All along the asset life cycle: Research opportunities for operations and supply chain management

Without well-functioning public utilities, our society breaks down. They are the organizations that facilitate or provide infrastructure-based services, such as basic amenities (power, water, and sanitation), public transportation, and communication. They are either state-owned or at least tightly regulated, due to their natural monopoly character: there are substantial economies of scale and large capital requirements involved, and given their typical network-based operations, having multiple parallel systems is inefficient (McNabb, 2016). Managing the operations of public utilities is vital for safe, reliable, affordable, and sustainable functioning of the physical assets, the infrastructure, through which key services are provided (De Bruijn & Dicke, 2006; Wilkeshuis, 2010) and, thus, for the security, economic prosperity, and social well-being of all citizens (Rinaldi et al., 2001). Furthermore, effective management of public utilities is—either directly or indirectly—imperative for meeting the United Nations' Sustainable Development Goals. Consider, for example, the centrality of water and energy networks for access to clean water (SDG 6) and energy (SDG 7) as well as for good health and well-being (SDG 3) and sustainable cities and communities (SDG 11). In light of the efforts to transition to a socially just and sustainable society, one would expect the operations of utilities to feature prominently in state-of-the-art operations and supply chain management (OSCM) research. So far, this is only partly the case. For example, Joglekar et al. (2016) found that of all the industry-specific studies in OSCM, only a small proportion covered public utilities, such as the energy sector and transportation. As we will elaborate, review of the literature for the purpose of this special issue still reveals only a limited number of contributions. The operational and supply chain aspects of public utilities manifest in different but highly related sets of processes. The first and probably most visible set of processes relates to how the services facilitated by the public utility assets are being designed and delivered. Literature within the operations management and operations research domains has addressed this topic in diverse areas, such as public transport services (Dollevoet et al., 2014), drinking water access (Zhai et al., 2023), and electric vehicle (EV) charging services (Guillet & Schiffer, 2023). The second set of processes pertains to asset operations and the life cycle of the physical assets that the utilities own—that is, how these assets are acquired, operated, maintained, and ultimately disposed or refurbished/recycled. Compared with the literature on service operations for utilities, the literature on asset operations for utilities is rather scant. Such studies of asset management, including utility assets, are traditionally more prevalent in the fields of (civil) engineering and public policy. Studying asset management for utilities from an operations perspective brings several benefits that society desperately needs, because the functioning of these public assets is increasingly under threat. This threat is significant for both old and new assets. The most visible category, and a significant share of all utility assets, are the old assets that were built in the postwar growth decades. Many, if not most, of these are in need of replacement, now that the end of their technical lifetimes is approaching. The United States, for example, has more than 610,000 bridges of which one in four is more than 65 years old. US infrastructure in general is rated by the American Society of Civil Engineers (2021) to be "mostly below standard." Similar problems with road transportation network maintenance are present throughout the world. For example, in France, an assessment of 45,000 bridges shows that 10% of the structures surveyed required immediate attention to ensure public safety (Koeppel, 2024). The same holds for water transportation networks, rail networks, and the like. Infrastructure that is much older than post-World War II, but which remains in use today, is of course also often at risk. Take, for instance, the often-centuries-old, but crumbling, bridges and canal walls of Amsterdam (Erdbrink, 2021). Sure enough, appropriate levels of maintenance can help raise the condition of these "aging assets" and extend their technical lifetimes. However, there is not only a shortage of public budgets for this but also an acute and growing shortage of skilled and experienced workers in most economies. Appropriate levels of maintenance are not achievable without drastic increases in labor productivity, which is one area where the OSCM community excels and thus could lend an experienced hand. Moreover, asset owners and regulators are typically reluctant to close down important infrastructure for long periods because these assets are used so intensively. As such, time windows for renovations and replacements are short. This calls for the planning of operations under time constraints, which is another strong area of expertise of the OSCM community. The construction and commissioning of new assets also present significant challenges. For example, the Dutch government aims to build more than 800 new offshore wind turbines in the North Sea by 2030. To date, there are some 300 turbines in that area, the oldest dating back to 2007. With conventional work methods and against historical labor productivity, building and commissioning these new and complex assets will be impossible. These wind farms are much farther from the coast, on a rough sea. Cargo traffic in these regions is intense and challenging to work around, and the availability of skilled technicians is again extremely limited. Meanwhile, that same North Sea is still littered with some 600 increasingly outdated oil platforms (Pearce, 2018), which must still be decommissioned in the coming years or refurbished for other purposes. Under current work methods, the associated costs are great. In sum, this presents yet another challenge for which an application of OSCM insights would be highly beneficial. These collective societal and managerial challenges, and the hitherto limited application of OSCM insights, has motivated us to organize a special issue on "Operational Excellence for Utilities." In the remainder of this editorial, we first take stock of what the literature in our field has contributed thus far. We then reflect on the objectives of this special issue and results from our call for articles. We close by providing suggestions for promising OSCM research topics in this field. Despite its importance, operations, and asset management for utilities has not attracted substantial empirical research interest in the OSCM literature. Contemporary evidence to this point emerges from a review of utilities-focused research studies appearing between 2020 and 2024 in empirically-focused OSCM journals, being JOM, Production & Operations Management, Manufacturing & Service Operations Management, Management Science, International Journal of Operations & Production Management, and Journal of Supply Chain Management. In our own review of this literature, we considered both abstracts content as well as the full text of articles, in cases where orientation to the topic of utility asset management could not be discerned by abstract alone. Quite a few of the articles we at first identified focus more on the management of services rendered through utility assets, rather than on the management of the assets themselves (see, e.g., Li et al., 2023; Shen et al., 2021; Thirumalai & Devaraj, 2024). Consequently, we dropped these articles from our set. We also removed articles for which utilities were mere context (e.g., Amaya & Holweg, 2024; Bhardwaj & Ketokivi, 2021). Some articles focus on pricing schemes, such as for charging in the context of electric vehicle adoption (Valogianni et al., 2020), subsidy policy design for electric vehicle adoption (Zhang & Dou, 2022), or consumer policy impact on solar panel production costs (Gerarden, 2023). Again, such articles were also not included in our final set. Eventually, this process resulted in the identification of 20 articles: 5 in Production and Operations Management, 5 in Manufacturing & Service Operations Management, 7 in Management Science, and 3 in JOM. Of these 20 articles that remained, the vast majority pertain to the planning phase of the overall public utility asset life cycle in the energy, mobility and drinking water sectors. These studies primarily use various types of modeling approaches. Using a dynamic programming approach, Wu et al. (2023) compare centralized versus distributed energy storage, Wu et al. (2022) study smart charging business models. Kaps et al. (2023) find optimal capacity levels for renewable generation and storage, while Fischetti and Fischetti (2023) study the combined optimization of turbine location and connection cables for offshore wind parks. Wang and He (2023) analyze capacity of park-and-ride lots and Liu et al. (2022) plan bike lane infrastructure. Yu et al. (2022) use game-theory for EV charging stations and Qi et al. (2023) look at battery swapping services for EVs. In the water sector, Zhai et al. (2023) study location decisions for drinking water projects. Sošić (2023) analyze the possibilities for desalination plants to coproduce salt and fresh water, while Mun et al. (2021) assess the development of hydro systems that can deal with interconnected issues pertaining to water, energy, food, and flooding in developing countries. A small number of studies specifically address the operations and maintenance stages of the asset life cycle. Zhang et al. (2024) draw on a single case study for the transition from projects to regular operations at Beijing Dax International Airport. Drawing on field experiments, Uppari et al. (2024) study consumer behavior and operational inefficiencies under an off-grid lighting model. Other studies address research questions more unique to utilities, specifically the energy sector. Agrawal and Yücel (2022) study electricity demand-response programs, particularly the role of baselines and baseline adjustment and corresponding rebates. Qi et al. (2022) use linear programming to determine how shared autonomous EVs could help reinforce solar-powered urban microgrids. Feng and Menezes (2022) examine a combined wind-grid hydrogen system to power manufacturing processes. Bensoussan et al. (2022) develop a real-options model in the context of renewable energy while Sunar and Swaminathan (2021) conduct numerical analysis to the impact of net-metered distributable renewable energy policies. Finally, only two very recent articles, both in JOM, address multiple stages of the asset life cycle. Fang et al. (2024) combine longitudinal case analyses and system dynamics modeling to investigate the contracting by public Dutch Water Authorities of the design, construction, operations, and maintenance of wastewater treatment plants by private contractors. In the area of satellite-based navigation in Europe, Rouyre et al. (2024) conduct a single longitudinal case study on how governance can help manage competition in the public–private collaborative delivery of the system. These studies provide us with three main insights. First is the ample opportunity for studies focusing on the acquisition of utility assets and their disposal, as well as their operations and maintenance. The field would benefit from adopting a system's perspective, so as to allow for the integral and careful study of interconnected asset life-cycle stages. Second is the opportunity for more qualitative research and, more generally, the adoption of a wider range of research methodologies. Systems-oriented research questions are well suited for studies using longitudinal perspectives, whether in the form of case studies or other types of longitudinal research designs. Third, the sectors and utility assets previously studied can be further diversified. That is, while emphasis on the energy sector is understandable in light of the major transition society is facing there, considerable potential remains to address OSCM questions pertaining to more traditional critical infrastructural networks and associated assets, such as bridges, sluices, airports, and pipelines. OSCM has from its origins adopted a systems perspective. Such a perspective is sorely missing in asset management for public utilities, particularly given that infrastructure assets tend to have such long life cycles. In theory, therefore, an OSCM perspective could offer substantial opportunity for integrated insights across all across the asset life cycle of public utilities (Browning & Honour, 2008): planning, acquisition, operations, maintenance, and disposal. How can we make such a systemic life cycle approach work for assets? Potentially, technology can perform an enabling role. From internet of things (IOT)- enabled sensors and big data analytics to virtual (VR) and augmented reality (AR) and drones, information technology provides many new techniques to manage technical assets as a system (Akkermans et al., 2024). Digitalization facilitates integration, which improves sustainability by, for instance, making maintenance activities more targeted. It also poses significant challenges on how to access and meaningfully use data, especially across utilities (Aben et al., 2021; Rijksoverheid, 2020). Digitalization and integration are areas where the field of OSCM has developed useful insights and where it can add value to purely technical asset management (Angelopoulos et al., 2023). The objectives of this special issue therefore are to stimulate OSCM research on utilities, and the infrastructures they use to provide services, which contributes to operational excellence in this domain and advances OSCM theory by applying an OSCM focus to it. In total, we received 15 submissions following our special issue call. The first authors for each of these submissions were employed at universities in Europe (8 submissions), Asia (6 submissions), and North America (1 submission). Given the wide societal relevance of infrastructure asset management, we had expected more submissions, especially from North America. This modest number of submissions suggests that for scholars in the OSCM domain, infrastructure asset management and operational excellence for utilities are not yet major topics of investigation. This is also underscored by the significant share of submissions coming from engineering schools. Of the 15 original submissions, 2 were ultimately accepted for publication. The main reasons for rejection of the others were a lack of fit with the special issue, a lack of rigorous and transparent empirical research, and an insufficient level of detail in the empirical study to support the theoretical claims made. Lack of fit occurred when articles were merely using infrastructure asset management as a backdrop and did not substantially leverage this context. The first article accepted for this special issue, by Roehrich, Taubeneder, Tyler, Squire, and Gnyawali (2024), deals with multiparty alliance formation in a large utility asset construction project. Asset management for utilities often involves many different actors, and managing the tension between collaboration and competition is a typical major challenge. This article is based on a case study of the design, construction, and commissioning of a new nuclear power station in the United Kingdom and investigates the relationships between the operator and five of its suppliers. The study relies on extensive, longitudinal real-time data collection, in which the lead researcher was embedded in an operator organization over a multiyear period. The main contributions of the study are its temporal perspective on the unique dynamics and challenges during the transition from dyadic contracts to a multiparty alliance contract and its focus on measures to maintain the balance between competition and cooperation in the supplier alliance. The second article, by Huo, Jiang, He, and Liu (2024), investigates the extent to which obstacles related to public utility assets—specifically, power outages and transportation obstacles—affect labor productivity growth across a range of sectors and the extent to which national culture moderates these effects. Using data from the World Bank encompassing 17,227 firm-year observations covering 28 industries in 41 economies from 2003 to 2020, Huo and colleagues find that power outages and transportation obstacles are both negatively associated with labor productivity growth. The detrimental impact of power outages on labor productivity growth is more pronounced in countries characterized by high power distance and uncertainty avoidance and less pronounced in countries with high levels of long-term orientation. High power distance and uncertainty avoidance may lead to rigidity and less innovation, hampering an adequate response to power outages, in contrast with long-term orientation that may facilitate such preparedness and resilience. Between them, these two studies are illustrative of the potential of utility asset management topics—from the "micro" topic of within-project governance to the "macro" topic of infrastructure disruptions. As argued, the study of operational excellence for utilities would benefit from a systems perspective that accounts for the overall life cycle of the assets and therefore will include aspects pertaining to planning, acquisition, construction, operations, maintenance, and disposal. In this section, we provide various examples of what we consider relevant opportunities for research on operational excellence for utilities. We emphasize that these are examples only, not a limiting set of questions. Moving all along the asset life cycle, we begin with research opportunities in acquisition and construction, then move to operations and maintenance, and conclude with the EOL and circularity phases. For the acquisition and construction phase, we highlight three phenomena that offer research opportunities for OSCM scholars. The first entails the allocation of risks between public utilities and their contractors. Public utilities have increasingly shifted risks to contractors, which can lead to the reduction of bidders in a tender. In early 2024, for instance, the Dutch Department of Waterways & Public Works had to redo a tender for the renovation of one of the Netherlands' busiest highway-bridges because the tender only found one bidder interested (Vestergaard, 2024). For the construction of utility assets, such as rail or road infrastructure, the utility is often a major and sometimes only client, and its contracting policies and behaviors can have a substantial and possibly long-lasting impact on the supply market. Such "marketshaping" processes are being studied also from a procurement perspective, but mostly in the case of innovation diffusion and supply-side market failure (e.g., Knight et al., 2015). OSCM scholars could leverage such more dynamic conceptualizations of markets (Kjellberg et al., 2015) in studies how specific contracting practices by public utilities affect the nature of supply markets, in terms of numbers and qualities of actors. A second phenomenon pertains to the use of performance-based contracting approaches. Performance-based contracts offered by public utilities may for instance take the form of a fixed annual fee for maintenance of a highway, with penalties for delayed maintenance works or bonuses related to the numbers of vehicles actually using the highway. While such contracting approaches are not new and have already been extensively studied (Selviaridis & Wynstra, 2015), there are still aspects that merit further study. Case studies suggest that some of the shortcomings of more classical performance-based contracts that shift risk predominantly to suppliers can be overcome (Akkermans et al., 2019). One central element in such a more collaborative approach is a deep understanding of the interdependencies between the service delivery processes at the supplier and the buyer. Further research could validate and refine the suggested success-factors for collaborative performance-based contracting, such as the involvement of representatives deeply familiar with the actual service operations and the service interdependencies between the supplier and the public utility provider. A third phenomenon in the area of acquisition and contracting is that some public authorities are moving from a project-by-project approach to so-called programmatic tendering contracting strategies for large-scale challenges. For example, the municipality of Amsterdam has set up a program in which it tenders the renovation of 200 km of canal walls and 850 bridges. In other programs, multiple contracting authorities (asset owners) collaborate to jointly put out a tender for the renovation and or construction of similar assets. Early policy studies reveal notable effects of programmatic tendering regarding, for instance, technical product innovations. Some participating contracting authorities and engineering and building contractors report substantial savings in construction costs—approximately 15%–30% in the case of bridges (De Bouwcampus, 2024). Research on these programmatic tendering approaches is beginning to emerge, focusing on the creation and transfer of interorganizational routines in project management (e.g. Frederiksen et al., 2021; Frederiksen et al., 2024; Manning, 2017). Complementing such studies, OSCM researchers could focus on the contracting phase, studying the conditions that foster the adoption of specific programmatic tendering formats and adjustments thereof, especially in relation to the actual operational outcomes of such programs in terms of costs, quality and delivery. In the construction phase of programmatic projects, OSCM studies may investigate the operational conditions for achieving successful outcomes, and the outcome differences with other (policy) instruments to enhance the efficiency and effectiveness of asset construction projects. The operations and maintenance life-cycle phases of assets for public utilities also offer ample opportunities for OSCM research. We again highlight three pertaining to (1) digitalization, (2) coordination, and (3) collaboration. Improved performance in each of these three aspects will likely lead to an increase in labor productivity, especially if they are combined. As mentioned previously, major productivity growth in maintenance is sorely needed in the coming decade. To achieve such major changes, society needs to find a transition path from how maintenance is done today (mostly periodic and corrective) to condition-based maintenance (CBM) (Akkermans et al., 2024). To get there, digital technologies such as IoT, sensors, and AI are crucial for the uptake of CBM, but they also create new challenges. First, many new digital technologies can increase productivity in the maintenance process. Figure 1 depicts the smart maintenance process (Bokrantz et al., 2020) as a plan–do–check–act (PDCA) cycle (derived from Akkermans & Van Kempen, 2016). Opportunities for digitalization (Holmström et al., 2019) are clearly abundant. So, why is digitalization happening at such a slow pace in public infrastructure maintenance? One reason may be that, as Figure 1 suggests, the loop can only be closed, and smart maintenance can only be achieved, through the combined use of all these digital technologies (Senge, 1990). How the introduction of new technology changes operations performance and management has long been a core research topic in technology management (Heim et al., 2021). So, how are these individual digital technologies changing operations, and how dependent are they on their combined use (Holmström et al., 2019)? The answer varies for each technology and stage. For example, as Figure 1 shows, digital twins are useful in all four PDCA stages, but the way they change operations is different for every stage. In the "do" stage, a digital twin helps technicians find their way around the asset, to sum up relevant information and to log maintenance data. Here, digital twins will benefit from the use of another digital technology: AR (Li et al., 2023). In the "check" stage, digital twins contain a digital shadow of past behavior (Ladj et al., 2021) based on historical data of operations, conditions, and maintenance activities. Such data are collected by sensors and transmitted via IoT. From these data, AI algorithms can develop and apply analytical models to determine triggers for maintenance in coming periods. In this way, all digital technologies are intertwined and reinforce each other. Second, supply chain coordination can make the synergetic use of these digital technologies possible. For example, to develop and run good degradation models for CBM, data from multiple actors in the manufacturer–asset owner–service provider triad (see Wynstra et al., 2015) are required. The manufacturer has in-depth knowledge about the intended performance of the assets, their degradation, and their foreseen failure modes. The asset owner knows most about how the assets are used and what loads these must bear. The service provider knows precisely about the condition of the assets before and after maintenance and what maintenance activities have been conducted. All these data help build better models. Typically though, such data are not freely shared between actors. Perhaps, the "fifth discipline" that is necessary for such efforts to succeed is again, as Senge (1990) argued, a systems perspective. From such a perspective, which spans both the supply chain and the asset life cycle, coordination between actors is desirable and natural. As mentioned, in practice today such a systems perspective on assets for utilities is lacking. This means that in the manufacturer–asset owner–service provider triad, relationships are often focused on actor-specific short-term interests. In the business models for these parties, costs and benefits of coordination remain misaligned in time and place. Third, data sharing alone between triad partners may not be enough. Whereas coordination is about sharing information, collaboration is about sharing assets or at least joint decision-making about the use of these assets across the supply chain and partners. In manufacturing and service supply chains, the notion of "supply chain control towers" is emerging (Gerrits et al., 2022; Topan et al., 2020). In such a control center, real-time data from the assets are evaluated in a Sales & Operations Planning (S Oliva & Watson, 2011) type of integrated planning to manage present and future maintenance needs as shown in the "act" stage in Figure 1. These are then set against current and future maintenance capacities and capabilities across the different service partners, leading to priorities and decisions. Those are then translated into concrete plans in the "plan" stage, using techniques, such as AI-enabled staff-scheduling/AR for training and digital workflow management. In many settings, not all interorganizational links between relevant parties are in the form of buyer–supplier relationships but instead are more similar to an ecosystem structure (Aben et al., 2023). Here, forms of network governance may be required to achieve the desired level of digital integration and interfirm collaboration (Van den Oord et al., 2023). How this combination of developments will evolve is not clear, either in practice or in theory. This lack of clarity forms a fruitful basis for OSCM research questions in the subfields of operational systems, interorganizational operations, and technology management. Historically, proper disposal and efforts to close the loop have taken a backseat in infrastructure projects. Society no longer tolerates this, so recovery and recycling are increasingly becoming major concerns for utilities. New knowledge needs to be developed, and in this way, OSCM research can make a substantial contribution. A first key OSCM research challenge for the EOL phase of utility assets is how to properly connect it with the design process. The majority of proper EOL recovery and recycling opportunities are decided up front when design choices are made. While this is fully acknowledged for consumer durables, such as cars and washing machines, it is not yet for utility assets. Perhaps it is because of their long lifetimes, spanning decades and sometimes longer, that EOL costs have traditionally been greatly underestimated for infrastructure projects. Given the uncertainties related to these long horizons and the resulting moral hazard for decision-makers, "shoving these costs under the rug" for the next generation to deal with is often tempting. Such pressures start during the design stage of the life cycle: construction work has a large carbon footprint, but design alternatives also have very different EOL costs, which need to be carefully considered. As a historical example, consider oil extraction in Pennsylvania, which began in the mid-19th century. Today, this state is plagued by more than 8000 ghost wells, emitting methane into the air and leaking chemicals into groundwater. These problems, in turn, stall local development plans and reduce property values (Aflaki et al., 2024). Did we learn from these past mistakes? The rapid development of the wind turbine industry is reminiscent of Pennsylvania's forgotten oil rush. Bigger blades on turbines located farther offshore capture wind more efficiently, but they are also more expensive to maintain and, especially, to decommission, dismantle, and properly recycle. A rush to create power generation capacity without a comprehensive approach that considers the entire life cycle can result in detrimental consequences for both the envi