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Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.

This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.

This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.

To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.

It is no news that Chinese construction companies are highly motivated to invest in Africa in terms of infrastructure and construction. This influx from the beginning of the millennium marked a game-changer for infrastructural development in most African countries. This study, therefore, explores how the partnership between China and Africa has impacted the construction industry in Africa with a focus on Nigeria.

A quantitative approach was adapted for the study, which is descriptive in nature, and the primary participants of the study were core construction professionals within the Nigerian construction industry. Data was collected via a structured questionnaire, and multivariate statistics was used to analyse the data.

The study results revealed that the benefits accrued from Chinese participation in the African construction industry can be classified into three distinct categories: socio-economic development through construction, land transportation system development and construction industry development. The study further revealed that Chinese involvement has been most beneficial to the development of the land transportation system in Nigeria with more investment in the construction and maintenance of roads and railways.

The study will serve as a basis for making informed future decisions on Chinese participation in the Nigerian construction industry as it exposes the impacts of the relationship within the current system. The outcome of this study can be used to refocus the partnership to ensure the optimum development of the local construction industry. The government and other relevant agencies can use the findings from this study to ensure that there is sustainable growth in the local construction industry through Chinese participation.

The study aims to investigate the effects of intellectual capital and its constituents on the performance of listed companies operating in China's construction sector. The study also intends to examine the moderating role of digital transformation.

Hypotheses will be tested using Modified Value-Added Intellectual Capital (MVAIC). The sample will be comprised of 93 Shenzhen and Shanghai A-share listed companies within the construction industry from the period of 2015–2021. Multiple regression analysis was employed to investigate the influence of intellectual capital, its components and digital transformation on the performance of construction firms.

The study's results reveal that the performance of construction firms greatly depends on intellectual capital and its components. Furthermore, digital transformation plays a vital moderating role between intellectual capital and its components and construction firm performance.

This study addresses a critical inquiry on how construction managers can employ intellectual capital to enhance the performance of firms during digital transformation. Additionally, this research bridges this gap by guiding construction managers to concentrate on their external surroundings when examining firm performance.

By focusing on the predictors influencing construction firms' performance, this study contributes to the existing corpus of knowledge. This study employs resource orchestration theory (ROT) to determine how the different components of intellectual capital impact the performance of construction firms, with digital transformation acting as a moderating variable. This research will be valuable to researchers, construction industry professionals and policymakers.

In developing countries, construction organizations are seeking to effectively implement green innovation strategies. Thus, this study aims to assess the importance of green innovation practices and develop a measurement model for quantifying the green innovation degrees of construction firms.

A mixed-methods research approach is adopted. First, an extensive literature review is performed to identify potential green innovation items, which are then used to design a preliminary questionnaire. Next, expert interviews are conducted to pilot-test this questionnaire. Subsequently, by using a convenience non-probability sampling method, 88 valid responses are collected from construction firms in Vietnam. Then, one-sample and independent-samples t tests are employed to assess the importance of green innovation practices. Fuzzy synthetic evaluation (FSE) is also applied to quantitatively compare such practices. Finally, green innovation level (GIL) is proposed to measure the green innovation indexes and validated by a case study of seven construction firms.

This study identifies 13 green innovation variables, of which several key practices are highlighted for small/medium and large construction firms. The results of FSE analysis indicate that green process innovation is the most vital green category in construction firms, followed by green product and management innovations, respectively. As a quantitative measure, GIL could allow construction firms to frequently evaluate their green innovation indexes, thereby promoting green innovation practices comprehensively. Hence, construction firms would significantly enhance green competitive advantages and increasingly contribute to green and sustainable construction developments.

This research is one of the first attempts to integrate various green innovation practices into a comprehensive formulation. The established indexes offer detailed green innovation evaluations, which could be considered as valuable references for construction practitioners. Furthermore, a reliable and practical tool (i.e. GIL) is proposed to measure the GILs of construction firms in developing countries.

This study aims to (1) develop a structural equation model in understanding the relationships between corporate social responsibility (CSR) performance and contractor competitiveness and (2) test the moderating effect of firm sizes on this relationship.

A literature review showed an urgent need to investigate the relationship between CSR implementation and contractor competitiveness holistically. CSR and contractor competitiveness variables were identified through the literature review and discussions with experienced professionals. Using a survey questionnaire, a total of 252 completed questionnaires were received. A structural equation modeling technique was then applied to analyze the data collected. Multigroup analysis was employed to test the moderating effect of firm sizes on the relationship between CSR implementation and contractor competitiveness.

The results indicated a strong relationship between CSR implementation and contractor competitiveness. This relationship is not moderated by firm size.

This research is one of the first studies to holistically explore the linkages between CSR implementation and contractor competitiveness. The findings can be served as a solid foundation to promote CSR performance in construction firms. Contractors of different sizes are suggested to implement CSR activities to foster competitiveness.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

This paper analyzes the effect of the Belt and Road Initiative (BRI) on firm green innovation upgrading using data on Chinese firms between 2009 and 2021.

The author adopts the staggered difference-in-difference (DID) method to estimate regressions, treating the proposal of the BRI in 2013 as a policy shock. Our analysis yields few findings.

The author yields few findings. First, the BRI can significantly promote Chinese firms green innovation upgrading. Specifically, the BRI can promote firm green innovation upgrading by 0.9%. Second, the BRI mainly promotes firms green innovation upgrading by promoting firms to increase green entrepreneurship, cooperative innovation and environmental investment. Finally, the BRI has a greater impact on the green innovation upgrading of firms in the digital industrialization industry rather than digital industry and firms with low pollution emissions rather than firms with high-pollution emissions. This research indicates that the BRI is not only an important platform for sustainable development and also an important opportunity for green entrepreneurship.

First, due to the low quality of data and the lack of detailed information on some firms' patents owned after 2018, fully applying data of all years for regression was not possible. Second, the author did not construct a theoretical model to explore the impact of the BRI on green innovation upgrading of firms from the perspective of outward foreign direct investment (OFDI), which is also the direction of future research. Finally, there are still some unexplored mechanisms of the BRI on firms green innovation upgrading, which should be further explored in the future.

First, from the micro perspective, the author measures the quality of firms' green patents, further measuring the firms' green innovation upgrading. Second, the author discusses the impact of the BRI on firm green innovation upgrading with the method of staggered DID, so that the policy effect of the BRI can be more accurately evaluated. Third, the author comprehensively analyzes the mechanism of cooperative innovation and green infrastructure investment, as well as analyzing the heterogeneity from the perspective of industry digital transformation and firm pollution emissions. Lastly, the author provides specific paths for firms to make high-quality investment from the green BRI construction.

The consulting team intervenes in the integrated construction consulting (ICC) network structure centered on “client-contractor-consultant.” Team boundary-spanning behavior (TBB) driven by the network structure is crucial to project performance. This article investigated how to stimulate the consulting project performance (CPP) improvement by considering the interactive effect of network structure and TBB. To be specific, this paper explored the configuration between structural characteristics of project networks, the dimension of TBB, and project performance in ICC projects.

Network density and centrality were used to reflect network structure. This study collected 216 valid responses from construction professionals (including project managers, department managers, and project engineers) via a questionnaire survey and analyzed the data using fsQCA.

Combining with the corresponding typical project case and analysis, the results concluded four types of configurations for achieving high performance in the ICC projects. Meanwhile, network centrality, density, ambassadorial behavior, coordination behavior, and detection behavior significantly impact high consulting project performance. Matching ICC network characteristics with the TBB is important. There are also three low performance configurations for the ICC projects. Low performance state also occurs when network centrality or density and coordination behavior is simultaneously low. Only the right match between the network characteristics and TBB can produce high consulting project performance.

The network centrality and density, the implementation of TBB vary, and the paths to achieve high consulting project performance are different. Clients, ICC projects, and consulting teams should choose the appropriate development paths according to the actual situation. (1) Clients should commit to applying the ICC project model with high network centrality, density, and coordination behavior of ICC enterprises to promote project performance. (2) Consulting enterprises should carry out ICC business based on detecting behavior and coordinating behavior. (3) The market should cultivate head consulting enterprises with independence and integration, and bring into play the effectiveness of consulting team ambassadorial behavior.

Comparing the results of the four high CPP configurations, the network structure characteristics are essential, which means that in the Chinese consulting practice between the owner and the consulting firm pay attention to the use of appropriate ICC organizational structure model and arrange the degree of centralization of authorized responsibilities. Coordination behavior is necessary to achieve high CPP. Therefore, Chinese consulting firms should pay attention to effective communication and exchange with project contractors in order to get high CPP in conducting business; meanwhile, enabling behavior can achieve high CPP both in the presence and absence of configuration H1 and H4, which indicates that enabling behavior has substitution effect. Comparing the three low CPP configurations also contrarily confirms the indispensability of coordinating behavior. Comparing the results of high and low CPP configurations, the TBB is seriously missing and not properly applied in CPP enhancement. In detail, Chinese consulting firms have been regarded as independent third parties providing services, and less attention has been paid to the TBB of Chinese consulting firms in past practice, thus leading to the dilemma of inadequate empowerment of consulting firms due to their unclear status. To solve this dilemma, the findings of this paper offer a solution at the micro level to change the previous perception of consulting and demonstrate that Chinese consulting practice needs to pay attention to TBB with owners and contractors, and apply it well to enhance the reputation, management consulting level and capability, and experience and expertise of consulting firms to achieve high CPP.

The research results changed from the previous bilateral project governance to a new perspective of network embedding. It provided a theoretical basis for the improvement path of high consulting project performance, as well as providing ideas for clients on the organizational design of ICC projects. On the other hand, it provided a practical reference for TBB positioning of ICC enterprises for transformation and upgrading development.

This study aims to explore the extent to which Chinese multinational enterprises (MNEs) rely on supranational institution – the Belt and Road Initiative (BRI) – versus host country institutional quality to navigate their foreign location choice.

This study uses a conditional logit regression model using a sample of 1,302 greenfield investments by Chinese MNEs in 54 BRI participating countries during the period 2011–2018.

The results indicate that as a supranational institution, the BRI serves as a substitution mechanism to address the deficiencies in institutional quality in BRI participating countries, thereby attracting Chinese MNEs to invest in those countries. In addition, the BRI’s substitution effect on host country institutional quality is more pronounced for large MNEs, MNEs in the manufacturing industry and MNEs in inland regions.

This study expands the understanding of the BRI as a supranational institution for MNEs from emerging markets and reveals its substitution effect on the host country institutional quality. Furthermore, it highlights that MNEs with diverse characteristics gain varying degrees of benefits from the BRI.

Under the trend of global economic integration and the new context of stagflation, frequent fluctuations in international interest rates are exerting far-reaching impacts on the world economy. In this paper, the transmission mechanism of the impact of fluctuations in international interest rates (specifically, the American interest rate) on the bankruptcy risk in China's pillar industry, the construction industry (which is also sensitive to interest rates), is examined.

Using an improved contingent claims analysis, the bankruptcy risk of enterprises is calculated in this paper. Additionally, an individual fixed-effects model is developed to investigate the mediating effects of international interest rates on the bankruptcy risk in the Chinese construction industry. The heterogeneity of subindustries in the industrial chain and the impact of China's energy consumption structure are also analysed in this paper.

The findings show that fluctuations in international interest rates, which affect the bankruptcy risk of China's construction industry, are mainly transmitted through two major pathways, namely, commodity price effects and exchange rate effects. In addition, the authors examine the important impact of China's energy consumption structure on risk transmission and assess the transmission and sharing of risks within the industrial chain.

First, in the research field, the study of international interest rate risk is extended to domestic-oriented industries. Second, in terms of the research content, this paper is focused on China-specific issues, including the significant influence of China's energy consumption structure characteristics and the risk contagion (and risk sharing) as determined by the current development of the Chinese construction industry. Third, in terms of research methods a modified contingent claim analysis approach to bankruptcy risk indicators is adopted for this study, thus overcoming the problems of data frequency, market sentiment and financial data fraud, which are issues that are ignored by most relevant studies.