There is an urgent need to improve our understanding of the digital transformation of the construction in order to leverage the benefits of the wider adoption of the Industry 4.0 paradigm. However, there is a lack of systematic research on the digital transformation pathway of the construction industry. In view of this, this study uses the LDA theme model to explore the key influencing factors for the digital transformation of the construction industry and builds a digital comprehensive evaluation system of the construction industry with DEMATEL-ANP. The findings are as follows: Firstly, five elements of the construction industry, such as enterprise resources, enterprise capabilities, enterprise spirit, macro environment and industry environment, have an important impact on the digital transformation of the construction industry. Secondly, the ability of construction enterprises has the most significant influence on the digital transformation of the construction industry. This empirical study provides policy suggestions and an implementation framework for realizing high-quality development of the construction industry based on digital technological innovation. The study helps construction enterprises to understand the necessity of digital transformation and provides a theoretical basis and practical ideas for construction enterprises to formulate their own digital transformation strategies.

With digital transformation underway in various Chinese construction enterprises, each enterprise has progressed differently, and a clear direction for future digital transformation and upgrading is lacking. As such, the importance of measuring the level of digitization among Chinese construction enterprises is increasing. This paper presents a model for evaluating digital transformation maturity within construction enterprises. The model considers six aspects: digital strategy, digital business applications, digital technology capabilities, and so on. The digital maturity of enterprises is determined using the Analysis of Hierarchy (AHP)-Decision Making Experiment and Evaluation Laboratory (DEMATEL) method. Technical abbreviations are explained when first used. This study demonstrates that digital business applications are the most significant primary indicator, with a weight of 29.53%. The success of digital transformation in the construction industry is strongly influenced by the interconnection between digital technology and construction sites, as well as other factors such as new technical personnel, digital infrastructure, digital innovation, and innovation iteration ability. It is crucial to understand how digital technology and the construction industry can effectively connect in order to achieve success in this realm. This paper aims to enhance the digital transformation capabilities and efficiency of construction companies and boost their core competitiveness through targeted measures.

Growth management depends on an accurate understanding of an organizations’ current situation within the market in which it operates. Literature indicates that there is still inefficiency in quantitatively diagnosing the driving factors of service innovation and growth management. The purpose of this research is to identify the levels and priorities of sustainable growth management strategies with detailed measurements for industrial service innovation. The research focuses on the construction industry as the case context to scrutinize and compare various indexes and policy platforms for the evaluation of service innovation and the development of a diagnostic framework. The paper further identified the developmental obstacles of service innovation from 585 survey responses from construction enterprise representatives from Shanghai, Beijing and Xi’an in China, using average score method and entropy weight method. The data analysis identified the service innovation level and development priorities for the enterprises can assist in determining sustainable service innovation paths. The research then combined the competitive advantage characteristics method using a cluster analysis to develop a growth management framework of service innovation in the construction industry. The research results indicated that the majority of analyzed enterprises were in the second phase of their development, with clear policy opportunities for increasing levels of service innovation. However, the results also indicate the majority of sample enterprises were not encouraging the efforts of employees to strive for innovation and were lacking appropriate investment funding towards service-related innovation. These two weaker aspects offer a starting point for firm-level managers to consider when aiming to improving service innovation. The paper contributes by advancing the quantitative evaluation of growth management policies for service innovation. Furthermore, it provides possible measures for improving service innovation with particular emphasis on service innovation in project-based construction enterprises. Finally, it offers a practical diagnostic tool to improve industry level growth via increased service innovation.

Environmental regulation policies are being continuously enriched today. To effectively improve green innovation efficiency through environmental regulations, it is urgent to better understand the impact of different environmental regulations on green innovation efficiency (GIE). However, due to the defects of previous methods for measuring GIE, existing studies may have deviations when analysing the effect of environmental regulations on GIE. To fill this gap, using Shaanxi, China, as a case study, the present study proposes a network data envelopment analysis (DEA) model based on neutral cross-efficiency evaluation to accurately measure the GIE of Shaanxi during the period of 2001–2017. On this basis, this study further analysed the impact of different types of environmental regulations on GIE from three aspects: causality, evolutionary relationships, and effect paths. The results indicate that (1) the GIE of Shaanxi Province showed a “fluctuation-slow growth-steady growth” trend during 2001–2017, and after 2014, the problem of an uncoordinated relationship between technology research and design (R&D) and technology transformation began to appear; (2) there was a linear evolutionary relationship between command-and-control environmental regulation and GIE and a “U”-shaped evolutionary relationship between market-based/voluntary environmental regulation and GIE; and (3) command-and-control environmental regulation and voluntary environmental regulation affected GIE mainly at the technology R&D stage, while market-based environmental regulation ran through the entire process of green innovation activities. This study improves the evaluation methods and theoretical systems of GIE and provides the scientific basis for government decision-makers to formulate environmental regulation policies.

With the continuous development of digital transformation and upgrading of Chinese construction enterprises, it is becoming increasingly important to measure their digital level, find the problems in the enterprise transformation process, and identify the key factors of enterprise digital capacity enhancement. This paper constructs a construction enterprise digital transformation maturity evaluation model from six first-level indicators and 20 second-level indicators, including digital strategy, digital business application, digital technology capability, data capability, digital organization capability, and change management. Digital maturity is divided into five levels: business management, process operation, intelligent construction, intelligent scene application, and industrial ecological collaboration. A detailed process of digital maturity evaluation based on the method of Analytic Hierarchy Process (AHP)-Decision Testing and Evaluation Laboratory (DEMATEL) is then developed. A questionnaire survey of 25 experts is used to weight the various parameters in the model, which is then demonstrated with an example construction enterprise. The model comprehensively reflects digital levels under the background of the digital economy. Its application will help understand the advantages and disadvantages enterprises face in their digital transformation to enable targeted measures to improve their digital transformation capabilities and efficiency, enhance their core competitiveness of enterprises, and promote the development of digital transformation in the construction industry.