Journal of Management in Engineering

Earned value management (EVM) is a project management approach that can enhance the probability of project success. It is applied widely across different industry sectors (e.g., energy, aerospace, construction, defense, and manufacturing), generally through the use of an earned value management system (EVMS). A holistic and up-to-date literature review on EVM and EVMS does not exist. A literature review can provide a comprehensive perspective on the topic, identifying and summarizing the existing body of knowledge, as a foundation to advance the state of practice of EVM/EVMS. Therefore, the objective of this paper is to investigate the EVM/EVMS state of the art by critically reviewing academic and industry publications, with a specific focus on the maturity of EVMS and the environment surrounding its implementation. By performing a systematic literature review, the authors identified 600 publications since the inception of the EVM concept in 1962, and then narrowed down this list to 160 relevant publications from the last decade for closer review. The findings include the discovery of eight emergent themes. Of these themes, “forecasting/prediction” constitutes the largest portion of the recent literature, followed by “application of EVMS.” One interesting finding is that EVMS maturity, although being a critical topic, is only discussed in one publication. Publications focused on EVM/EVMS have increased in the last decade and significant differences were found between academia and industry literature in terms of the limitations and extensions of EVM/EVMS, EVMS environment, and compliance. A key finding is that designing a reliable EVMS should combine both technical and social aspects of implementation. This forward-looking paper provides a state-of-the-art review while highlighting gaps in the existing EVM/EVMS body of knowledge and introducing new perspectives to support EVMS research and application.

Because of the long duration, multiplicity of technical disciplines, large number of project stakeholders, and high levels of complexity and uncertainty, project risk propagation control in large engineering projects (LEPs) is an enormous challenge for project managers. Although previous research has attained many risk propagation achievements regarding complex systems, complex coupled system modeling ignores the heterogeneity of the organizational structure of the actual LEPs, which affects the reliability of the calculated risk propagation results. To bridge this gap, this paper abstracts the LEP structure into a multilayer heterogeneous network comprising the stakeholder network and the project schedule network and proposes a method for characterizing the coupling relationship between two layers of the heterogeneous network. Then, the multiple uncertainties in risk propagation are greatly considered, and a risk propagation model is established based on the multilayer heterogeneous network and improved related schedule risk analysis model (CSRAM). Finally, the proposed model is applied to determine the delayed payment risk propagation in an actual LEP to verify the feasibility of the proposed model. The results indicate the following: (1) the delayed payment risk of a stakeholder evolves into a delay in the entire project; (2) several groups of comparative simulation experiments show that the proposed model, which considers multiple uncertainties and actual networks, includes more comprehensive and valuable risk information; (3) the multiple uncertainties of risk propagation are gradually superimposed with the increase in the number of construction activities affected by risk propagation; and (4) controlling for risk factors that have a high degree of influence and a large negative impact is an effective measure for blocking risk propagation across multilayer networks. This research lays an important foundation for risk propagation control in LEPs and contributes to the extension of the current theory of risk propagation in complex systems.

The sluggish adoption of building information modeling (BIM) is attributable to various technical, managerial, personnel, procedural, and institutional issues encountered by an organization in which such adoption takes place. However, these issues are under researched from a holistic perspective. Based on a proposed human-organization-technology (HOT) fit model, this paper aims to study the impacting factors of HOT fit in BIM adoption within construction project organizations (CPOs). The HOT fit indexes of 14 BIM case projects were operationalized using social network analysis (SNA) method and how different factors impact the HOT fit and its three subdimensions [i.e., human-technology (HT) fit, organization-technology (OT) fit, and human-organization (HO) fit] was investigated using a comparative case study. It was found that the project size has significantly negative relations with HOT fit, HT fit, and OT fit; while hierarchy steepness has positive correlations with HT fit, OT fit, and HO fit. OT fit was also found to have a weakly negative relationship with BIM level of details (LODs). A joint factor analysis further disclosed that the flatter the hierarchy, the larger the project size, and the higher the BIM LOD, the more difficult to achieve a high HOT fit, HT fit, or OT fit. Thus, CPOs should use steeper hierarchical structure and take a progressive BIM adoption strategy by adopting from smaller projects and/or lower LODs. This research empirically examined how project organizational and technological factors can impact BIM adoption. The HOT fit model can help CPOs evaluate their general HOT fit status, redesign optimal HOT configuration, diagnose the problems when the HOT fit is not ideal, and make strategic directions to better harvest the benefits of BIM. Limitations and future research directions are also identified.

Although building information modeling (BIM) is believed to have the potential to curb opportunistic behavior, opportunism is observed in some BIM-enabled projects surprisingly often. One possible reason is that, in current practice, the BIM capabilities of project participants are often imbalanced. This study proposes a theoretical framework to understand the impact of BIM capability imbalance on opportunistic behavior and to identify the boundary conditions. Two influential factors, BIM application scope and trust, are considered as moderators. Based on data collected from 296 responses to an electronic questionnaire survey sent to construction companies in China, the effect of BIM capability imbalance on opportunistic behavior was examined from the perspective of the Chinese construction market, and the moderating roles of BIM application scope and trust were explored. The survey results revealed that (1) BIM capability imbalance is positively related to opportunistic behavior (both strong-form and weak-form); (2) BIM application scope can enhance the positive effect of BIM capability imbalance on opportunistic behavior (both strong-form and weak-form); and (3) trust weakens the positive effect of BIM capability imbalance on opportunistic behavior (both strong-form and weak-form). This research contributes to the existing literature on the application of BIM by investigating the effects of BIM capability imbalance on opportunistic behavior and its boundary conditions, which helps to provide a better understanding of the opportunistic risk brought by BIM. This study also enriches the existing literature of information technology application and governance, as it provides empirical evidence in a construction project context for the moderating role of technology application scope and trust. Moreover, this research offers managerial suggestions for parties involved in BIM-enabled construction projects to better govern such projects by choosing partners with balanced BIM capability, determining an appropriate scope for BIM application, and implementing trust mechanisms.

Public–private partnership (PPP) infrastructure projects progress through separate phases, with each phase subject to unique risks, thereby requiring a phase-based strategy for managing risks. To date, most research on PPP risk has emphasized phases, with an obvious neglect of the final, transfer phase (TP) of PPP projects, in which the project ownership reverts to government. This study identified and evaluated critical risk categories of the TP, using China’s PPP water sector as the context of analysis. A two-stage approach was adopted, including both qualitative and quantitative research methods. Seven critical transfer risk categories (CTRCs) were identified, namely overhaul risks, contract risks, posttransfer operation risks, residual value risks, political risks, information risks, and succeeding operator risks, of which three are unique to the TP. Expert recommendations were presented for the facilitation of a smooth transfer of water PPPs in China. The findings of this study contribute to the body of knowledge in PPP risk management, and the specialized research approach employed may be utilized in similar exploratory studies.

As the COVID-19 pandemic continues, the role of facility managers in controlling and limiting the spread of the virus among facility occupants is critical. To enable facility managers to design and evaluate the effectiveness of facility operational measures (e.g., limiting room occupancy, staggering schedules), researchers have developed simulation models that can predict the physical distancing behaviors of occupants in a given facility layout and facility operational policies. However, these models do not take into consideration the impacts of spatial and temporal constraints in a facility, which can limit occupants’ ability to physical distance. To this end, this study examines whether and how such constraints affect occupants’ physical distancing behaviors in the context of K–12 educational facilities, where physical distancing is extremely important. A survey to examine students’ physical distancing behaviors in educational facilities was designed and conducted in four educational facilities ($n=527$). The results indicate that occupants’ physical distancing behaviors are significantly affected by crowdedness of space (i.e., spatial constraint) given that spatial density impacts the perceived risk of infection. On the other hand, it appears that time pressure due to limited time to meet occupancy schedules (i.e., temporal constraints) does not much influence physical distancing behaviors. These findings are expected to provide a basis upon which to enhance occupant behavior simulation efforts by deepening our understanding of physical distancing behaviors of children and adolescents in educational facilities.

Cross-border transport infrastructure (CTI) has been regarded as critical for boosting and supporting the coordinated development of regions. However, so far, very limited studies have examined the interconnection performance of CTI with particular emphasis on the overall dynamics of the complicated CTI system and how the dynamic interactions of management measures would affect the system performance as a whole. Therefore, this paper takes on a dynamic and holistic view to investigate how the overall interconnection performance of CTI is affected by the dynamic interactions of management measures. First, four broad indicators for measuring CTI interconnection performance, transportation time reliability, transportation easy accessibility, transportation safety, and transportation operating service quality were identified and analyzed. Second, the causal interactions among main variables were analyzed through causal-loop diagrams. Third, a system dynamics (SD) approach was employed to develop a model for quantifying the effects of variables. Finally, the model was verified and applied with data of the Hong Kong–Zhuhai–Macao Bridge; policy analysis was conducted as well. The findings prove that the dynamic interactions among various management measures are critical in evaluating the interconnection performance of CTI. In particular, impacts of certain combination sets of policies would be larger when management measures are collectively considered. The proposed model can be used as a basis for simulating various management measures, so that the optimum policy combinations can be explored in advance to improve the interconnection performance of CTI.

The current state of the art and applications of Internet-of-Things (IoT) in construction safety management were summarized for both academic and industrial practice based on an extensive literature review and questionnaire-based research. Because workers cannot prevent long-term contact with hazard sources during the construction process, a new hazard-prevention technology system was proposed that utilizes IoT-related technologies to integrate hazard source positioning and the task flow deployment of workers throughout the entire construction process, incorporating appropriate safety measures for different accident rate areas and constructing a four-level technology system framework that includes tasks, perceptions, networks, and applications. The new system aimed to deploy emerging technologies such as IoT via new task functional teams to form an all-around multifunctional integration and interactive system that maximizes and diversifies the use of safety resources, thus providing an array of safety measures that covers the entire construction process.

The insufficiency of continued nonpharmaceutical interventions (NPIs) and ongoing vaccination programs continues to pose challenges in recovering from the COVID-19 pandemic. Before herd immunity, controlling at-risk and vulnerable groups in combination with vaccination plans is strongly recommended. The construction industry is especially vulnerable to the negative impacts of COVID-19 as illustrated by frequent relevant clusters globally and given the manual labor performed by construction workers in close physical proximity, which increases the likelihood of exposure. To gain insights into the transmission dynamics of COVID-19 to inform the establishment of effective and targeted NPIs in the construction industry, a dual-community model was developed that includes the susceptible–exposed–infectious/asymptomatic–hospitalized–recovered–pathogen (SEI/AHR-P) model for construction workers and the susceptible–exposed–infectious/asymptomatic–hospitalized–recovered (SEI/AHR) model for their close contacts. The results of our sensitivity analysis corroborate previous findings that close contacts are significant participants in the spread of the infection. However, the contributions of indirect transmission pathways at a construction site were found to be weak, suggesting the need for further study given conflicting results in other research. Based on the parameters identified as significant in the sensitivity analyses, 28 NPI scenarios were devised to analyze the total attack rate (TAR) and duration of an outbreak (DO). The scenario in which exposed individuals are controlled in terms of close contacts performs best, reducing the TAR with 25% absolute efficiency (AE) and decreasing the DO in the whole population by 1.8 days. In addition to NPIs, both construction workers and their close contacts are suggested to get vaccinated. Vaccination of all construction workers would lead to a lower TAR compared to vaccination of only 15% of both construction workers and their close contacts. Vaccination of all construction workers along with at least 67% of their close contacts can extinguish an ongoing wave.

Practices of collaborative planning—as related to novel project delivery methods, information technologies, lean construction, and supply chain practices—can impact the cost and schedule performance of projects in the architectural, engineering, and construction (AEC) industry. However, there is a lack of research providing a quantitative holistic assessment of implementing collaborative planning practices. This paper fills this knowledge gap. Using an interdependent multistep research methodology, the authors (1) analyzed a holistic literature-based list of collaborative planning risks using 46 responses from industry expert surveys; (2) calculated the criticality of these risks and compared the obtained results using Spearman rank correlation; (3) statistically analyzed the impact of these risks—based on a project-based survey that collected data from 65 different projects—using distribution fitting analysis and weighted average calculations; (4) developed a framework for predicting the cost and schedule performance impacts in relation to utilizing collaborative planning in the AEC industry; and (5) mathematically verified the research steps using an extreme condition test and sensitivity analysis, and practically validated the research output utilizing a case study example and the insights of 25 industry experts. Within the context of collaborative planning, this paper highlighted and discussed the top six risks that affect cost and schedule project performance: resistance to change, no early involvement of key project participants, lack of construction coordination, late and ineffective communication, lack of leadership, and absence of flexibility and coordination of design. Ultimately, this study provides a necessary and highly customizable metric for industry practitioners to manage their collaborative planning practices efficiently and improve their project performance.

Design management is one of the most important construction project stages. Identifying the factors that impact a project’s performance is crucial for the overall success of construction projects. This research contributes to the body of knowledge by examining value engineering elements that might affect design management performance to keep the project team focused on those issues to achieve successful design management performance. As an integrated aspect of lean construction, this would result in a successful project with minimal waste of time, cost, or rework. Based on the assumptions made, these value engineering components were prioritized by their significance. To the best of the authors’ knowledge, this study is the first to quantitatively examine the impact of value engineering parameters on design management performance. After a detailed analysis of the literature and consultation with value engineering experts and design professionals, 22 value engineering design management factors were identified and then grouped into the three categories of designers’ conditions, owner and stakeholders’ conditions, and value engineering conditions. A questionnaire was designed and distributed to construction industry professionals to rank the factors on a five-point Likert scale. One hundred and fifty complete responses were received. The structural equation model (SEM) and the collected data were used to study the relationship and association between these value engineering factors and design management performance. After performing a thorough analysis of the results, the top-ranked group was found to be the owner and stakeholders’ conditions, followed by the group of value engineering conditions and design conditions, respectively. The results of this study will help design professionals consider the value engineering factors during the design stage of a project according to their importance, as suggested by this research.

Off-site construction (OSC) has received increasing attention worldwide, given its advantages over conventional counterparts. However, the performance of OSC’s practice has yet to be improved, despite the significant policy effort spent. This paper explores OSC project development strategy optimization from the synergetic perspective of the government and developers. A dynamic Stackelberg game is constructed and, after rigorous theoretical deductions, an example analysis is conducted to determine a proper algorithm for the model’s solution. Using Changchun City, China, as an example, the data are collected from policy documents and public web information, and through use of the Delphi method. The optimal development strategies of the local government and developers and the influences of key parameters are then obtained. The synergetic optimization model proposed by this study is conducive to achieving a “win-win” goal of maximizing both developers’ economic benefits and the total social benefits. This is a breakthrough in the previous research, contributing to effectively promoting OSC within and beyond the Chinese context.

Onsite assembly is a critical stage for modular construction. Its success or failure depends on accurate information sharing among numerous stakeholders who, unfortunately, often possess unsynchronized information. Owing to its decentralized consensus mechanism, blockchain has the potential to improve information-sharing accuracy on construction sites. However, little research has documented how this can be done. Adopting a design science research (DSR) method, this study aimed to explore the use of blockchain technology to improve information-sharing accuracy in the onsite assembly of modular construction (OAMC). First, an OAMC business process analysis was conducted to understand the issues leading to information sharing, in particular its accuracy. Then, a blockchain-based conceptual model was developed. Its components, such as membership registration, information sharing-request, ordering service, consensus mechanism, and distributed storage, were described. Finally, a prototype system was developed and validated in a mock-up OAMC. The results show that the prototype system can improve the accuracy of information sharing in OAMC by allowing project participants to endorse information about the modules and their assembly through the blockchain’s consensus mechanism. This study explores and implements blockchain technology in a specific construction area. It can serve as a valuable reference for future endeavors in harnessing the power of blockchain technology, particularly for mobilizing information endorsement mechanisms for various value-added applications.

Building information modeling (BIM) is an emerging approach to managing the design, construction, operation, and maintenance of projects. However, the lack of organizational BIM capabilities prevents BIM from being generally adopted across the architecture, engineering, and construction (AEC) industry. Therefore, AEC organizations must develop strategic plans to support BIM implementation and ensure that the anticipated benefits of BIM are realized. This study identifies the underlying factors and strategies related to organizational BIM capabilities and develops a structural equation model to establish their causal relationships. A systematic literature review of 26 articles and semi-structured interviews with BIM practitioners provided 19 factors and 14 strategies. A total of 121 BIM practitioners evaluated the criticality of the factors and strategies through a survey. The collected data were analyzed using the Kruskal–Wallis test, exploratory factor analysis (EFA), and partial least-squares structural equation modeling (PLS-SEM). The factor analysis classified the factors into two groups (organizational BIM capabilities and organizational capabilities) and strategies into three groups (capability requirement, organizational culture, and organizational competitiveness). The structural equation model revealed that organizational culture positively affects both organizational and BIM capabilities. Moreover, organizational competitiveness is shown to positively influence organizational capabilities. These results provide evidence for the development of strategies for implementing BIM. Practitioners may use these strategies to develop strategic plans and prioritize efforts in a more effective manner. With the findings of this research, users will have a better understanding of the relationships between factors and strategies that are associated with organizational BIM capabilities.

Emerging digital technologies such as building information modeling (BIM) and the Internet of Things (IoT) have been widely adopted in construction projects and have attracted great attention from researchers and practitioners in the architecture, engineering, and construction (AEC) industry. To better understand the benefits of adopting digital technologies in construction projects from the sustainability perspective, this research investigated the impact of digital technology adoption on sustainability performance and proposed the mediating role of stakeholder collaboration based on organizational information processing theory (OIPT). Survey data were collected from managers and members of Chinese construction projects, and the partial least squares structural equation modeling (PLS-SEM) method was used to test the hypothesized relationships. The results show that digital technology adoption has direct effects on economic, environmental, and social performance and that stakeholder collaboration can directly influence only economic and environmental performance. Additionally, stakeholder collaboration partially mediates the relationship between digital technology adoption and economic and environmental performance. These findings enrich the current research on digital transformation and project sustainability management and provide managerial implications for how to realize the benefits of digital technology adoption in the AEC industry.

The COVID-19 pandemic has triggered a global economic crisis and is leading multiple local, regional, and national governments to increase public debt to unprecedented levels. This situation endangers current and future road public-private partnership (PPP) programs, given their dependence on user fees and/or government availability payments. Accordingly, this study aims to explore recovery measures to address short- and long-term road PPP-related challenges associated with the COVID-19 pandemic, by considering recuperation actions implemented during the 2008 global financial crisis (GFC). To do so, this research examines the PPP-crisis literature through the lens of social network analysis (SNA) and concepts linked to network modularity and community detection techniques. The analysis focuses on unraveling semantic relationships between PPP-related keywords in order to understand lessons learned from the GFC and to propose suitable remedies for overcoming the consequences of the global economic crisis derived from the COVID-19 pandemic. Findings show that the PPP-crisis literature forms a comprehensive self-contained interwoven network that can be organized into five semantic communities according to concepts related to risk, financing, governance, procurement, and institutional environment. Based on such communities, the analysis suggests five recovery measures and highlights two implementation challenges (i.e., global supply chain disruptions and quantitative easing policies). Future research is required to examine effective ways to apply the proposed PPP remedies in the long-term.

The green loans program has continued to attract attention as an effective measure for promoting green retrofit to reduce energy consumption in old buildings. Various external factors negatively affect the decision-making process for the government and building owners. In particular, it is unclear how incentives and penalties take effect and to what extent they can influence the green loans program. Therefore, this study identified the influence of political factors, such as loan support and carbon taxation, on the strategic choices of the government and building owners. The results of this study showed that (1) as the supporting interest rate increases, both government and building owners are more likely to select a positive strategy; (2) as the carbon tax rate increases, both government and building owners are more likely to select a positive strategy; and (3) if the maximum supporting interest rate of 4.45% is applied, the greenhouse gas (GHG) emission reduction effect can be increased by about 3–5 times from the current level. It is not easy to achieve the national carbon emission reduction target for 2030 and 2050 only through green retrofitting of old buildings under the green loans program. Therefore, the government should develop an additional research and development budget and encourage developers to enhance the efficiency of green technologies.

Public–Private Partnership (PPP) programs have been developed widely for more than 30 years across the world. The continuity of these programs depends on an adequate balance of three-dimensional sustainability (i.e., economic, environmental, and social). Nevertheless, social sustainability has been demonstrated as being fragile because of the challenges to achieving the intended social legitimacy in PPP programs. This study aims to understand key challenges in achieving social legitimacy in road PPP programs by analyzing contractual clauses, legal frameworks, and stakeholders’ interviews of two toll road PPP programs in Chile and Colombia. Three key challenges to social legitimacy were found: social involvement issues, distrust between impacted and responsible stakeholders, and lack of social criteria within toll tariff policy. Findings reveal that it is required to move beyond current consultation mechanisms and thoroughly involve the impacted groups as a relevant stakeholder typology in order to maximize value creation in user-pay PPP programs. In line with that, this study exposes that the claim of previous research for developing relational governance between the public and the private sectors is not enough for overcoming governance limitations and addressing social legitimacy in user-pay PPPs. It is also necessary to enhance relational governance in a triadic approach. This study contributes to the PPP body of knowledge by redirecting the discussion from overall legitimacy to social legitimacy challenges and by including the impacted stakeholders in the analysis of PPP governance mechanisms.

While cloud-based collaborative building design processes have become commonplace, colocated meetings remain a central and integral part of the management of such processes in the construction industry. The restrictions on colocated meetings due to the Covid-19 pandemic have therefore created challenges for the management of building design. This study sought to develop an alternative method for design coordination in a cloud-based Building Information Modeling (BIM) environment, which reduces the need for such meetings. This was also seen as an opportunity to improve the way design coordination is currently managed in the construction industry, by changing several practices that for a long time have been assumed to be the default choice. It was found that online design coordination requires a more structured and formal approach and the definition of design tasks at a much higher level of detail or granularity than is currently common. There is consequently a need for a systematic process and supporting tools to correctly plan and effectively control the execution of a larger number of individual design tasks. A suitable method has been defined for online design coordination, which incorporates tools such as resource leveling and four-dimensional BIM that have not previously been used in this context. The method was successfully implemented in a real project, highlighting its feasibility and the ability to reduce the need for colocated meetings, while at the same time improving the design process.

Cities in many countries are witnessing an era of transformative innovations in vehicular technologies and mobility-on-demand (MoD) services in the context of global initiatives of smart and connected cities. However, advances in the built environment where vehicles operate have not maintained the same pace. The new MoD especially burdens curb environments in urban cores due to competition for spaces for pick-ups and drop-offs (PUDO). These uncoordinated and diverse uses without data-driven management have led to increased safety and sustainability issues. This research intends to address the increasing curbside uses of PUDO activities due to MoD services and proposes a data-driven agent-based simulation approach to plan designated PUDO zones in limited public curbside spaces. A case study was conducted for five street blocks in urban cores of the City of Gainesville, Florida, United States, based on longitudinal parking transaction and violation records, place visitation data, and geospatial data of parking assets. The results show that temporary PUDO zones should be designated at all investigated blocks during peak hours even when the MoD market penetration rate is low (i.e., 10%), which helps mitigate the occurrences of competing use events, while permanent PUDO zones should be designated for the two busiest blocks when the MoD market penetration rates increase to 30% or 50%. Sensitivity analyses suggest that the designated PUDO zones can mitigate curbside stresses more effectively when regulating MoD users’ PUDO dwell time (e.g., within one minute). This research aims to contribute to data-driven public asset managerial decision-making and strategies in smart cities and benefits more accessible and sustainable living environments in urban cores.

This study is aimed at analyzing how governance structure and mechanisms can support the cooperative principal–principal relationship between the public and private sectors in infrastructure public–private partnership (PPP) projects. This topic is important because PPP projects are prevalent in developing countries such as China, and the two sectors can face inherent conflicts when they come into the principal–principal relationship. To address this aim, we employed an in-depth qualitative case study of Beijing Metro Line 4—a typical and successful PPP project in China. Based upon retrospective primary and secondary data, we identified and analyzed effective governance mechanisms at institutional, corporate, and project levels. These mechanisms enable both sectors to balance power and protect mutual benefits against the adverse effects of principal–principal conflicts. This study contributes to the literature by revealing the link between governance and principal–principal relationships in Chinese infrastructure PPPs and illustrating how different levels of governance mechanisms together foster the cooperative relationship between public and private parties.

The externalities of investment decisions with regard to residential photovoltaic (PV) systems have been changing rapidly in recent years. This study thoroughly explored these fast-changing dynamics by investigating the costs and benefits of PV investment. Five case studies were analyzed to populate the generalized observations of various PV investment conditions. This research proves that the initially high one-time installation cost can be recouped by measured benefits, although the level of return may vary from state to state depending largely on the financial incentives provided. For those enjoying either low electricity prices or peak sun hours, the results of this analysis did not support the installation of a PV system. These findings provide up-to-date benchmarking results for PV investments that homeowners can reference when assessing the costs and benefits associated with the adoption of PV systems.

For credible project benchmarking, like-for-like project comparison is a prerequisite to set realistic targets for improvement, especially when a heterogeneous sample of healthcare projects is compared to another. However, the current method for determining the groups of similar projects relies on an ad-hoc technique that can lead to suboptimal target settings for improvement. To address this issue, this research proposes a novel approach to capture similarity for capital project benchmarking by leveraging Classification and Regression Trees (CART). This research focuses on healthcare projects. The data collected from a total of 89 healthcare projects were used to construct the trees by selecting a set of critical and flexible features that are closely associated with two metrics representing cost and schedule performance of the selected projects. The effectiveness of results derived from the proposed method was validated through statistical methods and comparative analysis. The proposed method allows for more targeted performance comparisons by capturing similarity using flexible sets of meaningful features, which reduces the search space of determining a group of similar projects. The new approach is, thus, expected to help organizations gain better insights into their relative performance position when benchmarking their capital projects.

Recent technological developments and advances in artificial intelligence (AI) have enabled sophisticated capabilities to be a part of digital twins (DTs), virtually making it possible to introduce automation into all aspects of work processes. Given these possibilities that DT can offer, practitioners are facing increasingly difficult decisions regarding what capabilities to select when deploying a DT in practice. The lack of research in this field has not helped. It has resulted in the rebranding and reuse of emerging technological capabilities such as prediction, simulation, AI, and machine learning (ML) as necessary constituents of DT. Inappropriate selection of capabilities in a DT can result in missed opportunities, strategic misalignments, inflated expectations, and the risk of it being rejected as hype by the practitioners. To alleviate this challenge, this paper proposes a digitalization framework, designed and developed by following a design science research (DSR) methodology over a period of 18 months. The framework can help practitioners select an appropriate level of sophistication in a DT by weighing the pros and cons for each level, determining evaluation criteria for the digital twin system, and assessing the implications of the selected DT on the organizational processes and strategies and value creation. Three real-life case studies illustrated the application and usefulness of the framework.