of the network in socio-political terms	Index	M&R Optimization/Prioritization	[35]
Road Noise Health Impact Indicator	Indicator of the impact of road noise on local residents	Index	M&R Optimization/Prioritization, and LCCA	[26,44]
Users’ Time Saving Indicator	Time loss for a vehicle	Index	M&R Optimization/Prioritization, and LCCA	[26]
Climate and Economic Justice Screening Tool (CEJST)	Identifies “disadvantaged communities” based on environmental, health, and economic indicators. Used in the Justice40 initiative.	Binary (Disadvantaged/Not Disadvantaged)	M&R Optimization/Prioritization	[58]
Demographic Indicators	Census-based racial and ethnic composition, including majority Black or African American and Hispanic or Latino tracts.	Percentage	M&R Optimization/Prioritization	[58]
Median Household Income	Socioeconomic indicator measuring the median income of households in a given census tract.	US Dollars ($)	M&R Optimization/Prioritization	[58]

presents the range of social sustainability metrics incorporated into TAM frameworks, along with brief descriptions and associated sources.

Although a wide range of social indicators have been proposed, their applicability in TAM depends on both data availability and regional context. Indicators such as the Gini index, the Theil index, demographic composition, and median household income are typically derived from census or publicly available socioeconomic datasets (e.g., the American Community Survey [ACS]). However, these indicators are often context dependent, meaning that factors suitable for identifying disadvantaged communities in one region may not accurately represent social conditions in another. Therefore, their relevance should be carefully evaluated before integrating them into TAM decision frameworks. In contrast, several other indicators, such as user costs, LCRUC, and users’ time savings, are calculated in transportation economic analyses and can be more directly incorporated into life-cycle cost analysis or M&R prioritization models. Other indicators, including Social Return on Investment (SROI), sociopolitical factors, and health impacts of road noise, may require additional modeling or stakeholder input. Finally, when incorporating social indicators into TAM decision processes, appropriate weighting approaches such as multi-criteria decision-making or stakeholder-informed weighting are needed to balance social considerations with engineering and economic objectives.

3.2.3. Governance Indicators

The governance part of ESG is all about how organizations are run and held accountable, ensuring they act ethically and transparently. Good governance builds trust among employees, customers, and stakeholders. Governance factors can be broken into four main areas. Ethics involves establishing clear codes of conduct, upholding organizational values, complying with laws, and preventing bribery, corruption, and discrimination. Strategy and Risk Management focuses on setting up and monitoring internal controls and embedding risk oversight into everyday operations. Inclusiveness ensures that shareholders and other affected groups have a voice and are engaged in decision-making. Finally, transparency is about openly sharing policies, reporting executive pay and incentives, and maintaining clear, honest communication [19].

The governance dimension plays a critical role in ensuring accountability, transparency, and ethical decision-making across transportation infrastructure projects. In the transportation sector, strong governance practices are essential for managing risks, preventing corruption, and promoting fair stakeholder engagement across the planning, funding, and implementation stages. However, despite its recognized importance, the literature reveals a significant gap in incorporating governance considerations into TAM in a quantitative, measurable way. In contrast to the environmental and social dimensions, where numerous indicators have been embedded in TAM processes such as LCA and M&R prioritization models, governance aspects are rarely translated into explicit metrics or standardized indicators that can support decision-making. Because only a limited number of studies on governance were identified in the primary search results, a snowballing approach was used to identify additional studies on governance in infrastructure and project management.

In terms of transparency, Terry [61] examined fiscal transparency and sustainability in transportation infrastructure, finding that revenue-expenditure alignment varied across asset types: water infrastructure demonstrated strong fiscal consistency, roads and active transportation showed moderate alignment, and transit systems displayed weaker revenue linkage. Additionally, several studies have explored governance-related issues through risk management frameworks. For instance, Seyedshohadaie, Damnjanovic [62] proposed a practical approach for developing optimal M&R strategies for transportation infrastructure using the Conditional Value at Risk (CVaR) method. This approach allows decision-makers to account for extreme or uncertain outcomes, thereby improving the resilience and cost-effectiveness of M&R plans—an essential aspect of good governance in infrastructure management.

Governance in infrastructure and project management literature is typically examined through institutional arrangements, oversight structures, and decision-making mechanisms rather than through measurable indicators. For instance, Guo, Chang-Richards [63] analyzed how different governance structures influence risk management in major infrastructure projects. Similarly, Turner [64] examined how governance mechanisms shape decision-making in project-based organizations. Zhang, Fu [65], further investigated project-level ESG practices in architecture, engineering, and construction firms and identified governance-related considerations such as transparency, stakeholder engagement, regulatory compliance, accountability mechanisms, and organizational oversight. Previous governance studies have also emphasized the role of governance in aligning projects with organizational strategy and defining the institutional context in which project decisions are made [66]. Furthermore, governance research frequently focuses on stakeholder relationships and multi-level governance structures linking organizations, projects, and external actors [67]. However, although these studies highlight important governance dimensions, none translate them into quantifiable indicators that can be integrated into TAM decision-support tools such as project prioritization models or life-cycle assessment frameworks.

3.3. Qualitative and Framework-Based Metrics in TAM

In the previous section, the focus was on reviewing quantitative metrics developed to support the prioritization of M&R activities for pavements and bridges. However, a considerable number of studies have adopted a qualitative perspective, either by examining how transportation assets contribute to sustainability or by developing frameworks to guide decision-makers in integrating sustainability principles into TAM. These include sustainability rating tools for infrastructure [68,69,70], process-based sustainability frameworks [71,72,73], and data-driven or digital sustainability incorporation [74,75,76,77,78]. Collectively, these studies emphasize that sustainable TAM requires not only additional indicators but also rethinking underlying decision processes, stakeholder engagement, and institutional structures.

Overall, the state of sustainability integration in transportation planning and asset management demonstrates an increasing recognition but uneven implementation across its core dimensions, reflecting a broader disconnect between high-level sustainability ambitions and their operational integration into infrastructure planning and management practices [79]. Manaugh, Badami [80] found that although most transportation plans acknowledge the importance of equity, few translate these commitments into specific goals or measurable indicators, revealing a gap between conceptual intent and practical application. Ramani, Zietsman [81] noted that U.S. transportation planning has increasingly incorporated sustainability considerations such as climate change, energy efficiency, land use, and public health; however, progress is often constrained by fragmented governance, limited funding, and institutional inertia. Similarly, it has been observed that studies in transportation decision-making tend to emphasize economic and environmental dimensions, while the governance aspect encompassing transparency, accountability, and stakeholder participation remains largely overlooked. Likewise, reviews of social life-cycle assessment point to fragmented methodologies and persistent difficulties in translating social impacts into measurable, decision-relevant metrics [82,83]. These studies suggest that while sustainability is gaining prominence in the field, its operationalization, particularly in relation to equity and governance, remains limited and requires more systematic integration into planning and decision-making processes.

In response to the growing demand for sustainable practices in infrastructure development, several sustainability rating tools have emerged, each emphasizing different dimensions of sustainability [84]. Griffiths, Boyle [85], through an evaluation of four major tools—CEEQUAL, Envision, Greenroads, and the Infrastructure Sustainability (IS) tool—found that over 61 percent of projects utilizing these systems were in the transportation sector. Similarly, Shaw, Walters [86] specifically examined the IS tool, highlighting its applicability across different stages of infrastructure project delivery. More recently, Mehraban, Tsantilis [1] reviewed eight sustainability rating tools used in road infrastructure and reported that approximately 43 percent of the assessment criteria focused on environmental factors, 42 percent on social aspects, and only 15 percent on the economic dimension of sustainability.

Table 3. Summary of ESG Criteria in Leading Sustainability Rating Tools.

	Envision	Ceequal	Green Roads	IS
Environmental	Natural world; climate change and risk	Physical resources; land use and landscape; ecology and biodiversity; the water environment; the historic environment	Material and resources; pavement technologies; environment and water	Using resources, materials, and waste; ecology
Social	Quality of life	People and communities	Access and equity	People and places
Governance	Leadership; resource allocation	Project strategy; project management	Project requirements; construction activities; custom credits	Management and governance; innovation

summarizes the main focus areas of these rating systems across the environmental, social, and governance dimensions.

Beyond the major rating systems already in use, several newer or adapted tools have emerged to fill important gaps that mainstream frameworks often overlook. The SUNRA framework, for example, was created to give European road agencies a common structure for defining and measuring sustainability [68], and later versions have shown that it can be applied effectively at regional and municipal levels [69]. Other tools broaden sustainability assessment into phases that have traditionally received less attention. The pHJKR (Road) system now includes operation-and-maintenance and carbon-related criteria, addressing a notable omission in many international rating tools [87]. Likewise, Environmental Impact Assessment approaches have been tailored to evaluate rural road maintenance through customized indicators developed using Delphi methods [88]. Practical evaluations add further insight: Greenroads-certified projects tend to outperform typical projects, yet self-assessments often overestimate performance and concentrate points in only a few categories [89]. At the national scale, multi-criteria techniques like TOPSIS have been used to select rating systems appropriate to local contexts, with Envision identified as the best fit in Hungary [70].

Beyond the commonly used sustainability rating tools, many researchers have developed customized frameworks to better integrate sustainability into transportation infrastructure and guide more informed decision-making. Myakala and Sabavath [90] designed a comprehensive assessment framework that includes 26 indicators covering environmental, social, technical, economic, material, managerial, safety, and innovation aspects to evaluate the sustainability of rural road maintenance projects. The case study showed that the examined project could not be considered sustainable, pointing to the need for more balanced and systematic evaluation methods. Similarly, Tighe and Gransberg [91] examined eight case studies using seven sustainability impact factors, such as material use, in-service monitoring, emissions, noise, water quality, and energy consumption, and emphasized that incorporating sustainability parameters into pavement management systems can support more effective and evidence-based maintenance decisions. Similarly, other studies have proposed multi-criteria evaluation frameworks for assessing the sustainability of linear infrastructure projects, incorporating environmental, economic, social, technical, and safety indicators to support infrastructure decision-making [28].

Building on this perspective, other scholars have proposed structured and conceptual frameworks that address specific aspects of sustainability. Dokyi, Tookey [92] introduced a framework with 32 sustainability indicators grouped into four key dimensions, namely, environmental, economic, social, and institutional, with a particular focus on the often-overlooked institutional dimension, including governance, regulation, and enforcement. The authors of [93] developed a conceptual performance framework aimed at embedding resilience into road asset management by shifting from traditional performance metrics toward those that capture long-term sustainability and risk-informed investments. In the same direction, Boakye and Okte [94] proposed a framework to quantify the social impacts of pavement management decisions, including indicators such as fatalities in work zones, injuries during construction, and disparities in pavement condition across communities. Finally, Dostál, Anděl [95] developed a methodological framework to help decision-makers identify and prioritize interventions for environmentally problematic and aging transport infrastructure—such as bridges, tunnels, and roads—through risk evaluation, multi-criteria analysis, and stakeholder engagement. Together, these frameworks reflect the growing effort to translate sustainability principles into actionable strategies across all stages of TAM.

4. Discussion and Future Research Directions

The reviewed literature reveals a clear evolution in how sustainability has been approached within TAM. Broadly, the studies fall into two main categories: those that developed quantitative metrics to support prioritization or optimization of M&R activities, and those that proposed conceptual or framework-based approaches to guide more holistic and sustainable asset management. Through these efforts, the three aspects of ESG have received uneven levels of attention over time.

In the early 2010s, the environmental dimension dominated research efforts. This focus can be attributed to both the tangible environmental footprint of transportation activities and the relative ease of quantifying environmental impacts through measurable indicators. Pavement management emerged as the most studied area, largely because pavement construction and rehabilitation have direct and observable environmental consequences such as GHG emissions, material consumption, and energy use. As a result, numerous studies have incorporated metrics such as GHG emissions, fuel and energy consumption, and recycled material use into optimization models and life-cycle assessment frameworks. These approaches successfully demonstrated how environmental indicators could be embedded in M&R decision-making, helping agencies balance technical performance, economic efficiency, and environmental responsibility. By contrast, studies focusing on bridges were fewer and tended to emphasize conceptual frameworks rather than detailed quantitative applications.

In recent years, the social dimension of sustainability has gained increasing prominence. Researchers have begun to examine how infrastructure conditions and maintenance decisions affect communities, accessibility, and social equity. Several studies highlighted disparities in pavement conditions across socioeconomic and demographic groups, showing that residents of disadvantaged or rural areas often experience lower-quality infrastructure and higher user costs. However, only a limited number of studies have moved beyond identifying these disparities to formally integrating social metrics into optimization or prioritization models. Measures such as the Gini index, the Theil index, or the benefit distribution ratio provide valuable insight into inequality, but their use in operational decision-support systems remains rare. This indicates a crucial research gap: while social sustainability is increasingly recognized as essential, its quantitative integration into TAM processes remains limited. Future research should focus on bridging this gap by incorporating social equity measures directly into M&R optimization frameworks, thereby enabling a more balanced and equitable allocation of infrastructure resources.

The governance dimension, meanwhile, remains the least developed and most overlooked across the reviewed literature. Few studies explicitly address governance indicators, such as transparency, accountability, or stakeholder participation. When governance-related concepts do appear, they are often discussed only indirectly within the context of fiscal management, procurement, or risk-based decision frameworks. Even widely used sustainability rating systems—such as Envision, CEEQUAL, Greenroads, and the IS tool—tend to allocate only limited weight to governance criteria, often reducing them to project leadership or management components. This absence of governance integration presents a critical gap, as effective governance underpins the credibility and long-term success of sustainability efforts. Without transparent, participatory, and accountable decision-making processes, the implementation of environmental and social goals risks remaining largely procedural rather than transformative.

Based on these findings, several promising directions emerge for advancing the integration of ESG principles within TAM. Future research should prioritize three key areas: methodological development, indicator operationalization, and practical implementation. From a methodological perspective, future research should first focus on developing comprehensive frameworks that conceptually integrate environmental, social, and governance considerations across TAM processes, including planning, performance evaluation, and decision-making. In particular, such frameworks should examine how different governance structures and institutional mechanisms (e.g., stakeholder engagement and interagency coordination) influence social and environmental outcomes and overall infrastructure decision-making. In parallel, there is a need to develop quantitative decision-support approaches, such as multi-objective optimization models, that allow agencies to evaluate trade-offs among ESG objectives when prioritizing M&R strategies.

From an indicator-system perspective, future research should move beyond qualitative discussions of governance and develop measurable indicators such as transparency scores, stakeholder participation indices, and accountability metrics that can be incorporated into TAM analytical frameworks. Similarly, considerations of the social dimension should move beyond the current reliance on primarily income-based measures and develop more comprehensive indicators that capture additional aspects, such as accessibility and community vulnerability.

From a policy and implementation perspective, future studies should examine how ESG principles, particularly governance practices such as public participation, fiscal transparency, and interagency coordination, can be integrated into transportation agencies’ operational practices. This includes incorporating ESG indicators into decision-support tools, such as pavement and bridge management systems, and embedding them into project prioritization and budgeting processes. In addition, environmental assessments should expand beyond pavements to include other infrastructure assets such as bridges and tunnels, where sustainability impacts remain less explored. Developing a preliminary conceptual framework illustrating how ESG indicators can be systematically integrated into TAM processes could further support both future research and practical implementation.

5. Conclusions

In this study, our goal was to understand how the ESG framework is currently being translated into measurable practice within TAM. To do that, we carried out a systematic literature review of peer-reviewed studies that integrate sustainability metrics into TAM. Using a PRISMA 2020-based procedure across four major databases, we screened an initial pool of 175 records and arrived at 75 studies that directly addressed sustainability in TAM through quantitative indicators, qualitative frameworks, or rating tools.

Across these studies, we identified a rich but uneven set of ESG attributes. On the environmental side, 31 papers attempted to incorporate environmental indicators into TAM, most often through measurable factors such as GHG and carbon emissions, fuel and energy use, raw material consumption, recycled materials like RAP and RCA, and indices that consolidate several environmental categories into a single decision variable. In contrast, only 14 papers integrated social indicators into TAM using quantitative metrics, relying on measures such as the Gini and Theil indices, user cost components, benefit distribution metrics, and tools such as SROI and SPF to capture social value or sociopolitical relevance. None of the reviewed papers incorporated governance indicators in a quantitative way. While quantitative integration of social and governance metrics was limited, the qualitative literature was more active. Twenty studies proposed frameworks or conceptual models for incorporating social aspects into TAM, reflecting growing interest in equity, accessibility, and community impacts. Twenty-five studies presented qualitative or framework-based approaches for environmental sustainability, often through sustainability rating systems or holistic environmental assessment methods. In contrast, only a small number of studies discussed governance, typically in terms of institutional capacity, procurement practices, or stakeholder participation, but without developing operational indicators suitable for TAM decision models.

These findings highlight several notable gaps in the current literature. Environmental sustainability is by far the most developed area, especially within optimization and prioritization models. Social equity, on the other hand, is recognized as important but is rarely treated as an equal priority when agencies make maintenance or investment decisions. Governance shows the widest gap: even though it plays a central role in how infrastructure decisions are made, it is almost never translated into measurable indicators that can be used in TAM models. Instead, governance is usually discussed in general terms such as transparency or institutional processes. Taken together, these trends indicate that current TAM practice still falls short of achieving a fully balanced and integrated ESG-based approach to managing transportation assets.

The results of this review can support several different audiences. For practitioners and asset owners, the study offers a clear, organized catalog of ESG metrics already applied in TAM, making it easier to identify indicators that can strengthen current decision-making processes. Agencies looking to advance their practices can use these metrics to broaden pavement or bridge management systems beyond technical and cost considerations, for example, by incorporating emission-related constraints or equity-focused prioritization rules. For researchers, the review serves as a roadmap of the existing landscape, showing which aspects have been quantified, where social and governance metrics are still lacking, and which indicators hold the greatest potential for integration into future multi-criteria or multi-objective models. This provides a strong foundation for building the next generation of sustainability-focused TAM research.

This study also has several limitations. Most of the studies we reviewed focus on roads and pavements, while far fewer examine other transportation assets, such as bridges and tunnels; therefore, the conclusions of this review primarily reflect findings from pavement-focused studies, and generalizations to other asset types may require additional research. In addition, the findings reflect the institutional and policy settings in which the original studies were conducted, suggesting that some metrics or frameworks may not transfer easily to other countries or governance structures without modification. Our decision to limit the review to peer-reviewed, English-language publications from 2010 onward also means that some relevant literature or earlier conceptual work may not have been captured. Despite these limitations, the synthesis provided here offers a broadly useful reference that can be adapted to a range of asset types and institutional contexts.

Looking ahead, the primary message of this review is that integrating ESG into TAM necessitates more than simply incorporating a few environmental or equity-related indicators at the margins. Future research and practice should develop decision-support frameworks that embed environmental impacts, social equity, and governance quality at the core of prioritization and optimization processes. This involves developing stronger and more scalable metrics for social and governance dimensions, expanding environmental and social assessments beyond pavements to include other critical assets, and examining how governance practices such as public participation, transparency, and risk oversight influence long-term sustainability outcomes.