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Purpose

This research explores how digital technologies can improve the environmental (E), social (S) and governance (G) performance of infrastructure projects.

Design/methodology/approach

Grounded in the dynamic capability view (DCV), this study adopted an exploratory qualitative approach. Semi-structured interviews were conducted with infrastructure professionals experienced in digital transformation and Environmental, Social, and Governance (ESG). An inductive thematic analysis was applied to derive insights directly from the data. To interpret and refine the emerging themes in relation to DCV, the research employed an abductive logic through a process of systematic combining allowing theory and empirical data to iteratively inform each other.

Findings

The results revealed that digital transformation improves ESG performance through informed decision making using real-time data, reduces time consumption in manual data processing, enhances system complexities and facilitates local and global standardization of ESG performance. Furthermore, digital technologies have far-reaching impacts on data collection, structuring, reporting and transparency. Environmental (E), social (S) and governance (G) elements of ESG can significantly be promoted using advanced technologies. The drivers and challenges associated with the adoption of digital technologies to improve ESG performance of infrastructure projects are also highlighted.

Practical implications

The findings of this research offer valuable insights to infrastructure professionals aiming to improve ESG performance to achieve net-zero targets, promote sustainable investment and enhance competitive advantages by adopting digital transformation in the era of digital economy.

Originality/value

There is dearth of empirical studies focusing on qualitative research methods that explore the use of digital technologies to advance the performance of infrastructure projects within the framework of ESG.

Infrastructure projects are one of the major drivers of local, regional and national economic development (Ghanbaripour et al., 2025). Infrastructure projects advance economic development by substantially contributing to a country’s gross domestic product (GDP) and offering various benefits such as job creation, economic revitalization, enhanced quality of life, and efficient allocation of public resources (Willar et al., 2020). Infrastructure projects are booming worldwide. By 2030, it is estimated that approximately $57 trillion will be spent in infrastructure projects worldwide to maintain the GDP growth worldwide (Garemo et al., 2015). There are 94 prospective infrastructure projects spanning roads, rail, transport, energy, water, social, and telecom in the Australia and New Zealand pipeline costing approximately $250 billion (Infrastructure Partnerships Australia, 2024). However, infrastructure projects have acquired significant attention from policymakers and researchers due to their substantial societal and environmental consequences (Li et al., 2022). Consequently, infrastructure projects are often referred to as a “double-edged sword” because of their potential to drive significant positive changes while posing challenges that need careful management. Sustainable infrastructure has gained enormous attention in the past decades which aim to reduce negative consequences on environment and enhance economic and social values (Taherian et al., 2024).

Sustainability has become a global issue due to the emergence and need to mitigating climate changes and reducing global temperature (Akomea-Frimpong et al., 2025; Hosny et al., 2022). The infrastructure sector is responsible for emitting 70% of greenhouse gas emissions (Akomea-Frimpong et al., 2024a, b). This necessitates the need for adopting innovative practices in design, construction and operation of infrastructure projects (Sierra et al., 2017). Driven by the 2030 Agenda for Sustainable Development (SDGs) and net-zero targets by 2050, infrastructure projects need to integrate sustainable practices in the project lifecycle (Tumpa and Naeni, 2025). Sustainable infrastructure projects are critical for achieving sustainable development as these projects have substantial and direct impacts on all sustainability indicators (Hosny et al., 2022).

To promote sustainability in infrastructure projects and make responsible infrastructure investments, ESG is highly relevant (Fan et al., 2023). Integrating ESG considerations into investment processes positively influences key parties like communities, governments, and investors. The implementation of ESG not only enhances environmental, social and economic competitive advantages, but it also improves risk-return profile investment. Introduced in 2004 by the United Nations Global Compact (UNGC), the ESG framework examines the impact of projects on the environment, society, and governance from three distinct angles (Qi et al., 2023). The environmental aspect assesses projects’ compliance with environmental regulations and its influence on pollution, energy use, resource management, and waste generation (Ma et al., 2023). Social responsibility covers a wide range of values, including the treatment of employees, community impact, and business partnerships, while fostering economic progress and societal harmony (Opoku et al., 2023). Governance involves transparency towards shareholders, respecting the interests and values of stakeholders, appointing board members, and implementing governance structures, legal frameworks, and policy systems (Lu and Cheng, 2023). ESG performance has received attention from many scholars as a potential concept to improve sustainability in infrastructure projects (Yang and Li, 2023). Introducing this concept to various stakeholders gives an opportunity to address public welfare along with improving social and economic goals (Qi et al., 2023).

The ubiquity of digital technologies is prominent in all sectors, including infrastructure, driving rapid transformation within the industry. With the advent of digital technology in the context of Industry 5.0, several digital technologies are being implemented in infrastructure projects (Wang and Yin, 2022). Digital technologies and sustainability stand as megatrends shaping the economy and society (Brenner and Hartl, 2021). The potential use of digital technologies in advancing sustainable development is considerable (Hoyos Muñoz and Cardona Valencia, 2023). It enables nations to make the most of innovative technologies and data-driven strategies for more efficient resource use (Riesener et al., 2019), lowering carbon emissions (Shang et al., 2023) and enhancing efficiency (Skvarciany and Jurevičienë, 2021). Specific technologies like smart grids, Internet of Things (IoT), energy management systems, and sophisticated analytics are transforming the energy sector by integrating renewable energy and improving energy efficiency (Kharazishvili et al., 2021). Digitalization also improves the monitoring, reporting, and management of environmental impacts, allowing projects to gauge and monitor their environmental performance more effectively (Miśkiewicz, 2020). This helps pinpoint areas needing improvement and implement precise sustainability strategies, improving transparency and accountability in meeting ESG goals.

Beyond environmental aspects, digital technologies are also instrumental in social and governance aspects. It ensures the delivery of inclusive services, ensuring vulnerable groups are included in the digital age (Naeni and Tumpa, 2025). Digital platforms enhance stakeholder engagement, fostering collaboration among citizens, businesses, and governments in tackling societal challenges (Carrasco-Farré et al., 2022; Katsamakas et al., 2022). The significance of ESG performance is growing as investors and consumers increasingly value sustainable and ethical practices. Digital transformation is crucial in aiding the measurement, reporting, and analysis of ESG, offering stakeholders precise and current data on countries’ sustainable development efforts (Wang and Esperança, 2023).

Scholars and industry professionals have paid enormous attention to the achievement of ESG performance by the utilization of state-of-the-art technologies. Some studies explored the relationship between digital transformation and ESG performance and competitiveness (Fan et al., 2023; Luo et al., 2023; Ma et al., 2023; Peng et al., 2023; Zhai et al., 2023; Zhang et al., 2023). However, the majority of those studies were conducted in the context of Chinese infrastructure industry and investigated the relationship quantitatively. The studies tested a range of hypotheses which lack rigor of nuances. Furthermore, a few studies only focused on the environmental aspects of ESG (Diófási-Kovács and Nagy, 2023; Liu et al., 2024; Ren et al., 2023; Xie et al., 2023a) which lack a holistic overview of the phenomenon. Although the literature has paid attention to the relationship between technology transformation and firms’ responsible practices (Christ and Helliar, 2021; Fan et al., 2023; Li et al., 2022; Shan et al., 2019; Zhang et al., 2023), research explicitly examining how digital technologies can influences the ESG performance of infrastructure projects remains limited. Therefore, this study aims to explore the use of digital technologies in improving ESG performance qualitatively in infrastructure projects in Australia. The successful implementation of digital technologies to amplify ESG performance in infrastructure projects requires overcoming barriers and enabling key drivers. However, existing literature lacks insights from infrastructure professionals on these enablers and challenges. This research seeks to address the following questions:

  1. What is the role of digital technology in enhancing the ESG performance of infrastructure projects?

  2. How does digital technology facilitate data collection, structuring and reporting in ESG?

  3. How does digital technology improve the environment (E), social (S) and governance (G) aspects of ESG?

  4. What are the enablers and challenges in adopting digital technology to improve ESG performance in infrastructure projects?

From a theoretical perspective, this research bridges a critical gap by adopting dynamic capability view (DCV) theory to offer a crucial understanding and discourse as to how dynamic capabilities such as sensing opportunities, seizing advantages, and reconfiguring operations can be accelerated by adopting digital technologies to improve ESG performance of infrastructure projects. From a practical point of view, infrastructure project professionals can advance their comprehension of leveraging digital technologies for uplifting ESG performance. Project-based organizations can invest in digital technologies to seize, sense and reconfigure capabilities to improve competitive advantages, hence, augmenting ESG initiatives.

The rest of the paper is organized as follows. Section two presents a thorough review and critical discussion of the relevant literature. Theoretical framework is presented in section three. Section four outlines the research design, including the data collection and analysis process. Results and discussion of the results are discussed in section five and six respectively. Finally, the conclusion, implications and limitations are presented.

In the aftermath of COVID-19, where the most susceptible individuals and nations faced significant challenges (UN Environment Programme, 2021), the importance and objectives of sustainability and sustainable development have gained significance across various scientific fields and societal aspects (Yang and Li, 2023). According to the UN’s Brundtland Commission Report “Our Common Future”, sustainable development is characterized as a process that fulfils the current generation’s needs without hindering future generations’ ability to meet their own needs (Our Common Future, 2021). Similarly, Harrington (2016) describes it as the ability to preserve or enhance the availability and condition of valuable resources or environments over an extended period. Essentially, this approach to sustainable development aims to meet today’s demands while ensuring that future generations have the resources necessary for a comparable quality of life. All definitions of sustainability inherently emphasize a long-term perspective (Babatunde et al., 2020).

The concept of sustainability is often referred as Triple Bottom Line (TBL) – economic, social and environmental – which aims to maximizing social and economic benefits and minimizing environmental impacts (Goel et al., 2019; Srivastava et al., 2024). The environmental aspect focuses on projects’ impacts on the conservation of natural resources, environmental protection and energy consumption (Opoku et al., 2019). The economic aspect involves generating profits, reducing costs, fostering research and development, and promoting overall economic progress. Overall, it aligns with projects achieving more or better outcomes with the lowest possible costs (Tian et al., 2023). The social dimension is concerned with enhancing the living standards of the community, education, and equal opportunities (Stanitsas et al., 2021). Moreover, social sustainability is associated with ensuring health, safety, self-identification, sense of belonging and accessibility (Wang et al., 2018). The interconnection of these sustainability dimensions becomes evident when considering that society forms the basis of the economy, which in turn cannot exist without society, and society itself is reliant on the environment for essential resources (Fibuch and Van Way, 2012).

Sustainability has been gaining urgency in many industries, and its significance is being realized in many sectors, including infrastructure development (Babatunde et al., 2020). Infrastructure projects can make a significant contribution to sustainable development (Alnoaimi and Rahman, 2019; Taherian et al., 2024). An infrastructure project cannot be sustainable if all three aspects of sustainability are taken into consideration when undertaking projects (Bragança et al., 2010). Infrastructure projects have been developed for decades, and they continue to be the focus of nations and their budget allocations in the years to come due to their contribution to socio-economic benefits. Therefore, it is important to find ways to deliver these projects considering sustainable practices (Babatunde et al., 2020).

On the other hand, ESG is typically used to evaluate a company’s non-financial performance which is associated with corporate ethical or social responsibility investment (Lee and Kim, 2022). Non-financial performance refers to the social impacts that are not directly tied to the quantitative financial indicators (Park et al., 2023). ESG is an investment philosophy that is used to incorporate sustainability (Liu et al., 2024). ESG principles originated from the Principles for Responsible Investment (Qi et al., 2023). Investors often use ESG as a measure to evaluate the conduct and prospective economic outcomes of a corporation (Aschauer, 1989). ESG is a tool to evaluate the sustainability of infrastructure and promote sustainable infrastructure investments (Liu et al., 2024; Qi et al., 2023; Ren and Isa, 2023). ESG holds significance for institutional investors in guiding their investment decisions (Duncombe et al., 2023) as driven by the United Nations General Assembly (Liu et al., 2024) and gained enormous attention in mainstream businesses (Ma et al., 2021; Peng et al., 2023). A number of stock exchange companies enforced the disclosure of ESG performance for listed companies which was 24% of all exchanges globally (Kluza et al., 2021). The release of reports that address environmental, social, and governance perspectives is anticipated to become a mandatory requirement in the coming years (Ogachi and Zoltan, 2020). Investors are interested in considering ESG chiefly for two reasons: (1) ESG promotes ethical business practices aligned with corporate social responsibility, (2) ESG contributes to improving portfolio performance, increasing returns on investments and reducing risks on the portfolio level (Broadstock et al., 2021). Additionally, the adoption of ESG practices is associated with better risk and opportunity management, improved employee engagement, transparency in supply chain management, better decision making and overall economic performance (Park and Jang, 2021).

The environmental (E) component of ESG encompasses projects’ commitment to reducing pollution, lowering carbon emissions, optimizing resources, reducing energy consumption and addressing climate changes, thus gaining competitive legitimacy advantages in the environmental realm (Akomea-Frimpong et al., 2025; Ma et al., 2023; Qi et al., 2023). The social (S) dimension of ESG adheres to health and safety, child labor, poverty, workforce management, supply chain dynamics, diversity, and human rights, impacts on neighboring communities, stakeholder engagement and treatment of workers (Luo et al., 2023; Opoku et al., 2023). The governance (G) aspect refers to transparency, governance structure, legal requirements, policy systems, corporate performance, stakeholders’ interests and values (Nirino et al., 2021; Tan and Zhu, 2022).

Worldwide, investment in infrastructure has soared to new heights, influencing the path of development for many years ahead. These investments are primarily motivated by the desire to boost economic productivity (Lee and Kim, 2022). Along with economic benefits, infrastructure projects play a critical role in addressing the fundamental needs of human beings. While infrastructure projects contribute significantly to the economic development of nations (Babaei et al., 2023), there are many challenges which need to be addressed in infrastructure projects such as corporate social responsibility (Ansar et al., 2016; Waddock, 2008) which implies the significance of understanding social responsibility in infrastructure projects (Zeng et al., 2015), while maintaining financial investment, political governance and technological governance (Gregory and Sovacool, 2019). Additional challenges in infrastructure projects emerge from uncertainty in policy and political tensions. Therefore, infrastructure projects demand comprehensive consideration of environmental, social and governance than delivering the product(s) itself (Qi et al., 2023).

Investments in infrastructure need to incorporate principles of ESG to align with the Sustainable Development Goals (SDGs) and the Paris Climate Agreement established in the United Nations Climate Change Conference (COP26) (Akomea-Frimpong et al., 2024a, b). In the past, ESG factors were often overlooked in infrastructure investment due to high costs and reluctance to change (Cherkasova and Nenuzhenko, 2022). However, three main factors have altered this view. Firstly, evolving social and political pressures have highlighted the significant costs of disregarding ESG risks. Secondly, there is a growing recognition that integrating ESG can reduce financial risks and enhance returns. Thirdly, increasing demands from investors and project owners have shifted ESG from being a peripheral issue to a central concern in infrastructure investment (UN Environment Programme, 2021). The implementation of ESG in infrastructure investment has positive impacts on major stakeholders such as society, government and investors (Qi et al., 2023).

Effective execution of infrastructure investments requires governments and businesses to have a strategic plan that enhances ESG performance while minimizing uncertainty (Qi et al., 2023). Given the dynamic nature of the future environment, Haasnoot et al. (2013) recommend that nations and corporations develop a forward-looking vision, undertake immediate actions, and establish a theoretical framework to navigate evolving circumstances. Infrastructure investments can also lead to adverse environmental and social impacts, increase vulnerability to natural disasters, and result in unsustainable debt. Thacker et al. (2019) emphasize the need for researchers to identify both the positive and negative outcomes of infrastructure, consider the interconnections among different infrastructure sectors, and devise strategies that align with their envisioned goals. Some researchers have developed theoretical models to assess the effects of climate change, aiding policymakers in deciding the appropriate location and time to invest (Ferry et al., 2022).

Collectively, digital transformation and sustainability play a critical role to drive societal and ecological changes (Osburg, 2017). Digital technologies have been identified as catalysts to promote SDGs (Camodeca and Almici, 2021; Peng et al., 2023). In order to advance the sustainable performance of infrastructure projects on economic (E), social (S) and governance (G) dimensions, digital technologies are essential (Maqbool et al., 2023; Piyathanavong et al., 2024; Robertsone and Lapiņa, 2023).

In the age of digital revolution, digital technologies make information management easier and more efficient, reduce operational costs and analyze real-time information with accuracy (Mergel et al., 2019; Yoon and Pishdad-Bozorgi, 2022). Adopting digital technologies in infrastructure projects involves implementing cutting-edge digital technologies to revolutionize products, processes, and information systems (Nitlarp and Kiattisin, 2022). This transformation aims to lower costs, increase social responsibility, and meet stakeholder expectations, ultimately enhancing the value of the enterprise (Thacker et al., 2019).

Digital transformation could improve the ESG performance of infrastructure projects in three ways. Firstly, digital technologies allow for more efficient labor division, reducing energy waste and boosting operational efficiency. Real-time control of processes through digital technologies enhances environmental safeguards (Yang and Li, 2023). In operations, digital technologies support green production by utilizing dormant resources, achieving zero carbon and pollutant emissions. Secondly, digital transformation encourages companies to adopt a “product + service” business model with higher value, prompting them to take on more social responsibility (Tuyen et al., 2023). For customers, digital technologies bridge the gap with enterprises, allowing for prompt feedback and continual improvement of products and services, thereby increasing customer satisfaction. For shareholders, it lowers the marginal costs of research and innovation, elevates product and service quality, and improves market reputation, leading enterprises to focus more on their image and brand reputation. Lastly, digital transformation reinforces corporate governance by enhancing production, management, and information processes. Regarding data circulation, digital technology refines the information system in multiple dimensions, removes internal communication barriers, and facilitates data mining and application and the dissemination of current knowledge (Su and Li, 2021).

Digital technologies can enhance the performance of ESG in project settings. One of the widely discussed technologies is Building Information Modelling (BIM). BIM has been applied to improve environmental (E) sustainability (Mandičák et al., 2024). Abdel-Tawab et al. (2023) empirically demonstrated that BIM contributes to the overall sustainability of infrastructure projects. Technology such as BIM, with its detailed design and model, can highlight the use of inefficient resources, which helps promote waste reduction and recycling, thus contributing to overall resource optimization. BIM, with its high efficiency, can analyze energy-related data, which can assist project professionals in reducing carbon emissions. Collectively, digital technologies can help amplify economic and environmental sustainability (Tabejamaat et al., 2024). Similarly, blockchain can monitor excessive extraction of resources, utilization of natural resources, and manage waste, thus addressing environmental sustainability (Kouhizadeh and Sarkis, 2018).

Digital technologies can contribute to improving the social (S) dimension of ESG. One of the vastly discussed areas in the extant literature is the relation to tracking the supply chain to improve the procurement process for infrastructure projects (D'Eusanio et al., 2019). Social sustainability in the context of the supply chain ensures that procurement decisions required for infrastructure projects do not have negative repercussions on human rights and labor practices. Digital technologies can track the supply chain to ensure ethical procurement (Chong et al., 2017; Goel et al., 2019). BIM allows the integration of detailed information about materials and resources used in project work. By tracking the supply chain and analyzing detailed information about the materials, professionals can get insights into the ethical procurement of resources (Yevu et al., 2021). The detailed information also portraits the ethical labor practices present in the supply chain and gives an understanding of the exploitation of labor, thus improving the detection of modern slavery in the supply chain (Chong et al., 2017; Goel et al., 2019). Similarly, blockchain technology can drive ethical procurement, which is aligned with SDG12 (Responsible Consumption and Production) while reducing the administrative burden and costs and improving efficiency (Arabian et al., 2022; Govindan et al., 2024).

The governance (G) element of ESG is aligned with decision-making, transparency and stakeholder engagement. Digital technologies can help project professionals make decisions effectively as they can provide them with real-time information with a great level of detail (Martínez-Ferrero and Lozano, 2021). Organizations are incumbent to collect information in relation to tracking SDGs and digital technologies can present the information to project professionals, thus helping them make informed decisions based on authentic data (Peng et al., 2023). In addition, with the advancement of digital technologies, project professionals have the opportunity to assess various options and make decisions with transparency and accountability (Maheshwari et al., 2023; Peng et al., 2023). Instead of relying on past experiences entirely, project professionals can make data-driven decisions (Li et al., 2021). Digital technologies such as BIM can present stakeholders with relevant information to make decisions, which is key to improving ESG performance (Abdel-Tawab et al., 2023).

A great deal of transparency can be assured as technologies provide transparency in data gathering and processing with accuracy (Ionescu et al., 2021). The elimination of manual processes contributes to enhancing transparency as it records every transaction of data processing and management (Xu et al., 2019). In addition, transparency reduces the possibility of greenwashing behavior (Li and Ding, 2024). Blockchain makes the transaction process decentralized, providing greater transparency (Mahmudnia et al., 2022).

Furthermore, stakeholder engagement is key to achieving SDGs and ESG requirements. With the help of digital technologies, stakeholders can access relevant information, which enhances communication among stakeholders (Bican and Brem, 2020). An integrated platform for data collection, structuring and processing from various stakeholders can improve the efficient flow of data among stakeholders, thereby improving their engagement (Diófási-Kovács and Nagy, 2023; Sraml Gonzalez and Gulbrandsen, 2022). Digital technologies such as BIM have been widely used to improve stakeholder engagement (Babatunde et al., 2019; Kumar and Padala, 2024; Oke et al., 2023). BIM can be used to share critical information which can be useful for stakeholder engagement. Similarly, digital technologies can present stakeholders with design, cost and emissions, which can be used to make informed decisions regarding the sustainability performance of projects.

While digital technologies promise to achieve ESG performance in project settings, the implementation of digital technologies across the project lifecycle to advance comprehensive improvement in ESG performance is not an easy endeavor. One of the prominent drivers of adopting digital technologies in infrastructure projects is project managers’ leadership styles (Afzal and Tumpa, 2024; Bag et al., 2021; Schneider, 2018). The transformation requires novel ideas and competencies, thus urging a need for an innovation leadership style (Al Amri et al., 2021; Lee et al., 2018). Moreover, a new skillset is required for project managers aiming to embrace digital technologies. Al Amri et al. (2021) called for new skillset which is essential for adopting digital technologies, including (1) marketing orientation, (2) open innovation, (3) complexity and (4) talentism, (5) digital receptivity. Furthermore, project professionals need to be familiar with digital technologies and their applications (Benešová and Tupa, 2017; Longo et al., 2017). Therefore, training programs should be offered as project professionals with robust training and qualifications demonstrate a better understanding of digital transformation than those without training (Al Amri et al., 2021).

In order to promote digital technologies in achieving ESG performance, organizations need to implement stringent policies (Bag et al., 2021) and engage stakeholders throughout the transformation (Bang and Andersen, 2022; Tian et al., 2023b; Waqar et al., 2023). Policies need to be enforced at project, team, industry and individual levels. A holistic approach and the support from the senior management levels are key to navigating the challenges associated with digital technology implementation and accelerating ESG performance (Tian et al., 2023b). Another critical enabler to promote digital technology in ESG requirements is stakeholders’ engagement and willingness to embrace digital transformation. The change requires all stakeholders to come forward, participate, and cooperate in the process (Tian et al., 2023a, b).

On the contrary, some challenges impede the application of digital technologies in elevating ESG performance in infrastructure projects. Lack of awareness about the benefits offered by digital technologies among project professionals and stakeholders is a commonly mentioned barrier (Oke et al., 2023; Piyathanavong et al., 2024). Additionally, the lack of support from senior managers is another barrier to digital technology endorsement (Rahim et al., 2022). Financial constraints, clinging to legacy software and attitudinal barriers contribute to the list (Agyekum et al., 2022; Alam et al., 2019). Therefore, organizations along with key stakeholders need to team up to accelerate the drivers and address challenges to successfully embrace digital technologies to improve ESG performance of infrastructure projects.

The Dynamic Capability View (DCV) theory serves as the theoretical foundation for this research. DCV is particularly suited to environments undergoing rapid change (Teece et al., 1997). It is an extended version of the Resource-Based View (RBV) theory which is appropriate for studying unpredictable environment that requires constant reconfiguration of organizational capabilities (Bromiley and Rau, 2016; Wang et al., 2016). RBV is unable to showcase how resources need to be developed, integrated and coordinated in a dynamic market condition (Smith et al., 2014) which can be addressed by DCV (Majhi et al., 2023).

Dynamic Capability View (DCV) theory has been one of the frequently used theoretical framework to explain how ESG and sustainability drive sustainable development goals through its capacity to sense opportunities, seize competitive advantages, and transform operations (Dang et al., 2024). Dynamic capabilities imply “an organization’s ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments” (Teece et al., 1997, p. 8). In order to facilitate dynamic transformation in organizations, dynamic capabilities play an essential role (Wijayarathne et al., 2024). Dynamic capabilities are crucial for advancing innovation and promoting green business strategies (Chen, 2024). Digital technologies, being a key enabler to enhancing dynamic capabilities, are pivotal to expedite digital transformation resulting in increased productivity and performance (Aghimien et al., 2023). For instance, digital transformation strengthens ESG performance by fostering dynamic capabilities such as green innovation, social responsibility, and operational excellence (Su et al., 2023). Various aspects of digital technologies enhance dynamic capabilities such as automation and data analytics to improving ESG performance (Wei and Zheng, 2024). Furthermore, dynamic capabilities moderate the relationship between digital technologies and improved ESG performance (Lee et al., 2024).

While other management theories such as institutional theory and stakeholder theory unveil how regulatory, legislative pressure and stakeholder expectations drive ESG adoption in project-based organizations, these theories lack to explain organizations’ internal strategic capabilities to advance ESG performance of infrastructure projects, thus remain unexplored. This research adopts the DCV theory as a theoretical lens to unravel how digital technologies can be promoted to accelerate ESG initiatives in infrastructure project-based contexts.

The DCV theory was initially developed to explore organization-level success and failure (Jiang and McCabe, 2021). According to Chowdhury and Quaddus (2017), DCV refers to “identifying strategic organizational processes, reconfiguring resources, and the identifying the path to follow to attain competitive advantage” (p. 186). Barreto (2010) argues that dynamic capabilities enable organizations to systematically solve problems, ensuring time-sensitive and market-oriented decision-making. By analyzing dynamic capabilities of an organization, professionals can better understand the complexities of systems characterized by market volatility and rapid technological advancements (Masteika and Čepinskis, 2015). In such environments, the use of dynamic capabilities becomes essential (Fainshmidt et al., 2016). These capabilities are typically embedded in organizational processes (Teece et al., 1997), and their integration is crucial for achieving strategic advantages (Jiang and McCabe, 2021). Previous research demonstrated that dynamic capabilities contribute to innovation to gain a competitive advantage (Eisenhardt and Martin, 2000; Zott, 2003) and promise a prolonged survival of an organization in a changing environment (Majhi et al., 2023).

Dynamic capabilities are classified into three categories: sensing, seizing and reconfiguring abilities (Jiang et al., 2018; Teece, 2014). An organization’s ability to identify opportunities to meet customers’ needs in a dynamic and volatile environment is referred to as sensing ability. These skills allow an organization to detect the disruption in the early stages and act immediate actions to adapt (Chatterjee et al., 2024; Kähkönen et al., 2023; Teece, 2007). Seizing ability translates to integrating the changes to satisfy customers’ demand in a changing environment (Pattanayak et al., 2023). Organizations need to recombine a specific number of resources to successfully complete the tasks. This ability is known as reconfiguring ability (Fainshmidt et al., 2016). According to DCV, organizations can adapt to changing environment by reconfiguring and transforming its capabilities (Kyläheiko et al., 2002).

In a dynamic business environment, there is an intense competition among organizations (Liang et al., 2022). In order to encounter rapid and evolving challenges, organizations need to adopt innovative practices for the survival of organizations. In order to achieve a sustained competitive advantage, organizations need to respond and react to changing environments (Chatterjee et al., 2024). In recent years, emerging technologies have started to impact an organization’s digital transformation (Ghosh et al., 2022). Digital technologies such as Big Data, the Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML) can seize opportunities – which are the dynamic capabilities (Mendonça and Andrade, 2018). The revolution is moving from Industry 4.0 to Industry 5.0, which requires the seamless integration of man and machine through the utilization of digital technologies (Nahavandi, 2019). By adopting digital technologies, a large amount of data can be collected and analyzed in real-time for decision-making (Sisinni et al., 2018).

This study aims to understand how digital technologies influence ESG performance of infrastructure projects and gain a competitive advantage in the long run. In this study, we propose that digital technologies as dynamic capabilities can help improve ESG performance by capturing, and analyzing data, thus advancing decision-making processes. Digital technologies would be able to improve environmental, social and governance dimensions of ESG in infrastructure projects in the competitive market environment. Through embracing digital technologies, projects can stay ahead and gain competitive advantages.

Dynamic technology applications seek to optimize business processes, reduce production costs, expand market share, and accelerate R&D, enabling more efficient, flexible, and innovative operational models and commercial value (Gao et al., 2023). Digital technologies decrease pollution emissions, increase energy efficiency, and optimize resources through waste management (Liu et al., 2023; Wang and Shao, 2023). Digital technologies can reduce environmental impacts by managing, monitoring pollution emissions, optimizing emission processes, and controlling emission concentrations (Shang et al., 2023). Organizations can also anticipate energy consumption trends and fluctuations by applying digital technologies (Matthess et al., 2023). Digital technologies facilitate firms to monitor and manage resource recovery, optimize the recycling process, improve the efficiency and quality of recycling, thereby reusing resources (Kurniawan et al., 2023).

Applying the framework of the DCV theory, we argue that digital technologies can enhance ESG performance through capitalizing dynamic capabilities: sensing, seizing and reconfiguring. Digital technologies can sense real-time data monitoring in the context of environmental impact, social conditions, and governance processes. This process allows infrastructure project professionals to identify opportunities and risk early in the process. Seizing capabilities ensure that digital technologies are integrated into the project life cycle effectively. Integration of digital technologies allows professionals to achieve improved environmental performance, social performance through effective stakeholder engagement and project teams’ performance and governance objectives by tracking supply chain. Finally, digital technologies can contribute to reconfiguring capabilities by adjusting strategies to unforeseen circumstances.

To answer the research questions, we adopted a qualitative research method which is mainly applied to studies which are exploratory in nature (Flick, 2022; Mani et al., 2016). Semi-structured interviews were adopted to unpack how digital technologies can be utilized to improve ESG performance of infrastructure projects. Semi-structured interviews allow to get insights into the interviewees’ perspectives (Goodell et al., 2016). It enables interviewers to explore interviewees’ experiences which provide different phenomena of experienced and perceived interest (McGrath et al., 2019). In addition, semi-structured interview format allows the interviewer to ask the same questions to the all potential interviewees while allowing the opportunity to contextualize the findings and to get room for the clarification (Adams, 2015). Before conducting interviews, ethics approval was obtained from the first author’s affiliated University’s Ethics Committee. Participants’ anonymity and confidentiality were maintained before analyzing the collected data. Potential participants were provided with an information sheet and consent was obtained prior to conducting interviews. Furthermore, the participants were assured that their experiences and perceptions shared in the interviews will not have any impact on their current employment. Their right to withdraw from the interview was also confirmed prior to the commencement of the interviews.

A purposive sampling technique was adopted for this research to identify potential interviewees who are considered proficient in knowledge and expertise about the phenomenon under study (Etikan et al., 2016). The following criteria were applied to identify potential interviewees (1) having experiences in utilizing digital technologies for ESG requirements, (2) possessing experiences in sustainability and/or ESG in the context of Australian infrastructure projects. The authors identified the potential interviewees by using their personal network and LinkedIn as this platform is widely used by project professionals for networking, career progression and showing expertise (Sauer et al., 2024). Professionals meeting the inclusion criteria were invited to participate in the interviews. Interview recruitment and analysis occurred concurrently, consistent with iterative qualitative methods. A total of 67 invitations were sent to eligible infrastructure professionals. Upon sending out the 67 interview invitations, data analysis suggested that the data saturation was reached. Theoretical saturation was considered reached after 17 interviews, at which point additional data no longer yielded novel insights or contributed to thematic elaboration (Guest et al., 2006; Saldaña and Omasta, 2016). Therefore, sending invitations to infrastructure professionals stopped after 67 invitations. The small sample size in this study is consistent with the principles of exploratory qualitative research, where depth of insight and thematic richness are prioritized over numerical generalizability (Goodman and Kruger, 1988; Humphreys et al., 2011). This study also draws from abductive reasoning and the logic of “systematic combining” (Dubois and Gadde, 2002), whereby empirical data, theoretical framing, and coding processes evolve iteratively and simultaneously. This approach is particularly suitable for under-researched and complex domains like digital ESG integration in infrastructure, allowing the development and refinement of emergent themes through engaged analysis of a smaller but information-rich dataset. Following established precedents in qualitative ESG and digital technology research, data saturation was achieved at 17 interviews, with no novel themes emerging from additional data collection (Atkins et al., 2023; Guest et al., 2006; Rieg et al., 2023). Previous studies focusing on digital technologies, ESG and sustainability achieved data saturation with seventeen or a smaller number of interviews (Efthymiou et al., 2023; Holland et al., 2024; Jonsdottir et al., 2022; Khan et al., 2020).

All the interviewees met the inclusion criteria to be interviewed and possessed the required knowledge and expertise to answer the research questions. A wide range of roles in relation to sustainability and ESG were covered to get insights into the different perspectives on the use of digital technologies in improving ESG performance of infrastructure projects. Table 1 lists the demographic information of the interviewed participants.

Table 1

Participants’ demographics

Participant noGenderYears of experienceRole
P1Female11 monthsSustainability and Strategy Consultant
P2Male40 yearsDirector
P3Female6 yearsESG Senior Research Manager
P4Male2 yearsSpecial Advisor on ESG & Sustainability
P5Male16 yearsDirector
P6Male5 yearsESG and Sustainability Principle
P7Male13 yearsDirector
P8Female1.5 yearsPrinciple–Engagement and Change Advisory
P9Female1.5 yearsESG Advisor
P10Male6 yearsSenior Environment and Sustainability Consultant
P11Male20 yearsDirector Digital Transformation
P12Male4 years 7 monthsManager Environment
P13Male5 monthsSupply Chain Sustainability and Energy Lead
P14Male1 year 3 monthsManager ESG Implementation
P15Male8 monthsManaging Director ESGI
P16Female6 yearsSocial Impact Advisor and Managing Director
P17Male2 years 10 monthsTeam Lead Environmental and Sustainability/Practice Lead Sustainability

An interview protocol was developed before commencing data collection through semi-structured interviews. The questions were designed to get insights into the implications of digital technologies in improving ESG performance of infrastructure projects. The aim was to extend the current understanding and knowledge on the use of digital technologies to improve environmental (E), social (S) and governance (G) performance of infrastructure projects. The initial questions in the interview protocol were designed to get demographic information and details in relation to their involvement in the application of digital technologies in infrastructure projects. Since ESG may be a new concept to some project professionals, general questions regarding the association between digital technologies and ESG performance were explored in the beginning of the interview. The next section of the questions was around the application of digital technologies in the following themes: (1) automation of ESG data collection, (2) structuring ESG data, (3) data consistency, accuracy and reliability, (4) transparency in ESG reporting and disclosure. This section was finally preceded by enablers and barriers in the adoption of digital technologies in ESG performance improvement. All the interviewees were provided with the same questions to answer, and follow-up questions were asked when required. Finally, the interviews were given an opportunity to express any final thoughts.

Semi-structured interviews were conducted online via Zoom. Zoom was selected for convenience including avoiding the need to find a suitable location for interviews, saving time and cost, needing to arrange an interview recorder and ease in data transcription (de Villiers et al., 2022; Shapka et al., 2016). All the interviews ranged between 45 min to an hour. The interviews were video recorded to improve the interaction between the interviewees and the interviewer. Figure 1 shows a step-by-step data collection process.

Figure 1
A flowchart showing steps from interview preparation to data analysis in a sampling and interviewing process.The flow begins with a text box labeled “Interview questions preparation”. From “Interview questions preparation”, a downward arrow arises and points to a text box labeled “Identification of interviewees through purposive sampling”. From this box, a dashed line connects to another box titled “Interviewees' inclusion criteria”, with the following pointers: “(1) Having experiences in utilizing digital technologies for E S G requirements”, “(2) Possessing experiences in sustainability and or E S G in the context of Australian infrastructure projects”. From “Identification of interviewees through purposive sampling”, a downward arrow arises and points to a text box labeled “Interview invitation sent”. From “Interview invitation sent”, a downward arrow arises and points to a text box labeled “Semi-structured interviews execution via Zoom until data saturation”. From “Semi-structured interviews execution via Zoom until data saturation”, a downward arrow arises and points to a text box labeled “Data analysis”.

Step-by-step process of data collection

Figure 1
A flowchart showing steps from interview preparation to data analysis in a sampling and interviewing process.The flow begins with a text box labeled “Interview questions preparation”. From “Interview questions preparation”, a downward arrow arises and points to a text box labeled “Identification of interviewees through purposive sampling”. From this box, a dashed line connects to another box titled “Interviewees' inclusion criteria”, with the following pointers: “(1) Having experiences in utilizing digital technologies for E S G requirements”, “(2) Possessing experiences in sustainability and or E S G in the context of Australian infrastructure projects”. From “Identification of interviewees through purposive sampling”, a downward arrow arises and points to a text box labeled “Interview invitation sent”. From “Interview invitation sent”, a downward arrow arises and points to a text box labeled “Semi-structured interviews execution via Zoom until data saturation”. From “Semi-structured interviews execution via Zoom until data saturation”, a downward arrow arises and points to a text box labeled “Data analysis”.

Step-by-step process of data collection

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Interviews were transcribed using the Zoom auto-transcription functionality. The transcriptions of the interviews were available within 24 h after the interviews were conducted. Data analysis was conducted using an inductive thematic approach. An inductive thematic approach for semi-structured interviews is frequently employed in research, which is exploratory in nature (Di Maddaloni and Sabini, 2022). Thematic analysis is deemed appropriate for this research. Previous qualitative research used thematic analysis for analyzing data following Braun and Clarke’s (2006) six steps: data familiarization, code generation, theme identification, review of themes, defining and naming themes and final report production (Braun and Clarke, 2006). Prior to thematic analysis, the interview transcripts were de-identified and identified as P1, P2, P3 … P17 to protect anonymity. The data analysis followed a systematic six-step process to ensure rigor and clarity. In the first step, the first author carefully reviewed the complete recordings of the interviews and manually cross-checked the transcripts against the recordings. This meticulous process ensured transcription accuracy and facilitated a deep familiarization with the data, enabling an initial understanding of the content. In the second stage, the transcripts were uploaded onto NVivo, where coding was conducted inductively. This allowed for an open exploration of the data, free from preconceived categories. From the interview transcripts, 203 initial codes (referred to as first-order concepts) were identified. The third stage focused on the transition from coding to sub-themes generation, guided by the approach of Gioia et al. (2013). These codes were then grouped into 24 sub-themes, providing nuanced insights into the research questions. In the fourth stage, the 24 sub-themes were further refined and synthesized into seven overarching themes. These themes directly addressed the study’s four research questions, ensuring alignment between the data and the study’s research questions. The fifth and sixth stages involved finalizing the names of the themes and drafting the final report. The detailed data analysis process is shown in Figure 2. The detailed coding and theme development process have been shown in  Appendix 1. The trustworthiness of themes was maintained through the use of credibility. Member checking was conducted through discussion among the authors (Nowell et al., 2017). Any disagreement was resolved among the authors through discussion. A record of the collected data on Microsoft Excel was maintained to improve the transparency and consistency of the process, thus achieving audit trails of qualitative data.

Figure 2
A flowchart showing transcript processing, coding, thematic development, and links to four research questions.The flow begins with a text box labeled “Interview transcripts available within 24 hours via Zoom functionality”. From “Interview transcripts available within 24 hours via Zoom functionality”, a rightward arrow arises and points to a text box labeled “De-identification of transcripts”. From “De-identification of transcripts”, a rightward arrow arises and points to a text box labeled “Inductive thematic analysis through Braun and Clarke’s (2006) method”. A downward arrow from this box leads to the next box labeled “Listening to the recordings to rectify errors in transcripts” and “Full understanding of the data and context”. From this box, a leftward arrow arises and points to a text box labeled “Inductive data coding via N Vivo”. From “Inductive data coding via N Vivo”, a leftward arrow arises and points to a text box labeled “203 initial codes as first-order concepts”. From “203 initial codes as first-order concepts”, a downward arrow arises and points to another box labeled “203 initial codes clustered into 24 sub-themes”. From “203 initial codes clustered into 24 sub-themes”, a downward arrow arises and points to a text box labeled “7 main themes emerged from 24 sub-themes”. From “7 main themes emerged from 24 sub-themes”, seven arrows extend downward, each pointing to one of the seven theme boxes placed horizontally along the bottom section of the diagram. The first arrow points to the text box labeled “Theme 1-Benefits of incorporating technology in E S G initiatives”, and a further downward arrow from this box points to a cloud-shaped label reading “R Q 1”. The second arrow points to the box labeled “Theme 2-Technology in data collection, structuring and reporting”, which connects downward to a cloud-shaped label reading “R Q 2”. The third arrow points to a box labeled “Theme 3-Technological impacts on environmental aspects of E S G”. The fourth arrow points to the box labeled “Theme 4-Technological impacts on social aspects of E S G”. The fifth arrow points to the box labeled “Theme 5-Technological impacts on governance aspects of E S G”. From the fourth, fifth, and sixth box, an arrow extends downward and points to a cloud-shaped label reading “R Q 3”. The sixth arrow points to the box labeled “Theme 6-Success factors for adopting technology in E S G implementation”. The seventh arrow points to the box labeled “Theme 7-Challenges for adopting technology in E S G implementation”. From the sixth and seventh box, an arrow extends downward and points to a cloud-shaped label reading “R Q 4”.

Data analysis process

Figure 2
A flowchart showing transcript processing, coding, thematic development, and links to four research questions.The flow begins with a text box labeled “Interview transcripts available within 24 hours via Zoom functionality”. From “Interview transcripts available within 24 hours via Zoom functionality”, a rightward arrow arises and points to a text box labeled “De-identification of transcripts”. From “De-identification of transcripts”, a rightward arrow arises and points to a text box labeled “Inductive thematic analysis through Braun and Clarke’s (2006) method”. A downward arrow from this box leads to the next box labeled “Listening to the recordings to rectify errors in transcripts” and “Full understanding of the data and context”. From this box, a leftward arrow arises and points to a text box labeled “Inductive data coding via N Vivo”. From “Inductive data coding via N Vivo”, a leftward arrow arises and points to a text box labeled “203 initial codes as first-order concepts”. From “203 initial codes as first-order concepts”, a downward arrow arises and points to another box labeled “203 initial codes clustered into 24 sub-themes”. From “203 initial codes clustered into 24 sub-themes”, a downward arrow arises and points to a text box labeled “7 main themes emerged from 24 sub-themes”. From “7 main themes emerged from 24 sub-themes”, seven arrows extend downward, each pointing to one of the seven theme boxes placed horizontally along the bottom section of the diagram. The first arrow points to the text box labeled “Theme 1-Benefits of incorporating technology in E S G initiatives”, and a further downward arrow from this box points to a cloud-shaped label reading “R Q 1”. The second arrow points to the box labeled “Theme 2-Technology in data collection, structuring and reporting”, which connects downward to a cloud-shaped label reading “R Q 2”. The third arrow points to a box labeled “Theme 3-Technological impacts on environmental aspects of E S G”. The fourth arrow points to the box labeled “Theme 4-Technological impacts on social aspects of E S G”. The fifth arrow points to the box labeled “Theme 5-Technological impacts on governance aspects of E S G”. From the fourth, fifth, and sixth box, an arrow extends downward and points to a cloud-shaped label reading “R Q 3”. The sixth arrow points to the box labeled “Theme 6-Success factors for adopting technology in E S G implementation”. The seventh arrow points to the box labeled “Theme 7-Challenges for adopting technology in E S G implementation”. From the sixth and seventh box, an arrow extends downward and points to a cloud-shaped label reading “R Q 4”.

Data analysis process

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The results of the research are discussed below. Table 2 shows the main findings of the research.

Table 2

Main findings of the research

ThemesSub-themesMain findings
Benefits of technology in ESG initiativesInformed decision making
  1. Data driven decision making

  2. Efficient decisions made on experiential data

  3. Better access to data by relevant stakeholders

Time saving
  1. Elimination of manual processing of data collection from stakeholders, analysis and processing

  2. Streamlining and expedition of data

Better management of system complexity
  1. Effective management of project complexity through state-of-the-art technologies such as AI

  2. Efficient handling of system intricates

  3. Technologies’ capacity to surpass human abilities to process big data

Global comparative assessment through technology
  1. Comparative analysis of ESG outcomes on the local and global scale across different industries

  2. Technologies abilities to analyze large dataset and perform analysis to meet ESG outcomes

Technology in data collection, structuring and reportingAutomated data collection
  1. Automated data collection from operations, stakeholders, shareholders and platforms

  2. Use of an integrated platform to reduce challenges in coordination

Data structuring and reporting
  1. Conversion of data in a useful format

  2. Pulling data from various sources to a single platform

Data transparency
  1. Data transparent and accessible to relevant stakeholders

  2. Improved reliability and credibility

  3. Advanced data integrity and safeguarding

Data accuracy
  1. Less human intervention

  2. Elimination of manual data entry

Technological impacts on environmental aspects of ESGReduction in embodied carbon emissions
  1. Measurement of carbon in buildings and other infrastructures

  2. Tracking carbon emissions through advanced technologies

Energy saving
  1. Technology to monitor carbon usage and control energy consumption

  2. Use of various technologies to reduce carbon emissions and improve energy efficiency

Technological impacts on social aspects of ESGStakeholders’ feedback
  1. Technology to collect customers’ and employees’ feedback

  2. Monitoring stakeholders’ satisfaction

Supply chain tracking
  1. Tracking products’ origin, manufacturing process and potential issues around modern slavery

  2. Tracking supply chain in real-time

Employees’ accounts
  1. Accounts on employee’s details

  2. Details on diversity and inclusivity

Employees’ health, safety and well-being
  1. Tracking safety incidents

  2. Managing employees’ retention rights, well-being and experiences

Technological impacts on governance aspects of ESGEffective governance mechanism
  1. Efficient tracking and evaluating information, aligning goals, and resource requirements

  2. Improved stakeholder engagement

Success factors for adopting technology in infrastructureCompatibility with existing system
  1. Aligned with the pre-existing system

  2. Simple, easy and less time consuming to use

Company’s appetite
  1. Willingness to adopt

  2. Intention to drive change

Training arrangements
  1. Training and qualification about digital technologies

  2. Training in data sharing, data ownership and security

Collaborative approach
  1. Collaborative approach among stakeholders

  2. Stakeholders’ participation in digital transformation

  3. Stakeholders’ willingness to embrace change

Challenges for adopting technology in infrastructureCost implications
  1. Investment of a large amount of money

  2. Cost associated with ongoing cost and subscription fees

Lack of awareness among organizations
  1. Lack of proper understanding about ESG and technological implementation

  2. Confusion among ESG and sustainability

Lack of government legislation
  1. Lack of government legislation

  2. Lack of clear pathway set by governments

Resistance to change
  1. Resistance to new technologies

  2. Organizational culture

  3. Cling to legacy software

Lack of resources with adequate skills
  1. Scarcity of resources with adequate skills

  2. Pre-occupied with many tasks

  3. Lack of technical competencies and expertise

All interviewees unanimously acknowledged the benefits of incorporating digital technologies in ESG initiatives in infrastructure projects. Technologies have the potential to provide a range of benefits ranging from facilitating informed decision making to saving time by replacing manual work to improving the management of system complexity to enabling comparative analysis on a global scale.

5.1.1 Informed decision making

One of the commonly highlighted advantages mentioned by all interviewees pertains to digital technologies’ capacity to facilitate data-driven decision making. According to the interviewees, decisions made based on data through digital technologies are significantly more efficient than decisions made on experiences. By leveraging digital technologies, stakeholders can get access to project’s critical information which helps them understand project dynamics in more advanced ways. Making good decisions is linked to cost saving and more successful projects as wrong decisions can cost money and delay projects. P2 stated that:

Technology is making huge inroads and huge advances because it enables people to have real time data to make quick decisions rather than having to make decisions based on no data and based on gut feel and experience. So that's the big change. Those decisions will be better informed, and they'll hopefully be better decisions and with big projects that run very fast.

Real-time data accessibility is critical for understanding project scenarios. Digital technologies have the capacity to capture real-time information, process data efficiently, and deliver information to professionals at their fingertips. This process enhances transparency in data capturing and processing, dissemination, thus helping project professionals make informed decisions. Furthermore, it enables project professionals to track progress in achieving SDGs more realistically which leads to improved governance of an organization. P3 mentioned that:

More access to information, so they'll be able to make better informed decisions. It'll enable them to track. So say, you've got an organization that's committed to 7 of the sustainable Development Goals. It'll enable them to attract much more efficiently how they're going across those, so you'll be able to align your goals with your finance.

While all interviewees agreed to utilize digital technologies as a decision-making enabler, it should not take over the role of human judgement. While digital technologies are capable of providing data-driven insights, efficiency, and analytical capabilities, it lacks nuanced understanding, empathy, and contextual awareness inherent in human decision-making. Digital technologies should be viewed as a supportive tool rather than a substitute for human judgment. P7 confirmed that: “No, definitely, not and, as I said before, it’s got to be data driven, it can’t be technology making the decision”.

5.1.2 Time saving

Many participants emphasized the importance of saving time when it comes to the adoption of digital technologies. They pointed out that manual processing of data collection and analysis is time consuming which requires collecting information from various stakeholders. Interviewees noted that data collection, analysis and reporting currently conducted manually. Many participants noted the prevalence of Excel and similar software. Manual process entails filling out various word documents and generating reports which is a time-consuming endeavor. Eliminating manual interfaces is seen as a means to save time and enhance overall efficiency. The consensus is that the implementation of digital technologies not only accelerates data processing but also mitigates the laborious aspects of traditional manual workflows. Furthermore, participants stressed that a wealth of information is readily available to companies through the integration of digital technologies. P10 stated that:

There's a huge amount of paperwork that's involved. So, if everything was quicker and automated, and it would give you more time to figure out these sustainability outcomes and figure out how they're going to be implemented and talk to stakeholders and get the broader project to understand the implications.

The adoption of digital technologies streamlines and expedites the process. The use of digital technologies helps professionals seamlessly communicate information to stakeholders and shareholders. Digital technologies not only accelerate the data processing process, but it also makes the dissemination of information efficient. Automated data collection and processing facilitates swift and smooth transmission of critical information to relevant stakeholders and shareholders. P3 explained that:

There are so many individual players who've got a component for Green Star. There's one person managing it … But you can also put your architectural drawings up, and the architect can do that, and the engineer can do their component, and the water calculator can be filled in by the right person, and it all seamlessly comes together in a way, and technologies enable that.

5.1.3 Better management of system complexity

Several participants highlighted the effectiveness of digital technologies in managing system complexity. Infrastructure project is a complex system with a number of elements interplay in the system. Artificial intelligence (AI), in recent years, has proposed numerous benefits in dealing, navigating and comprehending system intricacies in a way which surpass the capacity of individuals. There is a vast amount of data available in projects which is referred to as big data’. Project professionals have less capacity to analyze, handle and interpret large data sets which can be easily performed by various digital technologies or AI. Digital technologies can optimize decision making by dealing with various elements. Digital technologies can help overcome human limitations and optimize system complexity. P6 mentioned that:

AI can deal with ESG system complexity in a way that humans and acumen processes tend to not carry through. So, I think there's some really interesting opportunities around embracing the ability to think and plans it within the context of systems and complex systems.

5.1.4 Global comparative assessment through technology

A few participants highlighted the instrumental role of digital technologies in performing comparative analysis of ESG outcomes on the local and global scales across industries. Without the assistance of digital technologies, it is considered extensively time consuming to analyze and compare ESG outcomes at local and global levels. Digital technologies can aid analyze, compare large datasets efficiently, perform ongoing monitoring of variations in ESG outcomes and take necessary actions as required. P2 mentioned that:

Without technology and technology's ability to do the data analysis and comparisons, those reports would take forever to produce. So, the technology enables the data to be processed very, very quickly and meaningfully.

With the advent of digital technologies, it is possible to compare organizations’ ESG outcomes against the benchmark set for projects in the infrastructure sectors. However, some participants expressed the concern regarding the lack of a universally accepted standard. P1 said:

We need some sort of standardization in order for all of us to do kind of same. And you know, your data being similar to my data or my results being similar to some other organization. It is not like super standard right now.

Among the interviewees, there was a shared understanding that actual success in enhancing ESG outcomes hinges on the use of actual measurement of environmental, social and governance data. The critical role of data management depends on its effectiveness of measurement. Therefore, all interviews acknowledged the role of digital technologies in data collection, structuring and reporting ESG outcomes. They collectively mentioned that “What is measured get managed” (P2).

5.2.1 Automated data collection

All participants highlighted the importance of automated data collection when it comes to aiming to boost ESG performance in infrastructure projects. Preparing an ESG report requires a wide range of data collected from various stakeholders, shareholders and platforms. As discussed above, collecting data manually or lacking an integrated platform can make the data collection process enormously challenging and time consuming. Therefore, all participants acknowledged to have an integrated platform for data collection. The data which is collected by maintaining a log can be done by setting up a machine which automatically collects data.

The concept of dashboard is discussed by some interviewees. Projects have a range of stakeholders who is required to input data for preparing ESG reporting. Instead of collecting data from each of the relevant stakeholders and managed by one person, if data can be collected on a single platform where data comes together in a seamless manner, that would facilitate the process to a great extent. Digital technologies can help bring all data to a single platform which is easily managed by the required person. P10 highlighted that:

I guess that would obviously help heaps if everyone had a dashboard that they could just plug their relevant information into the platforms.

Digital technologies can help get real-time information from the operation itself. Digital technologies such as digital twins and Building Information Modelling (BIM) can collect a lot of information from the project itself. P5 stated that:

Those systems (BIM) are going right through into operation. All it does is create a long-term piece of information so that you can see what's happening on the way through.

A government project can have many contractors; inputting data from different contractors is a challenge task. Digital technologies are critical tools because a central platform can be maintained so that each of the entities needs to be fed into and report into at a certain point rather than sending their data to someone in who then needs to input the data into the system. Digital technologies can help pull the data into reporting frameworks. P8 highlighted that

A government project, it could be 50 different stakeholders, all of whom need to demonstrate how they're striving towards that target. So, when you're talking about that level of data collection off that many entities, technologies are critical tool because you can have a central platform. Each of those entities needs to feed into report at a certain point rather than sending their data to someone in government who then needs to input the data into the system.

5.2.2 Data structuring and reporting

Several interviewees highlighted the role of digital technologies in structuring data by consolidating data from various sources. There is a consensus among participants regarding the use of data which can be pulled by technologies from various scattered formats and converted into a usable format. Moreover, technologies have the capacity to scan large data without the need to navigate through various files. Technology, particularly AI has the ability to present integrated data in a single platform. P3 mentioned that:

Having a platform where we can pull data together and the tech behind that, that's taking the data and all the different formats and trudging through Pdf and grabbing the bit of information that you need and putting in a format where it's useful. This is the cleaning of that data. Will be extraordinary.

5.2.3 Data transparency

More than half of the interviewees mentioned that digital technologies can increase the transparency of ESG related information significantly as individuals with security clearances can scrutinize and verify the information. Transparency also improves the reliability and credibility of the data. Relevant stakeholders have access to real-time information which improves the transparency of the data. P1 stated that:

I would say, once you have it available in a data set. It's just that availability of someone else being able to access that data within security clearances. That just improves transparency. The utilization of digital technologies introduces an additional layer of protection to the data ensuring its integrity and safeguarding it against unauthorized access or tampering.

5.2.4 Data accuracy

Majority of the participants highlighted that digital technologies improve data accuracy as there is less human involvement. Automated systems will improve data accuracy as it does not require an individual to enter or collect data manually, thus improving accuracy and human error. P7 highlighted that:

Usage is a good example. So, we're using X amount to kilojoules per whatever the unit is at a time. And then it varies. It goes up significantly, and you can go, well, there's a problem. And so that way, you can then address that that problem ultimately. You can use AI then to have to look at it. It will tell you where there's a variation.

While majority of the interviewees concurred on the use of digital technologies in terms of providing transparency and accuracy on the data, they emphasized the need of human intervention for cross-checking information, identifying potential inaccuracies, identifying conflicting information and missing parts. A periodic review and audit of information is required to address anomalies and discrepancies. P5 mentioned that:

It needs to be an intervention of people who are responsible and held responsible at various levels. You can't have technology taking them over and doing it because it will drift, head off and do some things. It will be inaccurate. Won't be a true representation of what's going on. So, I think people need to be involved, all levels and people need to be responsible, not just involved, but responsible.

All interviewees shared a common understanding that environmental aspects of ESG gets highest attention in infrastructure projects. The consensus revolves around two aspects (1) reduction in embodied carbon emissions (2) efficient saving of energy.

5.3.1 Reduction in embodied carbon emissions

Majority of participants underscores the need for improving environmental aspects of ESG by reducing the embodied carbon emissions. Interviewees believe that digital technologies help measure carbon in buildings and is considered as a valuable tool for tracking and reducing carbon footprints in the future. P3 mentioned that:

If your goals to be net-zero, for your building an hourly measurement of the carbon that your electricity is using will be much handier for you than an annual average measure, because it's not actually a measure of the carbon in your building.

Furthermore, carbon emissions can be reduced by introducing advanced project processes, material innovations and sustainable design. In building projects, a range of digital technologies are being integrated to reduce carbon emissions. The implementation of advanced technologies will help buildings to be energy efficient, fossil fuel free and reduce the amount of natural gas within buildings. P3 stated that

In terms of technology, hate pumps for space station as well as for domestic hot water. There's been a really fast shift across to induction cooking both in retail and in individual homes. And then we expect to see industrial heat pumps in the future.

Infrastructure projects involve significant transportation activities. During these transportation activities, advanced technologies can be installed on various transports. Internet of Things (IoT), one of the digital technologies with its associated sensors which can be installed on various modes of transport used in projects to have an account on carbon emissions. The IoT devices can measure fuel consumption, engine efficiency, and other relevant parameters to calculate and analyze carbon emissions. P5 mentioned that

It might include the emissions from trucks. So, it's possible to estimate those things from pretty good estimates around place of how much truck uses. We have been quite some time measuring the fuel consumption and loads on the trucks and a whole lot of information tracks produce more information.

The participants acknowledged that once the size of the emissions is identified, initiatives can be undertaken to reduce the emissions by integrating innovative practices in infrastructure projects. Digital technologies can help identify the sources of carbon emissions so that appropriate measures can be taken to curb the emissions.

I think, technology can demonstrate where the emissions or where the ESG data is coming from and see the source behind the reports. I think helps really prove the integrity of the data and the trust behind it (P13)

5.3.2 Efficient energy saving

Majority of the participants unanimously agreed that digital technologies play a critical role in conserving energy. This involves the application of smart technologies, automation, and energy-efficient systems across various industries. Participants acknowledge that technological advancements enable more precise monitoring and control of energy consumption, leading to optimized efficiency and reduced environmental impact. P1 mentioned that:

Technology and automation can help you identify what are like peak time, slow time, use and help with energy efficiency. Putting in place technology can help you optimize the use of energy and thus reduce it and thus reduce your footprint.

For making building much more energy efficient, a range of technological advancements are taking place. These include the use of heat pumps for space station, domestic hot water, induction cooking in retail and individual home, low DWP refrigerants in chillers and in hate pump, advanced insulation, advances in thermal breaching, high performance glazing, and mix mode ventilation. All of these advanced technologies improve energy efficiency and contribute positively to the environmental aspects of ESG. P7 stated that:

The big one is smart metering. So, if most people have that in their homes, most organizations don't really think about energy usage in their buildings. The technology is there. And so what they can do is to use smart rendering to look at their energy usage and how much of that comes from fossil flow fuel, and how much is sustainable energy potentially looking if they've got if it's you know.

Majority of the interviewees shared a common observation that social aspects of ESG have not received much attention as environmental dimension of ESG within infrastructure projects. Interviewees agreed that the social domain of ESG is less regulated and did not receive the same level of emphasis and scrutiny. However, the interviewees highlighted four aspects where digital technologies can play a role including collecting customer feedback, supply chain tracking, understanding employees’ accounts and exploring employees’ health and safety and wellbeing.

5.4.1 Stakeholders’ feedback

According to most of the interviewees, digital technologies are a valuable tool to collect various stakeholders’ feedback including customers and employees. By the use of digital platforms and data analytics, stakeholders’ experiences and feedback can be collected and analyzed. Based on the outcomes of the social aspects, essential measures can be adopted to continue and identify room for improvements for the social values of stakeholders. P8 stated that:

“When you’re talking about social dimensions of ESG, so participants lived experience of participating in a program or initiative. Those things can’t be automated because they’re very much human experience, so that has to be, to some extent, data that is collected. It can be fed into a system, but it couldn’t be automated”.

5.4.2 Tracking supply chain

Majority of the interviewees pointed that with the help of digital technologies, supply chain of products can be tracked which improves traceability and transparency on the detailed understanding of the product’s origin, manufacturing process and issues related to modern slavery. One of the commonly mentioned technologies, Radio Frequency Identification (RFID) was highlighted in the interviews to track the supply chain. RFID provides real-time tracking of products. Digital material passports possess information about the products which is helpful for understanding the product details including the use of modern slavery in making those products. P3 stated that:

“RFID is making it easier for us to scan a product and have custody of where it came from. And that means that you can track socially, the S part. You can track back into your supply chain and check the with the modern slavery requirements, for example, of the factories that where the product was originally built that coupled with digital material passports means we'll be able to get a really good idea of where products come from and how they used”.

A few participants also highlighted the potential use of digital technologies in tracking suppliers’ emissions. An economically viable technology can substantially identify the amount of greenhouse gas emissions by suppliers. P12 mentioned that:

Let's have a look at a different type of suppliers. It (technology) can really push forward how companies keep track their supply chain emissions.

A few participants commented that construction and infrastructure supply chains get opaque and difficult to track. Digital technologies can be leveraged to explore the supplier and their reputation in relation to sustainability. P13 highlighted that:

The supplier that you're buying from, it probably should follow the chain all the way down to make sure there's no bribery corruption associated with the products. You know, terrorism funding is another example of sanctions.

One of the repeatedly mentioned phenomena was the identification of modern slavery. Digital technologies can help detect modern slavery through stakeholders’ financial systems, identifying product origin, fair and ethical condition, and use of vulnerable individuals in projects. Organizations have enacted modern slavery legislation; therefore, supplier needs to be chosen accordingly in order to ensure that modern slavery regulations are being followed within organization.

5.4.3 Employees accounts

A few interviewees mentioned that tracking and measuring social aspects of ESG is difficult. Some innovative measures can be implemented to track social aspects of ESG. Having an account of employees’ details such as gender distribution, disability status and aboriginal and indigenous representation on workforce is useful to track social dimension of employees effectively. Organizations’ gender distribution provides insights into organizations’ commitment to diversity and equality. P4 stated:

In terms of social right, it takes a bit of innovation to do it. You can do it by issuing an ID card for every employee. The moment an ID card is issued, they have places, and then you can track who's the employee? And all this information is then stored into the ID card as an example. It's can still be automated, but it requires a fair bit of innovation to do it.

5.4.4 Employees’ health, safety and well-being

A few participants highlighted the need for tracking safety incidents and health and safety measures of employees as a part of improving social dimensions of ESG within infrastructure projects. Safety related incidents and information can be tracked on a platform. In addition, a range of programs can be implemented and feedback aiming to improve employees’ experiences, retention rights, and well-being can be collected and measured through the use of technology. Organizations can solicit feedback from employees and tailor programs based on the feedback collected through technology.

A vast majority of the interviewees highlighted that digital technologies facilitate governance element of ESG by accessing efficient information, tracking and evaluating information, aligning goals, and assessing resource requirements. As mentioned above, advanced technologies help streamline the information which facilitates informed decision making in projects. Governing bodies and senior management can track organizations’ SDGs and align those goals across the organization. Digital technologies have the potential to track resource usage and exchange resources as required. Furthermore, digital technologies can improve organization security and privacy protection. P7 and P8 respectively stated that:

It's around that decision making. So be more informed by that data driven decision making. improves governance ultimately.

How accompanies internal governance systems are established? How people are educated in those government governance systems, the governance of data, the protection of personal data, IP, all of those sensitive matters, certainly from a governance perspective, technology can support effective governance and help implement effective governance … … …. There's definitely a strong contribution to the effectiveness of governance and the management of risk through the appropriate use of technology and technological systems.

Project governance revolves around effective decision making and stakeholder engagement. As explained above, digital technologies can automate data collection, offer integrated platform for data collection, processing, improve data accuracy and effective data analysis.

Stakeholder engagement is one of the building blocks of good project governance. Digital technologies can automate data collection, streamline data collection, and analyze a large number of data efficiently and effortlessly. With the advancement of technologies, stakeholders can get insights into the data and projects information which enhances stakeholder engagement. P8 stated that:

Technology is absolutely key to how listed entities are feeding information, how information is being assessed by regulators, Key to how information is being communicated with shareholders and other stakeholders. So, it would really play an incredibly important role in all of that.

5.6.1 Cost implications

One of the most widely mentioned barriers to the implementation of digital technology in infrastructure projects pertains to its cost implications. Majority of the interviewees highlighted that the adoption of digital technology in improving ESG initiatives requires a colossal amount of money to be invested. There is a cost for implementing the system and its associated ongoing costs including subscription fees. Although it may be cost saving in the long run as data collection, analysis and reporting can be automated to some extent, the initial capital outset is high. P8 outlined that:

The cost of the system and the cost of implementing ongoing running of the system, any ongoing costs of who has supplied the system and anything like that. The clients are concerned about the cost of any new system, any new technology.

5.6.2 Lack of awareness

Almost all interviewees indicated that many project-based organizations do not have proper understanding about ESG and technological implementation on ESG initiatives. Some large infrastructure organizations are aware of the importance of sustainability and ESG in infrastructure projects. However, many small to medium sized project-based organizations do not have proper understanding of ESG let alone leveraging digital technology to improve ESG performances. There is a lot of confusion between sustainability and ESG. Some interviewees perceive that ESG is merely a corporate exercise. Many project-based organizations are occupied in operational business. Organizations are early on their journey with regards to their commitment to ESG initiatives. P4 narrated that:

But today, unfortunately, ESG has become more of a corporate exercise. That's. there's a lot of talk about it. But most lot of people don't really understand what it is (P4)

5.6.3 Lack of government legislation

Adhering to sustainability and ESG commitment is a voluntary act highlighted by the interviewees. There is a lack of government legislation enforced on organizations which was concurred by a few interviewees. There is a lack of clear pathways to net-zero set by federal and state governments. Governments lack law enforcement when it comes to aligning with the ESG initiatives. Therefore, many project-based organizations do not take sustainability and ESG implementation in projects seriously. P3 remarked that:

We need regulations, we need a really clear plan at a commonwealth level that then flows through states and local governments for a commitment to a net zero pathway so that everyone can then line up behind it.

5.6.4 Resistance to change

A few participants indicated that individuals have natural resistance to change. Sometimes the culture of project-based organizations is less likely to accept the changes and implement digital technologies in ESG initiatives. Some of the organizations have a lot of legacy applications. Therefore, they show resistance to the addition of another software in the existing system. P2 noted that:

I can only presuppose that culture or old-fashioned processes are preventing people adopting technology. It's always the barrier of change, isn't it.

5.6.5 Lack of resources with adequate skills

A few participants highlighted the scarcity of appropriate resources as one of the barriers to implementing digital technology in ESG initiatives. The interviewees acknowledged that project professionals are overloaded with many operational works and there is always a lack of resources with appropriate skills. ESG reporting is currently a voluntary act with a lack of resources with appropriate skills and technical expertise is considered challenging. P1 highlighted that:

It's much more likely that they're gonna do it, because even if it's just a little bit might be a little bit of extra work, and if they are already overworked, they might not do it.

5.7.1 Compatibility with existing system

One of the most widely discussed success factors for adopting digital technologies in ESG initiatives is compatibility with the existing system. When implementing digital technology, it needs to be aligned with the pre-existing system. The ease of using a system and how it integrates with other systems is really key. A lot of Excel sheets are still used as a tool in a lot of cases for data collection and reporting because it’s a tool that is widely accessed and used. There are a number of risks involved when implementing a new system which can impact on the smooth operation of business. P8 acknowledged that:

The risk involved of implementing a new system that's going to touch a number of different parts of their business, the ability to trust any new system. You always hear horror stories about a system.

There are a lot of systems already operating in business. When implementing a new technology in the existing system, its impact on the existing system has to be investigated. The system needs to as simple as possible. A few interviewees commented that the new system needs to be user-friendly, simple, easily understood by users and less time-consuming to operate. P10 reported that:

As long as it's streamlined or utilized in a manner that you know it doesn't take a case of time, aligns with pre preexisting systems.

5.7.2 Company’s appetite

A few participants indicated that the development of ESG report and the adoption of digital technology in implementation has to be company’s desire. Without the strong motivation to change, the application of digital technologies is not going to be successful. P3 indicated that:

The metering and monitoring being in place, the desire for companies to have it as a goal

5.7.3 Training arrangements

Majority of the participants indicated that training must be provided for employees in order to get accustomed to new system. Training employees is considered critical and a key element for the successful adoption of new technology for ESG initiatives implementation. P10 and P1 respectively mentioned that:

Training person at the time that the money it takes to train people and have a new system come in on.

Yes, definitely, training is a big part of adopting technology. Otherwise, yeah, it goes. It goes in use. It just happens like, I've seen it happen, you know.

5.7.4 Collaborative approach

Many interviewees commented that ESG is a voluntary act and the use of digital technology in order to improve ESG performance in infrastructure projects is a new dimension. As mentioned above, resistance to changing to a new system is one of the barriers. Therefore, according to the interviewees, one of the success factors is the need for a collaborative approach among different stakeholders. Taking everyone on the board when implementing technology is considered as a success factor. P10 reported that:

Take everyone on that journey if they don't understand it, or it seems different and scary. It's gathering the information and demonstrating to everyone that yeah, look, it's okay. These guys have done it over here. And it's been used here.

The findings of this research suggest that the adoption of digital technologies significantly improves the decision-making process, saves time, assists professionals in dealing effectively with system complexity and enhances global comparative assessment of ESG outcomes in infrastructure projects (Peng et al., 2023; Ren et al., 2023; Tumpa and Naeni, 2025; Zhai et al., 2023).

The implementation of digital technologies promotes the use of real-time data collection, improves the availability and accessibility of the data. Previous studies adopted various digital technologies such as blockchain and artificial intelligence to improve real-time data collection, thus enhancing decision-making processes as the decisions are made based on real-time and authentic information. The improved decision-making process can be explained by sensing and seizing dynamic capabilities of DCV. With the help of digital technologies, project professionals can get a sense of real-time information, identify patterns, and anomalies which may not have been possible through traditional approaches. The availability of appropriate information at the right time would help professionals seize opportunities and make informed decisions. When organizations make key business decisions, professionals should use high-quality data instead of just simply pulling data from various sources (Li et al., 2022). Emerging technologies, such as IoT, can help project managers make informed decisions that are strategic in uncertain circumstances (Ghosh et al., 2022). The findings underscore the need for integrating digital technologies into decision making for infrastructure project professionals to improve transparency and accountability for achieving long-term sustainability and improve ESG performance.

In addition, digital technologies reduce the manual data capturing, collection and analysis which can be time consuming (Ma et al., 2023). The scarcity of digital technologies result in manual data processing, leading to limited data sharing. Digital technologies such as blockchain, big data and artificial intelligence can significantly improve the data processing and contribute to efficient data management (Bezerra et al., 2024). The emergence of Industry 5.0 requires project-based organizations to quickly adapt to changing landscape to avoid disruption. Reconfiguring capability of DCV allows projects to eliminate manual data collection and adapt to digital technologies to stay competitive in the market. Infrastructure project professionals adopting digital technologies can benefit from reduced errors in data collection, and accelerated data processing, thus optimizing resources and saving time.

The findings also suggest that digital technologies can better deal with project system complexity when it comes to improving ESG performance of infrastructure projects as it has the capacity to structure and interpret a large set of data. There is a lack of evidence in the literature to support this finding. With the help of digital technologies, ESG performance of an infrastructure organization can be measured at a local and global level. Leveraging innovative technologies improves the competitive advantage of organizations, hence improving performance. In the rapidly changing environments, infrastructure projects can use digital technologies to stay competitive and contribute positively to elevating ESG performance of infrastructure projects, according to the dynamic capability view theory. Meanwhile, with the help of digital technologies, professionals in infrastructure projects can identify inefficiencies and allow seamless integration of data from multiple sources within the complex system of infrastructure projects.

In conjunction with the previous research, the findings of this research suggest that the integration of digital technologies significantly improves data collection, structuring and reporting of ESG initiatives (Wang and Esperança, 2023). Digital transformation of ESG related data improves data circulation, facilitates data management and promotes latest knowledge sharing (Su et al., 2023). An integrated platform for data collection and sharing improves efficient flow of data among stakeholders. Infrastructure projects usually have a large number of stakeholders. An integrated platform helps collect data from various stakeholders which substantially reduce the time and resources involved in the process. Digital technologies such as artificial intelligence, natural language processing and machine learning significantly process a vast amount of unstructured data and turn into a structured format (Zhai et al., 2023). By adopting digital technologies, project professionals can facilitate streamlined stakeholder engagement thus enhancing stakeholder collaboration, trust and facilitating real-time stakeholder interaction.

Data accuracy and transparency in ESG reporting is a prevalent topic of discussion in the existent literature (Karlsson et al., 2021; Wang et al., 2016). ESG reporting is a complex process. The report requires large amounts of data to be stored, processed and analyzed which can be done easily with the help of digital technologies (Watts, 2015). Digital technologies foster data accuracy as data is collected real-time with minimum intervention of humans, thus reducing human errors (Antoni et al., 2020).

Transparency of ESG data and reporting can be improved by adopting digital technologies (Niu et al., 2023). Digital technologies ensure that project stakeholders can access to symmetrical data (Ma and Zhu, 2022). When the information is not symmetry between organizations and external stakeholders, there may be possibility of greenwashing passing selective information to maximize the benefits of organizations (Xie et al., 2023b). Blockchain reduces bias, inconsistencies and enhances ESG data transparency and trustworthiness which facilitates the easy retrieval of supporting documents for addressing greenwashing issues (Ghaemi Asl et al., 2023). Professionals in infrastructure projects can develop a robust trustworthy relationship with stakeholders and improve the reputation of their organizations through the use of digital technologies as it improves the overall transparency of ESG outcomes. Digital technologies can promote sensing dynamic capabilities by real-time data access allowing stakeholders to verify processes, thus enhancing overall transparency. This process allows stakeholders to seize information and act to improve ESG performance of infrastructure projects.

Digital technologies can significantly improve the environmental aspects of ESG which is aligned well with the existing literature. There is direct proportional relationship between digitization and environmental performances (Bendig et al., 2023). Similar to this research’s findings, extant literature supports the use of technology in enhancing environmental aspect of ESG (Diófási-Kovács and Nagy, 2023; Peng et al., 2023; Zhai et al., 2023). Digital technologies can help infrastructure project professionals track carbon emissions (Fang, 2023; Shang et al., 2023), optimize emission processes, control pollutant emissions, concentration, monitor and reduce the embodied carbon (Ma et al., 2023), thus enhancing environmental performance (Yuan and Pan, 2023).

Digitally advanced organizations are capable of measuring environmental performances in multiple dimensions with various indicators (Diófási-Kovács and Nagy, 2023). Advanced technologies such as IoT can be installed to machines to track carbon emissions. Mahmood et al. (2022) found that the installation of advanced technologies reduces the emissions of carbon emissions by 43%. Similarly, digital technologies improve the energy saving and reduce energy consumption by installing advanced technologies in buildings and monitoring energy consumption (Miśkiewicz, 2020; Peng et al., 2023). Sensing dynamic capabilities of DCV detect changes and trends in emissions more accurately. Therefore, project professionals can reconfigure or adjust their strategies and processing. By following this approach, professionals can advance their understanding of utilization of digital technologies to optimize their approaches to improving environmental performance of ESG outcomes.

The application of digital technologies in achieving social sustainability is still in its infancy (Grybauskas et al., 2022). The adoption of digital technologies promote better catering of stakeholders’ needs (Dalenberg, 2018) as stakeholders’ feedback can be accumulated by the use of digital technology which ultimately improves stakeholders’ well-being (Zhang et al., 2023) and expectations (Su et al., 2023). Project professionals can initiate the idea of distributing various surveys advanced by digital technologies in order to collect information about the needs of stakeholders which can contribute to gaining a greater understanding of stakeholder expectations. The gathering of critical information about stakeholders’ social welfare provides project professionals with an indication to improve their approaches, leadership styles (Afzal and Tumpa, 2024) and work culture.

Supply chain of materials can be tracked by using state-of-the-art digital technologies which can address the issue of modern slavery and improve the transparency in the supply chain (Feroz et al., 2021; Ford and Nolan, 2020). Blockchain creates a record of every moment of a product journey through the supply chain. Considering opacity in supply chains is one of the main reasons why modern slavery exists, end-to-end transparency within a supply chain could help reduce abuses (Christ and Helliar, 2021). Digital technologies that can be used to extract information of modern slavery in supply chains by capturing satellite pictures, tracking big data analytics through mobile phones, machine learning and the Internet of Things (Berg et al., 2020). Collectively, this can significantly improve management practices as digital technologies can provide professionals with intriguing information about any discrepancy in the supply chain, thus taking immediate and corrective actions.

Digital technologies are valuable for tracking employees in infrastructure organizations to practice an inclusive work environment where in gender distribution, disability status and aboriginal and indigenous representation on workforce is maintained (Kwilinski et al., 2023). For instance, Blockchains can capture an “objective” score of working conditions, which are obtained through digital worker engagement tools (Berg et al., 2020). According to DCV, data analytics can track community well-being indicators, labor practices, and social equity metrics, helping organizations identify areas for improvement and ensure their actions align with social sustainability goals. Digital technologies enable organizations to adapt their social sustainability strategies based on real-time data and feedback. For example, if stakeholder feedback indicates concerns about working conditions, organizations can quickly adjust their practices and policies to address these issues. This suggests that project professionals can adjust their leadership and management strategies to improving social aspects of ESG, thus contributing to overall ESG performance.

The impact of digital technologies on governance element of ESG is rarely discussed in literature. Governance plays a critical role in gaining SDGs by effective stakeholder engagement, adaptive management, and collaborative decision-making (Das, 2024). The governance mechanism has transformed from analogue to automated or digital governance (Hanisch et al., 2023). The results suggest that digital technologies can transform the way the decisions are made, stakeholders are engaged, and transparency is maintained. Digital technologies help access sufficient amount of data, evaluating information, improve decision-making and resource utilization. Large amounts of data can be accessed which assists to make informed decision-making with the implementation of digital technologies. Similarly, an improved level of transparency, accountability, data visualization and disclosure can be achieved with the help of digital technologies (Jiang et al., 2021). Real-time updates and feedback mechanisms promote transparency and responsiveness, dismantling traditional communication barriers and fostering a more informed and engaged community (McKelvey and MacDonald, 2019). Furthermore, an advanced digital infrastructure system is able to track resource utilization, improve resource allocation and efficiency (Peng et al., 2023).

One such example is the use of Digital Twin which can be integrated into the existing data systems. Digital Twin creates various types of visualizations such as statistical and distribution charts to represent operational data across areas like resources, infrastructure, and public security. With the assistance of digital twin, project professionals can perform multidimensional analysis and provide a comprehensive data analysis dashboard, supporting parallel monitoring of multiple indicators. Similarly, IoT and blockchain contribute to good governance required for achieving SDGs (Chen et al., 2023).

The findings can be discussed in light of the DCV theory. With the employment of digital technologies, project professionals can identify issues related to ESG. Once issues are identified, digital technologies enable organizations to implement and manage initiatives more effectively. For example, blockchain technology can enhance transparency and traceability in supply chains, while data visualization tools can help in crafting actionable strategies and policies. Digital technologies facilitate the reconfiguration of processes and practices to better align with ESG objectives.

According to the findings of this research, the main barriers to adopting technology in ESG implementation are lack of awareness about ESG among organizations, inadequate government legislation, resistance to change, associated costs, and lack of resources with adequate skills. Many infrastructure organizations have limited or no awareness about ESG and how digital technologies can be effectively implemented to improve ESG performance. Some tier one infrastructure organizations have started reporting their ESG performance. However, most of the small to medium organizations are early on their journey. The digitization of ESG initiatives requires a substantial number of investments in green technologies, research and development, manpower, maintenance, cyber security, operation and other aspects (Chen et al., 2023; Zhang et al., 2023). Along with funds allocated to digital technologies in ESG initiatives, digital transformation requires adequate technical resources who are expert in data analysts, artificial intelligence and machine learning (Benešová and Tupa, 2017; Popkova et al., 2019). Insufficient resources with lack of technical expertise are considered barriers to technology adoption in ESG improvement (Peng et al., 2023). Project professionals need to be a strong advocate for change and shift towards advancing ESG in project-based organizations and need to promote the need for advancing ESG to senior leadership teams.

In order to drive the use of digital technology in improving ESG performance of infrastructure projects, governments have to implement legislation on the federal and state levels to enforce ESG initiatives. Currently, there is no obligation from governments to enforce ESG initiatives. Governments are incumbent to allocate special funds to research and development sectors to incorporate digital technologies to improve ESG performance (Su et al., 2023). A collaborative approach should be adopted among all relevant stakeholders. The successful integration of digital technologies in organizations’ ESG performance depends on clients’ willingness. Some clients possess too conventional mindset that hinders digitization (Tian et al., 2023a, b). Furthermore, organizations need to adopt technologies which are compatible with the existing system and user friendly. To be able to use digital technologies efficiently, employees should be given adequate training which has been highlighted as one of the key success criteria (Al Amri et al., 2021). In order to establish the practices of ESG in project-based organizations, a slow, albeit deliberate elimination of these barriers is essential.

This research aims to explore how digital technologies can be leveraged in infrastructure projects to improve ESG performance. The findings suggest that digital technologies significantly advance ESG performance of infrastructure projects. Advanced digital technologies facilitate informed decision making as project professionals have access to a sufficient level of real-time data through digital technologies. Manual processes involved in data collection, gathering, structuring and processing are time intensive processes which can be significantly enhanced by adopting stat-of-the-art technologies, thus ultimately improving ESG performance. Digital technologies facilitate data automation using an integrated system. A large of amount data can be structured and processed using digital technologies which rarely can be performed by humans. Data transparency can be obtained as it provides a real-time information and access to data by all relevant stakeholders. The results of this research suggest that digitization contributes positively to improving environmental, social and governance elements of ESG in infrastructure projects. Environmental aspects can be improved by reducing embodied carbon emissions and saving energy. Digital technologies enhance social aspects by organizing stakeholders’ feedback, tracking supply chain, accessing employees’ information and tracking health and safety of employees. Informed decision making and resource utilization encompasses governance elements of ESG. The findings of this research can be explained through the lens of Dynamic Capabilities View theory which suggests organizations can adopt digital technologies to become innovative in the changing environment which ultimately improve ESG performance by providing up-to-date data, analytics and monitoring process. Digital technologies have the potential to provide evolving regulatory information and industry standards. Dynamic Capabilities View theory suggests that innovation is key to success which is evident in this research findings as digital technologies transform how data is collected, captured, reported with accuracy and transparency. The results of this study also highlighted the barriers and enablers to adopt digital technologies to improve ESG performance of infrastructure projects.

The findings of this research provide several practical and theoretical implications. With emerge of sustainable infrastructure, project-based organizations will have to report on their ESG performance in near future. Manual process consumes significant amounts of time which can be one of the barriers to ESG performance improvement. With the advent of industry 5.0, digital technologies play a promising role in improving ESG performance of infrastructure projects. Theoretically, this research bridges a significant gap in the literature. Previous research quantitatively demonstrated positive correlation between digital technologies and ESG performance. However, there is lack of research which explored the nuances between digital technologies and ESG performance qualitatively. This qualitative research showed how digital technologies can be efficiently leveraged to improve ESG performance of infrastructure projects.

While this research provides several theoretical and practical implications, the findings of the research should be interpreted with caution. The results are based in the context of Australia. Therefore, the findings may be different in other regions and contexts. Cross country examination may introduce several complexities and nuances which can be further investigated in future research. While several steps were taken to reduce bias, for instance, using qualitative data analysis software and iterative coding by multiple authors and experts, human error still must be considered. The findings are based on the perceptions, experience and knowledge of ESG professionals which may have cognitive and subjective bias. Future research should examine cross cultural examination of ESG initiatives both in developing and developed countries using mixed research methods. Furthermore, future research should explore the use of digital technologies on various project sizes.

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A figure showing five data structures linking first-order concepts, sub-themes, and overarching themes.The description of the first data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains four rectangular boxes, each listing multiple empirical statements derived from qualitative data. Each group of boxes connects through a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesizes the sub-themes into one major overarching conceptual area. The first box in the “First Order Concepts” column lists the following points “Data-driven decision making”, “Efficient decisions made on experiential data”, “Better access to data by relevant stakeholders”, “Cost and schedule implications from poor decisions”, “Real-time data accessibility”, “Improved accountability on data capture and dissemination”, “Tracking progress for achieving S D Gs goals”, and “Inclusion of human judgement in decision making”. This box points to the box labeled “Informed decision making” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the following points: “Elimination of manual processing of data collection from stakeholders, analysis and processing”, “Eliminating manual interfaces leading to improved overall efficiency”, and “Streamlining and expedition of data”. This box points to the box labeled “Time optimisation” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following: “Effective management of project complexity through state-of-the-art technologies such as A I”, “Efficient handling of system intricates”, and “Technologies’ capacity to surpass human abilities to process big data”. This box points to the box labeled “Better management of system complexity” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Comparative analysis of E S G outcomes on the local and global scale across different industries”, and “Technologies abilities to analyse large dataset and perform analysis to meet E S G outcomes”. This box points to the box labeled “Global comparative assessment through technology” in the “Sub-themes” column. All the four text boxes in the “Sub-themes” column, an arrow arises from each box and points to “Benefits of incorporating technology in E S G initiatives”, in the “Theme” column. The description of the second data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains four rectangular boxes, each listing multiple empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesises all sub-themes into one overarching conceptual area. The first box in the “First Order Concepts” column lists the following points: “Automated data collection from operations, stakeholders, shareholders and platforms”, “Use of an integrated platform to reduce challenges in coordination”, and “Implementation of a dashboard for seamless data management”. This box connects through a right-pointing arrow to the box labeled “Automated data collection” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the points “Conversion of data in a useful format” and “Pulling data from various sources to a single platform”. This box connects to the box labeled “Data structuring and reporting” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following statements: “Data transparent and accessible to relevant stakeholders”, “Improved reliability and credibility”, and “Advanced data integrity and safeguarding”. This box connects through a right-pointing arrow to the box labeled “Data transparency” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Less human intervention” and “Elimination of manual data entry”. This box connects to the box labeled “Data accuracy” in the “Sub-themes” column. All the four text boxes in the “Sub-themes” column, an arrow arises from each box and points to “Technology in data collection, structuring and reporting”, in the “Theme” column. The description of the third data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains seven rectangular boxes, each listing multiple empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, titled “Theme”, consolidates the sub-themes into three overarching conceptual areas related to environmental, social, and governance aspects of E S G. The first box in the “First Order Concepts” column includes the points “Measurement of carbon in buildings and other infrastructures” and “Tracking carbon emissions through advanced technologies”. This box connects to the sub-theme labeled “Reduction in embodied carbon emissions”. The second box in the “First Order Concepts” column lists the following: “Technology to monitor carbon usage and control energy consumption” and “Use of various technologies to reduce carbon emissions and improve energy efficiency”. This box connects to the sub-theme labeled “Energy saving”. Both “Reduction in embodied carbon emissions” and “Energy saving” lead to the box labeled “Technological impacts on environmental aspects of E S G” in the “Theme” column. The third box in the “First Order Concepts” column contains the points “Technology to collect customers’ and employees’ feedback” and “Monitoring stakeholders’ satisfaction”. This connects to the sub-theme labeled “Stakeholders’ feedback”. The fourth box in the “First Order Concepts” column lists “Tracking products’ origin, manufacturing process and potential issues around modern slavery”, “Tracking supply chain in real-time”, and “Tracking suppliers’ commitment to net-zero”. This box connects to the sub-theme labeled “Supply chain tracking”. The fifth box in the “First Order Concepts” column includes the points “Accounts on employee’s details” and “Details on diversity and inclusivity”. This connects to the sub-theme labeled “Employees’ accounts”. The sixth box in the “First Order Concepts” column lists “Tracking safety incidents” and “Managing employees’ retention rights, well-being, and experiences”. This connects to the sub-theme labeled “Employees’ health, safety and well-being”. The sub-themes “Stakeholders’ feedback”, “Supply chain tracking”, “Employees’ accounts”, and “Employees’ health, safety and well-being” lead to the box labeled “Technological impacts on social aspects of E S G” in the “Theme” column. The seventh box in the “First Order Concepts” column contains the points “Efficient tracking and evaluating information, aligning goals, and resource requirements”, “Improved stakeholder engagement”, and “Addressing security and privacy concerns”. This connects to the sub-theme labeled “Effective governance mechanism”, which in turn points to the box labeled “Technological impacts on governance aspects of E S G” in the “Theme” column. The description of the fourth data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains four rectangular boxes, each listing several empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesises all sub-themes into one overarching conceptual area. The first box in the “First Order Concepts” column lists the following points: “Aligned with the pre-existing system”, “User friendly software”, “Simple, easy and less time consuming to use”, and “Integration with the existing software”. This box connects through a right-pointing arrow to the box labeled “Compatibility with existing system” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the points “Willingness to adopt”, “Intention to drive change”, and “Organisations’ target to S D Gs goals”. This box connects to the box labeled “Company’s appetite” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following statements: “Training and qualification about digital technologies” and “Training in data sharing, data ownership and security”. This box connects through a right-pointing arrow to the box labeled “Training arrangements” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Collaborative approach among stakeholders”, “Stakeholders’ participation in digital transformation”, and “Stakeholders’ willingness to embrace change”. This box connects to the box labeled “Collaborative approach” in the “Sub-themes” column. From all four text boxes in the “Sub-themes” column, an arrow arises from each box and points to the box labeled “Success factors for adopting technology in infrastructure” in the “Theme” column. The description of the fifth data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains five rectangular boxes, each listing several empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesises all sub-themes into one overarching conceptual area. The first box in the “First Order Concepts” column lists the following points: “Investment of a large amount of money” and “Cost associated with ongoing cost and subscription fees”. This box connects through a right-pointing arrow to the box labeled “Cost implications” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the points “Lack of proper understanding about E S G and technological implementation”, “Confusion among E S G and sustainability”, and “Organization early on their journey to E S G”. This box connects to the box labeled “Lack of awareness among organisations” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following statements “E S G being a voluntary act”, “Lack of government legislation”, “Lack of clear pathway set by governments”, and “Dearth of enforcement in E S G alignment”. This box connects through a right-pointing arrow to the box labeled “Lack of government legislation” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Resistance to new technologies”, “Organisational culture”, “Cling to legacy software”, and “Presence of a lot of existing software”. This box connects to the box labeled “Resistance to change” in the “Sub-themes” column. The fifth box in the “First Order Concepts” column lists the following points: “Scarcity of resources with adequate skills”, “Pre-occupied with many tasks”, and “Lack of technical competencies and expertise”. This box connects through a right-pointing arrow to the box labeled “Lack of resources with adequate skills” in the “Sub-themes” column. From all five text boxes in the “Sub-themes” column, an arrow arises from each box and points to the overarching theme in the “Theme” column, which is labeled “Challenges for adopting technology in infrastructure”.
A figure showing five data structures linking first-order concepts, sub-themes, and overarching themes.The description of the first data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains four rectangular boxes, each listing multiple empirical statements derived from qualitative data. Each group of boxes connects through a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesizes the sub-themes into one major overarching conceptual area. The first box in the “First Order Concepts” column lists the following points “Data-driven decision making”, “Efficient decisions made on experiential data”, “Better access to data by relevant stakeholders”, “Cost and schedule implications from poor decisions”, “Real-time data accessibility”, “Improved accountability on data capture and dissemination”, “Tracking progress for achieving S D Gs goals”, and “Inclusion of human judgement in decision making”. This box points to the box labeled “Informed decision making” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the following points: “Elimination of manual processing of data collection from stakeholders, analysis and processing”, “Eliminating manual interfaces leading to improved overall efficiency”, and “Streamlining and expedition of data”. This box points to the box labeled “Time optimisation” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following: “Effective management of project complexity through state-of-the-art technologies such as A I”, “Efficient handling of system intricates”, and “Technologies’ capacity to surpass human abilities to process big data”. This box points to the box labeled “Better management of system complexity” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Comparative analysis of E S G outcomes on the local and global scale across different industries”, and “Technologies abilities to analyse large dataset and perform analysis to meet E S G outcomes”. This box points to the box labeled “Global comparative assessment through technology” in the “Sub-themes” column. All the four text boxes in the “Sub-themes” column, an arrow arises from each box and points to “Benefits of incorporating technology in E S G initiatives”, in the “Theme” column. The description of the second data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains four rectangular boxes, each listing multiple empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesises all sub-themes into one overarching conceptual area. The first box in the “First Order Concepts” column lists the following points: “Automated data collection from operations, stakeholders, shareholders and platforms”, “Use of an integrated platform to reduce challenges in coordination”, and “Implementation of a dashboard for seamless data management”. This box connects through a right-pointing arrow to the box labeled “Automated data collection” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the points “Conversion of data in a useful format” and “Pulling data from various sources to a single platform”. This box connects to the box labeled “Data structuring and reporting” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following statements: “Data transparent and accessible to relevant stakeholders”, “Improved reliability and credibility”, and “Advanced data integrity and safeguarding”. This box connects through a right-pointing arrow to the box labeled “Data transparency” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Less human intervention” and “Elimination of manual data entry”. This box connects to the box labeled “Data accuracy” in the “Sub-themes” column. All the four text boxes in the “Sub-themes” column, an arrow arises from each box and points to “Technology in data collection, structuring and reporting”, in the “Theme” column. The description of the third data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains seven rectangular boxes, each listing multiple empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, titled “Theme”, consolidates the sub-themes into three overarching conceptual areas related to environmental, social, and governance aspects of E S G. The first box in the “First Order Concepts” column includes the points “Measurement of carbon in buildings and other infrastructures” and “Tracking carbon emissions through advanced technologies”. This box connects to the sub-theme labeled “Reduction in embodied carbon emissions”. The second box in the “First Order Concepts” column lists the following: “Technology to monitor carbon usage and control energy consumption” and “Use of various technologies to reduce carbon emissions and improve energy efficiency”. This box connects to the sub-theme labeled “Energy saving”. Both “Reduction in embodied carbon emissions” and “Energy saving” lead to the box labeled “Technological impacts on environmental aspects of E S G” in the “Theme” column. The third box in the “First Order Concepts” column contains the points “Technology to collect customers’ and employees’ feedback” and “Monitoring stakeholders’ satisfaction”. This connects to the sub-theme labeled “Stakeholders’ feedback”. The fourth box in the “First Order Concepts” column lists “Tracking products’ origin, manufacturing process and potential issues around modern slavery”, “Tracking supply chain in real-time”, and “Tracking suppliers’ commitment to net-zero”. This box connects to the sub-theme labeled “Supply chain tracking”. The fifth box in the “First Order Concepts” column includes the points “Accounts on employee’s details” and “Details on diversity and inclusivity”. This connects to the sub-theme labeled “Employees’ accounts”. The sixth box in the “First Order Concepts” column lists “Tracking safety incidents” and “Managing employees’ retention rights, well-being, and experiences”. This connects to the sub-theme labeled “Employees’ health, safety and well-being”. The sub-themes “Stakeholders’ feedback”, “Supply chain tracking”, “Employees’ accounts”, and “Employees’ health, safety and well-being” lead to the box labeled “Technological impacts on social aspects of E S G” in the “Theme” column. The seventh box in the “First Order Concepts” column contains the points “Efficient tracking and evaluating information, aligning goals, and resource requirements”, “Improved stakeholder engagement”, and “Addressing security and privacy concerns”. This connects to the sub-theme labeled “Effective governance mechanism”, which in turn points to the box labeled “Technological impacts on governance aspects of E S G” in the “Theme” column. The description of the fourth data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains four rectangular boxes, each listing several empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesises all sub-themes into one overarching conceptual area. The first box in the “First Order Concepts” column lists the following points: “Aligned with the pre-existing system”, “User friendly software”, “Simple, easy and less time consuming to use”, and “Integration with the existing software”. This box connects through a right-pointing arrow to the box labeled “Compatibility with existing system” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the points “Willingness to adopt”, “Intention to drive change”, and “Organisations’ target to S D Gs goals”. This box connects to the box labeled “Company’s appetite” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following statements: “Training and qualification about digital technologies” and “Training in data sharing, data ownership and security”. This box connects through a right-pointing arrow to the box labeled “Training arrangements” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Collaborative approach among stakeholders”, “Stakeholders’ participation in digital transformation”, and “Stakeholders’ willingness to embrace change”. This box connects to the box labeled “Collaborative approach” in the “Sub-themes” column. From all four text boxes in the “Sub-themes” column, an arrow arises from each box and points to the box labeled “Success factors for adopting technology in infrastructure” in the “Theme” column. The description of the fifth data structure is as follows: The flowchart is organized into three vertical columns titled “First Order Concepts”, “Sub-themes”, and “Theme”. The “First Order Concepts” column contains five rectangular boxes, each listing several empirical statements derived from qualitative data. Each box is connected by a right-pointing arrow to a corresponding box in the “Sub-themes” column. The third column, labeled “Theme”, synthesises all sub-themes into one overarching conceptual area. The first box in the “First Order Concepts” column lists the following points: “Investment of a large amount of money” and “Cost associated with ongoing cost and subscription fees”. This box connects through a right-pointing arrow to the box labeled “Cost implications” in the “Sub-themes” column. The second box in the “First Order Concepts” column contains the points “Lack of proper understanding about E S G and technological implementation”, “Confusion among E S G and sustainability”, and “Organization early on their journey to E S G”. This box connects to the box labeled “Lack of awareness among organisations” in the “Sub-themes” column. The third box in the “First Order Concepts” column lists the following statements “E S G being a voluntary act”, “Lack of government legislation”, “Lack of clear pathway set by governments”, and “Dearth of enforcement in E S G alignment”. This box connects through a right-pointing arrow to the box labeled “Lack of government legislation” in the “Sub-themes” column. The fourth box in the “First Order Concepts” column contains the points “Resistance to new technologies”, “Organisational culture”, “Cling to legacy software”, and “Presence of a lot of existing software”. This box connects to the box labeled “Resistance to change” in the “Sub-themes” column. The fifth box in the “First Order Concepts” column lists the following points: “Scarcity of resources with adequate skills”, “Pre-occupied with many tasks”, and “Lack of technical competencies and expertise”. This box connects through a right-pointing arrow to the box labeled “Lack of resources with adequate skills” in the “Sub-themes” column. From all five text boxes in the “Sub-themes” column, an arrow arises from each box and points to the overarching theme in the “Theme” column, which is labeled “Challenges for adopting technology in infrastructure”.
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Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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