Construction is a resource-intensive industry where a circular economy (CE) is essential to minimize global impacts and conserve natural resources. A CE achieves long-term sustainability by enabling materials to circulate along the critical supply chains. Accordingly, recent research has proposed a paradigm shift towards CE-based sustainability. However, uncertainties caused by fluctuating raw material prices, scarce materials, increasing demand, consumers’ expectations, lack of proper waste infrastructure, and the use of wrong recycling technologies all lead to complexities in the construction industry (CI). This research paper aims to determine the enablers of a CE for sustainable development in the CI. The system dynamics (SD) approach is utilized for modeling and simulation purposes to address the associated process complexity. First, using content analysis of pertinent literature, ten enablers of a CE for sustainable development in CI were identified. Then, causality among these enablers was identified via interviews and questionnaire surveys, leading to the development of the causal loop diagram (CLD) using systems thinking. The CLD for the 10 shortlisted enablers shows five reinforcing loops and one balancing loop. Furthermore, the CLD was used to develop an SD model with two stocks: “Organizational Incentive Schemes” and “Policy Support.” An additional stock (“Sustainable Development”) was created to determine the combined effect of all stocks. The model was simulated for five years. The findings show that policy support and organizational incentive schemes, among other enablers, are critical in implementing a CE for sustainable development in CI. The outcomes of this study can help CI practitioners to implement a CE in a way that drives innovation, boosts economic growth, and improves competitiveness.

Sustainable supply chain management (SSCM) involves the managing of information, materials, cash flows, and collaboration among enterprises along the supply chain, integrating sustainable development goals. This research paper aims to determine challenges in SSCM adoption and to address related complexity using the system dynamics (SD) approach utilizing modeling and simulation techniques. This research identified challenges from the literature using content analysis. Causality among these identified challenges was determined using interviews and questionnaire surveys that led to the development of a causal loop diagram (CLD), which was used in the development of the SD model. Among the 19 shortlisted variables, CLD had IV reinforcing and II balancing loops. Moreover, CLD was used to build an SD model with two stocks, and a new stock named ‘project performance’ was added to envisage the cumulative impact of all stocks. The model was simulated for five years, and the results predict that the lack of top management commitment and corporate social responsibility adversely affects project performance. This implies that there is a need to improve numerous factors, in particular corporate social responsibility and top management commitment, which would lead to the adoption of SSCM, thus leading to a performance improvement for the construction industry (CI). The model was validated using boundary adequacy, structure, and parametric verification tests, which showed that the developed model is logical and approximately replicates the industry’s actual system. The research findings will help the CI practitioners to adopt sustainability principles in terms of the supply chain and will not only enhance productivity and performance but will also help in the minimization of delays, promote long-term relations, and reduce communication gaps and project complexities.

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Job stress (JS) is a significant issue in the construction industry of developing countries. This study aims to examine the impact of error-management climate (EMC), safety climate (SC), and psychological capital (PC) (as a mediator) on employee JS in the construction industry, and establish relationships between these constructs. A questionnaire survey was conducted to gather data from 144 respondents. The study’s hypothesized relationships were tested using partial-least-squares structural-equation modeling (PLS-SEM). The analysis indicated a positive association between EMC and PC. Conversely, EMC did not have a negative impact on JS. The study also established a constructive relationship between SC and PC, and a significant negative association between SC and JS. Regarding mediation, PC was found to partially mediate the effect of EMC on JS, accounting for 55% of the variance accounted for (VAF). The study’s innovative contribution lies in exploring the limited research on PC within the construction industry, and investigating the interactions among SC, EMC, PC, and JS.

In the globalized world, one significant challenge for organizations is minimizing risk by building resilient supply chains (SCs). This is important to achieve a competitive advantage in an unpredictable and ever-changing environment. However, the key enablers of such resilient and sustainable supply chain management are less explored in construction projects. Therefore, the present research aims to determine the causality among the crucial drivers of resilient and sustainable supply chain management (RSSCM) in construction projects. Based on the literature review, 12 enablers of RSSCM were shortlisted. Using the systems thinking (ST) approach, this article portrays the interrelation between the 12 shortlisted resilience enablers crucial for sustainability in construction projects. The causality and interrelationships among identified enablers in the developed causal loop diagram (CLD) show their dynamic interactions and impacts within the RSSCM system. Based on the results of this study, agility, information sharing, strategic risk planning, corporate social responsibility, and visibility are the key enablers for the RSSCM. The findings of this research will enable the construction managers to compare different SCs while understanding how supply chain characteristics increase or decrease the durability and ultimately affect the exposure to risk in the construction SCs.