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Given the heavy pollution feature of the construction industry, construction corporations need to adopt an effective environmental governance strategy. The quality and quantity of environmental information disclosure (EID) implementation, as an essential part of a corporate environmental governance strategy, is impacted by the characteristics of the top management team (TMT). This paper aims to analyze the relationship between the demographic characteristics of the TMT (i.e. gender, age, tenure, educational level, and duality) and corporate EID.

Using data from listed construction corporations generated between 2014 to 2018 in China, this study employs the Tobit regression model to test the research hypotheses. Also, this study applies a novel analytical approach, necessary condition analysis (NCA), to conduct a series of additional tests.

The results reveal that tenure and educational level are significantly and positively related to EID, while gender, age, and duality in the executive role are not significantly related to EID. When considering the TMT size as a moderator, the TMT age is positively related to the corporate EID, and the size of the TMT acts as a moderator to weaken the positive effect of the TMT age on the EID. The NCA results show that TMT gender, age, tenure, and educational level are necessary when the levels of EID exceed 40%.

Our findings suggest that TMT characteristics have a relatively significant effect on corporate EID levels, which extends EID research to the construction industry. Corporate planners can endeavor to shape TMT characteristics to improve EID levels. The results of NCA provide insights into what TMT characteristics construction corporations need to satisfy in their pursuit of transparent EID, as well as the levels at which these characteristics are desired.

Early termination of public–private partnerships (PPPs) in China is caused by various risk factors, resulting in significant losses. This study aimed to clarify the key factors and identify the causal relationships among these factors.

Social network analysis (SNA) was used to analyze 37 risk factors that were summarized from 97 early terminated PPP cases and to identify the relationships among these key risk factors. Interpretive structural modeling (ISM) was conducted to explore the causal relationships. Data were collected from case documents, questionnaires and interviews.

A total of 17 key risk factors were identified and distributed in a hierarchical structure with six tiers. Among these key risk factors, the root causes affecting the early termination of PPP projects were government oversight in decision-making, local government transition, policy and law changes and force majeure. The direct cause was insufficient returns. Furthermore, local government and private sector defaults were essential mediating factors. Local government transition and the low willingness of the private sector were highlighted as potential key risks.

The cases and experts were all from China, and outcomes in other countries or cultures may differ from those of this study. Therefore, further studies are required.

This research provides knowledge regarding the key risk factors leading to the early termination of PPP projects and guidance on avoiding these factors and blocking the factors' transmission in the project lifecycle.

This study contributes to the knowledge of risk management by emphasizing the importance of local government transition, the low willingness of the private sector and project cooperation and operation, whose significance is ignored in the existing literature. The proposed ISM clarifies the role of risk factors in causing early termination and explains their transmission patterns.

This study aims to investigate the relationship between supply chain leadership, digital supply chain practices and corporate sustainability strategies on the sustainability performance of logistics firms in Nigeria, one of Africa’s largest economies. It indicates that collaborative efforts within the supply chain context can improve sustainability performance.

Data from 468 firms in a major sub-Saharan African market were collected through a structured questionnaire. The analysis used descriptive statistics, principal component analysis and hierarchical regression analysis. Factor analysis and Cronbach’s alpha analysis were used to assess the validity and reliability of the instrument.

The results of this study reveal significant findings: proactive sustainability strategies exert a substantial positive effect on sustainability performance (β = 0.694, SE = 0.025, p < 0.01). Even when proactive sustainability strategies are included in the model, the positive impact of reactive sustainability strategies remains significant (β = 0.694, SE = 0.025, p < 0.01: Model 5). Regarding the moderating role of proactive and reactive corporate sustainability strategies, there is a notable interaction effect between supply chain leadership and proactive sustainability strategies concerning sustainability performance (p < 0.05). This confirms the positive relationship between supply chain leadership and sustainability performance when proactive sustainability strategies are at a high level (β = 0.844, SE = 0.0010, p < 0.01), supporting H4 that this relationship strengthens with higher levels of proactive sustainability strategies. Conversely, for Hypothesis H5, the interaction effect of reactive sustainability strategies with supply chain leadership changes the relationship from significantly positive to significantly negative (β = −0.068, SE = 0.0009, p < 0.01). Using the Baron and Kenny approach to test mediation, the mediating effect of digital supply on digital leadership is significant (β = 0.345, p = 0.000, p < 0.01). Furthermore, the effect of digital supply on sustainability performance is statistically significant (β = 0.081, p = 0.006, p < 0.01), as is the effect of digital leadership on sustainability performance (β = 0.181, p = 0.000, p < 0.01). These results indicate a mediation effect of digital supply.

This study of logistic management has limitations, including its cross-sectional nature, which precludes the establishment of causality, thus necessitating longitudinal research to determine causal relationships. In addition, the focus on Nigerian firms, which vary significantly in their stages of learning and institutional development, emphasizes the need for further research in diverse contexts. Future studies should examine alternative institutional environments or developed economies to validate these assumptions. Another limitation is the potential for bias due to six employees rating their firms on each variable; therefore, using multiple data sources is recommended to objectively evaluate the validity of the self-reported questionnaire.

This study advises managers to exercise caution when selecting between proactive and reactive sustainability strategies to enhance sustainability performance. Proactive strategies reinforce the relationship between supply chain leadership and sustainability performance, while reactive strategies diminish it. Therefore, managers are encouraged to adopt more proactive strategies. This paper suggests that managers in emerging economies should recognize the distinct impacts of proactive sustainability strategies and allocate more resources toward them to improve sustainability performance, even in competitive markets. In addition, it highlights the importance of digital supply in fostering sustainability performance.

This study presents a novel perspective on the moderating role of corporate sustainability strategies in the relationship between supply chain leadership and the sustainability performance of logistics firms. It provides empirical evidence and fresh insights on proactive and reactive sustainability strategies for logistics firms in Nigeria. The findings highlight that proactive sustainability strategies enhance the connection between supply chain leadership and sustainability performance, whereas reactive strategies do not.

This paper systematically presents a critical review of data envelopment analysis (DEA) for performance measurement in the construction field.

The review approach consists of a systematic literature search, validation analysis and content analysis. The paper systematically reviews previous papers according to the year of publication, journal, authors, region, research keywords, performance measurement indicators and methodology framework.

A total of 192 journal papers from the first year of publication to 2022 are identified. DEA applications have increased over the years, particularly after 2020. All of the top five journals which published the most identified papers are Q1 journals. Around 74 primary indicators of performance measurement are recognised for the construction industry, company and project levels. A total of 21 top keywords are identified and then divided into five clusters using VOSviewer. DEA has been widely utilised to measure construction performance and benchmark technologies, particularly where sustainable development performance has become a popular topic recently.

How to effectively distinguish performance indicators, collect research data, build DEA models and deeply analyse DEA results are illustrated for future practitioners. The performance measurement and improvement cycle based on DEA is provided. Research directions and method recommendations are developed for future scholars using DEA.

This is the first comprehensive review that has initially presented various performance indicators and a methodology framework for developing DEA models to investigate performance measurement in the construction field. The methodology framework of DEA is developed, including data collection, model construction and further analysis of DEA results.