The Exploration of a Causal Mechanism for Corporate Environmental Performance in Hydropower Engineering Enterprises: Evidence from China and the United States

Abstract

Sustainable resource and environmental development has become a crucial scientific issue that urgently needs to be addressed. Hence, the issue of green social responsibility has undergone profound exploration. Hydropower engineering, as a significant clean energy source, exhibits promising prospects for fulfilling green social responsibilities. This article analyzed the causal mechanism and behavioral evolution of green social responsibility fulfillment in hydropower between China and the United States by employing event causality extraction, content analysis, and system dynamics as research methodologies. This study revealed a causal relationship between the fulfillment of green social responsibilities in hydropower projects and ethical governance, green development, and risk response. Through the content analysis of the causal relationships, it was found that China expressed a strong emotional inclination toward green development, whereas the United States showed positive values in terms of risk response. Through the simulation of system dynamics, this study found that the causal driving mechanisms of the two countries were generally favorable at different dimensional levels. Among them, under endogenous driving forces, the promoting effect of ethical governance and green development by risk response was more obvious. Under basic driving forces, green development has the most significant driving effect on the fulfillment of green social responsibilities in both countries.

1. Introduction

In recent years, the increasingly intricate climate and resource crises, including the insufficiency of energy, water, and food supplies to meet the escalating demands of a rapidly expanding population, are significant ramifications of the development of industrial society [1]. At present, the crises confronted by humanity are not isolated occurrences but rather a complex combination of ecological, resource, and economic crises that result in frequent incidents of biodiversity loss, land degradation, and increased waste generation. The degradation of ecosystem functions driven by climate change will intensify resource scarcity, which may in turn further provoke social instability and political turbulence. Ultimately, these interconnected factors could escalate into broader regional security challenges [2].

Heavy industry and manufacturing enterprises, as important components of economic development, are the main sources leading to environmental issues (such as climate change, water pollution, and air pollution) and energy problems (including natural resource depletion and energy security) [3,4]. Particularly in the current technological stage, the excessive utilization of traditional fossil fuels has emerged as a pivotal obstacle for enterprises to attain their sustainable environmental objectives due to its associated carbon emissions and resource consumption [5]. In a global context, the two core challenges of ecological environment and sustainable resource utilization have prompted international organizations, government authorities, and relevant scholars to raise higher expectations for the overall performance of enterprises in terms of the economy, society, and environment.

The International Energy Agency (IEA) released a report on the “World Energy Outlook 2022” on 27 October 2022, pointing out that the ongoing energy crisis has exacerbated the vulnerability and unsustainability of the global energy system, further highlighting its predicament in sustainable development [6]. In January 2023, Dasgupta, President of the World Resources Institute (WRI), took the phenomena of tropical rainforests, the energy crisis, financing for low-carbon transformation, and climate actions in the United States as research cases, indicating that building eco-friendly environmental strategies and innovatively using green and renewable energy are the correct paths for the sustainable development of the global industrial chain [7]. As the prelude to the 2024 U.S. presidential election unfolded, Trump pledged that upon taking office, he would dismantle bureaucratic barriers, substantially boost domestic energy production, expedite the approval of new drilling projects, oil and gas pipelines, power plants, and reactors, and streamline the permission process for new energy infrastructure [8].

From the perspective of macro governance, the Third Industrial Revolution, characterized by advancements in new energy, new materials, and artificial intelligence, has made remarkable progress in alleviating economic and environmental issues stemming from the overexploitation and gradual depletion of traditional energy sources. The integrated innovation of technological means provides potential solutions for building a new type of human society that is ecologically balanced, green, low-carbon, and sustainable [9]. From the perspective of micro governance, countries worldwide are actively restructuring their energy portfolios to decrease the reliance on fossil fuels and are vigorously promoting the development of clean energy to facilitate green and low-carbon development [10,11].

Based on this, the issue of corporate social responsibility and green social responsibility in resource and environmental hotspots has garnered significant attention. Green social responsibility pertains to the responsibility of enterprises to proactively safeguard the environment and promote public well-being while concurrently pursuing the maximization of economic interests [12]. As an important driving force for maximizing economic benefits, enhancing environmental governance, and achieving sustainable resource utilization, green social responsibility has progressively integrated into the core domains of corporate operations [13]. Meanwhile, the mature, reliable, and cost-effective hydroelectric engineering technology has evolved as a new approach to address the global issues of resource depletion and environmental pollution.

Hydropower projects, as a crucial form of clean energy and a high-quality resource for achieving a sustainable development strategy, are among the most widely utilized in the energy sector. Their zero-emission and low-carbon characteristics, along with their roles in water resource management and climate regulation, provide essential technical support for ecosystem restoration and green renewable energy innovation [14,15]. With the increasing attention of the public to corporate moral responsibility as well as environmental protection commitments, hydropower enterprises have demonstrated extensive strategic value and sustainable development business prospects in fulfilling green social responsibilities [16]. Therefore, actively promoting corporate social responsibility and advancing the green social responsibility of hydropower engineering enterprises from the perspective of resource and environmental foundations is a cutting-edge direction with substantial application value and broad prospects.

In recent years, the sustainable development of resources and the environment has emerged as a critical scientific challenge that urgently requires resolution in light of the rise of emerging economies and the sharp increase in the global population. Consequently, the issue of fulfilling green social responsibilities in traditional highly polluting industries along with highly-energy-consuming engineering projects has received widespread attention and thorough discussion [17]. As a pivotal force for maximizing economic benefits, enhancing environmental governance, and achieving resource sustainability, hydropower projects have demonstrated substantial potential in fulfilling green social responsibilities. However, existing research on the green social responsibilities of hydropower projects still faces several bottleneck problems that require urgent solutions in both theoretical exploration and practical case studies [18,19]. In previous studies, we identified three research gaps. First, there is a lack of understanding regarding the appropriate relationship between compliance disclosure, environmental governance, sustainable development, risk management in hydroelectric engineering enterprises, and the fulfillment of green social responsibilities [20,21]. Second, empirical research conducted by academia on the mechanisms linking ethics and governance in hydroelectric engineering enterprises with green development, risk response, and fulfillment of green social responsibilities remains limited to a single time sequence, lacking cross-temporal interactions that capture the evolution of corporate environmental responsibility behavior [22,23]. Third, there is insufficient diverse research on the paths for implementing green social responsibilities by hydroelectric engineering enterprises in different regions or countries [24,25,26].

In order to bridge these gaps, we selected hydropower projects in China and the United States as our research object. China and the United States, as the world’s two largest economies, play a pivotal role in the energy sector and possess abundant technical resources for hydropower projects. The United States, as a global pioneer in hydropower development, has over a century of experience in advancing hydropower technology. It has accumulated mature practices in clean hydropower, community engagement, and accident prevention while establishing a comprehensive regulatory framework for environmental impact assessment along with the ecological restoration of hydropower projects. However, following the 2024 U.S. presidential election, the anticipated return of the Trump administration to power may signal a diminished policy inclination toward clean energy infrastructure as well as reduced collaboration with the international community on climate change issues. Against this backdrop, this study aimed to investigate the dynamic causal evolution mechanism of green social responsibility for hydropower projects between China and the United States. China, as a rapidly developing country, initiated its hydropower projects relatively late but has achieved remarkable growth. Since the 1990s, China’s hydropower industry has experienced significant development. Not only does China rank first globally in the total installed hydropower capacity, but it has also successfully implemented several hydropower projects with capacities exceeding 1000 MW, setting world records across multiple indicators. Consequently, a comparative analysis of the green social responsibility fulfillment mechanisms of hydropower projects in China and the United States can provide a reference for the green and sustainable management and production practices of other developed and developing countries.

Considering the significant differences in the development cycle, the data disclosure mechanism and policy environment of hydropower projects between China and the United States as well as the fact that the disclosure rate of Environmental and Social Impact Assessment (ESIA) reports for major global hydropower projects was less than 30% before 2012, we selected the period from 2013 to 2024 as the research interval. Furthermore, event causality extraction technology and system dynamics modeling were employed to explore the dynamic relationships and evolutionary trends of the mechanisms through which hydropower projects fulfill their green social responsibilities. Chinese samples were drawn from the “China Hydropower Engineering Yearbook” for the operational hydropower stations (including pumped storage) with installed capacities of 1 million kw or 500,000 kw and matched with entities disclosed in the financial reports of listed enterprises. American samples were screened from the EIA Form-860 database for commercial power generation facilities licensed by the Federal Energy Regulatory Commission (FERC), excluding experimental and decommissioned projects, and limited to engineering entities with complete ESG report records. The geographical distribution of the research samples encompassed major hydropower clusters such as the Yangtze River Basin and Columbia River Basin.

The feasibility exploration of fulfilling green social responsibilities in Chinese and American hydropower projects will provide valuable experience and case studies for developed countries and developing nations in their strategies for managing environmentally friendly hydropower projects. Based on the above content, this study raised the following questions: (1) Is there a causal mechanism relationship between transparency governance, legal compliance, energy environment, and monitoring evaluation in the fulfillment of green social responsibilities in hydroelectric projects in China and the United States? (2) What are the similarities and differences between regulatory scripts and institutional expectations in the causal mechanism relationship of green social responsibility fulfilment in hydroelectric projects in China and the United States? (3) How can we comprehensively analyze the dynamic impact mechanisms of fulfilling green social responsibilities in different contexts for hydroelectric projects in China and the United States?

The marginal contributions of this research are summarized as follows. First, this study adopted an international comparative perspective and multi-level integrated analysis, leveraging natural language processing (NLP), text analytics, and system dynamics models to investigate the causal relationships, emotional tendencies, and internal feedback mechanisms of green social responsibility fulfillment in hydropower projects between China and the United States. This approach offers a novel methodological framework for advancing research in the hydropower sector. Second, building upon the empirical findings, this study conducted a qualitative analysis of the ethical, governance, green development, and risk response dimensions of hydropower projects in both countries. Through comparative research, we gained deeper insights into the differences and similarities in organizational behavior as well as strategic design among enterprises in China and the United States on their path to sustainable hydropower development. This analysis provides a valuable management model for formulating green development strategies that are suitable for both developed and developing countries.

The rest of this study is organized as follows. First, the introduction provides a concise review of the existing literature, elaborates on the economic and ecological challenges confronted by the current global landscape as well as human development (as illustrated in Figure 1a), and identifies research gaps while emphasizing the innovative contributions of this paper. Second, building upon the preliminary overview, the literature review presents a keyword clustering knowledge graph for a definition of the connotation of green social responsibility, developed using Citespace, v. 6.2.R4 (64-bit) Advanced. Additionally, relevant system designs and policy frameworks concerning green social responsibility, proposed by both international scholars and institutional bodies, are examined (as illustrated in Figure 1b). Third, the research methodology section clearly delineates the research object and methodology (as illustrated in Figure 1c), specifying the parameters of the selected model and providing a comprehensive description of the sample data. Fourth, the analysis and results section delves into the characteristics and trends of the data presented in various charts, exploring the reasons for data variations and the underlying mechanisms. Fifth, the discussion section compares and contrasts the implementation mechanisms of green social responsibility in China and the United States, with an emphasis on the influences of social culture and policy regulations, along with industrial structure. Finally, the conclusion synthesizes the key findings and main contributions of the study, highlighting the practical significance of the research on green social responsibility implementation mechanisms, and outlining future research directions. An overview of the research background and research approach is shown in Figure 1.

2. Theoretical Background and Literature Review

2.1. Research Status on Green Social Responsibility

Currently, green social responsibility constitutes a critical branch within the global domain of corporate social responsibility (CSR) [27]. Rapid economic growth has led to substantial environmental degradation through corporate production and operational activities, exacerbating the tension between environmental pollution and resource depletion [28]. From the late 20th century into the early 21st century, the emphasis of corporate social responsibility progressively transitioned toward sustainable development and environmental conservation, thereby giving birth to the novel concept of green social responsibility [29]. Green social responsibility refers to the concept that enterprises, while striving for economic interests, proactively assume their responsibilities toward the environment, society, and stakeholders, ultimately fostering sustainable development across economic, environmental, and social dimensions [30,31]. From the traditional perspective, green social responsibility represents a dual-action approach that integrates the pursuit of maximum profit with the exploration of green renewable resources. Its primary objective is to maximize the protection of the ecological environment and product safety [32]. From an innovative standpoint, green social responsibility serves as a symbol of corporate citizenship, emerging from process and product innovations within enterprises. It underscores the responsibilities of enterprises in economic, social, and environmental aspects while seeking support from regulatory agencies as well as stakeholders for financial and political endeavors [33]. Furthermore, from the organizational dimension, in 2021, Malik et al. innovatively proposed a viewpoint based on symbolic background theory, arguing that green social responsibility acts as a critical symbol for shaping executive-level self-concepts aligned with environmental responsibility [34]. Their study revealed that, mediated by the executives’ green commitment, green social responsibility positively influences the adoption of corporate environmental strategies. Therefore, green social responsibility is broadly acknowledged as encompassing not only the enterprises’ environmental performance, but also their interactive behaviors with stakeholders such as suppliers, consumers, and communities [35].

Existing empirical research within the academic community on green social responsibility primarily falls into two categories: one focuses on the driving factors of green social responsibility, while the other examines its impact and outcomes. The driving factors of green social responsibility are numerous and can primarily be categorized into internal and external dimensions. Regarding the internal driving factors, many scholars argue that corporate values and corporate culture serve as critical internal elements that motivate enterprises to fulfill their green social responsibilities [36,37]. In addition, research has indicated that the demands of internal stakeholders within enterprises (e. g., shareholders, employees, management, etc.) also play a significant role in promoting green social responsibility fulfillment [38]. Regarding the external driving factors, consumer demand and market competition are key external factors that propel enterprises toward fulfilling their green social responsibilities [39,40]. Additionally, government policies, regulations, and supervisory pressures constitute crucial external forces encouraging enterprises to adhere to green social responsibility [41]. Green social responsibility has consistently been a critical and distinctive component within the framework of corporate social responsibility. To date, enterprises have increasingly prioritized the fulfillment of environmental responsibilities, reflecting a strengthening commitment to corporate social responsibility. To some extent, this also signals an enhancement in business performance [42,43]. On the one hand, it can effectively foster harmonious relationships between enterprises and stakeholders [44,45]. On the other hand, it significantly and positively influences the financial performance indicators [46,47,48]. An in-depth examination of the interplay between green social responsibility and sustainable performance revealed that green social responsibility not only facilitates sustainable enterprise development, but also confers numerous advantages. First, enterprises undertaking green social responsibility can bolster their corporate image and brand value, thereby attracting more customers and consumers [49]. Second, such enterprises can strengthen ties with various stakeholders, enhancing their sense of social responsibility and credibility [50]. Finally, enterprises embracing green social responsibility can mitigate environmental risks, boost competitiveness, and establish a solid foundation for long-term growth [51].

2.2. Research Status on Green Social Responsibility of Hydropower Projects

The rapid development of industry has triggered a cascade of resource and environmental predicaments, which not only impede the sustainable development of contemporary humanity, but also pose a serious threat to the survival of future generations [52]. Therefore, research on the green social responsibility of hydropower projects exhibits a certain degree of uniqueness. Drawing upon the characteristics and development status of the hydropower engineering industry, experts from different disciplinary fields have elucidated the connotation of green social responsibility for hydropower projects from their respective dimensions. From the perspective of resource and environmental science, Chinese and foreign scholars have initiated extensive research on the problems, causes, and solutions related to environmental sustainability as well as resource carrying capacity. They emphasize that fulfilling green social responsibility in hydropower projects is a complex task that involves the synergy between the Earth’s ecosystem and natural resources. It not only requires meeting the green social responsibility demands of the dam owners, but also needs to address the expectations of a broader range of interest groups represented by immigrant communities [53]. From a macroeconomic perspective, economists have identified the drawbacks of the traditional socio-economic development model by remodeling and deducing its limitations, revealing that the root cause of environmental problems lies in economic issues [54]. Consequently, the core essence of green social responsibility for hydropower projects involves integrating multiple dimensions such as clean production, ecological management, environmental protection, and biodiversity into the consideration scope of resource allocation efficiency, production costs, and benefits [55]. From the perspective of microeconomics, relevant scholars have proposed that the green social responsibility of hydropower projects represents a concrete equilibrium among ecological sustainability, economic efficiency, and social objectives for all stakeholders including contractors, communities, the environment, suppliers, and emergency management associations [56]. Based on the circular economy strategy for the green social responsibility concept in hydropower projects, the existing academic and informal literature predominantly emphasizes the efficient utilization of secondary raw materials, product reuse and recycling, waste reduction, the promotion of industrial symbiosis, and material renewal [57]. Meanwhile, recent studies have begun to delve into design strategies for the hydropower circular economy, particularly in resource recycling and extending the lifespan of product materials. These investigations encompass technical applications and process improvements as well as specific approaches and methods [58].

With the diverse research perspectives of scholars both domestically and internationally, the influencing factors of green social responsibility in hydropower projects have become a focal point in the field of hydropower research. In comparison to other industries, fulfilling green social responsibility in hydropower projects represents an optimal approach to promoting the integration of technology and the economy while achieving the efficient allocation of resources. Consequently, numerous scholars have investigated its influencing factors [24]. Gallardo et al. argue that environmental performance, corporate reputation, competitive advantage, innovation efficiency and financial benefits serve as critical driving forces for hydropower projects to fulfill their green social responsibilities [59]. Owusu et al. emphasize that the current green social responsibility practices in hydropower projects focus on environmental issues as a target carrier and are grounded in the value commitment to an ecologically sustainable society. Therefore, it is essential to investigate the incentive factors underlying the green social responsibility strategies of these projects [60]. They highlight that the internal driving factors include the enterprise’s environmental management capabilities and its knowledge and resources related to green innovation [61]. Furthermore, Dmytriyev et al., drawing on the perspectives of new institutional theory and stakeholder theory, highlighted that pressure from various stakeholders, including the media, community residents, competitors, suppliers, and consumers, plays a crucial role in shaping strategic decisions regarding green social responsibility in hydropower projects [45]. It is evident that the influencing factors of green social responsibility in hydropower projects can be categorized into two main dimensions: internal factors, such as corporate strategy, cultural values, and organizational structure, and external factors including government regulations, market competition, and stakeholder pressures.

2.3. Research Status on Causal Mechanism Theories and Methodologies

In the era of digital transformation and technological advancement, the precise and efficient extraction of salient elements from massive unstructured and heterogeneous textual data sourced from government meetings, news headlines, and social media has emerged as a key research direction in natural language processing [62]. In recent years, there has been widespread attention from scholars to application-oriented research focusing on text-based event causality extraction [63,64]. Event causality extraction (ECE) involves representing causal events and the resulting events in structured form within textual information, primarily comprising two subtasks: cause event extraction and result event extraction [65]. Generally, based on whether causes and results appear simultaneously in the text, event relation extraction is further divided into explicit causality extraction and implicit causality extraction.

The initial approach employed by researchers to address the problem of relation extraction was rule-based, which entailed manually formulating causal relationship rules based on expert knowledge or constructing them from dictionaries. However, this method necessitated significant manual intervention [66]. Consequently, machine learning algorithms have gradually emerged as a means for event causality extraction. This approach fundamentally treats relation extraction as a classification problem and constructs classifiers using specific learning algorithms to judge categories in domain corpus relations [67]. At present, the most commonly utilized learning algorithms are the MBL and SVM algorithms; however, they pose challenges when dealing with multi-classification problems [68]. With the increasing popularity of deep learning, event causality extraction methods based on deep learning algorithms have garnered considerable attention. Deep neural networks possess formidable representation learning capabilities and can effectively capture implicit and ambiguous causal relationships. Presently, this approach primarily relies on two frameworks: pipeline and joint extraction to accomplish causality extraction [69].

In order to comprehensively derive future trends in the evolution of events, system simulation methods, which combine systems engineering and computer technology, are employed to simulate the operational mechanisms and behavioral evolution of target systems through computational models. This facilitates organizational managers in obtaining various types of information required for decision-making [70]. System simulation is an important component of quantitative decision analysis, which encompasses three fundamental activities: establishing system models, constructing simulation models, and conducting simulation experiments [71]. In current practice, the value of system simulation in dealing with deep uncertainty issues, such as global climate change, crisis event response, and the regulation of irrational behavior processes, is self-evident [72]. Previous research has also proposed targeted simulation approaches based on the concepts and essence of uncertainty and deep uncertainty. Statistical quantification-based simulation methods have become an intuitive means to characterize uncertain system evolution when the evolutionary behavior of the target system exhibits characteristics such as incomplete knowledge about changes in the external environmental factors and random fuzziness [73]. Simulation paradigms based on optimal knowledge or information are considered important practices for integrating new knowledge or information into simulations when uncertainties arise from insufficient data, information, and knowledge regarding the system structure [74]. When the system conditions fail to satisfy probability statistics and the inherent evolutionary rules cannot be determined by models, exploratory simulation based on computational experiments has become a valuable tool for assessing the evolutionary trends of real systems. This approach, which has been widely adopted by simulation scholars [75], assumes that multiple potential scenarios exist in the future as an open system, necessitating decision-makers to construct diverse initial conditions to explore possible trajectories of the system.

3. Materials and Methods

Firstly, this study employed the event causality extraction method to conduct an in-depth exploration of green social responsibility practices in China and the United States, focusing on areas such as compliance disclosure, environmental governance, sustainable development, technological innovation, resource management, and risk control. The main sources of information were reports, the academic literature, and company websites. The research scripts focused on large- and medium-sized hydropower stations within the jurisdiction of China and the United States as well as hydropower engineering enterprises. Secondly, this study further utilized content analysis to describe and quantitatively analyze the causal mechanism relationship between green social responsibility fulfillment in both Chinese and American hydropower projects in order to dissect the differences and commonalities in their causal paths. Finally, in order to effectively predict simulation feedback mechanisms for the causal mechanisms behind green social responsibility fulfillment in Chinese and American hydropower projects as well as future behavioral evolution patterns, this paper adopted a system dynamics (SD) model to guide the research. There are three justifications for using system dynamics as a modeling framework: (1) system dynamics is highly applicable when dealing with long-term or cyclical problems especially those that do not require high precision; (2) system dynamics typically has no specific restrictions on the nature or quantity of system variables that support solving complex system problems with incomplete data or qualitative variables; (3) system dynamics aids in simulating strategic-oriented long-term analysis through structural characterization and behavior paradigms for complex systems. The research methodology technical roadmap is shown in Figure 2.

3.1. Event Causality Extraction

In order to comprehensively analyze and compare the disparities in the regulatory scripts and institutional expectations of hydropower projects between China and the United States under various scenarios of green social responsibility events as well as effectively explore the causal mechanisms linking green social responsibility fulfillment with transparency governance, compliance requirements, environmental protection, resource efficiency, monitoring, and evaluation, this study employed the event causality extraction (ECE) method for research.

The utilization of this methodology for research exhibits a certain technical feasibility: the extraction and summarization of causal relationships in financial events based on semantic analysis by leveraging the information embedded within financial texts [76,77]. As early as the turn of the century, researchers have proposed employing causal relationships present in financial text data to enhance predictive models for financial trading [56]. During that period, emphasis was primarily placed on news reports and predictions regarding stock price volatility [78]. However, with the advent of substantial social media data generated after 2010, numerous research endeavors have emerged, utilizing platforms like Twitter and Facebook to forecast stock market trends. Some analyses have indicated that decision-makers tend to rely more heavily on qualitative information such as news articles, events, or even rumors, rather than quantitative data when making investment decisions [79]. Consequently, the semantic-based extraction of event causality plays a pivotal role in analyzing and predicting market data concerning the fulfillment of green social responsibility by hydropower engineering enterprises [80].

Commonly used methods for causality extraction include rule-based methods, machine learning-based methods, and deep learning-based methods. The specific methodologies, model systems, and characteristics are summarized in

Table 1. Event causality extraction methods.

Type	Methods	Model	Characteristics
Rule-based	Manually or dictionaries	Proteus	Highly accurate patterns Personalized customization
		LaSIE-II
		NetOwl
		FACILE
Machine learning-based	Classification modeling	SVM	Small sample learning methods Avoid curse of dimensionality Good “robustness”
		DBN
	Sequential modeling	HMM
		HEMM
Deep learning-based	CNN + CRF	CNN-CRF	Excellent matching ability Strong robustness and fault-tolerance Possess the capacity for association Possess reasoning ability
		IDCNN-CRF
		RDCNN-CRF
	LSTM + CRF	LSTM-CRF
		BiLSTM-CRF
	CNN + LSTM + CRF	BiLSTM-CNN-CRRF
	Attention clustering	Bert-Attention-CRF-Clustering

. In this study, a deep learning algorithm-based attention network clustering model (Bert-Attention-CRF-Clustering) was adopted to extract causal relationships describing event information from textual databases within different contexts of the green social responsibility implementation mechanisms in the settings of both countries while presenting them in a structured format.

In the algorithm environment of Python 3.8 and Torch 2.1, the Bert-Attention-CRF-Clustering model accomplished the causal relationship extraction through a two-step process: event detection and relation classification. In the initial stage of event detection, this study aimed to extract information on groups of events from the text corpora. The corpus utilized in this study comprised text datasets associated with hydropower projects from the United States and China. Specifically, the Chinese corpus data were primarily sourced from operational hydropower stations (including pumped storage) with installed capacities of 1 million kW and 500,000 kW, as documented in the “China Hydropower Engineering Yearbook”, which aligns with the disclosure requirements of the listed enterprises’ financial reports. Additionally, relevant textual materials were collected using web crawlers from government websites, news media, and academic databases. For the American corpus, data collection was based on the EIA Form-860 database to identify commercial power generation facilities licensed by the Federal Energy Regulatory Commission (FREC) excluding experimental and decommissioned projects. The dataset was further restricted to engineering entities with complete Environmental, Social, and Governance (ESG) report records, primarily derived from the EIA-923 power generation report and SEC 10-K documents. The temporal scope of the corpus spanned from 2013 to 2024, while the geographical distribution of the samples encompassed major hydropower clusters such as the Yangtze River Basin and Columbia River Basin. The data processing pipeline of this study consisted of the following steps: (1) text preprocessing, where irrelevant characters and formats were removed, followed by slicing the corpus; (2) word segmentation and annotation, in which Jieba was employed for Chinese text segmentation and NLTK utilized for English text segmentation; (3) fine-tuning of the model; (4) model training; and (5) model optimization and extraction of causal information from event groups in the text. The Python code for model fine-tuning, training, and optimization is provided in Appendix A with detailed explanations. Figure 3 illustrates the technology roadmap for causal relationship extraction based on attention network clustering models.

3.2. Content Analysis

Building upon the aforementioned event causality extraction techniques, this study further utilized word cloud analysis and text sentiment analysis tools to investigate the primary areas of focus for monitoring protocols and institutional expectations concerning green social responsibility in hydropower projects. Additionally, it explored the emotional themes and fluctuations depicted in various texts such as social media posts, news reports, and official documents from both countries.

The text was sourced from a Chinese–English corpus. The Chinese corpus primarily consisted of operational hydropower stations and pumped storage power stations with installed capacities of 1 million kilowatts and 500,000 kilowatts, respectively, as documented in the “China Hydropower Engineering Yearbook”. The English corpus originated from commercial power generation facilities licensed by the Federal Energy Regulatory Commission (FERC) and recorded in the EIA Form-860 database. In addition, this dataset includes 1033 news articles obtained through web crawling technology, over 300 government reports, industry research papers, practical cases, and core journal articles referenced in related research scripts. To effectively address the semantic discrepancies between the Chinese and English texts, we developed an event causality extraction script named “translate” to acquire the English data and utilized an API for translation into Chinese. Despite some inaccuracies and malformed sentences in the final output, manual corrections were made to improve the results.

In terms of word cloud analysis, effective preprocessing was conducted on the extracted causal relationship events from the dataset. To enhance accuracy in the analysis, this study employed the Harbin Institute of Technology’s stop-word list and the deep learning-based segmentation tool called Jieba to generate word cloud maps. For the text sentiment analysis, deep learning-based text sentiment classification models such as Transformers and TextBlob were employed in this study to identify the portrayal of and attitude toward green social responsibility in public opinion regarding hydropower projects. The constructed analytical framework is illustrated in Figure 4.

3.3. System Dynamics Simulation

Based on the aforementioned deep learning algorithms, the researchers were capable of accurately extracting the causes and results of green social responsibility events in China and the United States from a substantial amount of structured text. To predict and simulate the interaction and feedback mechanisms between the causal relationships of green social responsibility in hydroelectric projects in both countries more comprehensively, this paper further adopted a system dynamics approach to construct a holistic model for green social responsibility mechanisms in both Chinese and American hydroelectric projects. The system was segmented into several subsystems, effectively revealing the causal relationships between subsystems or within subsystems while establishing mathematical models to quantify the impact of key factors on the green social responsibility mechanisms in both countries.

3.3.1. System Dynamics Fitness Analysis

System dynamics has wide application value and scientific orientation in investigating the green social responsibility fulfillment mechanism of hydropower projects in China and the United States, which is evidenced by several aspects. First, the green social responsibility system is a complex open-source framework that integrates intricate structures with functional mechanisms, necessitating an analysis of numerous interrelated influencing factors within its operational fulfillment mechanism. This structured approach enables a comprehensive examination of the intricate interactions and feedback relationships among various internal substructures of the green social responsibility system. Second, there are some difficult-to-quantify or data-missing causal factors in fulfilling green social responsibilities. However, multiple feedback loops in system dynamics can obtain reliable simulation results by reasonably estimating the relevant parameters when most variable parameters of a system are insensitive to its dynamic behavior patterns. Finally, researchers can effectively depict and simulate evolutionary patterns pertaining to green social responsibility fulfillment under diverse scenarios using system dynamics models, which facilitates an analysis of the dynamic impact mechanisms resulting from different influencing factors on such fulfillment.

3.3.2. System Boundary, Basic Hypothesis, and System Structure

The system boundary includes spatial and temporal boundaries. This study defined the spatial boundary of the system as large- and medium-sized hydropower stations and hydropower engineering enterprises with capacities of 1 million kW and 500,000 kW in China as well as those in various basins in the United States. The temporal boundary was set from 2020 to 2035 (with 2020 as the base year) with a simulation time step of one year, aiming to simulate and predict possible trends and evolutionary paths of the system in the future, while conducting corresponding policy analysis.

Furthermore, in order to simplify the analysis of the complex green social responsibility system and ensure the scientific and logical nature of the model setting, this study proposed the following basic assumptions: (1) external factors will not have any impact on the model; (2) there will be no significant changes in the system during the simulation period and the development trends of all elements of the system will remain relatively stable; (3) the level of green social responsibility can be evaluated from three dimensions: ethics and governance, green development, and risk response; and (4) moderately simplifying factors such as different dimensions of green social responsibility and comprehensive development level based on scientifically describing relative values and trends of variables in the system will not affect its operational effectiveness.

In the scientific framework of system dynamics, this study divided the causal dynamic mechanism system model for fulfilling green social responsibilities in hydropower projects into three substructures: ethics and governance, green development, and risk response. Regarding the ethics and governance subsystem, it examined the impact of fulfilling green social responsibilities on establishing robust management structures and ethical standards in enterprises from three aspects: supervision acceptance, disclosure of social responsibility, and government relations. Regarding the green development subsystem, it categorized the concept of green into four areas: energy conservation and emissions reduction, energy audit and assessment, clean energy, and green supply chain. It comprehensively measures the impact of fulfilling green social responsibilities on environmental efficiency and resource efficiency in enterprises. As for the risk response substructure, it divided the risk response into four domains: risk assessment, risk management strategies, monitoring early warning systems, and disaster management to evaluate the influence of fulfilling green social responsibilities on business stability and resilience against risks.

4. Results

4.1. Causality Extraction Results

4.1.1. Causal Relationship Entity

After conducting a series of semi-supervised text classification analyses based on the Bert-Attention-CRF-Clustering model, this study identified causal relationship entities closely related to the green social responsibility performance mechanism of Chinese and American hydropower engineering, as shown in Figure 5.

4.1.2. Regulatory Scripts and Institutional Expectations

In addition, to further explore and discuss the disparities and resemblances in green social responsibility fulfillment mechanisms between China and the United States across various causal entities with the aim to provide experiential guidance for the sustainable development of global hydropower projects, this study categorized the factors related to government regulations and regulatory agencies in the event groups of green social responsibility for hydropower projects as regulatory scripts, while their corresponding outcomes were defined as institutional expectations.

Table 2. Regulatory scripts and institutional expectations.

Regulatory Scripts	China Institutional Expectations	United States Institutional Expectations
Ethics and governance	1. Disclose the work of immigration relocation, quality, environment and occupational health; 2. Regularly disclose corporate social responsibility reports and willingly accept supervision; 3. Promote information sharing and government collaboration.	1. Comply with license standards and accept public supervision; 2. Disclosure of social responsibility through all reports and documents; 3. Cooperate with the federal government to provide low-interest funds.
Green development	4. Carry out green partner certification, build a green supply chain; 5. Establish green development assessment and renovation plans; 6. Optimize scheduling for green low-carbon energy 7. Strengthen the construction of new energy storage and create a clean energy base.	4. Enhance the level of renewable energy dispatch and promote the construction of wetland projects; 5. Introduce renewable energy, energy storage, and carbon capture technologies into power grid; 6. Conduct green energy audits on past dam rupture incidents; 7. Improve green infrastructure planning and clean energy financing.
Risk response	8. Conduct security risk assessment and establish a risk event response mechanism; 9. Promote risk control measures and methods; 10. Establish an intelligent risk supervision system.	8. Conduct a system risk assessment and carry out emergency management work; 9. Develop a comprehensive and long-term risk management plan; 10. Establish monitoring and early warning mechanisms.

below provides a detailed explanation of the causal relationship between green social responsibility for hydropower projects in China and the United States including regulatory scripts and institutional expectations. Furthermore, employing the VOSviewer quantitative analysis method, this study further constructed a co-linearity network diagram of keywords related to regulatory scripts and institutional expectations within the causal mechanism of fulfilling green social responsibilities for hydropower projects in China and the United States, as illustrated in Figure 6.

4.2. Content Analysis Results

4.2.1. Descriptive Analysis

Based on the aforementioned content, this study focused on conducting a high-frequency keyword extraction and semantic analysis of regulatory texts and institutional expectations concerning green social responsibility performance in hydropower projects in China and the United States. The objective was to compare and contrast the primary emphases and objectives of the strategies for fulfilling green social responsibilities within the hydropower sector in both countries, ultimately resulting in the keyword ranking histogram presented in Figure 7.

According to the types of thematic words and node relevance, the causal relationship between Chinese hydropower engineering and green social responsibility can be divided into three categories. The first category comprises central and interconnected thematic words such as early warning, hydropower stations, energy, green, risk, management, supervision, and so on, reflecting the close association between Chinese hydropower engineering construction and supervision management, green energy, and risk warning. The second category consists of recurring responsible entities like power enterprises and water conservancy departments at all levels of government including the State Council. It demonstrates that the implementation and promotion of green social responsibility by Chinese hydropower engineering mainly rely on collaborative efforts among multiple departments. The third category includes frequently mentioned keywords such as governance, responsibility rectification, emergency response, and so on, indicating that various departments generally attach importance to emergency governance in the hydroelectric system and fulfilling their responsibilities.

Similarly, the causal relationship between green social responsibility and hydropower projects in the United States can be divided into three categories. The first category includes words such as energy, regulation, risk, information, warning, and safety that reflect the priority given to production safety in hydropower project development in the United States. The second category includes recurring terms like federal, state, government, and electricity department, which demonstrate the evident federal characteristics of fulfilling green social responsibilities in U.S. hydropower projects. The third category consists of keywords mentioned multiple times such as evaluation, water resources, infrastructure, and emergency management, which indicate a deep understanding of the importance of risk assessment and emergency management in hydropower infrastructure and development at all levels in the United States.

4.2.2. Quantitative Research

After conducting a descriptive analysis of the causal mechanism between green social responsibility and hydropower projects in both countries, this study employed topic modeling to identify the main issues, trends, and sentiment tendencies in the textual causality relationships. The quantified analysis results are shown in Figure 8 and Figure 9.

First, the study visually presented the causal relationship between the fulfillment of green social responsibility in Chinese and American hydropower projects and the sentiment scores of different policy titles through a parallel bar chart and scatter plot. The study revealed that compared with the English texts, the Chinese policy texts expressed more positive concepts and practices related to green social responsibility in areas such as ethics and governance, green development, and risk response. This difference may be attributed to various factors including disparities in the developmental stages of hydropower projects, conceptual awareness, and institutional systems between both countries. China initiated its hydropower development relatively late compared with the United States. However, as a developed country with matured hydropower technology and a well-established green technology system, the United States has long prioritized sustainability and the safe management of hydropower energy. Consequently, in recent years, Chinese hydropower projects have demonstrated a strong inclination toward fulfilling their green social responsibilities when confronted with dual challenges from society and the environment. Based on clustering results depicted in the scatter plots, it can be observed that certain text policies from both countries exhibited similar sentiment scores regarding the causal relationships between ethics/governance, green development, and risk response. The similarity may be attributed to the complex coupling effect of various factors such as international standards, industry norms, social expectations, and global environment.

Second, the causal relationship between the fulfillment of green social responsibilities in both Chinese and American hydropower projects and the sentiment score matrix among different textual policy titles and languages was demonstrated through heatmaps. The heatmap for the causal relationship of green social responsibilities in Chinese hydropower projects revealed that there were 376 events within the range of −0.1 to 0 scores that were related to “green development”. Due to involvement in various fields and issues such as environmental protection, sustainable development, and clean energy, these events may exhibit diverse and complex characteristics. On the other hand, the heatmap for the causal relationship of green social responsibilities in American hydropower projects showed that there were 764 events within the range of 0.9 to 1.0 scores that were related to “risk response”. This result indicates a high level of attention and recognition given by society and stakeholders toward risk response measures in American hydropower engineering.

4.3. Dynamical Simulation Results

4.3.1. Causal Relationship Diagram

Based on the structural analysis of the system model in the previous section, this paper used Vensim software 7.3.5 to construct a causal relationship diagram for the driving mechanism of fulfilling green social responsibilities in hydropower projects in both countries, as shown in Figure 10. The main feedback loops are presented as follows: (a) level of green social responsibility in hydropower projects → ethics and governance; (b) level of green social responsibility in hydropower projects → risk response; (c) level of green social responsibility in hydropower projects → green development; (d) level of green social responsibility in hydropower projects → green supply chain → green development; (e) level of green social responsibility in hydropower projects → disaster management → risk response; (f) level of green social responsibility in hydropower projects → risk response → disclosure of corporate social responsibilities → ethics and governance; (g) level of green social responsibility in hydropower projects → green supply chain → clean energy → green development.

It is undeniable that China and the United States exhibit significant differences in economic systems, policy environments, and regulatory frameworks. However, when analyzing the causal relationship entities, regulatory scripts, and institutional expectations derived from the fulfillment of the green social responsibilities of hydropower projects in both countries as discussed in Section 4.1.1 and Section 4.1.2, it became evident that the two nations shared commonalities in ethics and governance, green development, and risk response mechanisms. The causal relationship diagram (Figure 10) served as a high-level analytical framework that integrated both China and the United States, emphasizing the overarching principles of sustainable hydropower development for the future, rather than focusing on specific national policies. Consequently, this framework remains applicable within the contexts of both countries.

4.3.2. System Dynamics Model

Based on the selected system-related variable parameters and causal relationship diagram, a stock flow diagram of the cause effect mechanism for fulfilling green social responsibilities in hydropower projects in both countries is further depicted in Figure 11. This study initially determined the parameter values of the model variables using the expert estimation method and adjusted the parameters and equations of variables based on practical correction experience to ensure that the values and trends of variables in the model were consistent with the actual development of green social responsibilities in hydropower enterprises.

4.3.3. Model Verification and Simulation Scenario Design

Model Verification

In order to verify the accuracy and reliability of the system dynamics model in simulating real systems, this study used two methods, namely intuitive inspection and the model running test, to validate the effectiveness of the model before conducting the model simulation and scenario analysis.

Firstly, in terms of the intuitive examination of the model, the system dynamics model for the causal driving mechanism of green social responsibility fulfillment in Chinese and American hydropower projects was constructed based on a holistic sustainable scientific framework. The division of the structural system of the model and the causal relationship diagram and stock flow diagram fully considered the current situation of green social responsibility fulfillment in China and America. The dynamic equations between the model parameters and system variables were reasonably set. This study believes that the model passed an intuitive examination.

Secondly, in terms of model validation, this study conducted structural and unit tests on the dynamic equations between the overall system variables to ensure the reasonable completeness and consistency of the parameter variable equations in the model. By clicking “Check Model” and “Units Check” in the Vensim software, we found that the models all displayed “Model is OK” and “Units are OK”, indicating that they passed the validation test.

Simulation Scenario Design

The study set up three types of simulation scenarios. The first type was the baseline scenario, which kept the initial state of the model and did not modify any system parameters. The second type was the endogenous driving force scenario, which only changed the internal driving forces related to green social responsibility in the Chinese and American hydropower projects without altering other parameters. The third type was the fundamental driving force scenario, which only changed the basic driving forces related to green social responsibility in Chinese and American hydropower projects without modifying other parameters.

First, under the premise of maintaining the initial state of the system dynamics model unchanged, simulation and modeling were conducted to obtain the simulation results of the causal mechanism of green social responsibility performance in hydropower projects in both countries at different dimensions and levels of comprehensive development, as shown in Figure 12. The results showed that, during the simulation period, the hydropower projects exhibited an overall positive trend in terms of different dimensions and levels of green social responsibility mechanisms. This trend was mainly attributed to the positive development in various aspects such as internal governance, environmental sustainability, and social risk response within both countries’ hydropower projects. Moreover, there existed a self-enhancing positive feedback effect within the system itself. Specifically, both the comprehensive level of green social responsibility performance and the causal dimension level for green development in hydropower projects in both countries showed an exponential increase. On the other hand, the ethical governance dimension level and risk response dimension level demonstrated a pattern characterized by rapid growth initially, followed by gradually reaching higher levels.

The second step was to explore the impact of endogenous factors on the level of green social responsibility in hydropower projects in China and the United States by improving the internal driving force of the causal mechanism for green social responsibility based on the benchmark scenario analysis. This study selected ethical and governance factors, green development factors, and risk response power as proxy variables for endogenous driving forces. By increasing the parameters of the regulatory factors by 10%, we examined the changing trends in various relevant output variables under an endogenous driving force scenario, as shown in Figure 13. The results showed that with the improvement in the level of the endogenous driving force for green social responsibility in hydropower projects in China and the United States, there was a significant improvement in the ethical and governance aspects, green development aspects, and risk response aspects.

From the perspective of the main driving paths for the fulfillment of green social responsibility mechanisms by endogenous motivation, the model showed that the ethical and governance levels were determined by factors such as supervision acceptance, government relations, and disclosure of social responsibility. Furthermore, when both green development and risk response increased by 10%, risk response had a more significant impact on ethical and governance improvement. On the other hand, in the model, the green development level was mainly determined by factors such as clean energy, green supply chain, energy audit, and assessment as well as energy conservation and emissions reduction. Additionally, when both the ethical and governance levels along with risk response increased by 10%, the risk response had a more noticeable effect on promoting green development. Finally, in the model, the risk response level was determined by factors such as monitoring warning systems, disaster management strategies, and risk assessment. Moreover, when both the ethical and governance levels along with green development increased by 10%, green development had a more prominent influence on enhancing the risk response.

Finally, the third step was to explore the impact of the fundamental driving factors on the level of green social responsibility in hydropower projects between China and the United States by improving the causal mechanism of green social responsibility based on the benchmark scenario analysis. By increasing the regulating factor parameters by 10% and examining changing trends in the relevant output variables under a fundamental driving scenario, as illustrated in Figure 14, our findings suggest that when the ethical governance, green development, and risk response parameter factors are all increased by 10% in Chinese and American hydropower projects, green development has the most significant impact on fulfilling the green social responsibility mechanism in both countries, followed by risk response and ethical governance.

4.3.4. System Simulation Results

This study employed the system dynamics methodology to construct a system dynamics model that elucidated the causal mechanism of green social responsibility in Chinese and American hydropower engineering. The model was utilized to simulate and analyze the dynamic evolution characteristics of various dimensions and the overall levels of hydropower enterprises in both countries under three distinct driving scenarios. The key findings are as follows:

(1)

The cause-and-effect mechanism of green social responsibility in hydropower projects in both countries exhibited an overall positive trend across different dimensions and levels of comprehensive development;

(2)

Under the influence of endogenous motivation, the effects of hydropower projects in both countries were more pronounced in terms of ethics and governance, green development, and risk response. Moreover, the risk response had a more noticeable impact on enhancing ethics and governance as well as promoting green development, while green development exerted a stronger influence on enhancing the risk response;

(3)

Under the scenario of basic power driving, the driving effect of green development power factors on the fulfillment mechanism of green social responsibility in hydropower projects was the most significant, followed by the risk response-related factors and ethical and governance-related factors.

5. Discussion

Based on the previous section, ethics and governance, green development, and an enhancement in the risk response capacity are crucial for the level of the green social responsibility performance mechanism and sustainable development in hydropower projects. Therefore, we further employed VOSviewer to construct temporal network diagrams for the three regulatory scenarios and institutional expectations, thereby uncovering the dynamic differences in green social responsibility strategic behaviors of hydropower projects between China and the United States, as illus-trated in Figure 15 below. Based on this, this study delved into the similarities and differences in green social responsibility strategic behaviors between the two countries’ hydropower projects in terms of ethics and governance, green development, and risk response.

5.1. Ethics and Governance Discussion

The ethical and governance regulations for hydropower projects in China and the United States included three green social responsibility mechanisms: accepting supervision, disclosing social responsibilities, and maintaining government relations.

In terms of supervision, both Chinese and American hydropower projects emphasize the scientific and reasonable supervision of the structural safety operation of hydropower stations in accordance with the prescribed standards and procedures. Chinese hydropower enterprises adopt a leading expert model for responsibility regulation in green hydropower development mechanisms through measures such as responsibility lists and issue logs, reflecting their pursuit of order, norms, and respect for expert authority. In contrast, American enterprises authorize the operation of green hydropower plants under regulatory activities through license standards or rules, using methods such as general manager certificates and individual licenses to reflect consistency with personal rights and legal provisions, individual responsibilities, and self-management in American cultural traditions.

Based on the paradigm of social responsibility disclosure, Chinese and American hydropower engineering enterprises have established quantifiable and scientific sustainable development goals, and regularly disclose their green performance achievements. The difference in social responsibility disclosure between Chinese and American hydropower engineering mainly lies in the fact that Chinese enterprises emphasize the public disclosure of the energy-saving and emissions reduction targets achieved in supply chain management, highlighting the concept of integration between enterprises, society, and the environment. On the other hand, American hydropower enterprises create a “green planning zone process” between private industry and regulatory agencies to ensure transparency requirements for stakeholder information. This is because most dams in the United States are privately owned and are not subject to public sector transparency restrictions, reflecting America’s emphasis on individual rights and private property, while fully trusting the dual driving force of free markets and industry self-regulation to implement green social responsibility strategic goals.

Based on government relations, the hydropower project aims to build an information exchange and sharing platform between upstream and downstream enterprises, government departments, and consumers in the supply chain, in order to increase the preference of government and social capital for investing in the green governance of river basins. Chinese hydropower enterprises achieve a green social responsibility operating model through cooperation with governments and social capital, which reflects the characteristic of the government-led development stage in the Chinese economy, while American hydropower enterprises provide low-cost financing solutions for potential local and private participants in green hydropower through collaborative efforts with insurance enterprises and federal governments, fully reflecting the importance of individualism and private interests in American societal values.

5.2. Green Development Discussion

The green development supervision script for hydropower projects in China and the United States includes four green social responsibility institutional expectations: energy conservation and emission reduction, green supply chain, clean energy, and energy audit assessment.

In terms of energy conservation and emissions reduction, both Chinese and American hydropower projects focus on environmental energy-saving standards, energy consumption limits, and carbon footprint assessments in the construction process. Chinese hydropower enterprises control carbon emissions by implementing the online monitoring of energy consumption and emission reduction database systems as part of their green social responsibility strategy. On the other hand, American hydropower enterprises promote diversified energy solutions through the connection of north–south power grids within states as their green social responsibility actions in energy conservation and emissions reduction. This practice highlights China’s use of energy monitoring technology as a guide for sustainable development, while the United States places more emphasis on market mechanisms and regional innovation.

In terms of the green supply chain, hydropower projects in both countries aim to establish a cooperative mechanism for stakeholders in the supply chain to quickly respond to the green social responsibilities of new energy projects. Chinese hydropower enterprises conduct green partner certification for suppliers in the green supply chain system, reflecting China’s value concept of advocating material environmental protection and green production. American hydropower enterprises are committed to innovative cooperation in green supply chain ports such as electricity, transportation, wetlands, etc., demonstrating the mature technological development stage of American hydropower.

In terms of clean energy, hydropower projects in both countries prioritize achieving low-carbon electricity production and the electrification of energy consumption, actively promoting the efficient utilization of green and clean energy. Chinese hydropower enterprises are committed to accelerating the construction of a comprehensive system for injecting clean energy, reflecting their emphasis on diversified clean energy sources. On the other hand, American hydropower enterprises adopt efficient power selection and technologies such as heat pumps as substitutes for clean energy, demonstrating their leading position in energy technology research and application.

Based on energy audit assessments, both Chinese and American hydropower projects conduct investigations and evaluations on various aspects of hydroelectric plants including their basic conditions, approval procedures, and social factors. Chinese hydropower enterprises mainly implement green transformation plans for hydroelectric stations with incomplete procedures or fail to meet the environmental requirements. American hydropower enterprises take historical flood events and risk exposure estimates into full consideration, tending to issue permits to manage environmental compliance, reflecting the safety and reliability of energy audit assessments in both countries.

5.3. Risk Response Discussion

The risk response regulatory script for hydroelectric projects in China and the United States includes four green social responsibility institutions: risk assessment, risk management strategies, monitoring and early warning, and disaster management.

Based on risk assessment, China and the United States combine moral and integrity compliance requirements to conduct risk checks for the green and sustainable development of hydropower projects throughout their life cycle. Chinese hydropower enterprises carry out routine green environmental risk assessments through activities such as interviews, tool access, and risk calculations. American hydropower enterprises, on the other hand, use an evidence-based approach to assess the risks of operating a green hydroelectric power station based on existing information regarding dam safety conditions and personnel risks. This practice reflects both countries’ organizational behavior paradigm of transforming dam risk analysis issues into multi-criteria decision-making problems.

Based on risk management strategies, both Chinese and American hydropower projects emphasize the need to establish risk management awareness, develop risk management models, promote risk control measures, and construct a dynamic system for the green operation and safe risk control of hydropower stations. The fulfillment of green social responsibilities by Chinese hydropower enterprises reflects the shift from experiential management to scientific management through strategies such as interval requirements for regular inspections, dam safety classification assessments, treatment of potentially dangerous dams, and emergency measures. On the other hand, American hydropower enterprises model the impact of green governance strategies on infrastructure like dams and formulate longer-term solutions for managing risks, demonstrating standardization, normalization, and informatization.

In terms of monitoring and disaster management, both Chinese and American hydropower projects actively implement engineering measures and non-engineering measures to strengthen the monitoring and early warning network for the green operation of hydropower stations as well as the technical support for disaster prevention and control. The fulfillment of green social responsibilities by Chinese hydropower enterprises relies on intelligent monitoring and early warning systems as well as remote sensing diagnostic identification technology for environmental disaster risk assessment and prevention research, reflecting an innovative thinking culture. On the other hand, American hydropower enterprises tend to develop disaster warning mitigation plans, encourage collaboration among disaster mitigation teams, and promote funding programs for disaster mitigation, reflecting a risk management model involving multiple agencies.

6. Conclusions and Future Outlook

This study examined the green social responsibility mechanisms of hydropower projects in China and the United States, employing the event causality extraction and system dynamics methods to derive empirical evidence. The key findings of this article center on three principal aspects: from the perspective of extracting causal relationships from event causality, there exist causal relationships between the fulfillment of green social responsibility and ethical governance, green development, and risk response as three regulatory mechanisms in hydropower projects. The entities involved in these causal relationships include supervision acceptance, the disclosure of social responsibility, government relations, energy conservation, and emissions reduction expectations, among other institutional expectations. From the analysis of the descriptive text and results of the quantitative analysis, influenced by stage, environment, and policy factors, Chinese hydropower enterprises have expressed more positive concepts and practices regarding green social responsibility while placing high importance on green development. On the other hand, American hydropower enterprises have paid more attention to risk response. From the perspective of system dynamics results, the causal driving mechanism for green social responsibility is a complex system that evolves continuously with orderly operation. Under three driving scenarios in hydropower projects in both countries, this mechanism demonstrated a trend toward benign development.

This research supports hydropower projects in China and the United States by enabling them to more effectively balance economic benefits with ecological and social impacts during both construction and operation. It provides a valuable reference for establishing more scientifically robust and equitable green social responsibility mechanisms. Both countries have accumulated substantial practical experience in hydropower project management, and the findings facilitate mutual learning and benchmarking. Specifically, Chinese hydropower management should emphasize the promotion of innovative green technology applications and further refine the responsibility assessment criteria, while the United States should focus on enhancing ecological restoration planning and expanding stakeholder participation channels. In the future, this research will be extended to a broader range of countries and diverse hydropower projects. This will involve conducting comparative analyses of the green social responsibility mechanisms across different regions and scales, identifying both differences and commonalities, and summarizing more universal principles. With the evolution of the times and technological advancements, deep text mining technologies and system dynamics simulation methods will continue to evolve. This is expected to enable the exploration of the causal dynamic mechanisms and quantitative evolutionary relationships between the fulfillment of green social responsibility and the economic, social, and ecological benefits of hydropower projects under diverse scenarios, institutional frameworks, and cultural backgrounds. Consequently, it has become feasible to more accurately simulate the dynamic changes in the fulfillment of green social responsibility across the entire life cycle of hydropower projects.