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Real estate investment trusts (REITs) have shown great potential in addressing the current contradiction between underinvestment and sustainable development of urban regeneration in China, as well as in further facilitating the transformation and upgrading of China's urban development. In this regard, this study aims to investigate critical success factors (CSFs) and explore the relationships among these factors, and serve as a reference to provide recommendations and strategies for the successful implementation and sustainable development of urban regeneration REITs.

In this study, an integrated total interpretive structural modeling–matriced impact croises multiplication applique (TISM–MICMAC) approach using the TISM technique and MICMAC analysis is then implemented to explore the relationships among CSFs, demonstrate the hierarchical structure and classify these factors into clusters based on calculated driving powers and dependence.

This study has determined a final list of 11 CSFs through literature review and expert survey. The TISM model demonstrates a six-level hierarchical structure encompassing the influence transmission paths of CSFs, in which the most significant factors and links are established, while the MICMAC analysis further classifies CSFs into four clusters as a complement for the findings of the TISM technique.

This study offers practical implications for governments, individual and institutional investors, REITs and property managers, and other stakeholders concluded in urban regeneration REITs. The final list of determined CSFs can serve as the decision points for management and control of the implementation processes, while the findings of the TISM–MICMAC approach can be a significant reference to provide strategies for optimization and enhancement of urban regeneration REITs.

This study is a novel attempt to use both the TISM technique and MICMAC analysis to investigate CSFs for the implementation of urban regeneration REITs, and to address the theoretical and methodological research gaps in the existing literature.

Promoting technological innovation is important to address the complexity of major engineering challenges. Technological innovations include short-term innovations at the project level and long-term innovations that can enhance competitive advantages. The purpose of this study is to develop an incentive mechanism for the public sector that considers short-term and long-term efforts from the private sector, aiming to promote technological innovation in major engineering projects.

This study constructs an incentive model considering the differences in short-term and long-term innovation efforts from the private sector. This model emphasizes the spillover effect of long-term efforts on current projects and the cost synergy effect between short-term and long-term efforts. It also explores the factors influencing the optimal incentive strategies for the public sector and innovation strategies for the private sector.

The results indicate that increasing the output coefficient of short-term and long-term efforts and reducing the cost coefficient not only enhance the innovation efforts of the private sector but also prompt the public sector to increase the incentive coefficient. The spillover effect of long-term innovation efforts and the synergy effect of the two efforts are positively related to the incentive coefficient for the public sector.

This research addresses the existing gap in understanding how the public sector should devise incentive mechanisms for technological innovation when contractors acting as the private sector are responsible for construction within a public-private partnership (PPP) model. In constructing the incentive mechanism model, this study incorporates the private sector's short-term efforts at the project level and their long-term efforts for sustained corporate development, thus adding considerable practical significance.

Promoting low-carbon in the construction industry is important for achieving the overall low-carbon goals. Public–private partnership is very popular in public infrastructure projects. However, different perceptions of low-carbon and behaviors of public and private sectors can hinder the realization of low-carbon in these projects. In order to analyze the willingness of each stakeholder to cooperate towards low-carbon goals, an evolutionary game model is constructed.

An evolutionary game model that considers the opportunistic behavior of the participants is developed. The evolutionary stable strategies (ESSs) under different scenarios are examined, and the factors that influence the willingness to cooperate between the government and private investors are investigated.

The results illustrate that a well-designed system of profit distribution and subsidies can enhance collaboration. Excessive subsidies have negative impact on cooperation between the two sides, because these two sides can weaken income distribution and lead to the free-riding behavior of the government. Under the situation of two ESSs, there is also an optimal revenue distribution coefficient that maximizes the probability of cooperation. With the introduction of supervision and punishment mechanism, the opportunistic behavior of private investors is effectively constrained.

An evolutionary game model is developed to explore the cooperation between the public sector and the private sector in the field of low-carbon construction. Based on the analysis of the model, this paper summarizes the conditions and strategies that can enable the two sectors to cooperate.

This research aims to argue that manual geometric modeling is blocking the building information modeling (BIM) promotion to small-size companies. Therefore, it is necessary to study a manner of automated modeling to reduce the dependence of BIM implementation on manpower. This paper aims to make a study into such a system to propose both its theory and prototype.

This research took a prototyping as the methodology, which consists of three steps: (1) proposing a theoretical framework supporting automated geometric modeling process; (2) developing a prototype system based on the framework; (3) conducting a testing for the prototype system on its performance.

Previous researches into automated geometric modeling only respectively focused on a specific procedure for a particular engineering domain. No general model was abstracted to support generic geometric modeling. This paper, taking higher level of abstraction, proposed such a model that can describe general geometric modeling process to serve generic automated geometric modeling systems.

This paper focused on only geometric modeling, skipping non-geometric information of BIM. A complete BIM model consists of geometric and non-geometric data. Therefore, the method of combination of them is on the research agenda.

The model proposed by this paper provide a mechanism to translate engineering geometric objects into textual representations, being able to act as the kernel of generic automated geometric modeling systems, which are expected to boost BIM promotion in industry.

Collaboration is essential to BIM-enabled construction projects (BECPs). To facilitate collaboration, various strategies have been proposed. Usually, project team adopts single collaboration strategy for convenience. However, BIM-based collaboration is rather dynamic and exposed to a lot of barriers and risks, which easily changes collaboration conditions among partners. Therefore, better understanding of collaboration conditions in BECPs is crucial to develop flexible and suitable strategies. To fill in the gap, this study intends to identify typical collaboration profiles in BECPs and develop a profile-oriented strategy selection framework.

This study establishes a six-dimensional collaborative behavior matric based on a comprehensive literature review to profile collaboration. Then a questionnaire survey is conducted to collect the collaboration data from 162 BECPs in China. Finally, latent profile analysis (LPA) is utilized to identify the typical collaboration profiles in BECPs.

Through LPA, four profiles are identified, including restricted collaboration profile, smarmy collaboration profile, intuitive collaboration profile, and modest collaboration profile. A profile-oriented strategy selection framework is also established to match strategies with collaboration profiles. Two major categories of strategies are proposed to promote these collaboration profiles including trust building and elevating strategies and collaborative behaviors facilitating strategies.

These identified profiles can provide an insightful understanding on the diversified collaboration conditions in BECPs.

The profile-oriented strategy selection framework will help managers develop strategies flexibly to promote collaboration in BECPs.

This study validates four typical collaboration profiles in BECPs. Moreover, a profile-oriented strategy selection framework is also established for collaboration facilitation in BECPs.

The purpose of this paper is to test the density dependence theory and explain the deep changes that the Chinese construction industry is experiencing. Focusing on both organizational level and industry level, it aims to identify the factors and to show how these factors affect the mortality of the Chinese construction companies.

The Jiangsu construction industry is chosen as a proxy of the Chinese market. With the event history analysis method and life history data on all companies known to have operated during the period 1989‐2007 in Jiangsu, an expanded Cox model is established to achieve the purpose.

The construction industry level evolution plays an important role on exit rate of construction companies; however, this effect does not conform with density dependence as expected, and it interacts with organizational age. Besides, age and size of organizational level, and macro environment also act on mortality.

Owing to the difficulty in data acquisition, only 19 years of the Jiangsu construction industry have been reported here, which may not provide the whole picture of the evolution process. Furthermore, the different ending events, such as disbanding and merge, have not been identified, which may affect the results to some extent.

The paper provides a new perspective to analyze the evolution of the Chinese construction industry and the mortality of construction companies.

This is the first article that applies the density dependence theory to analyze the evolution process of the construction industry. It is also the first attempt to analyze the interaction of density, macro factors and organizational age, which is a contribution to the organizational ecology theory and the study of construction industry development.

Construction is a risky industry. Therefore, organizations are seeking ways towards improving their safety performance. Among these, the integration of technology into health and safety leads to enhanced safety performance. Considering the benefits observed in using technology in safety, this study aims to explore digital technologies' use and potential benefits in construction health and safety.

An extensive bibliometrics analysis was conducted to reveal which technologies are at the forefront of others and how these technologies are used in safety operations. The study used two different databases, Web of Science (WoS) and Scopus, to scan the literature in a systemic way.

The systemic analysis of several studies showed that the digital technologies use in construction are still a niche theme and need more assessment. The study provided that sensors and wireless technology are of utmost importance in terms of construction safety. Moreover, the study revealed that artificial intelligence, machine learning, building information modeling (BIM), sensors and wireless technologies are trending technologies compared to unmanned aerial vehicles, serious games and the Internet of things. On the other hand, the study provided that the technologies are even more effective with integrated use like in the case of BIM and sensors or unmanned aerial vehicles. It was observed that the use of these technologies varies with respect to studies conducted in different countries. The study further revealed that the studies conducted on this topic are mostly published in some selected journals and international collaboration efforts in terms of researching the topic have been observed.

This study provides an extensive analysis of WoS and Scopus databases and an in-depth review of the use of digital technologies in construction safety. The review consists of the most recent studies showing the benefits of using such technologies and showing the usage on a systemic level from which both scientists and practitioners can benefit to devise new strategies in technology usage.

The aims of this study are to conduct a systematic review of public–private partnership (PPP) studies published from 2009 to 2019, to compare the results with Ke et al. (2009) who reviewed the PPP literature published from 1998 to 2008, and to trace the evolution of the PPP knowledge in the past two decades. This study also presents the possible directions that the PPP research may go towards in the future, arguably.

This study carried out a top journal-based search to identify the quality PPP articles published from 2009 to 2019. A total of 12 top-tier construction journals were systematically searched in the database of web of science (WOS), from which 279 PPP articles were identified for review.

The number of the identified articles, the titles of the journals, institutions, the most cited papers, and prevalent research methods were analyzed and compared. The existing PPP studies in construction journals were classified into seven streams. Through analysis of the PPP research status and gaps, five future research directions were revealed.

This study contributes to the current body of knowledge by revealing the research trend of PPP from 2009 to 2019. It presents the change of PPP development trend in the past decade through comparison with Ke et al. (2009). It also reveals the major research streams and points out the directions that the PPP research may go towards in the future. Moreover, this study is helpful to the practice as well. It can enhance the practitioners' understanding of the PPP development in the past decade. In addition, it identified the research institutions contributing the most in the area of PPP, which may serve as valuable reference for practitioners to locate the best institutions for consultancy or collaboration.

Meaningful feedback at work signals effective performance management. Drawing on a new perspective of the conservation of resources (COR) theory, this paper aims to examine the mediating effect of relational energy in the relationship between supervisor developmental feedback and subordinates' task performance with the moderating role of learning demands.

Data from 230 supervisor-subordinate dyads were collected at two time points of four enterprises in China.

The results support the proposed mediation effect that supervisor developmental feedback positively predicts subordinates' task performance via boosting subordinates' relational energy. Furthermore, the results highlighted the moderating role of learning demands in the relationship between supervisor developmental feedback and subordinates' relational energy. The moderated–mediated relationship for subordinates' task performance was also supported.

Drawing on COR theory, this paper contributes to a complete understanding of how supervisor developmental feedback may support or build employees' relational energy, facilitating task performance and further exploring learning demands as a boundary condition of this indirect relationship.

1. To improve the causality analysis performance, a novel causality detector based on time-delayed convergent cross mapping (TD-CCM) is proposed in this work. 2. Identify the root cause of plant-wide oscillations in process control system.

A novel causality analysis framework is proposed based on denoising and periodicity-removing TD-CCM (time-delayed convergent cross mapping). We first point out that noise and periodicity have adverse effects on causality detection. Then, the empirical mode decomposition (EMD) and detrended fluctuation analysis (FDA) are combined to achieve denoising. The periodicities are effectively removed through singular spectrum analysis (SSA). Following, the TD-CCM can accurately capture the causalities and locate the root cause by analyzing the filtered signals.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. Simulation studies show that the proposed method is able to improve the causality analysis performance. 3. Industrial case study shows the proposed method can be used to analyze the root cause of plant-wide oscillations in process control system.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. The influences of noise and periodicity on causality analysis are investigated. 3. Simulations and industrial case shows that the proposed method can improve the causality analysis performance and can be used to identify the root cause of plant-wide oscillations in process control system.