Introduction

In the absence of proactive measures by nations toward ecological and environmental preservation, Earth’s average temperature will surpass the threshold (a 2 °C increase) above which people cannot endure (Saeed et al. 2021), threatening human survival. How to harmonize the relationship between economic development and ecological and environmental protection has become a global focus. As a result of China’s reliance on a development model characterized by resource waste and environmental destruction since its reform and opening up, the country has experienced a decline in environmental carrying capacity and has become one of the world’s largest emitters of carbon dioxide (Wang et al. 2023). The resulting climate change and environmental pollution have caused frequent smog (Shan et al. 2023; Cheng et al. 2024) and a sharp increase in cancer rates (Li et al. 2022). Therefore, the green development strategy has become the key for China to break through resource and environmental bottlenecks, economic restructuring, and environmental governance (Adams 2008; Li and Huang 2024). As a pillar industry of the national economy, the construction (CON) industry has not only contributed to economic development but also become one of the sectors with high pollution and high energy consumption. Its total carbon emissions account for 50.9% of the national total, with construction materials contributing 28.2%. (China Building Energy Efficiency Association Secretariat 2022). Additionally, the resource utilization rate of construction waste is only 30%–40% (Wang et al. 2024), far lower than that of developed countries such as the United States, where it is approximately 76% (Zhang et al. 2022), and Germany and Japan, where it is as high as 90% (Nelles et al. 2016; Rodriguez-Morales et al. 2024). In addition to making landfill and garbage disposal more difficult, this situation permanently damages the environment (Nawaz et al. 2023). Therefore, the CON sector must address issues related to energy consumption, carbon emissions, and material recycling by applying enterprise green development behavior. This behavior refers to the organizational actions taken by enterprises to achieve green development goals, benefiting both environmental protection and economic growth (Li et al. 2023; Du et al. 2024). Through ecological design, production, and supply chain integration, it has become a good way to bring the economy and the environment together, fix problems with the environment, cut costs, and promote long-term growth (Hu et al. 2021; Sandra Marcelline et al. 2022). Therefore, this study chooses highly polluting and energy-consuming construction material enterprises as research objects and explores realistic paths for realizing green development.

In this context, scholars have conducted much research on enterprise green development behavior, mainly in terms of environmental regulation (Aydin et al. 2025), social supervision (Wang et al. 2023), market competition (Hu et al. 2022), and internal organizational factors (Oliveira et al. 2022). Although such research provides valuable theoretical support and insights for this paper, there are still several limitations. First, previous research has no consensus on how a single variable influences enterprise green development behavior. For example, from an environmental regulation perspective, some scholars have argued that government incentives or regulatory measures significantly promote corporate innovation (Lian et al. 2022). Scholars who support traditional economic views, on the other hand, say that environmental regulation imposes significant pollution control costs and fines on enterprises, thereby hindering green development (Peng et al. 2021). Therefore, the relationship between a single variable and enterprise green development behavior is relatively ambiguous. Second, the research on the relationship between executives’ personal attributes and enterprise green development behavior is relatively limited, but the decisive role of executives in the selection and effectiveness of such behaviors deserves special attention. Finally, existing research has focused mostly on the “net effect” of a certain type or a single factor on enterprise green development behavior, ignoring the complex causal relationship that exists in the context of enterprise behavior, where multiple conditions are interdependent and combine to form a complex cause-and-effect relationship with multiple concurrent factors. To make up for these problems, this paper introduces fuzzy-set qualitative comparative analysis (fsQCA), which can compensate for the shortcomings of traditional regression analysis and is more suitable for solving the intricate issue of interdependence between variables and generating results. Furthermore, we decide to focus on key decision-makers, the “executives,” and integrate the institutional environmental factors influencing green development behavior in construction materials enterprises to construct a comprehensive research framework. From a configurational perspective, we explore the “joint effects” and “interactions” between influencing factors. This paper seeks to answer the following questions. First, what preconditions are necessary for enterprises to adopt enterprise green development behavior? Second, how do multiple factors synergize to form conditional configurations that promote the implementation of enterprise green development behavior? Third, which conditions play a more important role in promoting enterprise green development behavior?

More importantly, construction materials have become a nonnegligible part of the global sustainable development process because of their highly polluting and energy-consuming nature. This study aims to enrich the research on the green development of construction materials enterprises, stimulate academic interest and contribute to related fields: (i) a research framework is developed focusing on “enterprise executives” as the core and “institutional pressure” as the driver, which is based on the new institutionalism theory and strategic cognition theory, enriching the factors influencing enterprise green development behavior; (ii) the introduction of a configurational perspective and fsQCA method provides new insights and approaches for understanding the synergistic effects of multiple factors in driving green development behavior in building material enterprises; and (iii) the study reveals multiple paths for the realization of high-level enterprise green development behaviors, providing a theoretical basis on which construction materials enterprises can establish a long-term mechanism that facilitates their own green development.

This paper arranges the remaining sections as follows. Section 2 presents the literature review and research hypotheses. Section 3 provides an overview of the research design, including methods, samples, and variables. Section 4 presents the empirical results of the driving paths of green development behavior in construction materials enterprises. Section 5 offers discussion and analysis. Section 6 concludes the study and highlights its significance and limitations.

Literature review and research hypotheses

Institutional pressure

New institutionalism theory suggests that firm behavior and decision-making are influenced and constrained by the embedded network of social relationships and the external institutional environment (DiMaggio and Powell 1983; Scott 2005). This theory has been utilized to examine how organizations respond to environmental issues (Du et al. 2023). The key elements of institutions are categorized into regulatory, normative, and cultural-cognitive elements. In turn, this study analyzes the influence of institutional factors (government, society, and market dimensions) on enterprise green development behavior, laying the foundation for later studies to delve into the complex interaction mechanism between the two.

Regulatory elements

Regulatory elements supervise organizational behavior mainly through the establishment of rules, rewards, penalties, etc., which impose mandatory constraints on enterprise behavior.

Environmental laws and regulations are key regulatory factors influencing enterprises’ implementation of green development behavior. The government manages enterprise behavior through either constraining or incentivizing environmental regulatory measures. On the one hand, constraining environmental regulations have a deterrent effect on enterprises through mandatory measures, forcing them to improve their pollution situation and implement environmental protection behaviors. Research shows that strict environmental regulations internalize the external costs of corporate pollution, leading to increased production costs and pollution control investments. This encourages companies to adopt green development practices, such as green technology innovation and environmental information disclosure, to overcome these challenges. By doing so, they can ensure compliance while reducing operational costs and achieving sustainable development (Liu et al. 2023). On the other hand, incentive-based environmental regulation guides enterprises in taking the initiative in green innovation and boosts the implementation of green development behaviors by means of tax incentives or government subsidies (Liu et al. 2022). First, the government provides R&D subsidies for green technological innovation, which alleviate financial burdens and motivate enterprises to actively engage in green innovation (Hewitt-Dundas and Roper 2010; Szücs 2020). Second, green innovation is riskier and less stable than other types of innovation. However, businesses that get green R&D subsidies can put their money into safer green innovation projects with help from the government to get unique green benefits and competitive advantages (Huang et al. 2019). Therefore, environmental regulation can effectively prompt enterprises to take the initiative to implement enterprise green development behavior and realize the organic unity of economic, environmental and social benefits.

Normative element

The normative element primarily governs organizational behavior through societal values and roles in terms of social norms; it represents society’s expectation of how an enterprise should behave.

Enterprise behavior is subject to the standards and expectations of stakeholders, especially media attention and public surveillance. Enterprises recognize this normative pressure as a significant motivator for adopting enterprise green development behavior. With the growth of the internet and digital media, the power of the media cannot be underestimated, as it is an important medium for communication between enterprises and stakeholders (Chen et al. 2022) and can help guide social topics and public opinion. The media, through positive or negative reports on enterprise-related environmental behaviors, can trigger stakeholder trust or skepticism, which in turn affects the reputation and interests of enterprises and even management (Jia et al. 2016; Shipilov et al. 2019). Thus, academics recognize the media as both an important external governance mechanism and an important monitoring tool that is an effective alternative to inadequate institutional protection measures. In addition, public surveillance plays a crucial role in eradicating enterprise infractions, and working in tandem with government regulation can be an effective long-term deterrent to enterprise environmental damage (Wang et al. 2023). Since the government serves the public, its regulations and behaviors are scrutinized. Thus, public surveillance helps strengthen the efficiency of government environmental enforcement and indirectly promotes eco-innovation by enterprises (Chu et al. 2024). In summary, normative pressure can encourage enterprises to adopt enterprise green development behavior, motivated by media and public surveillance.

Cultural-cognitive element

The cultural-cognitive element emphasizes that the belief systems and cultural frameworks of the environment in which an organization operates shape its behavior, including shared beliefs and logics of action. This element highlights that enterprises often adhere to “common situational definitions, frames of reference, or recognized role templates or structural templates” to gain cognitive legitimacy (Suchman 1995). The effect of this element on enterprises is based mainly on imitative mechanisms, where enterprises tend to emulate the green management behaviors of successful enterprises in their industry when in an uncertain environment (Bansal and Roth 2000; Nawaz and Guribie 2024).

Compared with command-and-control regulatory instruments, regulatory instruments based on market competitiveness and openness can provide sustained incentives for enterprises to innovate (Lanoie et al. 2011). In response to strict environmental rules and competitive market conditions, enterprises often emulate industry leaders to navigate rivalry and reduce uncertainty (Huang et al. 2022). While this imitation can weaken competitive differences, it also motivates enterprises to adopt unique green development strategies to maintain low costs and secure future advantages, increasing both profits and the degree of social recognition (Fernández‐Kranz and Santaló 2010; Hu et al. 2022). in addition, China’s Belt and Road Initiative and community of human destiny have led to the opening up of markets as globalization intensifies. A more liberalized market environment can reduce enterprises’ financing constraints through the free flow of capital, share financial risk through Sino-foreign cooperation and outward investment, and reduce the degree of enterprise green development behavior uncertainty and information asymmetry through shareholder governance (Moshirian et al. 2021). Market liberalization improves information efficiency, enabling enterprises to adapt their green strategies quickly to global changes, as noted by Alhaj-Yaseen et al. (2017). Thus, market competition and liberalization may motivate enterprises to adopt enterprise green development behavior.

Executive green cognition

Executive green cognition is the subjective awareness and knowledge structure formed by enterprise executives on the basis of their understanding of resource and environmental issues and their psychological experience when they assume the responsibility of saving resources and protecting the environment, which includes mainly factors such as green competitive advantage, social responsibility, and external pressure (Sabbir and Taufique 2022; Tu et al. 2024). The theory of strategic cognition suggests that the subjective understanding and cognition of enterprise decision-makers of external factors and stimuli are the most direct factors influencing enterprise strategic decisions. Even in similar political and market situations, executives’ green cognition is influenced by their capabilities, external surroundings, and values, which can lead to divergent interpretations and strategic decisions (Bassyouny et al. 2020). This means that business leaders can only become more environmentally friendly if they understand how important it is to protect the environment and promote green development. Only then can they make green behavior a strategic part of their business and allocate the right resources (Rui and Lu 2021).

An increasing number of scholars have incorporated strategic cognition theory into the research of enterprise green development behavior and have discovered the beneficial impact of enterprise executive qualities on facilitating this behavior. First, the stronger the green cognitive ability of executives is, the more they can explore the potential benefits and market opportunities of enterprise green development behavior. Liu et al. (2024) say that companies can create unique competitive advantages by seeing the focus on green and environmental protection from outside stakeholders as an opportunity (Yong et al. 2019) and using green development behaviors to meet consumer demand, lower the risk of green innovation, and gain market share. Second, executives with greater levels of green cognitive ability have a greater sense of social responsibility and are more inclined to allocate resources to green development. They tend to integrate green development concepts into the company’s strategy, optimize resource allocation, and actively engage in green technology research and product innovation, thereby contributing to both environmental and economic benefits (Wang 2024). Therefore, the green cognitive ability of executives, as key players in enterprise strategic decision-making, is an important factor in determining whether a company can effectively realize enterprise green development behavior.

Research framework and hypotheses

The configuration perspective and the QCA method look at things from a systemic and all-around point of view. They say that businesses should be seen as networks or clusters rather than as loosely connected individuals (Fiss 2007). However, previous studies have examined organizational behavior only in isolation from the external environment or within the firm, thereby neglecting their interaction. Moreover, a substantial amount of research confirms the strength of configuration theory in analyzing the drivers of enterprises’ adoption of green development behaviors (De Marchi et al. 2022; Jiao et al. 2020; Shahzad et al. 2021). We are sure that enterprises’ actions toward green development are the result of a lot of different factors interacting with each other, as shown by the new institutionalism theory, strategic cognition theory, and the analysis we just talked about. Therefore, we propose the following two hypotheses:

H1: No single antecedent condition can lead to a high level of green development behavior in construction materials enterprises.

H2: The green development behaviors of construction materials enterprises are driven by the synergistic effects of multiple factors, including the government, society, the market, and enterprise executives, resulting in various configurations.

Executives typically interpret changes in the external institutional environment on the basis of their own values and perceptions, and as leaders and strategy makers, their green cognition directly influences enterprise behavior. Therefore, this study suggests that the green cognition of executives is a key factor and driving force behind how construction materials companies develop in a green way. Thus, we propose the following hypothesis:

H3: Executive green cognition, as a core condition, is prevalent in the configuration results.

Combining the above analyses, this paper introduces the key characteristics of enterprise executives on the basis of the simultaneous consideration of the three institutional factors of the government, society, and the market and constructs a research framework for the synergistic effects of environmental regulation, media attention, public surveillance, market competition, market liberalization and executive green cognition in promoting the green development behaviors of enterprises, as shown in Fig. 1.

Fig. 1: Research framework.
figure 1

The research framework includes the synergistic effects of environmental regulation, media attention, public surveillance, market competition, market liberalization and executive green cognition in promoting the green development behaviors of enterprises.

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Research design

Research methods

QCA is a case-oriented research method based on Boolean algebra and set theory to explore multiple causal concurrencies. Unlike traditional regression analysis methods, QCA doesn’t depend on the size of the sample. Instead, it offers new ways to deal with the problem of having either too few samples for quantitative studies or too many samples for qualitative studies (Greckhamer et al. 2013). Second, emphasizing the “net effect” between the condition and outcome variables, traditional regression analyses place rigorous limits on the independence, linearity and symmetry of the variables, and the interactions between variables are at most ternary (Beynon et al. 2024; Fiss 2011). The QCA method, which is based on configuration theory and emphasizes the interconnections among factors, complex causes, and combination effects, more effectively reveals the complex nature of the green development behaviors of construction materials enterprises. In addition, this method eliminates the assumption of independence between influencing factors and is inclusive of cross-level embedding between factors at different levels (Lacey and Fiss 2009), and thus, there is no need for special treatment of cross-level antecedent conditions, fitting the research framework of this paper. QCA methods can be further classified into crisp-set QCA (csQCA), multivalue QCA (mvQCA) and fsQCA methods because of the differences in terms of data assignment and analytical operations. The fsQCA method, developed in combination with fuzzy set theory, can effectively solve the problems of continuous variables and partial affiliation (Schneider and Wagemann 2012) and is more accurate in its consistency assessment than the other QCA methods. This is why more scholars choose it over the other two methods. (Ampofo et al. 2023; Beynon et al. 2024; Li et al. 2023). Given the preceding explanation and the causal conditions outlined in this work, the fsQCA technique is chosen. The method’s fundamental principles and steps are as follows:

Variable calibration

In fsQCA, an important procedure involves transforming conditional variables into fuzzy sets through calibration, which determines the case’s affiliation scores within each set of variables (Fiss 2011). The antecedent and outcome variables are converted to a set of data by either direct or indirect calibration methods in conjunction with research, practice, or external standards, and the calibration method needs to be flexibly adapted according to the type of variable. Here, the set of antecedent conditions is set as (X), and the set of outcome variables is set as (Y).

Analysis of necessary conditions

Necessary conditions are converted to the set concept, i.e., the set of outcome variables (Y) constitutes a subset of the set of antecedent conditions (X). The consistency level is a significant criterion for measuring the necessary conditions; usually, a consistency level of ≥0.9 with extensive coverage is considered necessary, and the variable should be excluded from the fuzzy set truth table for separate treatment (Schneider and Wagemann 2012). The formula for this is as follows:

$${Consistency}({Y}_{i}\le {X}_{i})=\sum [\min ({X}_{i,}{Y}_{i})]/\sum ({Y}_{i})$$
(1)

where Xi is the condition variable’s calibration value and Yi is the outcome variable’s calibration value, “min” refers to selecting the smaller of the two.

Constructing the truth table

The program with 2k rows according to the number of condition variables k automatically creates the truth table, i.e., all combinations of antecedent conditions that may lead to the results. The researcher needs to further select the consistency level and case frequency thresholds to filter out the antecedent condition configurations that can adequately explain the results.

Sufficiency analysis

Subset relationships are at the core of causal complexity problems (Liu et al. 2024). The sufficiency analysis reveals the degree to which a certain set of antecedent conditions are sufficient for the outcome. This phase helps find shared and alternative variables, as well as multiple paths leading to the outcome variable. When examining fuzzy subset relationships, we must introduce two critical indicators: the level of consistency and the degree of coverage. The level of consistency indicates the degree of consistency of the cases in the shared condition configuration state that share the same outcome and is calculated via the following formula:

$${Consistency}({X}_{i}\le {Y}_{i})=\sum [\min ({X}_{i,}{Y}_{i})]/\sum ({X}_{i})$$
(2)

Coverage indicates the extent to which the pooled relationships that pass the consistency test explain the results and is calculated as follows:

$${Coverage}({X}_{i}\le {Y}_{i})=\sum [\min ({X}_{i,}{Y}_{i})]/\sum ({Y}_{i})$$
(3)

Robustness test

There is no fixed practice for this step, and the robustness of the results is typically assessed by adjusting consistency levels, frequency thresholds, calibrating anchors, and censoring cases. If the new configuration that is obtained after adjustment doesn’t change much and there is a clear subset relationship with the original configuration, then the results of the original configuration are thought to be robust.

Sample selection and data sources

This study focuses on construction materials enterprises listed on the Shanghai and Shenzhen A-share markets in China from 2010 to 2021. The screening steps for the sample enterprises are as follows: (i) considering data continuity, enterprises listed before January 1, 2008, are selected, and 1433 enterprises are initially obtained; (ii) according to the China Securities Regulatory Commission’s Industry Classification Guidelines (2012 edition), construction materials enterprises belong to the Class C manufacturing industry, and 755 samples are screened and retained (China Securities Regulatory Commission 2012); (iii) on the basis of the results of the classification of construction materials and the industry classification of the China Securities Regulatory Commission, enterprises related to the production of construction materials are selected according to the main business of the company in the Class C manufacturing industry; and (iv) missing key data and ST and *ST companies, and ensuring that the sample results include both “positive” and “negative” cases. Following the above steps, we ultimately select 53 construction materials enterprises for inclusion in the subsequent study. Research experience with QCA method suggests that n factors can have 2n configurations, and the corresponding sample size should reach 2n-1 to support the analysis (Greckhamer 2011; Judge et al. 2014). The sample size in this study is 53 (>25 − 1 = 31), which ensures a balance with the number of conditions. All sampled companies are publicly listed enterprises with complete information and data disclosure, providing a solid foundation for subsequent empirical analysis. Basic information about the sample enterprises is provided in the Appendix.

The data for this study come mainly from the official statistics published by the government and the annual reports of publicly traded companies. The data on the environmental regulation and market liberalization variables are sourced from the China Statistical Yearbook, the China Environmental Yearbook, the China Environmental Statistical Yearbook, and the China National Knowledge Infrastructure’s (CNKI’s) Laws and Regulations Database. The data pertaining to media attention originates primarily from CNKI’s China Important Newspaper Full Text Database. We choose year t-1 as the sample interval for media data, taking into account the delayed influence of media opinion on corporate conduct. Public surveillance data are acquired via the Baidu search engine, while the remaining variable data are taken from the annual reports of publicly traded corporations. To address missing years in the variables, Stata 17.0 is used to interpolate the linear difference to ensure the completeness and usability of the data.

Measurement

Outcome variables

Enterprise green development behavior (EGDB). Li et al. (2023a) proposed that enterprise green development behaviors can be categorized into the following two particular types of organizational behaviors: green supply chain management behaviors and cleaner production behaviors. If there is an expression of clean production behavior and green supply chain management behavior in the annual reports of listed enterprises, then the value is 1 and 0 otherwise.

Conditional variables

Environmental regulation (ER). In accordance with Wang et al. (2022), two indicators, environmental administrative control and environmental pollution regulation, are employed for measurement purposes. Environmental administrative control is assessed on the basis of the quantity of local regulations in the enterprise’s location, whereas environmental pollution regulation is assessed by comparing the number of environmental administrative penalties in the region where the enterprise is located to the national total. We specifically normalize and average the two indicators to estimate the intensity of regional environmental regulation each year.

Media attention (MA). This paper relies primarily on Fang and Peress (2009) and Chen et al. (2022) and utilizes CNKI’s Full Text Database of Important Chinese Newspapers to identify the following eight prominent national financial newspapers: China Securities Journal, Securities Daily, Securities Times, Shanghai Securities News, China Business News, Economic Observer, 21st Century Business Herald and First Financial Daily. As media reports can be further differentiated into negative and nonnegative reports, this study determines negative reports since when the headlines and content of the media’s news reports on a company involve negative expressions or direct criticisms of the company’s unlawful behavior, environmental pollution, and administrative penalties (Chen et al. 2018). This research posits that negative reports best communicate the media’s subjective view of the incident and that the social repercussions triggered in the dissemination process are also the strongest. Therefore, we measure the media attention monitoring effect using the natural logarithm of “1 + the number of negative media reports.”

Public surveillance (PS). Prior research has assessed the public’s demand for environmental quality and green production mostly on the basis of the number of local environmental letters and visits. Nevertheless, owing to the swift advancement and widespread use of the internet, an increasing number of individuals opt to utilize online resources to acquire environmental knowledge and voice their environmental concerns and viewpoints. Therefore, this research cites the study of Peng et al. (2021) and utilizes the Baidu search engine to establish the Baidu index for the keyword “environmental pollution” as an indicator of public participation in environmental surveillance.

Market competition (MC). Previous research used the Herfindahl–Hirschman index (HHI) to evaluate imitation pressure but failed to account for enterprises’ innovation tactics in various competitive positions and settings. Previous research ignored resource effects and focused entirely on competitive pressure (Shen et al. 2016). Therefore, this paper refers to the study by Peress (2010), in which the Lerner index was adopted to measure the perceived imitation pressure of enterprises. Lerner index = (operating income - operating costs - selling expenses - administrative expenses)/operating income.

Market liberalization (ML). According to Wang and Su (2020), foreign investment is quantified as a proportion of provincial GDP.

Executive green cognition (EGC). Zhou and Jin (2023) used text analysis to find keywords that were connected to three areas: the perception of green competitive advantage, corporate social responsibility (CSR), and external environmental pressure. This study then counts the frequency of keywords appearing in these three dimensions in listed companies’ annual reports from 2010 to 2021.

Results

Calibration

Since the outcome variables in this study are dichotomous data, no calibration is needed. Instead, all the antecedent condition variables are continuous data and need to be transformed into fuzzy set membership scores beforehand. This involves evaluating their degree of membership between ‘full membership (1)’ and ‘full non-membership (0)’ before proceeding with the analysis. The best practice for this procedure is to base it on empirical data or theoretical knowledge. Drawing on the work of Fiss (2011) and Kabengele and Hahn (2021), this paper uses the direct calibration method and places the calibration anchors at the 75th, 50th, and 25th percentiles. Using fsQCA 3.0, the results of the calibration and descriptive data analysis for each antecedent condition and outcome are shown in Table 1.

Table 1 Calibration results and descriptive statistics.
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Furthermore, the calibration process is not mechanical. Researchers typically decide on the assignment of fuzzy values and the use of thresholds based on their understanding of the data (Fiss 2007; Lee and Choi 2024). To prevent the threat posed by parameter settings to the results of the fsQCA analysis (Ding 2022; Sukhov et al. 2023), this paper re-examines the data by replacing the three anchors with 0.8, 0.5, and 0.2, following Zheng et al. (2020). The results demonstrate robustness. For details on the testing process and results, see Section 4.3.

Analysis of necessary conditions

Consistent with mainstream QCA research, this study uses fsQCA 3.0 to examine, on a case-by-case basis, whether there are necessary conditions that lead to green development behaviors in Chinese construction materials enterprises; i.e., when an outcome occurs, a certain condition must necessarily exist (Rihoux and Ragin 2009). The level of consistency is a critical metric for determining the necessity of a condition. Schneider and Wagemann (2012) determined that a level of consistency greater than 0.9 renders the condition necessary for the outcome.

Table 2 shows that the consistency level of all the antecedent conditions is less than 0.9; thus, there are no necessary conditions leading to the green development behavior of enterprises, and H1 is confirmed. This finding further indicates that individual conditions do not constitute a bottleneck for construction materials enterprises to achieve green development and that although there are differences in policies, markets, social concerns, etc., among different enterprises, they do not necessarily prevent these enterprises from integrating or cultivating the above conditions to form different configurations to promote high levels of enterprise green development behavior. Consequently, investigating the synergistic propelling effects of the four-dimensional elements of the government, society, the market, and enterprise executives from a configuration perspective is imperative.

Table 2 Results of necessity analysis.
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Sufficiency analysis

To test H2, the key indicators for sufficient analysis are set via the following principle: (i) to be deemed a sufficient conditional configuration, the consistency level should typically be greater than 0.75 (Schneider and Wagemann 2012); (ii) the frequency threshold should encompass a minimum of 75% of the observed samples (Rihoux and Ragin 2009); and (iii) to prevent the issue of conflicting configurations and simultaneous subset relations, the threshold of proportional reduction in inconsistency (PRI) should be ≥ 0.75 (Greckhamer et al. 2018). Consequently, in this study, the raw consistency threshold is set to 0.85, the frequency threshold is set to 1, and the PRI is set to 0.75 based on the features of the sample.

The counterfactual analysis section sets the presence or absence of antecedent conditions based on existing research. Since scholars make different arguments about the role of environmental regulation in relation to enterprise green development behavior, the environmental regulation variable is set as “present” or “absent.”. Considering the evidence that media attention can effectively oversee and regulate enterprise behavior (Luo et al. 2022), the media attention variable is designated as “present.”. Given the limited impact of public surveillance in promoting enterprise green development behavior and the need to collaborate with the government and media (Wang et al. 2023), the variable of public surveillance is set as “present” or “absent.”. A favorable competitive market environment can increase the drive and potential for innovation development in regional enterprises (Liu et al. 2022), and thus, this variable is set as “present.”. Market liberalization can promote green development to a certain extent but may also exacerbate vicious competition and financial risk; thus, the market liberalization variable is set as “present” or “absent.”. Executives’ green cognition has been proven to play a decisive role in enterprise development strategies and behavioral decisions; therefore, the conditional variable of the green cognition of executives is set as “present.”.

Through the above settings and Boolean simplification operations, fsQCA generates simple, intermediate, and complex solutions. In this paper, we report configuration outcomes using the “intermediate solution as the main solution and the simple solution as the secondary solution.”. If a condition appears in both the intermediate solution and the simple solution, then it is recognized as the core condition, whereas the condition that appears only in the intermediate solution is recognized as the edge condition (Fiss 2011). Table 3 displays the configuration outcomes of high-level green development behavior in construction materials enterprises.

Table 3 Configuration results of the green development behaviors of construction material enterprises.
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Table 3 displays the results of the H2 test, which identify four combinations of sufficient conditions that drive construction materials enterprises to implement green development behaviors. The results indicate that the consistency levels of the overall solution and the individual configuration paths surpass the minimum acceptable standard of 0.75 (Schneider and Wagemann 2012). The overall solution obtains a consistency level of 0.919 and a coverage of 0.291, which are consistent with the criteria for fsQCA. Regarding the configuration itself (vertically), each path in the case of the stable realization of high-level green development behaviors in enterprises reflects the characteristic of “different paths to the same destination” (Fiss 2007), with different initial conditions and their combinations. In other words, the synergy between the government, society, the market, and enterprise executives can produce multiple paths with equivalent outcomes, reaffirming H2. A cross-sectional analysis of all the configurations reveals that executive green cognition is a core condition in three of them. This finding suggests that this condition plays a key role in facilitating businesses’ green development behaviors, which supports H3. In particular, when synergized with media attention in P1, it has the strongest explanatory power, as it has the highest consistency level, at 0.95. Hypotheses 1, 2, and 3 are all supported, and the results are summarized in Tables 4.

Table 4 Summary of Hypothesis Testing.
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To enable the analysis of the complex relationships among the configurations, this paper uses the constituent elements and assigns the following names: P1 is referred to as the public opinion crisis type, P2 is referred to as the public surveillance type, P3 is referred to as the market incentive type, and P4 is referred to as the institutional environment copromotion type. We analyze each configuration in detail using theoretical explanations and practical cases.

Public opinion crisis type

Configuration P1 (~ER*MA* ~ PS* ~ MC*EGC) shows that enterprises can be encouraged to act in a green way when their executives are aware of how the outside world sees them and the pressure from the public. This is true even when there aren’t enough government rules and there isn’t much competition in the market. This is because businesses can be watched and talked about on social media. With the power of the media, enterprises can not only identify target audiences and develop product and marketing strategies but also increase word of mouth and awareness through their communication function. (Abbasi et al. 2023). Nevertheless, negative coverage can lead to adverse outcomes, such as diminished effectiveness and eroded trust among stakeholders. These legitimacy pressures can compel enterprises to address their misconduct (Damberg et al. 2022; Zhang et al. 2024). Therefore, harnessing the power of the media is key for enterprises to achieve green development. For example, let us consider the case of Hunan Valin Iron & Steel Company Limited. From 2010 to 2021, the company was faced with more than 10 negative reports in reputable Chinese financial newspapers. These reports, to some extent, negatively affected the company’s reputation and undermined the trust of its stakeholders. In the midst of this furor, Valin Iron & Steel took the initiative to make a clarification announcement and emphasized that the company takes its reputation and social responsibility very seriously. Since then, the enterprise has taken action to fulfill its commitment to technically adhere to “innovation-driven” as the main engine, accelerated its key core technology-independent innovation, and, in terms of environmental protection, continued to promote the key processes of ultralow emissions, efficiency enhancement, and other transformation projects. Enterprises can take the initiative to strengthen their orientation toward enterprise social responsibility and promote the implementation of enterprise green development behavior to avoid the pressure of public opinion generated by negative media reports in society, which affect their image and interests.

Public surveillance type

Configuration P2 ( ~ MA*PS* ~ MC* ~ MO*EGC) indicates that when government regulation is limited and market competition and openness are low, using societal oversight as a “third party” along with quick responses and feedback from enterprise executives to public demands can help enterprises adopt green development behaviors. In addition to the basic rights of life, body, and health (Ghodsi and Terzi 2024), citizens are entitled to freedom of expression and surveillance. Given China’s large population, a sound public monitoring mechanism can help reduce the cost of the government’s regulation of enterprises and increase their trust and recognition among the public. Moreover, Zhang et al. (2023) demonstrated that reserving space and interfaces for public participation in environmental governance significantly reduces the number of enterprise environmental violations. For example, Shanghai Yue Xin Health Group Co., Ltd., is subject to oversight by a dedicated department established by the Shanghai Municipal Market Supervision Administration. This department facilitates communication between the government and the public, with the aim of monitoring the conduct of this enterprise. The public can promptly report any instances of improper or unlawful activities in the market and request appropriate corrective measures through channels such as “I want to make suggestions” and “12315 Complaint and Reporting.” In addition, the Bureau uses online consultation, online interviews, and other forms of local standards for public consultation. The amount of public participation and monitoring in Shanghai is notably high, resulting in a significant degree of public constraint regarding the behavior of firms. In this environment, Shanghai Yue Xin Health Group Co., Ltd. uses humanities, health, green, and low-carbon factors to guide the transformation and upgrading of businesses. They put the customer experience first and make sure they provide high-quality architectural ceramic products and friendly, high-quality services to win customers’ favor and gradually achieve green development.

Market incentive type

Configuration P3 (~ER*~MA*~PS*MO*EGC) indicates that enterprise executives who are sensitive to and accurate at understanding how market environment work can encourage green development in very open markets, even when government regulation and social concerns are weak. Survival and sustainable development require enterprises to continuously create new growth points. Market liberalization can help businesses optimize their investor structure (Zhang et al. 2024), share financial risk (Moshirian et al. 2021), and upgrade production technologies (Fonseca and Van Doornik 2022), thus laying the foundation for green development. Jiangxi Wannianqing Cement Co., Ltd., which is in Jiangxi Province in East China, benefits from the region’s exceptional geographical advantages. Jiangxi Province serves as an inland open economy pilot zone and a crucial node for the enterprise to connect with the “Belt and Road” strategy. This situation creates favorable market conditions for foreign cooperation and development. The company is actively working on a globalization strategy layout to attract a wide range of foreign investments. It is also working on international and domestic projects in the construction materials industry and is expanding its industrial chain and related diversified business projects to give the company a new growth pole. Simultaneously, management should actively implement the principles of green development, adhere to the strategic policy of continuous improvement in the environmental protection and sustainable development of the enterprise, and build a 2 × 2500 t/d cement production line and a pure low-temperature waste heat power station project via a “capacity swap” to improve the utilization rate of energy and achieve a win‒win situation of carbon emission reduction and economic benefits.

Institutional environment copromotion type

Configuration P4 (ER*MA*~PS*MO*~EGC) indicates that when public surveillance is insufficient and enterprise executives lack strong environmental awareness, relying on the government’s “visible hand” and the market’s “invisible hand” to play a role at the same time, coupled with appropriate media attention, can motivate enterprises to implement green development behaviors. Research has demonstrated that efficient markets and active governments can maximize firms’ dynamism and intrinsic motivation through administrative and market instruments and exert innovative coupling effects (Fu et al. 2024; Wang et al. 2024). Therefore, in regions with a high level of market liberalization, economic development can lead to political and cultural upgrades, providing all-round support for the low-carbon and healthy development of energy-intensive industries such as construction materials. Fushun Special Steel Co., Ltd. serves as a significant research and production center for special steel materials in China. The company receives substantial policy support from both the national and Liaoning provincial governments for its scientific and technological R&D, environmental protection technology, and efforts to upgrade and revitalize the industry. Owing to its coastline location in Liaoning Province, at the core of the Northeast Asian Economic Circle, the corporation can send its products to Japan, South Korea, Europe, and other regions by port. Moreover, while establishing a regular communication mechanism with all stakeholders, the enterprise incorporates their needs and perspectives into their decision-making process. Fushun Special Steel Co., Ltd. embraces the green development concept of environmental protection, cleanliness, and recycling and fully implements resource-saving and environmentally friendly development strategies under government policies, market conditions, and social supervision.

Robustness testing

Using Schneider and Wagemann’s (2012) method, this study changes the calibration anchors and the initial consistency threshold to test how robust the results are.

(1) The calibration anchor points are modified from 0.75, 0.5, and 0.25 to 0.8, 0.5, and 0.2, respectively (Zheng et al. 2020). The consistency level of configurations 1, 2, and 3 is significantly higher than the minimum standard of 0.75 when the configuration results are compared before and after the adjustment (Table 5). The consistency level of the solution is 0.895, which is slightly lower than the original configuration results but still meets the analysis requirement. It’s important to note that the parts of configurations 1, 2, and 3 mostly match the results in Table 3, and there is a clear subset of relationships with the original configurations. This shows that the results are very reliable.

Table 5 Configuration after changing the calibration thresholds.
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(2) The raw consistency threshold is increased from 0.85 to 0.9 (Jovanovic and Morschett 2022). Since a higher threshold decreases the number of truth table rows that meet the criteria, the adjusted configuration results should be a subset of the original configuration results. Table 6 shows that adjusted configurations 1 and 2 are identical to P1 and P3, respectively, in the original configuration and are a subset of the original configuration results (Table 3), indicating the robustness of the results.

Table 6 Configuration after adjusting the consistency thresholds.
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Discussion

This study introduces the configuration perspective and fsQCA methodology to reveal the multiple driving paths of the green development behaviors of construction materials enterprises through a comparative analysis of construction materials enterprise cases. The results reveal that a single antecedent condition cannot independently drive the green development behavior of enterprises, thus supporting H1. Nevertheless, it is not clear what effects each antecedent condition has on itself or how the conditions are connected to each other, and thus, it is important to compare the connections between the antecedent conditions and the differences in the configuration elements. This analysis can facilitate a more thorough comprehension of the dynamic evolution process underlying the green development behavior of construction materials enterprises.

Alternative roles of social surveillance and market liberalization

During H2 testing, the four driving paths are found to share a common attribute—social surveillance variables (media attention and public surveillance) and market liberalization variables alternate. These variables are combined with other antecedent conditions, and all of them can produce high levels of enterprise green development behavior, which suggests that there is a substitution effect between the two.

On the one hand, market liberalization conditions are absent in P1 and P2, but the covered case firms have high levels of media and social attention. The simple dissemination of the internet and social media rapidly transforms the debate over environmental problems into public opinion pressure, forcing firms to correct their illegal behaviors to preserve their image and interests. Liao et al. (2020) and Kim et al. (2022) support this observation. In addition, the long-term risks associated with violations outweigh the short-term benefits. Forward-thinking companies prioritize compliance by disclosing environmental information and developing green technologies, which further confirms the importance of social surveillance and aligns with these studies (Van Fan et al. 2018; Luo et al. 2022). On the other hand, P3 and P4 show that even without public surveillance, construction materials enterprises can still exploit economic globalization and capital market liberalization to access raw materials, technology and capital on a global scale and develop a wider consumer market (Li and He 2024). In addition, Sha et al. (2022) discovered that market liberalization helps firms fulfill individualized and diversified consumer demands, hence improving product quality, innovation and service levels and creating more conditions under which to achieve green development.

However, unlike previous studies, this work reveals the substitution effect of social surveillance and market liberalization through the advantages of the configuration approach. This approach provides new insights and another feasible way for construction materials enterprises to avoid stagnation in green development due to the failure of a single mechanism when breaking through environmental constraints.

Universal role played by executive green cognition

This study reveals the following interesting finding: executive green cognition plays a more universal role in driving enterprises’ green development behavior than do the other factors considered. H3 is not only verified, but the notion that executives have a significant effect on enterprise behavior is also reinforced.

The more cognitively capable enterprise executives are, the more they can discern the benefits of environmental regulation policies and convert them into business opportunities. Although environmental regulations present both opportunities and risks for firms, corporate executives can utilize incentives in environmental regulations to offset R&D expenses and pollution control costs, as supported by scholars from Bai et al. (2019) and Wang (2024). Executives with a high level of green cognition can realize that green sustainability is the source of a company’s competitive advantage. Under the situation of vigorously promoting green construction materials, the development of core technologies and green products with their own characteristics can not only enhance the recycling of construction solid waste (e.g., high-titanium heavy-slag concrete), reflecting the positive image of the enterprise’s social responsibility (Wang et al. 2023), but also ensure that the material performance is up to standard to meet the needs of stakeholders and the green demand to obtain a sustainable green competitive advantage (Grossman and Helpman 2018).

Therefore, the role and position of executives in a firm determines that their subjective initiative is critical in influencing enterprise behavior. This finding complements existing research on the relationship between executives and enterprise organizational behavior by reinforcing the impact of executives’ cognition on the green development of their enterprises, especially their coping strategies in the face of environmental regulation and social surveillance pressures.

Theoretical and practical implications

A lot of the existing research on enterprise green development has focused on single variables, linear relationships with only one direction, and causal symmetry. This ignores the fact that businesses are affected by how different factors interact in social networks. To address this shortcoming, this study, which is rooted in new institutionalism theory and strategic cognition theory, identifies the entry point as the “executives” of construction materials enterprises. This work also integrates the external institutional environment, constructs a research framework to drive enterprise green development behavior, and enriches the research on the factors influencing this behavior. At the same time, this study shows how the paths and conditions for green development in construction materials businesses are intricately connected from a configuration point of view. This finding not only supports the theoretical view that different paths lead to the same destination but also compensates for the limitations of the traditional perspective and provides new insights into the existing controversial issues. Currently, the research on the complex causality of multiple concurrencies in the developmental stage is particularly scarce in the construction materials industry. Therefore, this study innovatively introduces the fsQCA method to add new evidence from Chinese construction materials enterprises to the study of configuration effects.

In view of the above, this study offers practical recommendations for the green development of construction materials enterprises. Initially, enterprises need to refine their talent selection criteria and precisely recruit executives with green cognitions, offering appropriate incentives such as salaries and green performance bonuses. Especially during the rapid development of digitalization and information technology, executives should formulate clear plans for the introduction of emerging technologies and talent development programs. By leveraging technologies such as artificial intelligence and BIM, they can build a lifecycle management system for green building materials, laying a forward-looking foundation for the enterprise’s green transformation (Yigitcanlar et al. 2023). Second, enterprises should choose an appropriate driving path, considering external conditions and development needs. They need to accurately assess the market environment, policy pressures, resource endowments and social responsibility requirements in which they operate. Based on their resource advantages, they can select different paths, such as technology innovation-driven or market demand-oriented. By regularly evaluating and adjusting their strategies, they can ensure alignment with the enterprise’s long-term strategic goals and core business. Finally, construction materials companies should intentionally cultivate or cater to alternative conditions. The substitution effects of social surveillance and market liberalization provide enterprises with greater strategic flexibility. When the efficacy of one mechanism wanes, another mechanism can cover the gap and ensure the continuity of the enterprise’s green development.

Conclusions and research limitations

Conclusions

This paper employs the new institutionalism theory and strategic cognition theory to establish a theoretical framework that examines the influence of multidimensional factors on the green development behaviors of construction materials enterprises. We use 53 A-share listed construction materials in Shanghai and Shenzhen, China, as examples. The fsQCA method is used to determine the realization path of the green development behaviors of Chinese construction materials enterprises. The conclusions of the study are as follows:

  • Environmental regulation, media attention, public surveillance, market competition, market liberalization and executive green cognition cannot drive the green development behavior of construction materials enterprises individually as a necessary condition, but executive green cognition plays a more universal role in this behavior.

  • There are four driving paths for the green development behavior of construction materials enterprises, namely, the public opinion crisis type, public surveillance type, market incentive type and institutional environment copromotion type. The constituent elements of these four paths are distinct, demonstrating the multiple ways in which enterprises can achieve their goals under different internal and external pressures, which reflects the characteristic of “different paths leading to the same destination”.

  • There is an alternative relationship between social surveillance and market liberalization in driving enterprises green development behaviors.

Research limitations and future research directions

This paper has three main limitations that need to be improved upon in future research. First, this paper considers only the effect of the intensity of environmental regulation and does not discuss it separately in terms of regulatory instruments. Future research should explore the effects of incentives, such as government subsidies and tax benefits, on enterprise green development behavior. Second, there are many internal influencing factors, such as technological innovation ability and enterprise green culture. However, the variable for executives’ green cognition is weak, and future research could incorporate more comprehensive internal and external influencing factors for in-depth study. This paper’s research objective is China’s construction materials industry, and only 53 listed construction materials enterprises are selected as the research sample; therefore, the generalizability of the research conclusions needs to be tested. In future studies, the construction materials industry could be expanded to include manufacturing or other polluting enterprises, and additional local and international samples could be collected for verification.