The High-Quality Development of the Construction Industry in the Context of the Digital Economy—Based on the Mediating Effect of Entrepreneurship

Abstract

The digital economy is an important engine in leading the high-quality development of the economy, and entrepreneurship is an endogenous force propelling economic growth. These factors are essential drivers for advancing the transformation and upgrading of the construction industry and improving efficiency. This study integrates entrepreneurship into the analytical framework of industrial development and explores the primary pathways and theoretical mechanisms of the digital economy for the high-quality development of the construction industry from the dimensions of entrepreneurial innovation spirit and entrepreneurial pioneering spirit. On this basis, we empirically test the role mechanism between the digital economy, entrepreneurship, and the high-quality development of the construction industry. The results of this study indicate that (1) the digital economy significantly promotes the high-quality development of the construction industry through an improvement in technical efficiency; (2) the innovation and entrepreneurship of entrepreneurs are important mechanisms for the digital economy to promote the high-quality development of the construction industry, and at this stage, entrepreneurial spirit promotes more than the spirit of innovation; and (3) the development of the digital economy plays a greater role in enhancing low-productivity regions and the central and eastern regions, and the inclusive characteristics of the digital economy are beginning to emerge.

1. Introduction

The construction industry is a cornerstone of China’s national economy. Its high-quality development is not only crucial for the overall high-quality development of the national economy but also serves as a vital prerequisite and guarantee for the high-quality development of other industries and sectors within the national economy [1]. In recent years, the high-quality development of the construction industry has attracted attention at both central and local levels. The Ministry of Housing and Urban-Rural Development of the People’s Republic of China issued the Guiding Opinions on Promoting the Synergistic Development of Intelligent Construction and Construction Industrialization (Jianshi [2020] No. 60), which puts forward that, “By 2025, the policy system and industrial system for the synergistic development of intelligent construction and construction industrialization will be initially formed, and the levels of construction industrialization, digitization, and intelligence will be significantly improved. The construction industry Internet platform has been established with a solid industrial foundation, advanced technical equipment, enhanced scientific and technological innovation capacity, and the level of building safety and quality has comprehensively improved, labor productivity has significantly improved, energy and resource consumption as well as pollution emissions have been notably reduced, leading to a significant positive impact on environmental protection” [2]. This shows that the future of China’s construction industry needs to rely on the “digital economy” as an emerging force to achieve high-quality development and industrial transformation.

The digital economy refers to a set of economic activities that use digital knowledge and information to assess the necessary factors of production, contemporary information networks, important carriers, and effective information and communication technologies as the main force behind increasing productivity and optimizing the structure of the economy [3]. Entering a new stage of high-quality development, the digital economy, based on new-generation information technology, is reshaping the economic structure with an unprecedented speed, scale, and scope of development. It has become one of the core growth poles of the national economy. The state attaches great importance to the development of the digital economy. In the “14th Five-Year Plan”, it is clearly stated that accelerating the development of the digital economy is a practical necessity to build a new engine for high-quality development. In the era of the digital economy, the development of the Internet has led to the emergence of new business forms, technologies, and models. This has shattered traditional time and space constraints, facilitating the cross-border allocation of capital, technology, talent, and other resources. Entrepreneurs now have excellent opportunities to leverage the Internet, big data, cloud computing, blockchain, and other digital technologies [4]. Under the new normal of China’s economy shifting to high-quality development, entrepreneurship has become an important driving force in promoting high-quality economic development, improving people’s well-being and fostering prosperity for the whole society. The report of the 19th CPC National Congress points out that “stimulating and protecting entrepreneurship and encouraging more social subjects to engage in innovation and entrepreneurship” are important elements of deepening supply-side structural reform. At present, research on entrepreneurship has gradually shifted from the micro-individual to the macro-regional level. Correspondingly, the focus of research has transitioned from emphasizing the “quantity” of entrepreneurship that impacts economic growth to the “quality” of entrepreneurship that influences economic development.

Obviously, the digital economy and entrepreneurship have become the “typical factors” and “key variables” for China’s economy to enter the stage of high-quality development. How can we effectively leverage the digital economy to promote high-quality development in the construction industry? In the era of the digital economy, how can entrepreneurship enable the high-quality development of the construction industry? Studying and answering these questions can offer empirical evidence to assess the impact of the digital economy on the high-quality development of the construction industry. It can provide valuable insights on how to effectively stimulate and nurture entrepreneurship in the new era to enhance the high-quality development of the construction industry. Subsequently, it can offer decision-making references for achieving high-quality development in the region and promoting the coordinated development of the region.

2. Literature Review

2.1. Digital Economy and High-Quality Development of the Construction Industry

At present, the digital economy has become an important force in promoting the high-quality development of various industries. The digital economy, primarily based on the Internet, is gradually emerging as a significant component of the national economy. For research related to the digital economy and the high-quality development of the construction industry, scholars mainly focus on the role and application of digital technology in the construction industry, as well as the current situation and mechanisms of the digital economy affecting the high-quality development of the construction industry. However, there is still a lack of relevant empirical research accurately assessing the impact of the digital economy on the high-quality development of the construction industry, which is still in its early stages.

Li Rong [5], discussing the integration and development of the digital economy and the real economy, emphasized that this integration and development of the digital economy and construction industry will reconstruct the technological foundation and enhance production efficiency. Forcael E et al. [6] and Craveiro F et al. [7] highlighted the role of digital technology and its current application status in the construction industry. They illustrated that intelligent building technology can boost energy utilization efficiency, enhance user experience, and improve building sustainability. Itami H [8] suggested that digital transformation in the construction industry aims to upgrade the entire enterprise business process, innovate the business model, and enhance enterprise management. The empirical study by Zhang Aiguo et al. [9] shows that the degree of obstacles to the coupling and coordination of the digital economy and the high-quality development of the construction industry varies significantly.

The discussion on the intermediate mechanism of the digital economy affecting the high-quality development of the construction industry mostly revolves around BIM, the Internet of Things, big data, cloud computing, “construction industry +”, and other new models. For example, BIM, the Internet of Things, and artificial intelligence can enhance the efficiency and quality of building design, construction, and operational management [10]. The application of big data, cloud computing, and other technologies can optimize the procurement and distribution process of construction materials and improve the quality and safety of construction materials [11]. The emergence of new models, such as “construction industry+”, can promote the high-quality development, transformation, and upgrading of the construction industry.

2.2. Digital Economy and Entrepreneurship

Digital economy and entrepreneurship are two important areas of contemporary economic research. Entrepreneurs, as important organizers of economic activities and the backbone of innovation and entrepreneurship, have always been the focus of mainstream economics. However, only individual scholars have conducted research on how the digital economy affects entrepreneurship. Through empirical analysis, Wang Zhi et al. [12] point out that the digital economy significantly enhances entrepreneurship through both direct and indirect pathways. The positive impact of the digital economy on entrepreneurship is more pronounced in northern cities compared to southern cities. Additionally, the promotional effect of the digital economy on entrepreneurship is more evident in peripheral cities compared to municipalities directly under the central government and sub-provincial cities. The findings of Zheng Jinhui et al. [13] indicate that the enhancement of digital finance can stimulate entrepreneurship and, consequently, promote high-quality economic development. Some scholars also argue that digital transformation plays a partial mediating role between entrepreneurship and innovation performance [14].

In recent years, there has been a gradual increase in academic research on the influencing factors of entrepreneurship. This research mainly focuses on traditional factors such as individual microtraits, the institutional environment, and the cultural environment [15]. In the era of the digital economy, the concept of Internet thinking, characterized by innovation, equality, and interconnection, aligns closely with entrepreneurship. Consequently, some scholars have delved into the impact of the digital economy on innovation and entrepreneurship through the lens of the Internet and information technology. The “innovation school” represented by Schumpeter emphasizes the entrepreneurial spirit of innovation and posits that innovation, defined as a novel combination of resource elements, is achieved by entrepreneurs. It suggests that entrepreneurship is fundamentally characterized by risk-taking and an innovative mindset [16]. In terms of the relationship between the Internet and innovation, most of the literature affirms the spillover effect of the Internet and explores the relationship between the two from a non-linear perspective. The Internet and Internet-based information technology applications can promote the growth of entrepreneurial innovation spirit by enhancing production efficiency and innovation performance, transforming the way enterprise innovation resources are integrated and lowering the transaction and governance costs of enterprise innovation [17]. The Internet can foster more entrepreneurial opportunities, enrich entrepreneurial resources, and promote entrepreneurship by boosting entrepreneurial activity, speeding up the exchange of information and the spread of ideas and facilitating knowledge sharing through various channels [18]. In addition, other scholars have discussed the regionally heterogeneous impact of the Internet on entrepreneurship. Scholars like Forman [19] have found that the Internet’s impact on entrepreneurship is more significant in rural areas. Cumming and Johan [20] argue that the Internet can stimulate regional entrepreneurial activity through pre-existing entrepreneurial clusters, promoting urban entrepreneurship to a greater extent. Other scholars have found that the breadth of coverage, depth of use, and level of support services of digital finance all have a significant effect on entrepreneurship [21].

2.3. Entrepreneurship and High-Quality Development of the Construction Industry

In entrepreneurship research, scholars focus on entrepreneurs’ leadership [22], team management [23], and organizational innovation [24]. Entrepreneurship research also delves into the influence of the social environment, institutions, and policies on entrepreneurial behavior, along with the contribution of entrepreneurship to economic growth and social development [25]. However, the impact of entrepreneurship on the high-quality development of the construction industry has not yet attracted the attention of academics, and only a few scholars have explored this aspect. Sun Jian et al. [26] point out that enterprises with higher levels of entrepreneurship are more innovative and flexible and can better cope with market competition. This, in turn, enhances the overall competitiveness of the construction industry. At the same time, entrepreneurship can stimulate entrepreneurs’ willingness and behavior, promoting the development and economic growth of the construction industry. Marcin W et al. [27] identified entrepreneurship as a key factor driving innovation in the construction industry. Kauskale L et al. [28] highlighted that entrepreneurship influences the sustainable development of the construction industry.

2.4. Research Gaps

The limitations of the current research can be identified by reviewing the relevant literature. Firstly, there is a lack of comprehensive research on the digital economy and the high-quality development of the construction industry. At present, most studies focus on the application of digital technology in the construction industry, but there is a lack of in-depth discussion on the overall impact and mechanism of the digital economy on the high-quality development of the construction industry. Especially in the context of the digital economy, the balanced and coordinated development of the construction industry has a far-reaching impact on achieving regional coordinated development and alleviating the main social contradictions of imbalance and inadequacy. Therefore, more comprehensive research is needed to uncover the internal logic and developmental trajectory of the relationship between the digital economy and the construction industry. Secondly, the role of entrepreneurship and the digital economy in the construction industry is neglected. Currently, there is limited academic literature that explores the mechanisms through which the digital economy influences the high-quality development of the construction industry, particularly through the mediating effect of entrepreneurship.

Therefore, this paper will further explore the relationship between the digital economy and the high-quality development of the construction industry. This paper puts entrepreneurship into the analysis frame and probes into the intermediary role of entrepreneurship from two dimensions: the entrepreneurial innovation spirit and the entrepreneurial pioneering spirit.

Based on the above shortcomings, the possible marginal contributions of this study are as follows: first, it constructs a theoretical model of the digital economy affecting the high-quality development of the construction industry, providing a theoretical analytical framework for related research; second, it empirically examines the relationship between the digital economy and the high-quality development of the construction industry, enriches the research on the influencing factors of the high-quality development of the construction industry, and supplements and improves the theoretical mechanism of the digital economy affecting the high-quality development of the construction industry; third, based on the two perspectives of entrepreneurial innovation and entrepreneurial pioneering spirit, the mediating mechanism of the digital economy on the high-quality development of the construction industry is sorted out to make up for the insufficiency of the existing literature on the study of indirect paths and provide empirical references for the high-quality development of the construction industry.

3. Theoretical Analysis and Research Hypotheses

The hyper-geographical features and information-sharing capabilities of the digital economy enable the construction industry to improve resource allocation and expand effective supply more efficiently. The wide application of digital technology has significantly advanced the development of informatization, intelligence, and visualization, thereby promoting the creation of sustainable and eco-friendly buildings. The digital economy can impact the high-quality development of the construction industry directly through its characteristics and indirectly by influencing the entrepreneurial spirit of innovation and entrepreneurship. The mechanism of the digital economy’s impact on the high-quality development of the construction industry can be divided into two aspects: direct and indirect mechanisms.

3.1. The Direct Mechanism of the Digital Economy in the High-Quality Development of the Construction Industry

The digital economy is an economic system in which industrial digitization and digital industrialization interact, driven by a new generation of information technology such as the Internet, big data, cloud computing, blockchain, intelligent construction, and so on. The digital economy transcends the constraints of time and space in the physical world, enhancing the efficiency of information production and dissemination. Its direct impact on the high-quality development of the construction industry is primarily manifested in the following four aspects:

Firstly, the digital economy improves the efficiency of building lifecycle management. The application of digital economy technologies such as BIM, the IoT, and AI improves the efficiency of the design, construction, and operation phases of a building project. Through digital modeling technology, construction projects can be comprehensively simulated and optimized in the design phase to reduce design problems and construction errors. During the construction phase, the digital collaboration platform enables real-time communication and information sharing, enhancing construction efficiency and quality control. During the operation phase, the real-time monitoring and maintenance of construction equipment can be conducted using IoT technology to enhance operational efficiency and prolong the service life of the equipment. This significantly improves the overall management efficiency of construction projects and promotes the construction industry towards high-quality development.

Secondly, the digital economy has accelerated the transformation and upgrading of the construction industry. The digital economy has brought innovative opportunities to the construction industry. Intelligent building technology has enhanced the comfort, sustainability, and safety of buildings by incorporating sensors and control systems. This technology enables functions like energy management, indoor environment control, and safety monitoring. It also improves energy utilization efficiency by intelligently matching centralized energy supply with distributed energy consumption. Collaboration among all parties in the supply chain can also enhance transparency and efficiency, leading to increased effectiveness in the supply chain. The application of digital economy technologies enables the construction industry to better respond to market demand and environmental challenges, enhancing the competitiveness of the construction industry, thus empowering its high-quality development.

Thirdly, the digital economy has broken down traditional industry barriers and promoted the integration of the construction industry with other sectors. The development of the digital economy has facilitated the deep integration of the construction industry with the Internet, finance, services, and other industries, enabling it to better align with the development requirements of the digital economy era. Through the application of digital technology, the construction industry can collaborate with Internet platforms to drive innovation in construction finance. This includes blockchain-based construction supply chain finance, intelligent investment, and financing platforms, among others, to offer construction enterprises additional financing channels and financial services.

China has a vast territory, and there are significant differences between regions in terms of factor endowment, human capital level, and institutional policies. These differences will have a significant impact on the spread and development of the digital economy in various regions. At the same time, because the digital economy has varying impacts and mechanisms on economic growth at different stages of development, its influence on the high-quality development of the construction industry will exhibit heterogeneity across different regions and developmental stages.

Based on the above analysis, the following research hypothesis is proposed:

H1: 

The digital economy can significantly enhance the technical efficiency of the construction industry, thereby improving the total factor productivity of the sector. Moreover, there is regional heterogeneity in this effect.

3.2. The Mediating Role of Entrepreneurship in the High-Quality Development of the Construction Industry

Cartner [29] pointed out that the fundamental difference between entrepreneurs and general managers is that entrepreneurs are the creators of new organizations; thus, creating organizations is a key aspect of entrepreneurship. With the gradual deepening of the discussion, the theoretical connotation of entrepreneurship is becoming richer and richer. However, as of now, there is still no standardized definition. Academics have reached a consensus on the fundamental characteristics of entrepreneurship. Entrepreneurship is generally defined by a sense of innovation, the willingness to take risks and recognize opportunities, strong management skills, and a deep sense of purpose and commitment. In the context of the new industrial revolution, digitalization is reconfiguring the enterprise innovation system and creating fertile ground for nurturing entrepreneurship. Whether it is product innovation, production method innovation, market innovation, raw material innovation, or organizational innovation, in the new business civilization system of the digital economy era, all of them exhibit new characteristics. These include a greater emphasis on openness, trust, transparency, sharing, and responsibility. In addition, in the context of the digital economy and the high-quality development of the construction industry, entrepreneurs are driven by multiple factors. On the one hand, the motivation of pursuing economic interests prompts entrepreneurs to constantly seek methods to reduce costs and improve efficiency, thereby promoting the high-quality development of the construction industry. On the other hand, the motivation of realizing personal value and promoting industry progress makes entrepreneurs pay more attention to innovation and social responsibility, bringing higher-quality products and services to the construction industry.

Based on the above research, combined with the current context, this study begins by examining the two aspects of entrepreneurial innovation spirit and entrepreneurial pioneering spirit. It aims to elucidate the theoretical mechanism through which the digital economy influences entrepreneurial spirit and subsequently impacts the high-quality development of the construction industry.

3.2.1. The Mediating Role of Entrepreneurial Innovation Spirit

The development of the digital economy can effectively promote the dissemination of information across time and space and improve the efficiency of information processing and integration, thereby stimulating entrepreneurial spirit and enhancing scientific and technological innovation capabilities [30]. On the one hand, entrepreneurs are the primary drivers of technological innovation, which can lead to advancements in production technology and green technology. The former can enhance the efficiency of input and output factors in existing enterprises, achieve economies of scale, and generate excess profits. The latter can decrease pollution consumption in enterprises and promote the green development of the construction industry. On the other hand, entrepreneurial innovation spirit can empower the construction industry through organizational management innovation for high-quality development. Entrepreneurs, as the orchestrators of resources, can introduce new systems into enterprises for organizational innovation. They can change the organizational structure and association mode and guide the production and innovation behavior of enterprises to shift gradually from closed and exclusive to open and inclusive. Entrepreneurs can promote the transformation of the enterprise organization mode into a collaborative innovation network of cross-field and multi-objects. This can enhance organizational collaboration, improve internal operational efficiency, and drive the construction industry towards greater efficiency, ultimately fostering high-quality development in the construction industry. Secondly, the integration of the innovation-driven development strategy with the development of strategic emerging industries is beneficial for promoting the deep integration of the digital economy and the real economy. It also enhances entrepreneurial innovation vitality, attracts high-skilled talents [31], and nurtures entrepreneurial innovation spirit by stimulating innovative thinking, optimizing the innovation ecosystem, and other means. In the era of the digital economy, Internet-based information dissemination is more open and timelier. This enables entrepreneurs to track technological advancements and dynamics more rapidly and extensively, strengthen continuous communication and exchange with the outside world, accelerate the sharing and collision of ideas, and stimulate innovative thinking. In addition, the digital economy can catalyze entrepreneurial innovation by optimizing the innovation ecosystem. With the increasing technological complexity, individual enterprises find it challenging to meet the technological and financial requirements for innovation. Entrepreneurial innovation increasingly depends on the material, institutional, and relational environments. The digital economy can simplify the innovation process, optimize the innovation environment, and promote an entrepreneurial innovation spirit by establishing an open innovation environment, integrating internal and external innovation resources organically and enabling open innovation in the stages of research and development, experimentation, construction, and marketization.

3.2.2. The Mediating Role of Entrepreneurial Pioneering Spirit

Stimulating the entrepreneurial pioneering spirit is one of the key mechanisms for the digital economy to empower the high-quality development of the construction industry. The popularization and application of digital technology can equip the construction industry with a high level of technological innovation and construction efficiency, give rise to new business forms and modes, and stimulate the expanding scope of the market. These advancements provide more opportunities for the development of entrepreneurial activities. Stimulated by new types of market demand, employment opportunities will expand towards entrepreneurship. Entrepreneurs will be able to leverage digital platforms to identify market gaps, seize potential entrepreneurial opportunities, and boost entrepreneurial activity. The strong connectivity and sharing in the digital economy can significantly reduce information asymmetry, provide entrepreneurs with a more reliable information source and base, and facilitate accurate matching between entrepreneurial projects and entrepreneurs. This enables entrepreneurs to rectify their mistakes promptly and enhance their entrepreneurial success rate. In addition, new financing methods such as digital finance are flexible and convenient, providing crucial financial support for entrepreneurial activities. This helps alleviate the issue of financing difficulties and transforms some entrepreneurs from being paid employees to independent entrepreneurs, thereby boosting entrepreneurial enthusiasm. In this sense, the digital economy has become a type of entrepreneurial incentive that stimulates entrepreneurs’ “risky” business activities.

Based on the above analysis, the theoretical mechanism of the mediating role of entrepreneurship is illustrated in Figure 1, and the following research hypothesis is proposed:

H2: 

The digital economy can further stimulate entrepreneurs’ innovation and pioneering spirit, thus empowering the high-quality development of the construction industry.

4. Research Design

4.1. Model Building

4.1.1. Main Models

Benchmark regression modeling enables the explicit establishment of the relationship between independent and dependent variables, facilitating the direct testing of research hypotheses. According to the theoretical mechanism analysis provided above, the following basic model is constructed to illustrate the impact mechanism of the digital economy on the high-quality development of the construction industry:

(1)$\mathit{ln}GTF{P}_{\mathrm{it}}={\alpha }_0+{\alpha }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\alpha }_2\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

where GTFP_it is concerned, it represents the high-quality development level of the construction industry of province i in period t.

where Dig_it is considered, it stands for the development level of the digital economy of province i in period t.

where X_it is involved, it represents a series of control variables.

where μ_i is related, it indicates the individual fixed effect that does not change over time.

where δ_i is in question, it represents the time fixed effect.

where ε_it is referred to, it represents the random disturbance term.

Further, GTFP_it is decomposed into technical change (tc_it) and technical efficiency change (ec_it), which can be further subdivided into pure technical efficiency change (pec_it) and scale efficiency change (sec_it). The specific decomposition is shown in Figure 2.

To clarify the primary focus of the digital economy within total factor productivity, the model is constructed based on four dimensions. This approach aims to explore the specific dimensions of the digital economy that impact total factor productivity:

(2)$\mathit{ln}t{c}_{\mathrm{it}}={\alpha }_0+{\alpha }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\alpha }_2\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

(3)$\mathit{ln}e{c}_{\mathrm{it}}={\alpha }_0+{\alpha }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\alpha }_2\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

(4)$\mathit{ln}pe{c}_{\mathrm{it}}={\alpha }_0+{\alpha }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\alpha }_2\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

(5)${\mathit{lnsec}}_{\mathrm{it}}={\alpha }_0+{\alpha }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\alpha }_2\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

4.1.2. Intermediation Mode

In order to further test whether the digital economy affects the level of high-quality development of the construction industry by enhancing entrepreneurship, the mediating mechanism is tested using the stepwise regression method drawing on the study of Baron and Kenny [32]. Model (6) is constructed to test the impact of the digital economy on entrepreneurial innovation spirit and entrepreneurial pioneering spirit. Model (7) is constructed to examine the impact of the digital economy and entrepreneurial spirit on the high-quality development of the construction industry:

(6)$\mathit{ln}Entr{e}_{\mathrm{it}}={\beta }_0+{\beta }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\beta }_2\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

(7)$\mathit{ln}GTF{P}_{\mathrm{it}}=t{\gamma }_1\mathit{ln}Di{g}_{\mathrm{it}}+{\gamma }_2\mathit{ln}Entr{e}_{\mathrm{it}}+{\gamma }_3\mathit{ln}{X}_{\mathrm{it}}+{\mu }_{\mathrm{it}}+{\delta }_{\mathrm{it}}+{\epsilon }_{\mathrm{it}}$

In Models (6) and (7), Entre represents entrepreneurship, including entrepreneurial innovation and entrepreneurial pioneering spirit.

The mediating effect test logic in this model is shown in the following Table 1:

4.2. Indicator Selection and Explanation of Variables

4.2.1. Explained Variables

The explanatory variable in this study is the high-quality development level of the construction industry (GTFP). At present, there are two main methods to measure the level of high-quality development of the construction industry: total factor productivity (TFP) and the construction of an evaluation index system. TFP is widely favored by academics due to its convenience in calculation and high efficiency in reflecting economic efficiency. The continuous enhancement of TFP signifies the technological progress of the construction industry and the effective allocation of various production factors. Former scholars primarily measured and decomposed total factor productivity from two perspectives: the Solow residual method [33] and the non-parametric method [34]. However, numerous assumptions may result in relatively complex measurement content and lead to more pronounced errors in the results. Therefore, this study draws on the research of Wei et al. [35] and utilizes Maxdea 9 to apply the DEA–Malmquist method to integrate green expectations into the index system. It measures the Malmquist index as a proxy indicator for the high-quality development of the construction industry, denoted as GTFP. The Malmquist index model is derived from the DEA model, which differs from the methods described in the previous section. While the previous methods can only analyze and compare the static analysis of each data index at a specific point in time, the Malmquist index model can dynamically analyze panel data. This allows for the observation of the trend of change for each decision-making unit during the study period. The Malmquist index model comprises the product of technical efficiency change (EC) and technical change (TC). The TC reflects the technological advancement or regression of the decision unit during the study period compared to the previous period. Under the premise of variable returns to scale, the TC can be decomposed into the product of pure technical efficiency (PEC) and scale efficiency (SEC). This decomposition allows for further exploration of the factors influencing the technical progress of the decision unit.

The level of high-quality development in the construction industry is influenced by various factors, including the establishment of a high-quality talent development mechanism, the level of IoT integration in equipment and facilities, digital business capabilities, digital vision development, and the ability to acquire market information. Considering the accuracy and comprehensiveness of the measurement, as well as the availability of the data, according to the research by Zhang Songyan and other scholars [36], the total assets of the construction industry, the total power of mechanical equipment, the energy input in construction, and the number of people working in the construction industry are selected as input indicators. The total output value and carbon dioxide emissions of the construction industry were selected as expected output and non-expected output indicators. The specific indicator system is shown in Table 2.

4.2.2. Explanatory Variables

The explanatory variable in this study is the level of digital economy development (Dig). At this stage, academics have not yet formed a unified understanding of the connotation of the digital economy. Drawing on the research of Zhao Tao and other scholars [37], we have selected fundamental indicators from the digital infrastructure, the digital talent reserve, and the digital economic environment to establish a comprehensive index system for the digital economy. We utilize principal component analysis to reduce dimensionality and obtain a comprehensive index representing the level of development of the digital economy, denoted as Dig. The specific index system is shown in Table 3.

4.2.3. Mediating Variables

Entrepreneurship is the mediating variable in this paper. Most of the previous studies have focused on the theoretical aspects of entrepreneurship. However, due to the multifaceted nature of entrepreneurship, which includes the spirit of risk-taking, the ability to seize opportunities, innovation, and an entrepreneurial mindset, there is a lack of uniformity in the measurement methods and selection of indicators for entrepreneurship. However, related studies focus on assessing the level of entrepreneurship or innovation, which cannot be examined uniformly. Entrepreneurship encompasses new aspects such as patriotic spirit and social responsibility, but its fundamental essence and most intuitive manifestation are innovation and entrepreneurial activities. Innovation and entrepreneurship are inseparable; innovation serves as the method and means of entrepreneurship, while entrepreneurship represents the goal and realization of innovation. Therefore, based on the theoretical analysis of the previous article and considering the availability of data, this paper draws on the research of Li Hongbin et al. [25] to analyze and measure entrepreneurship by focusing on two dimensions, innovation and entrepreneurship:

• (1). Entrepreneurial innovation spirit (Inn): This study uses the number of patents granted to measure the entrepreneurial innovation spirit. Specifically, it is measured by the ratio of the sum of the number of patents granted for three types of patents: invention patents, utility model patents, and design patents. The reason is that the patent grant data are valuable due to their objectivity, ease of collection, and ability to accurately represent the innovation output of each province and city.

• (2). Entrepreneurial pioneering spirit (Ent): Entrepreneurial pioneering spirit refers to a set of qualities and attitudes that drive entrepreneurs to take risks, create new ventures, and pursue opportunities. Entrepreneurs increase employment levels and generate social wealth through entrepreneurship. Entrepreneurial pioneering spirit is not only demonstrated through the establishment of individual units but also through the creation of private enterprises. Therefore, the proportion of employment in individual units and private enterprises relative to total employment is used as a measure of entrepreneurial pioneering spirit.

4.2.4. Control Variables

In order to reduce the impact of omitted factors on the model setting, combining the analysis of theoretical mechanisms with the practices of the existing literature [38], the following control variables are selected: green development level (Gre), expressed as the green coverage rate of urban built-up areas; financial development level (Fin), expressed as the ratio of end-of-year deposit and loan balances of financial institutions to the GDP; human capital (Man), expressed as the average number of years of schooling between provinces; the level of government intervention (Gov), expressed as the share of government fiscal expenditure in the total budget; city size (USca), expressed as the population density of the city; and labor productivity (LP), expressed as the ratio of the output or value of construction products and their corresponding labor consumption.

4.3. Data Sources and Descriptive Statistics

The data used in the empirical analysis come from the National Bureau of Statistics, National Research Network, Wind Database, and Cathay Pacific Database, as well as the China Industrial Statistical Yearbook [39], China Population and Employment Yearbook [40], China Environmental Statistical Yearbook [41], China Tertiary Industry Statistical Yearbook [42], and China Regional Economic Statistical Yearbook. Since the data after 2011 are more complete, the final statistics include panel data from 30 provinces (autonomous regions and municipalities) from 2011 to 2021. Tibet, Macao, Hong Kong, etc., are not included due to missing data. For the very few missing objective data, the linear prediction method and the average value method, which are commonly used in academia, are utilized for completion. To eliminate the effect of heteroscedasticity, the data were logarithmized, and the variables were analyzed with descriptive statistics using Stata16 software. The results are presented in Table 3. Analysis of the data in Table 4 reveals that all sample sizes are 330, there are no missing values in the data, and the data represent balanced panels. During the sample period, the average value of the high-quality development level of the construction industry is 0.269. The maximum value is 1.328, the minimum value is −0.354, and the standard deviation is 0.306. These values indicate significant disparities in the level of high-quality development across various provinces, highlighting uneven development levels within the construction industry. The standard deviation of the level of development of the provincial digital economy is 0.739. The average value is 1.041, with a minimum value of −1.312 and a maximum value of 2.847. The substantial difference between the maximum and minimum values indicates significant variation in the data, suggesting that provinces with advanced digital economy development have a distinct advantage.

In terms of time-series characteristics, the average value of high-quality development water in the construction industry increased from 1 in 2011 to 2.14 in 2021, showing an overall gradual upward trend (refer to Figure 3). The level of digital economy development shows a rising trend year by year during the sample period, and the growth trend is relatively stable. Specifically, the average value of digital economy development increased from 0.47 in 2011 to 1.91 in 2021, showing an average annual growth rate of 14.4%. This trend aligns with the research conducted by Wan Xiaoyu and Luo Yanqing [43]. Further, from the scatter plot and the fitted straight line (refer to Figure 4) depicting the digital economy index and the level of high-quality development in the construction industry, it is evident that there is a clear positive correlation between the two. It is intuitive that enhancing the regional digital economy development level contributes to improving the high-quality development level of the construction industry. Of course, to determine if the relationship between the two is genuine and dependable, further rigorous empirical testing and analysis are required.

5. Empirical Analysis

5.1. Benchmark Regression

The results of the baseline regression analysis of the research hypotheses using the model and measurement data above are shown in Table 5. Columns (1) and (2) in Table 5 display the results before and after incorporating the control variables. The regression results show that the coefficients of the digital economy are 0.266 and 0.326. In the process, the coefficients of the digital economy are increasing. This indicates that the results are robust. On the other hand, it shows that the control variables selected in this study are representative. At the same time, the regression results passed the 1% significance level test, which is significantly positive. This indicates that the development of the digital economy has a positive impact on the high-quality development of the construction industry, partially verifying hypothesis H1. Columns (3) and (4) present the decomposition analysis of the internal structure of the Malmquist index in the construction industry. The regression coefficients of the digital economy on TC and EC are 0.066 and 0.621, respectively. The EC is statistically significant at the 1% level. This indicates that the impact of the digital economy on the high-quality development of the construction industry is primarily reflected in an improvement in technical efficiency. Columns (5) and (6) further estimate the regression coefficients of SEC and PEC to investigate the specific impact of digital economy development on technical efficiency.

5.2. Heterogeneity Analysis

The regression analysis above primarily focuses on the average effect. However, various regional development characteristics can influence the impact of the digital economy on the high-quality development of the construction industry. This study focuses on analyzing the heterogeneous effects of the digital economy in the construction industry from two perspectives: high and low GTFP and regional advantages. The results are presented in Table 6.

The level of construction GTFP is divided with the help of the median. Columns (1) and (2) in Table 6 show that the digital economy has a slightly stronger impact on regions with low levels of construction GTFP. Columns (3–5) indicate that the digital economy in the east, center, and west has a positive impact on regional construction GTFP, with the promotional effect being the greatest in the east, followed by the center, and then the west. Among them, the impact of the digital economy’s level of development in the western region on the high-quality development of the construction industry is not significant. The results of Columns (6) and (7) indicate that, in comparison to the south, the digital economy in the north can more efficiently improve the level of GTFP in the construction industry. So far, hypothesis H1 has been fully verified.

5.3. Robustness Test

In order to verify the reliability of the above conclusions, drawing on the research of previous scholars [44], this study adopts three methods for robustness testing. First, the shrinking tail treatment is used. To prevent extreme values in the data from affecting the regression results, all variable sample values undergo upper and lower 1% trimming. The outcomes are presented in Table 7. Second, special samples are excluded. After considering the fundamental regression of the digital economy impacting the high-quality development of the construction industry, it is important to note that the sample selected for this study includes the year 2020. In 2020, the COVID-19 pandemic affected the world. This public event had a significant impact on the company’s operations as a strictly exogenous external shock. Failing to consider this factor may result in endogeneity due to omitted variables. After excluding the special year 2020 sample and conducting the regression again, the results are presented in Table 8. Third, the core explanatory variables are replaced. Referring to the research by Wang Jun et al. [6,37,45], the comprehensive index of the digital economy is measured using principal component analysis based on digital economy infrastructure, digital industrialization, and industrial digital aspects. The original model is re-estimated, and the results are presented in Table 9.

From the estimation results in Table 6, Table 7 and Table 8, the impact of the digital economy on the high-quality development of the construction industry shows positive significance. Additionally, the digital economy has a positive significant effect on the TC, EC, and PEC. These results are consistent with the findings of previous studies, indicating that the regression models’ estimation results in this study are robust. Furthermore, this study once again validates the hypotheses proposed in the previous paper.

5.4. Endogeneity Test

To mitigate the endogeneity estimation bias that may result from bidirectional causality and omitted variables, two instrumental variables (IVs) are employed to examine the presence of endogeneity issues using the two-stage least squares (2SLS) method. To ensure that the instrumental variables are independent of the random disturbance term and simultaneously correlated with the endogeneity variables, the level of digital economic development lagged by one period is selected as the instrumental variable. Second, drawing on Huang Qunhui et al. [46] and Zhao Tao et al. [37], an interaction term is constructed between the national income from information technology services in the previous year and the number of telephones per 10,000 people in each province in 1984, respectively, to serve as an instrumental variable for the core explanatory variables of this study. The data are obtained from the 1984 China Statistical Yearbook. On the one hand, the data on the number of telephone sets in a certain place in 1984 are utilized to represent its digital economy for that year. The historical telecommunication infrastructure could influence the advancement of digital technology, showing a significant correlation with the current stage of digital economy development and meeting the criteria for instrumental variable correlation. On the other hand, as the landline phone gradually fades out of the historical stage, its impact on the high-quality development of the construction industry is also gradually diminished, satisfying the exogeneity of instrumental variables. The estimation and test results are shown in Table 10.

In summary, the regression results are shown in Table 10. The Kleibergen–Paap rk LM statistics are all significant at the 1% level, rejecting the original hypothesis of the under-identification of instrumental variables. The Cragg–Donald Wald F statistic is also greater than the critical value of the Stock–Yogo F-test for the identification of weak instrumental variables at the 10% significance level. This rejects the original weak instrumental variable hypothesis, indicating that the selection of the instrumental variable set is valid. Therefore, the results of this study remain robust and reliable after considering the endogeneity problem.

5.5. Intermediary Mechanism Test

The above analysis confirms that the digital economy significantly enhances the high-quality development of the construction industry. As mentioned in the preceding theoretical analysis section, the digital economy can facilitate the high-quality development of the construction industry by boosting entrepreneurial innovation and entrepreneurship. Does entrepreneurship have a significant impact on the process of enhancing the level of high-quality development in the construction industry within the digital economy? What is the extent of the contribution? Next, the stepwise regression estimation method is used to conduct an in-depth study on these questions, and the results are shown in Table 11.

The coefficient of influence in the comprehensive effect of the digital economy on enhancing the level of high-quality development in the construction industry is 0.326. It is significant at the 1% level, which satisfies the criteria of the preliminary test for the presence of mediating effects (refer to Table 11). Therefore, according to the mediating effects framework, the comprehensive effect includes both direct and indirect effects. Column (1) in Table 11 displays the results of the baseline regression without including mediating variables. Columns (2) and (3) present the estimation results with entrepreneurial innovativeness as the mediating variable. The coefficient in Column (2) is significantly positive, indicating a positive effect of the digital economy on enhancing entrepreneurial innovation spirit. After incorporating the entrepreneurial innovation spirit into the baseline regression model, the coefficient of the digital economy decreases from 0.326 to 0.077. This suggests that entrepreneurial innovation spirit partially mediates the relationship between the digital economy and the high-quality development of the construction industry. Columns (4) and (5) present the estimation results with the entrepreneurial pioneering spirit as the mediating variable. From Column (4), there is a positive effect of the digital economy on the enhancement of the entrepreneurial pioneering spirit, with a coefficient of influence of 0.659. From Column (5), the coefficient of the digital economy after adding the entrepreneurial pioneering spirit into the baseline regression model is 0.315. It shows that the entrepreneurial pioneering spirit plays a positive mediating effect in the digital economy and the high-quality development of the construction industry, and it verifies hypothesis H2.

6. Discussion of Findings

Specifically, based on the regression results in Table 4, the positive impact of the digital economy on the EC is significantly greater than that on the TC. Moreover, the contribution to the PEC surpasses that of the SEC, aligning with Cardona’s [47] assertion that the advancement of the digital economy enhances the EC. Changes in the EC are typically influenced by a variety of factors, including but not limited to technological innovation, management practices, quality control, market competitiveness, and other related aspects. Digital technology can effectively alleviate the distortion level of labor and capital factor allocation, enhance the proportion of high-end factor inputs in the industry, achieve the upgrading of the factor allocation structure, and bring the output level closer to the production possibility curve with the same scale of factor inputs. This can lead to an enhancement in the EC of the entire society.

Columns (1) and (2) in Table 5 show that the impact of the digital economy is slightly stronger in regions with low levels of construction GTFP. The reason for this may be that regions with high levels of GTFP in the construction industry are generally more innovative and technologically productive. They have maintained a solid foundation for innovation and a first-mover advantage for an extended period, which also reflects the “factor saturation effect” in regions with high levels of GTFP in the construction industry. The factor input in the region is sufficient, or even excessive, and its productivity improvement depends on the reasonable deployment and full utilization of factors and resources. The “siphoning effect” of talent and capital caused by the digital economy results in diminishing marginal benefits of resource inputs, as observed in the study by Guo et al. [48]. The marginal efficiency gains from the further development of the digital economy are weaker. Overaccumulation in this sector may encroach on the allocation and utilization of other resources, ultimately weakening the positive impact of the digital economy on areas with high levels of GTFP in the construction industry. Regions with a low level of GTFP in the construction industry are unable to significantly increase productivity due to the insufficient accumulation of factor resources. From the above analysis, there is a “threshold effect” in the digital economy, and different stages of development require varying levels of digital economy integration to align with. The strong development of the digital economy may lead to inefficient use; the sluggish development of the digital economy will cause the effect not to be obvious. Thanks to the strong permeability, high external connectivity, convenience, flexibility, and intelligence of the digital economy, the promotion of the digital economy in the central, eastern, and southern regions is stronger compared to the western and northern regions. Its dividends have not fully realized their potential yet, offering greater room for productivity improvement and relatively more robust growth. Compared with other regions, the eastern region and the southern region have a strong foundation for the development of the construction industry. They possess a stable capital supply, an ample availability of high-level talent, and a well-established factor market system for construction. This provides them with a relatively robust basis for development. Superior infrastructure conditions promote better mutual promotion and complementarity between the digital economy and the construction industry. In the context of the transformation of old and new kinetic energy, the integration of the digital economy can accelerate the achievement of regional coordinated development.

Based on the results of the mediation mechanism test in Table 11, for every one unit increase in the level of the digital economy, entrepreneurial innovativeness and entrepreneurial pioneering spirit increase by 0.373 and 0.659 units, respectively, holding other factors constant. This implies that the digital economy fosters entrepreneurship, aligning with the conclusions of Lamine W et al. [49]. The rise in entrepreneurship consequently results in an indirect increase in the level of high-quality development in the construction industry by 0.077 and 0.315 units. This confirms that the mediating effect of entrepreneurship in the process of enhancing the high-quality development of the construction industry in the digital economy is significant, and the driving force of the entrepreneurial pioneering spirit is stronger. In the context of a market economy, the entrepreneurial spirit of innovation must be realized through entrepreneurial activities, and entrepreneurs’ innovative endeavors can only be effectively supported by capital and labor through market mechanisms. Entrepreneurship can help promote high-quality development in the construction industry through dual channels, thus its leading role is stronger. The digital economy era creates numerous opportunities for innovation and entrepreneurship, significantly reduces the risks associated with innovation and entrepreneurship, optimizes the allocation of resources for innovation and entrepreneurship, and effectively drives the high-quality development of the construction industry.

7. Conclusions

7.1. Research Conclusions

The digital economy is a novel economic form that has emerged due to advancements in information technology. Its impact on the high-quality development of the construction industry can be classified into two main mechanisms: the direct effect mechanism and the indirect influence mechanism. Based on theoretical analysis, this study develops a digital economy indicator system focusing on the digital infrastructure, the digital talent pool, and the digital economic environment. The green total factor productivity of the construction industry is measured by incorporating environmental considerations into the indicators of total factor productivity in the construction industry. Based on panel data from 30 provinces in China spanning from 2011 to 2021, this study measured the levels of digital economy development and high-quality development in the construction industry. On this basis, a series of methods, such as OLS, the fixed-effects method, and spatial econometric analysis, were utilized to test the effect and theoretical mechanism of the digital economy on the high-quality development of the construction industry. The research results contribute to two main aspects:

The theoretical contributions of the research results are as follows: (1) The research perspective is expanded. The inclusion of entrepreneurship in the high-quality development analysis framework of the construction industry emphasizes the key intermediary role of entrepreneurship in the digital economy and the high-quality development of the construction industry. This paper reveals the way in which the digital economy can promote the high-quality development of the construction industry by influencing entrepreneurship and deepens the theoretical understanding of the interrelationship between different economic factors. (2) The theoretical research content is deepened. The model is constructed from four dimensions of EC, TC, PEC, and SEC, and the specific dimensions of the impact of the digital economy on the high-quality development of the construction industry are deeply discussed. The theoretical analysis of the effect of the digital economy on the construction industry is further refined, and the theoretical connotation of related fields is enriched.

The practical contributions of the research results are as follows: (1) Guidance is provided for enterprise practice. The empirical data support of this study provides a practical basis for how to stimulate and cultivate entrepreneurship in construction enterprises under the background of the digital economy. It will help enterprises to clarify their own development direction in terms of technological progress and technical efficiency improvement and formulate more targeted strategies and measures. (2) A reference for policy formulation is provided. From a policy perspective, the findings emphasize the importance of entrepreneurship, which suggests that policy makers should attach importance to creating a policy environment conducive to stimulating and nurturing entrepreneurship. Research on the specific dimensions of the impact of the digital economy on the construction industry also provides a focus for policy makers. Policies can formulate corresponding measures around promoting technological progress and improving technical efficiency, to guide the construction industry to achieve high-quality development under the background of the digital economy.

The following research conclusions are obtained:

Firstly, the digital economy significantly enhances the high-quality development of the construction industry. From the perspective of internal decomposition indicators, the digital economy primarily enhances the high-quality development of the construction industry by fostering the enhancement of technical efficiency, particularly scale efficiency.

Secondly, concerning heterogeneity, the digital economy exerts a more pronounced driving force in the central and eastern regions as well as low-productivity areas in comparison to high-productivity regions and western regions. Compared to the north, the driving force of the digital economy in the south is more prominent, indicating that the significance of the digital economy for industrial development is starting to emerge.

Thirdly, further mechanism tests indicate that the digital economy can enhance the high-quality development of the construction industry by fostering and encouraging entrepreneurship. It is highlighted that the promotion of the entrepreneurial spirit plays a more significant role than entrepreneurial innovation. This suggests that the current phase of entrepreneurial activity forms the foundation for the high-quality development of the construction industry driven by the digital economy.

7.2. Recommendations for Development

Based on the research conclusions above, the following policy recommendations are proposed: Firstly, expedite the advancement of the digital economy and enhance the pivotal role of entrepreneurship for the high-quality development of the construction industry. As a new type of production factor, the digital economy has become a new driving force to stimulate entrepreneurship. Compared with developed countries, there is still a significant gap in the level of development of China’s digital economy. It is essential to further optimize the overall layout of the construction of “Digital China” and accelerate the process of industrial digitization and digital industrialization. At the same time, the digital economy plays a significant role in stimulating entrepreneurship by empowering the construction industry for high-quality development. Secondly, strengthen the construction of digital infrastructure, cultivate digital talents, and promote entrepreneurship. Considering the relatively weak digital economy in the western and northern regions, there is a need to expedite the development of digital “new infrastructure”, foster the growth of digital economy innovation talent, enhance market economy mechanisms, boost market vitality, expedite the utilization of the digital dividend and latecomer advantage in the western region, and nurture digital economy growth hubs. Promoting entrepreneurship, fostering an environment conducive to innovation and entrepreneurship, and leveraging the current situation to reduce the regional disparities in the construction industry’s development can facilitate coordinated regional growth. Thirdly, support and encourage the eastern and southern regions to take the lead in the R&D and innovation of digital technology to enhance the spillover effect of digital technology. The eastern and southern regions should accelerate technology R&D and innovation leadership. They should actively introduce foreign advanced digital technologies, enhance the independent innovation capability of digital technologies, accelerate the transfer and proliferation of digital technologies to the central, western, and northern regions, and provide technical support for the rapid development of their digital economy.

7.3. Future Outlook

This study provides a new perspective for the high-quality development of the construction industry under the background of the digital economy, but there are still many directions worth exploring in the future. On the one hand, with the continuous update of digital technology, it is possible to further study its dynamic impact on the development of entrepreneurship and the construction industry. On the other hand, research should be extended to different regional and cultural contexts to fully understand the universality of the mechanism. At the same time, we continue to pay attention to the deep integration of emerging digital technologies in the construction industry,

Although this study has some achievements, there are also limitations. For example, measures of entrepreneurship may be limited by existing indicator systems that do not fully capture its meaning. In addition, although the model construction considers multiple dimensions, it may not cover all the influencing factors. These limitations provide room for the improvement in and expansion of future research.

Author Contributions

Software, J.Z., Y.L. and Q.L.; Investigation, J.L. and Z.G.; Resources, G.Y.; Writing—review & editing, L.Z., Y.L. and Q.L.; Project administration, H.L. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Theoretical mechanisms of the mediating role of entrepreneurship map.

Figure 2. Decomposition of GTFP.

Figure 3. Changes in the digital economy index and the level of high-quality development of the construction industry, 2011–2021.

Figure 4. Correlation between the digital economy and the level of high-quality development of the construction industry.

Table 1

Mediating effect test logic.

Condition	Result
Coefficient α1 is significant, and coefficients β1 and γ2 are both significant. Also, γ1 is less than α1.	Entrepreneurial spirit is a partial mediating variable.
Coefficient α1 is significant, and coefficients β1 and γ2 are both significant. However, γ1 is not significant.	A complete mediating effect.
Coefficient α1 is not significant, or coefficients β1 and γ2 are not both significant.	No mediating effect.

Table 2

Indicator system for high-quality development of the construction industry.

Type of Indicator	Name of Indicator	Unit
Input	Total power of machinery and equipment	Kilowatts
	Total assets of the construction industry	Million
	Construction energy input	10,000 tons
	Number of employees in the construction industry	In persons
Desired output	Gross output value of the construction industry	Million
Undesired output	Carbon dioxide emissions	10,000 tons

Table 3

Comprehensive indicator system for the digital economy.

Indicator	Variable	Unit	Attribute
Digital infrastructure	Cell phone penetration rate	Dept./Hundred	+
	Number of Internet sites	10,000	+
	Number of Internet domain names	Million	+
	Cell phone exchange capacity	10,000 households	+
	Number of Internet broadband access ports	Million	+
Digital talent pool	Number of undergraduate graduates	In persons	+
	Number of people in information transmission, software, and information technology service industry	In persons	+
	Number of people in scientific research and technology service industry	In persons	+
Digital economic environment	Technology market turnover	Million	+
	Full-time equivalent of R&D personnel	Million	+
	Total telecommunications businesses	10,000 households	+
	Digital inclusive finance index	/	+

Table 4

Descriptive statistics of the main variables.

Variables	Obs	Mean	Std. Dev	Min	Max
lnGTFP	330	0.269	0.306	−0.354	1.318
lnDig	330	1.041	0.793	−1.312	2.847
lnMan	330	11.47	0.811	8.883	12.55
lnGre	330	3.679	0.0903	3.408	3.88
lnGov	330	−1.327	0.385	−2.031	−0.219
lnUSca	330	5.472	1.29	2.076	8.27
lnLP	330	12.77	0.29	12.09	13.53
lnFin	330	1.129	0.309	0.509	2.021

Table 5

Benchmark regression results of the digital economy affecting high-quality development in the construction industry.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	lnGTFP	lnGTFP	lntc	lnec	lnsec	lnpec
lnDig	0.266 ***(6.88)	0.326 ***(5.73)	0.066 *(1.88)	0.621 ***(6.94)	0.017(0.41)	0.331 ***(6.27)
Constant	−0.045(−0.58)	−11.978 ***(−3.41)	−1.921 *(−2.37)	−20.056 ***(−6.19)	−14.487 ***(−4.27)	9.75(1.65)
Controls	No	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes	Yes	Yes
Obs	330	330	330	330	330	330
R2	0.618	0.719	0.177	0.491	0.45	0.701

Note: t-values are in parentheses; *** and * indicate significant at the 1% and 10% levels, respectively.

Table 6

Results of heterogeneity analysis.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	lnGTFP	lnGTFP	lnGTFP	lnGTFP	lnGTFP	lnGTFP	lnGTFP
	Low	High	East	Mid	West	North	South
lnDig	0.274 *(2.52)	0.224 *(2.29)	0.548 ***(4.17)	0.315 **(2.91)	0.197(1.68)	0.342 ***(4.44)	0.372 **(3.15)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Constant	−8.846(−1.81)	−5.021(−0.74)	−20.006(−1.63)	9.326(1.72)	−21.646 ***(−3.47)	−15.481 **(−3.01)	−10.212(−1.55)
Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Obs	165	165	121	88	121	165	165
R2	0.83	0.796	0.832	0.798	0.818	0.878	0.744

Note: The t-values are in parentheses; ***, ** and * are significant at the 1%, 5% and 10% levels, respectively.

Table 7

Robustness tests (reduced tail treatment).

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	lnGTFP	lnGTFP	lntc	lnec	lnsec	lnpec
lnDig	0.246 ***(16.79)	0.302 ***(5.45)	0.068 **(2.09)	0.619 ***(7.78)	0.024(0.56)	0.431 ***(5.79)
Constant	−0.013(−0.14)	−10.91 ***(−3.57)	−1.678 **(−2.16)	−20.644 ***(−6.54)	−15.466 ***(−4.35)	10.64(1.86)
Controls	No	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes	Yes	Yes
Obs	330	330	330	330	330	330
R2	0.620	0.719	0.177	0.491	0.427	0.718

Note: t-values are in parentheses; *** and ** indicate significant at the 1% and 5% levels, respectively.

Table 8

Robustness tests (excluding exceptional samples).

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	lnGTFP	lnGTFP	lntc	lnec	lnsec	lnpec
lnDig	0.265 ***(5.53)	0.351 ***(6.07)	0.094 **(2.63)	0.610 ***(5.98)	0.02(0.46)	0.301 ***(5.23)
Constant	−0.092(1.35)	−14.474 ***(−5.32)	6.382 *(2.11)	−20.856 ***(−5.43)	−13.157 ***(−3.29)	8.505(1.25)
Controls	No	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes	Yes	Yes
Obs	300	300	300	300	300	300
R2	0.6	0.714	0.163	0.466	0.438	0.676

Note: The t-values are in parentheses; ***, ** and * are significant at the 1%, 5% and 10% levels, respectively.

Table 9

Robustness tests (replacement of independent variables).

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	lnGTFP	lnGTFP	lntc	lnec	lnsec	lnpec
lnData	0.223 **(2.9)	0.296 ***(4.91)	0.091 ***(5.57)	0.428 ***(4.53)	0.002(0.10)	0.304 ***(6.44)
Constant	−0.03(−0.25)	−11.127 **(−2.82)	7.349 *(2.55)	−18.477 ***(−4.39)	1.937 *(1.81)	10.613 *(2.04)
Controls	No	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes	Yes	Yes
Obs	330	330	330	330	330	330
R2	0.583	0.688	0.208	0.093	0.504	0.689

Note: The t-values are in parentheses; ***, ** and * are significant at the 1%, 5% and 10% levels, respectively.

Table 10

Endogeneity test (instrumental variables approach).

Variables	IV (One Period Behind)		IV
	Phase I	Phase II	Phase I	Phase II
lnDig		0.135 **(2.9)		1.898 *(2.54)
Phase I IV	0.841 ***(50.55)		0.364 *(2.25)
Controls	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes
Kleibergen–Paap rk LM statistic		2499.24 ***		1648.47 ***
Cragg–Donald Wald F statistic		2652.05 ***		111.12 ***
Obs	300	300	300	300
R2	0.98	0.239	0.752	0.689

Note: The t-values are in parentheses; ***, ** and * are significant at the 1%, 5% and 10% levels, respectively.

Table 11

Mechanism test of the digital economy affecting the high-quality development of the construction industry.

Variables	(1)	(2)	(3)	(4)	(5)
	lnGTFP	lnInn	lnGTFP	lnEnt	lnGTFP
lnDig	0.326 ***(5.73)	0.373 ***(4.98)	0.077 **(1.97)	0.659 ***(9.18)	0.315 ***(4.98)
lnInn			0.222 ***(7.88)
lnEnt					0.135 ***(4.32)
Controls	Yes	Yes	Yes	Yes	Yes
Constant	−11.978 ***(−3.41)	−1.18(−0.57)	−4.783 ***(−4.54)	0.464(0.23)	−5.107 ***(−4.57)
Year	Yes	Yes	Yes	Yes	Yes
Province	Yes	Yes	Yes	Yes	Yes
Obs	330	330	330	330	330
R2	0.719	0.781	0.391	0.897	0.313

Note: t-values are in parentheses; *** and ** indicate significant at the 1% and 5% levels, respectively.

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