The Binary Moderating Effect of Forest New Quality Productive Forces on the Efficiency of Forest Ecosystem Services Value Realization

Abstract

The realization of forest ecological functions value is an important path for implementing the “Two Mountains” theory. Improving the efficiency of forest ecological functions and benefits value realization faces several challenges, such as an underdeveloped value evaluation system that makes it difficult to quantify ecological value, a weak policy system lacking effective incentive mechanisms, and unclear ecological property rights leading to unfair benefits distribution. Forest new quality productive drivers are a key factor in promoting high-quality forestry development, and can effectively address several issues hindering the efficiency of forest ecological functions and benefits value realization. Forest ecological functions and benefits are divided into tangible forest products and intangible ecological services, with the efficiency of realizing their economic and welfare values reflecting the input–output status of forest ecological value. This paper constructs an indicator system for assessing the modern productive capacity in forestry and the efficiency of forest ecological value realization, and uses a two-stage network DEA model and a double fixed effects model for empirical analysis. The study finds that the advanced drivers of forestry productivity significantly enhance the efficiency of forest ecological economic value realization but constrain the efficiency of ecological welfare value realization, with significant regional differences. As a moderating variable, enhancing the resilience of the industry chain can significantly deepen the effect throughout the process, while improving the informatization level of residents can weaken the constraints of forest new quality productive drivers on the efficiency of forest ecological welfare value realization. Therefore, this paper offers targeted recommendations aimed at providing theoretical support and practical guidance for optimizing the efficiency of forest ecological value realization.

1. Introduction

“Green mountains and clear waters are as valuable as mountains of gold and silver.” The “Two Mountains” theory serves as a guiding principle for ecological civilization construction, and the realization of ecological value is an important way to implement the “Two Mountains” theory [1]. In practice, the efficiency of forest ecological value realization is constrained by multiple structural barriers. Specifically, these constraints are reflected in the absence of a scientific ecological value assessment system, which makes it difficult to quantify ecological services; fragmented policy support, leading to insufficient market participation incentives; an underdeveloped ecological transaction mechanism that obstructs the value realization chain; unclear property rights that reduce stakeholder engagement; weak technological support, causing delays in ecological value assessment and decision-making; insufficient financial resource allocation, leading to a lack of liquidity in market operations; and limited public awareness, reducing social participation. New quality productive forces in the forest, centered on the reconstruction of elements, deeply intervene in each link of the ecological value chain, helping to break the shackles of system, technology, market, and awareness imbalances, enabling the efficient transformation from ecological resource attributes to economic value attributes.

Forest ecological benefits emphasize the importance of nature in supporting human well-being. They reflect the interaction between forest ecosystems and human societies, specifically, including renewable forest resources such as timber and non-timber forest products, as well as ecological services provided by forests [2]. The realization of forest environmental value involves converting the potential value of these products into actual economic returns and social effects through market mechanisms, policy support, and social participation. The value realization of ecological benefits is not only key to optimizing forest ecosystem service functions but also an important approach to promoting sustainable development, and it has gradually become the focus of social attention [3,4]. Forest new quality productive forces refer to a new form of productivity that is driven by technological innovation. They aim to support green transformation, foster efficiency of production, and promote high-quality development. In the forestry sector, these forces are rooted in emerging and future industries. In such industries, the technological breakthroughs play a key role in fostering both production and the efficiency of resource allocation. Consequently, they support the sustainable development of ecological, economic, and social systems. Although, these innovations are important in providing a new pathway through which the value of forest ecological benefits can be realized, challenges remain. They particularly include the limited understanding and recognition of forest ecological value, with the process of releasing ecological dividends still constrained by resource bias and waste, which hinders the overall improvement of the efficiency of forest ecosystem services value realization.

Forest ecological economic value and ecological welfare value are two different yet closely related concepts. Firstly, economic value deals with the direct or indirect financial benefits, which are a result of the resources of the forest within a market economy. It is standardized and mainly expressed through various numerical indicators, which includes prices, revenues, or cost savings. In contrast, welfare value deals with the non-market benefits that are provided by forests to human well-being [5]. It includes health, recreation, and overall social welfare. These benefits are perceived as more personal and context-specific, which reflects individual experiences and social interactions. Secondly, economic values can be compared directly using quantitative measures. In this regard, welfare or social values are more qualitative in nature and are often difficult for assessing using market-based pricing. This is because they retain the unique characteristics of each context or group. Finally, economic value also serves as a tool to support broader social objectives; however, the welfare value deals with the ultimate goals of social life. It includes improved quality of life, public health, and social harmony.

New quality productive forces in the forest are reflected in two main aspects of forest resource utilization:

(1) Direct productive value: Forests yield products such as timber, resin, shiitake mushrooms, and matsutake mushrooms. These products hold clear market value. Harvesting and selling these resources generate direct economic income.

(2) Indirect productive value: This refers to the economic benefits that are attained by converting the ecological functions of a forest into marketable value through various mechanisms such as pricing and trade. For example, Wuyishan National Park saves on water-related costs by leveraging the water conservation function of the forest. Moreover, the Guangdong Changlong carbon sink afforestation project earns income through carbon credit trading. However, the Zhangjiajie National Forest Park fosters local spending through eco-tourism.

The efficiency of realizing forest ecological value is a form of non-market public benefit, which is shared by all. However, these can also be illustrated in four areas:

(1) Resident ecological welfare: Forests aid in regulating the microclimates, purify air and water, and reduce the impacts of disasters. For instance, Singapore’s “Garden City” also integrated forest transpiration so that urban heat island effects can be eased.

(2) Resident economic welfare: Forest resources support the alleviation of poverty. For example, Brazil’s Amazon rainforest, which is rich in rubber trees, plays an important role in offering Seringueiros a stable income through rubber tapping.

(3) Resident educational welfare: Forests act as open-air classrooms. In this context, they increase the outdoor activity time of students. In Norway, “Forest Kindergarten” programs provide children with about four hours of outdoor learning daily. It contributes to the top natural science literacy among OECD nations.

(4) Resident healthcare welfare: Forests serve as natural spaces for healing [6]. In Germany’s Black Forest, rehabilitation centers involve forest therapy in clinical treatment for chronic illnesses. Research has also indicated that patients with heart conditions, hypertension, and anxiety who spend extended time in forest environments are more likely to experience greater physiological stability. In this way, they experience advanced psychological resilience and more positive emotional responses.

Forest ecological economic value and ecological welfare value represent the dual value of forest ecological functions. A clean ecological environment, pleasant natural landscapes, and diverse ecological services reflect humanity’s continuous pursuit of a better life. The extensive economic development model, while effectively improving the efficiency of realizing forest ecological economic value, to some extent limits the efficiency of realizing forest ecological welfare value [7]. Industry chain resilience refers to the ability of an industrial chain to quickly absorb external shocks, adjust flexibly, and maintain continuous operation in the face of external disturbances [8]. The forestry industry chain is a critical part of regional industry chains, and strengthening industry chain resilience can optimize the forest supply chain, enhance robustness, alleviate the supply–demand contradiction in forest products, and improve the efficient allocation of forest ecological functions in the market [9]. However, while this enhances the economic value of tangible products, it can lead to ecological imbalance, thereby exacerbating the bottleneck in the realization of ecological welfare value. Improving residents’ access to information helps break the asymmetry in environmental value market transaction information. The development of the forestry economy should never exploit resources to exhaustion, and the initiation of ecological compensation mechanisms further lays a stable external environment for optimizing the realization efficiency of inherent ecological welfare values such as forest health and wellness, contributing to the adjustment and maximization of the efficiency of forest ecological value realization [3].

In this context, the objective of this study is to examine how new quality productive forces in forestry can enhance the efficiency of realizing forest ecosystem services value. The research also intends to focus on two key dimensions of this value: economic value and welfare value. In this regard, the moderating effects of forestry industry chain resilience and the digital literacy of residents have also been assessed.

The significance of this study lies in its contribution to the implementation of the “Two Mountains” concept. The study also contributes to the advancement of sustainable forest resource development. Although previous research has explored forest ecological functions and resource utilization, there has been limited attention regarding the role of advanced forestry productivity so that the efficiency of value realization can be improved.

Therefore, this paper explores the influence of forest new quality productive forces, industry chain resilience, and digital capabilities of residents on the efficient realization of forest ecological value. A key contribution of this study is related to its focus on social equity and environmental justice. It explores that forest policy should focus on strengthening industry chain integration, enhancing the digital skills of residents and developing inclusive governance mechanisms. These steps are essential for ensuring that marginalized groups are meaningfully involved in decisions regarding the use and benefit-sharing of forest resource. Consequently, the equitable distribution of ecological welfare can be promoted.

This perspective also holds practical value for China but also carries international relevance. It is important particularly for regions such as Europe, Latin America, and Southeast Asia. It offers new insights regarding the improvement of ecological policy frameworks and addressing ongoing challenges that are associated with forest degradation.

2. Theoretical Analysis and Research Hypothesis

2.1. Literature Review

Academic research regarding new quality productive forces in a forest primarily centers around defining their meaning, building conceptual frameworks, and exploring empirical pathways. However, the scientific understanding of these forces can be perceived from three key perspectives. From the perspective of political economy, forest new quality productive forces can be perceived as a new form of productivity that is driven by technological innovation. It aims to upgrade traditional productivity through breakthroughs in core and disruptive technologies [10]. From the factor endowment perspective, qualitative improvements in production inputs are focused, such as labor, materials, and tools. In terms of the relationship between “new” and “quality”, the “new” deals with the emerging technologies, elements, and industries. However, “quality” implies high standards, multidimensional value, and dual functional effects. Key dimensions include digitalization, greening, and openness, which shows the evolution of modern productivity. The measurement of forest new quality productive forces follows three main models: one is based on technological, green, and digital productivity [11]. It forms a unified evaluation system. Another is related to technology, industry, and factor innovation. However, the third focuses on the core production components such as laborers, materials, and objects. Empirical studies also concentrate on two areas, which includes the driving factors of transformation, such as digital finance, economic development levels, factor market reforms, industrial structure, institutional environments, and policy support. The second one involves the practical implementation paths, such as fostering forestry economic resilience, advancing reforms of forest rights, developing forestry industries, and improving the efficiency of forest ecological value realization [12].

The realization of forest ecological value has gradually attracted widespread attention in the academic community, covering various aspects such as theoretical analysis, empirical research, and experiential lessons. Ecosystem services value realization is an important approach to solving the externalities of ecological benefits. Research on the definition of forest ecological benefits and their value realization mechanisms has deepened over time. Scholars have not only explored the logical relationship between collective forest rights reform and environmental value realization but also analyzed the value realization models of ecosystem services in country like New Zealand, summarizing practical models for reference [13,14]. These models have provided significant insights for the development of a forest environmental value realization mechanism in China.

The value realization of forest ecological value is closely related to the development of forest-based economies, ecological economies, and digital economies. By establishing a comprehensive environmental value realization mechanism; promoting the assetization and capitalization of ecological value; and effectively solving issues in supply–demand matching, transaction costs, and quality traceability, digital technology plays an important role in improving the efficiency of ecological value transformation [15,16]. These efforts help promote the rational use of forest resources and ensure the smooth marketization process of ecological value. Despite the progress in research on forest ecological value realization, there remain many problems and challenges in practice. Currently, the transaction costs of ecological benefits are high, and there is a lack of effective quality traceability mechanisms. The policy environment is lagging, with insufficient implementation, and the market mechanism remains underdeveloped, preventing the full release of the potential value of forest ecological benefits. These issues have, to some extent, restricted the efficiency of ecological value realization [17,18,19]. Key questions, such as how to effectively integrate market, technology, and policy resources and how to promote the realization of ecological value, remain unresolved, and finding effective ways to improve the efficiency of forest ecological value realization is a critical issue that requires further exploration and improvement.

In recent years, research on the impact of new quality productive forces on the realization of forest ecological value has gradually deepened. New productive forces influence the realization of forest ecological value through four main aspects: theory, institutions, society, and technology. Improving resource utilization efficiency; promoting industrial technological progress and upgrading; establishing ecological compensation mechanisms; clarifying property rights systems; improving market transaction systems; handling the relationship between government and market; and utilizing technologies such as remote sensing, blockchain, big data, e-commerce platforms, and multi-channel financing can all contribute to improving the efficiency of ecological value realization [20,21].

New quality productive forces in the forest are a subdivision of emerging productive forces in the forestry sector. Specifically, forest innovative production drivers are closely related to the transformation of forest dependency, emphasizing the symbiotic relationship between the forest under-economy and the realization of forest ecological value. Through innovation in ecological value realization mechanisms, promoting the top-level design of forestry systems, and scientifically calculating forest ecological functions and service conversion rates, these actions embody the role of forest new quality productive forces in advancing the ecological value path [13,18,20,22].

New quality productive forces in a forest not only provide the driving force for the realization of forest ecological value but also, through diversified mechanisms and paths, drive the transformation and upgrading of ecological civilization construction. In the process of empowering the realization of forest ecological value, the role of the industry chain’s resilience is particularly important. The industry chain involves various stages, such as product production, processing, and sales, and also affects resource allocation and supply chain management. Through reasonable resource allocation, forest new quality productivity forces can better support the development and marketization of forest ecological value, promote the conversion of ecological resources into ecological benefits, and enhance the efficiency of ecological value realization [12,18]. Advanced forestry productivity drivers can also optimize supply chain management, enhance information transparency and response speed, improve production efficiency, and reduce operating costs, providing technological and innovative support for the realization of ecological value [23,24].

The existing research has also made notable progress in the theoretical development, practical pathways, and case-based analysis regarding the impact of forest new quality productive forces drivers on the efficiency of forest ecological value realization. However, there are several limitations. Most current studies remain at the theoretical level. These studies lack the empirical analysis regarding how these advanced productivity drivers influence the efficiency of realizing forest ecological value. This results in a misalignment between academic research and practical application. There is also limited comparative research that has examined the regional differences and variations across ecological environments. Thus, the lack of in-depth analysis also restricts the generalizability and applicability of current findings. There is also a scarcity of research regarding the interaction and coordinated effect of multiple driving factors. It includes markets, technology, and policy, which results in insufficient guidance regarding the structures and effective strategies for improving value realization efficiency. This paper proposes the following: Develop a comprehensive evaluation system for forest new quality productive forces and the efficiency of forest ecological value realization through the entropy method combined with a two-stage network DEA model. The researchers also apply a two-way fixed effects model so that the impact of these drivers on realization efficiency can be analyzed. After testing for endogeneity and ensuring model robustness, the research also introduces forestry industry chain resilience and informatization of residents as moderating variables so that the strength and regional differences in this impact can be explored.

This approach also intends to offer more precise empirical evidence and actionable policy recommendations. It ultimately provides both scientific insight and practical guidance for improving the efficiency of forest ecological value realization in diverse regional contexts.

2.2. Research Hypotheses

2.2.1. The Relationship Between New Productive Forces in Forestry and the Efficiency of Forest Ecological Value Realization

Grounded in Marxist labor theory, forestry laborers, means of labor, and objects of labor form the fundamental components of new quality productive forces in forestry [25]. Forest ecological value can be divided into tangible goods and intangible ecological services [26]. Tangible products, such as timber and non-timber forest products, primarily reflect ecological economic value. In contrast, intangible products, including forest environmental education and cultural dissemination, mainly represent ecological welfare value. New productive forces in forestry contribute to the realization of ecological value through improvements in precision processing, reduction of market transaction costs, and expansion of market scale (Figure 1).

Investments in the three core forestry elements enhance the refinement of forest ecological value processing, facilitating the realization of both ecological economic and welfare value. Modern forestry laborers are characterized by knowledge, creativity, and technical expertise [27]. Skilled workers, through continuous training and research, are capable of operating and maintaining precision processing equipment, advancing the purification of forest product components, and forming forestry–grass processing alliances. These efforts help to improve the quality and supply capacity of ecological value. The increasing intelligentization of forestry equipment also supports fine-scale processing. The widespread use of CNC workshops and automated machinery has advanced production techniques. Additionally, the integration of technologies such as bioinformatics supports cleaner production practices, reduces energy and resource waste, and improves overall production efficiency. These outcomes, in turn, contribute to the realization of ecological and welfare value. The development of stereoscopic forestry expands the object of labor in forestry. Supported by extensive computational infrastructure, innovative models such as forest–medicine intercropping have promoted the development of understory ecological value, including woody grains and oils [28]. The intensive processing of economic forest products and medicinal plants illustrates forestry’s multifunctionality. These practices enhance product value by improving provisioning, regulatory, and cultural services, thereby advancing the comprehensive realization of forest ecological value.

Furthermore, investments in the three forestry elements can reduce marketization and transaction costs, which also supports the realization of ecological value. New-generation forest operators, while improving their management capabilities, often focus on creating forest product brands with distinct regional and industrial features [29]. These brands, once recognized and trusted, reduce consumers’ perceived transaction risks, lower entry barriers to the market, and thereby help decrease transaction costs. This contributes to improved competitiveness and product premiums [30]. Technological advances in forestry tools and processes have enabled the development of standardized valuation systems for the environment. This helps to formalize transactions, unlock supply potential in areas such as forest tourism, and accelerate the monetization of natural resources, ultimately improving value realization efficiency [7,31]. In addition, the construction of digital trading platforms for forest ecological value and the development of comprehensive ecological service systems broaden the object of forestry labor. Real-time intelligent monitoring of forest operations allows for in-depth analysis of transaction data, facilitates the opening of market channels, reduces transaction costs, and thus significantly enhances the efficiency of forest ecological value realization [32].

Investments in the three core elements of forestry can expand the market scale of forest ecological value, thereby contributing to the realization of both ecological economic and welfare value. Forestry professionals equipped with advanced knowledge and technical skills can utilize gene editing and material development technologies to cultivate high-yield, high-quality tree species and achieve non-polluting treatment of ecological waste. These advancements help to increase the market share of high value-added environmental products [33].

Gradually establishing and improving a supervisory system for forest product supply and demand, along with a green product standards system, is essential for expanding market scale. For example, the Forest Stewardship Council (FSC) certification serves as a mechanism to link domestic and international markets. Enterprises engaged in forest and timber product development can overcome trade barriers and enhance the global competitiveness of their products by participating in FSC-certified trade. Moreover, the development of integrated land–air–space systems in forestry emphasizes the aggregation of satisfaction-related product data and the innovation of core business information models. This facilitates investment in ecological conservation projects, connects cultural and ecological goods within market systems, and promotes the realization of forest ecological value.

Research on the efficiency of forest ecological value realization involves evaluating how effectively natural resources are transformed into ecological value. This efficiency should be assessed through both ecological economic value and ecological welfare value perspectives [7]. Investments in the three factors of forestry productivity enhance forest management capacity, clarify property rights over forest resources, and improve ecological infrastructure. Based on theories of ecological and welfare economics, and in alignment with the restructuring of the forestry industry, such investments help to optimize resource allocation and ensure sustainable utilization. Ultimately, these actions generate both economic and social value from forest products [1,3,17,19]. Therefore, the following hypothesis is proposed:

H₁. 

New productive forces in forestry influence the efficiency of forest ecological value realization, including both ecological economic value efficiency and ecological welfare value efficiency.

2.2.2. The Moderating Role of Industrial Chain Resilience and Resident Informatization in the Empowerment Efficiency of Forestry’s New Productive Forces

A higher level of industrial chain resilience reflects a stronger capacity to withstand external shocks, indicating a healthier industrial system for forest ecological value. There are three primary pathways through which industrial chain resilience can moderate the empowering effect of forestry’s new quality productivity forces: the development of innovative industrial formats, the improvement of resource allocation efficiency, and the integration of digital and intelligent technologies to better match supply and demand.

According to the theory of technological innovation, science and technology are fundamental drivers of ecological industrial transformation and upgrading [16]. The theory of value co-creation highlights how stakeholders, including governments and markets, can shape the efficiency of ecological value transformation during the assetization and capitalization of the industrial chain [17,20]. The integration of information and intelligent technologies within forestry, livestock, understory economies, and economic forests enables a fully digitalized industrial chain from planting to harvesting. This process strengthens the resilience of the forestry industry chain and promotes the efficiency of new quality productivity forces in forestry. Enhancing resilience allows for more effective allocation of production factors across stages such as production, distribution, circulation, and consumption. In this way, forestry’s new quality productivity forces are reinforced and can influence the realization of ecological value through mechanisms such as ecological asset trading, conservation and restoration, and ecological industrialization [5,20].

As digital technologies continue to advance, their integration with real-world industries becomes more effective, facilitating easier coordination between supply and demand [16,23]. The moderating role of the industrial chain becomes increasingly evident and provides continuous momentum for the realization of forest ecological value. Therefore, this study proposes the following hypothesis:

H₂. 

Strengthening industrial chain resilience moderates the relationship between forestry’s new quality productivity forces and the efficiency of forest ecological value realization, including both ecological economic value efficiency and ecological welfare value efficiency.

Resident informatization reflects the breadth, depth, and accessibility of information obtained by the population [34]. According to forest dependency theory, in contexts where resources are scarce, the services provided by forests are irreplaceable and essential for human livelihood, ecological security, and sustainable development [13,19]. The interaction between people and natural resources underscores the critical role of humans in the process of ecological value realization. In Das Kapital, Marx criticized the illusion of prosperity achieved at the expense of resource extraction and ecological degradation. Similarly, sustainable development and green growth theories emphasize the need for a balanced approach to environmental protection and economic development.

Through increased informatization, forest producers and laborers can access updated management concepts and acquire new operational skills. They place greater emphasis on deriving ecological economic value without damaging the natural environment while also creating the necessary conditions for enjoying forest-provided ecological welfare services such as recreation, aesthetics, and health benefits [35]. This enhances the efficiency with which forestry’s new quality productivity forces contribute to ecological welfare value realization. Accordingly, the following hypothesis is proposed:

H₃. 

Improving resident informatization moderates the effect of forestry’s new quality productivity forces on the efficiency of ecological welfare value realization.

3. Methodology

3.1. Construction of the Forestry New Productive Forces Indicator System

The core of forestry new quality productive forces is their characterization as a form of advanced productivity, representing the capacity to organize and utilize various production factors effectively. Grounded in the Marxist theory of productive forces and informed by the indicator construction methods proposed by Xin Boda, Han Wenlong, and Yao Shujie [36,37,38], this study establishes a structured indicator system. The system comprises three primary dimensions: forestry laborers, objects of forestry labor, and means of forestry labor. These are further divided into seven secondary indicators and sixteen tertiary indicators, which collectively form a comprehensive framework for assessing forestry new quality productive forces. The reasons are as follows: Forestry Laborers are the core force driving the enhancement of forest new quality productive forces. Improving the education level of forestry workers, work efficiency, and motivation of forestry workers can better meet the needs of modern forestry and promote its sustainable development. The forestry labor target is the material basis of forest new quality productive forces. Increasing forest coverage and reducing pollution emissions are two key aspects of forest resource management and utilization. Forest pest and disease control, along with safety early warning systems, are important measures to ensure the sustainable use of resources. Forestry labor materials are crucial factors supporting forestry production. The number of forestry workstations reflects the level of resource management, and achieving higher production efficiency can be realized through improving energy use efficiency. Investment intensity in research and development funding and the number of technological innovations are important indicators of technological innovation capacity, which can drive the modernization of the forestry industry. Improving the quality, awareness, and work efficiency of workers, optimizing forest resource utilization and ecological environment protection, and enhancing technological innovation and infrastructure development all contribute to the overall improvement of forestry productivity (

Table 1. Indicator system for forestry new productive forces.

Primary Indicator	Secondary Indicator	Tertiary Indicator	Measurement Method	Primary Indicator
Forestry Laborers	Laborer Quality	Education Level of Forestry Workers (%)	(No. of rangers with junior high × 9 + senior high/vocational × 12 + college or above × 16)/Total no. of rural forest rangers	↑
		Proportion of Higher Education among Workers (%)	No. of rangers with college degree or above/Total no. of rural forest rangers	↑
	Labor Productivity	Per Capita Forestry Income (CNY)	Logarithm of on-the-job staff wages in forestry system	↑
		Forestry Output per Capita (CNY 10,000/person)	Total forestry output/Number of forestry workers	↑
	Awareness and Labor Structure	Labor Force Size (persons)	Logarithm of total number of forestry workers	↑
		Labor Force Structure (age-based)	No. of rangers under age 45/Total rural forest rangers	↑
Forestry Objects of Labor	Ecological Environment	Green Coverage (%)	Forest coverage rate	↑
		SO2 Emission Intensity (10,000 tons/CNY 10,000)	Sulfur dioxide emissions/Total forestry output	↓
			Wastewater emissions/Total forestry output	↓
			General industrial solid waste/Total forestry output	↓
	Ecological Security	Forest Risk Early Warning (%)	Rate of forest pest occurrence	↓
		Forest Disease Control Rate (%)	Rate of forest disease prevention and control	↑
Forestry Means of Labor	Material Infrastructure	Energy Intensity (10,000 tons/CNY 10,000)	Total energy consumption/Total forestry output	↓
		No. of Forestry Workstations	Total number of forestry workstations at year-end	↑
	Technological Innovation	Forestry R&D Investment Intensity (%)	Internal R&D expenditure × (Forestry output/Regional GDP)	↑
		Forestry Technology Innovation (cases)	Number of published forestry patents	↑

Note: Forestry indicators, such as the number of forest rangers, can be directly obtained from the Research Institute of Forestry Policy and Information. According to different education levels, the number of forest rangers with each level of education should be weighted based on the corresponding years of education.

).

3.2. Construction of the Indicator System for Forest Ecological Value Realization Efficiency

Drawing on the studies by Zhan Liulu, Kong Fanbin, and others [7,31], this paper adopts an input–output model to construct an evaluation system for forest ecological value realization efficiency. Research indicates that forest ecological resources such as timber and land participate in forestry activities as essential factors of production, contributing directly to the supply of ecosystem services. These resources also serve as material carriers in ecological restoration processes, supporting the transformation of ecological value into economic outcomes. According to the above, ecological welfare value is reflected in the welfare aspects of residents’ ecology, economy, education, and healthcare. There are also some potential values of forest ecosystem services that are difficult to monetize, which will be subject to secondary regulation through government measures such as ecological compensation, transfer payments, and market regulation, ultimately manifesting in these four aspects of welfare. Accordingly, the efficiency of ecological economic value realization and the efficiency of ecological welfare value realization constitute the core components of the forest ecological value realization efficiency evaluation system. The specific indicator framework is constructed as follows (

Table 2. Indicator system for measuring the efficiency of forest ecological value realization.

Indicator Type	Primary Indicator	Secondary Indicator	Tertiary Indicator
Input Indicators	Forest Ecological Resources	Forestry Land Resources (10,000 ha)	Area of Forestry Land
		Forestry Tree Resources (10,000 ha)	Forest Area
		Major Forest Products (10,000 m3)	Timber Output
	Forestry Social Resources	Labor Resources (persons)	Total Number of Forestry Employees (Year-End)
Intermediate Indicator	Forestry Economic Output	Total Forestry Output Value (billion CNY)	Total Output Value of the Forestry Industry
Output Indicators	Forest Social Welfare	Residents Ecological Welfare (%)	Forest Coverage Rate
		Residents Economic Welfare (CNY)	Per Capita Disposable Income of Rural Residents
		Residents Educational Welfare (years)	Average Years of Education for Rural Residents
		Residents Healthcare Welfare (per 10,000 persons)	Number of Rural Doctors and Health Workers

).

3.3. Selection of Control Variables

Based on the research of Kong Fanbin [31] and others, this study selects 5 indicators as control variables: forest support investment intensity, technological infrastructure in forestry areas, local residents’ consumption level, transportation infrastructure, and ecological protection intensity. Forest support investment intensity is measured by the ratio of forest area investment in forestry support and protection to annual forestry investment. Technological infrastructure in forestry areas is measured by the ratio of local fiscal expenditure on technology to general budgetary expenditure. Ecological protection intensity is measured by the ratio of ecological construction and protection investment to annual forestry investment. Enhancing forest support investment intensity, technological infrastructure in forestry areas, and ecological protection intensity can better support the research and application of forestry science and technology. This improves forest management efficiency and sustainability while increasing the value and diversity of forest ecosystem services. Local residents’ consumption level and transportation infrastructure are measured by per capita rural residents’ consumption expenditure and the logarithm of total freight volume, respectively. Higher consumption levels and good transportation infrastructure increase the payment potential for high-quality ecosystem services and reduce transportation costs for moving forest ecosystem services from production areas to markets, thereby stimulating the realization of their value.

3.4. Model Specification

3.4.1. Two-Stage Network DEA Model

The realization of forest ecological economic value and forest ecological welfare value are not independent processes. The former reflects the degree to which natural resources are monetized through market mechanisms, while the latter captures the monetized expression of the potential value of forest resources through secondary distribution mechanisms such as ecological compensation and public welfare policies. The two-stage network Data Envelopment Analysis (DEA) model divides the efficiency evaluation system of forest ecological value realization into two interconnected subsystems. In the first stage, the model assesses the efficiency of ecological economic value realization. The intermediate outputs of this stage serve as the input variables for the second stage, which evaluates the efficiency of ecological welfare value realization. Solving the model yields both stage-specific efficiencies and an overall efficiency score for the entire process. The mathematical formulation is shown below [39].

$$\begin{array}{l}{{\displaystyle E}}_a={\displaystyle {\sum }_{r=1}^s{{\displaystyle u}}_r^{*}}{Y}_{\mathrm{ra}}/{\displaystyle {\sum }_{i=1}^m{{\displaystyle v}}_i^{*}}{X}_{\mathrm{ia}}\le 1,\\ {{\displaystyle E}}_a^1={\displaystyle {\sum }_{p=1}^q{{\displaystyle w}}_p^{*}}{Z}_{\mathrm{pa}}/{\displaystyle {\sum }_{i=1}^m{{\displaystyle v}}_i^{*}}{X}_{\mathrm{ia}}\le 1,\\ {{\displaystyle E}}_a^2={\displaystyle {\sum }_{r=1}^s{{\displaystyle u}}_r^{*}}{Y}_{\mathrm{ra}}/{\displaystyle {\sum }_{p=1}^q{{\displaystyle w}}_p^{*}}{Z}_{\mathrm{pa}}\le 1,\\ {{\displaystyle E}}_a={{\displaystyle E}}_a^1\times {{\displaystyle E}}_a^2\end{array}$$

(1)

$$\begin{array}{ll}{{\displaystyle E}}_a& =\max {\displaystyle {\sum }_{r=1}^s{{\displaystyle u}}_r}{Y}_{\mathrm{ra}}/{\displaystyle {\sum }_{i=1}^m{{\displaystyle v}}_i}{X}_{\mathrm{ia}}\\ & {\displaystyle {\sum }_{r=1}^s{{\displaystyle u}}_r}{Y}_{\mathrm{rj}}/{\displaystyle {\sum }_{i=1}^m{{\displaystyle v}}_i}{X}_{\mathrm{ij}}\le 1,j=1,\mathrm{...},n,\\ & {\displaystyle {\sum }_{p=1}^q{{\displaystyle w}}_p}{Z}_{\mathrm{pj}}/{\displaystyle {\sum }_{i=1}^m{{\displaystyle v}}_i}{X}_{\mathrm{ij}}\le 1,j=1,\mathrm{...},n,\\ s.t.& \\ & {\displaystyle {\sum }_{r=1}^s{{\displaystyle u}}_r}{Y}_{\mathrm{rj}}/{\displaystyle {\sum }_{p=1}^q{{\displaystyle w}}_p}{Z}_{\mathrm{pj}}\le 1,j=1,\mathrm{...},n,\\ & u_r,v_i,w_p\ge \epsilon ,r=1,\mathrm{...},s;i=1,\mathrm{...}m;p=1,\mathrm{...}q.\end{array}$$

(2)

where E_a denotes the overall efficiency of forest ecosystem services value realization, E_a¹ represents the efficiency of forest ecological economic value realization, and E_a² denotes the efficiency of forest ecological welfare value realization. The model uses m input indicators, denoted by X_ia, representing forest ecological and forestry social resources (m = 4). The intermediate product Z_pa (q = 1) is the forestry economic output. The final outputs Y_ra (s = 4) represent indicators of forest-related social welfare. The multipliers u_r^∗, v_i^∗, and w_p^∗ are used to calculate efficiency within each stage of the model.

3.4.2. Two-Way Fixed Effects Model

The two-way fixed effects model is applied to control for both individual-specific and time-specific unobserved heterogeneity, thereby minimizing errors caused by omitted variables. In this study, the model is employed to investigate the influence of new quality productive forces in forestry on the efficiency of forest ecological value realization:

$$FG{R}_{\mathrm{mn}}={\partial }_0+{\partial }_{1}FNQ{P}_{\mathrm{mn}}+{\partial }_2{\mathrm{Control}}_{\mathrm{mn}}+{\mu }_{\mathrm{m}}+{\phi }_{\mathrm{n}}+{\epsilon }_{\mathrm{mn}}$$

(3)

Here, FGR_mn denotes the forest ecological value realization efficiency for province m in year n, including ecological economic value efficiency, ecological welfare value efficiency, and overall ecosystem services value efficiency. The sample includes m = 30 provinces over t = 10 years. FNQP represents the new quality productive forces in forestry, while Control denotes a set of 5 control variables. μ_m and ϕ_n are province and time fixed effects, respectively, and ε_mn is the error term.

3.5. Data Sources

This study is based on panel data from 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Macao, and Taiwan) spanning the period from 2013 to 2022. The data are obtained from various official statistical yearbooks, including the China Forestry Statistical Yearbook, China Forestry and Grassland Statistical Yearbook, China Statistical Yearbook, China Energy Statistical Yearbook, and China Urban Statistical Yearbook. The main descriptive statistics of the basic data are provided in Tables S1 and S2.

4. Results

4.1. Spatiotemporal Distribution of Forest Ecological Value Realization Efficiency

As shown in Figure 2, the overall efficiency of forest ecosystem services value realization in China improved from 2013 to 2022, although the absolute level remains relatively low. Among the regions, the Yellow River Delta performed notably well. This improvement can be attributed to several national policy initiatives since 2013. These include the release of a white paper on climate change by the State Forestry Administration and the continued implementation of the National Afforestation and Greening Plan Outline. These efforts have supported the expansion of the national carbon sink monitoring system, promoted research on forestry-based climate responses and carbon sequestration technologies, and increased subsidies for improved seed varieties and afforestation projects, which have contributed to overall efficiency gains.

However, challenges persist, such as rising forestry labor costs, illegal occupation and exploitation of forest land, and heightened risks from forest pests and fires. These issues have hindered the overall level of efficiency of forest ecosystem services value realization. Efficiency levels are relatively higher in the middle and lower reaches of the Yellow River, while the northeastern region has shown little variation over the years. This spatial pattern reflects successful projects in the Yellow River Basin, including wetland restoration, green ecological corridors, reforestation and grassland restoration programs, and the implementation of the Natural Forest Protection Project. The development of horizontal ecological compensation mechanisms in the basin has further supported the conversion of ecosystem services into value. In contrast, the Northeast Forest Belt, dominated by secondary forests, suffers from degraded ecological functions, high vulnerability to pest outbreaks, and a fragile forest ecosystem, resulting in a lower ecological value realization rate.

As illustrated in Figure 3, the efficiency of forest ecological economic value realization in China exhibited an overall upward trend from 2013 to 2022, with a relatively high efficiency level that generally declined from the southeastern regions toward the inland areas. Driven by policies such as the Implementation Plan for the Construction of National Reserve Forests during the 14th Five-Year Plan, forest area and timber stock have continued to grow. The development of the understory economy has contributed to both the protection and utilization of forest resources, enhanced the supply of high-quality forest ecological material products, and improved the economic value of forest resources. These factors collectively promoted the transformation efficiency of forest ecological economic value.

Southeastern forest regions are dominated by evergreen broadleaf forests. The presence of both plantations and secondary forests has ensured a stable supply of forest products. Favorable conditions such as abundant precipitation and a humid climate support tree growth and the exploitation of understory resources, enabling the effective realization of forest economic value. In contrast, ecological economic efficiency in Qinghai Province has shown instability. This may be attributed to the region’s high altitude and cold, arid ecological characteristics that result in a fragile and unstable environmental system. Consequently, the efficiency of ecological economic value transformation in Qinghai remains relatively low.

As shown in Figure 4, the efficiency of forest ecological welfare value realization in China exhibited a general downward trend from 2013 to 2022, with an overall low level. Shanghai and Tianjin demonstrated exemplary performance during this period. One primary reason is that extensive economic growth models and unstable ecosystem service management capacities tend to favor environmental polluters in the distribution of ecosystem services gains, particularly under conditions of environmental degradation and pollution. This reduces the quality of life and welfare of residents and undermines the transformation efficiency of forest ecological welfare value.

Furthermore, the realization mechanism of forest ecological welfare value relies on the modernization of forestry production tools and a growing public awareness of sustainable forest resource use and protection. However, due to the intangible nature of welfare products and the cognitive limitations of residents, the efficiency and contribution of forest resources to social welfare remain restricted, leading to relatively low transformation efficiency. During this period, Tianjin implemented a forest ecological benefit compensation system, while Shanghai launched major initiatives such as the “Thousand Parks” project. These cities have actively explored diverse approaches to converting ecosystem services value into public welfare, offering valuable insights for other regions, particularly in enhancing functions such as eco-tourism and forest recreation.

4.2. The Impact of New Quality Forestry Productivity on the Efficiency of Forest Ecological Value Realization

As shown in

Table 3. Empirical results of the two-way fixed effects model.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	Efficiency of Forest Ecological Economic Value Realization	Efficiency of Forest Ecological Welfare Value Realization	Efficiency of Forest Ecosystem Services Value Realization	Efficiency of Forest Ecological Economic Value Realization	Efficiency of Forest Ecological Welfare Value Realization	Efficiency of Forest Ecosystem Services Value Realization
Forest New Quality Productive Forces	1.6266 ***	−0.3675 ***	−0.0524	1.5864 ***	−0.8555 ***	0.2514 ***
	(0.1533)	(0.1338)	(0.0500)	(0.2102)	(0.1965)	(0.0829)
Control Variables	No	No	No	Yes	Yes	Yes
Spatiotemporal Fixed Effects	Two-Way	Two-Way	Two-Way	Two-Way	Two-Way	Two-Way
Constant Term	0.0429	0.3415 ***	0.1006 ***	−1.1687 **	0.1847	−0.6977 ***
	(0.0562)	(0.0462)	(0.0173)	(0.5074)	(0.4406)	(0.2605)
Observations	300.0000	300.0000	300.0000	300.0000	300.0000	300.0000
R2	0.9144	0.8049	0.8031	0.9197	0.8569	0.8818

Note: Values in parentheses represent standard errors of the corresponding coefficients. *** indicates significance at the 1% level (p < 0.01), ** at the 5% level (p < 0.05), and * at the 10% level (p < 0.1). (As the same note applies to all tables in this paper, it will not be repeated in subsequent tables for brevity).

, the inclusion of control variables does not alter the original research findings, indicating that the selection of control variables is appropriate. After controlling for these variables, new quality forestry productivity is found to significantly influence the efficiency of forest ecological value realization at the 1% significance level.

Specifically, for every one-unit increase in the average level of new quality forestry productivity, the efficiency of forest ecological economic value realization increases by an average of 1.5864 units. This demonstrates that new quality forestry productivity significantly enhances the transformation efficiency of forest ecological economic value. The underlying reason is that new quality forestry productivity not only promotes the upgrading of means of production but also optimizes algorithm-driven production processes. It facilitates the refined development of ecosystem services, giving rise to more high-value economic outputs and thereby accelerating the transformation and realization of forest ecological economic value in a positive manner.

However, for every one-unit increase in the average level of new quality forestry productivity, the efficiency of forest ecological welfare value realization decreases by an average of 0.8555 units. This suggests that new quality forestry productivity, to some extent, hinders the transformation efficiency of forest ecological welfare value. When the exploitation and utilization of natural resources become unbalanced, local residents in forestry operation areas may fall into the trap of “environmental health poverty”. Under such conditions of environmental inequality, a small group of dominant stakeholders reap most of the benefits, while disadvantaged groups experience lower environmental quality and limited access to ecosystem services, thereby obstructing the realization of ecological welfare value.

In conclusion, while new quality forestry productivity substantially improves the transformation efficiency of forest ecological economic value, it may impede the realization of ecological welfare value. This dual effect confirms Hypothesis H₁: as public demand for well-being continues to rise, the realization of forest ecosystem services value is shifting from a focus on economic returns toward a focus on social welfare. In this context, public values are undergoing a structural shift from “economic returns as a priority” to “social welfare as a priority”. This shift is not only a correction of the side effects of forest new quality productive forces but also a reflection of the policy direction and institutional design in the era of ecological civilization. Therefore, tools for forest new quality productive forces urgently need to be reoriented and scientifically managed to balance the economic goals of ecosystem services with social welfare objectives. First, an ecological welfare-oriented performance evaluation mechanism should be introduced at the institutional design level. In addition to traditional output indicators, social indicators such as ecological equity, residents’ perceived happiness, and green employment should be added. Second, the development of ecological welfare products, such as green education, should be promoted. These products not only provide stable economic income but also directly enhance the quality of life for residents. Third, establishing an ecological dividend feedback mechanism is crucial. Through mechanisms like ecological compensation systems and public ecological welfare funds, the redistribution of ecological value should be realized, ensuring that ecological services truly benefit all levels of society.

The reliability and validity of the baseline regression results are commonly assessed through tests for endogeneity and robustness. This study conducts a series of such tests from the perspectives of instrumental variable selection, regression method transformation, and variable modification. As shown in

Table 4. Results of endogeneity and robustness tests.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Endogeneity Test		Double Tobit Regression		Replace Dependent Variable		Replace Independent Variable
	Efficiency of Forest Ecological Economic Value Realization	Efficiency of Forest Ecological Welfare Value Realization	Efficiency of Forest Ecological Economic Value Realization	Efficiency of Forest Ecological Welfare Value Realization	Efficiency of Forest Ecological Economic Value Realization	Efficiency of Forest Ecological Welfare Value Realization	Efficiency of Forest Ecological Economic Value Realization	Efficiency of Forest Ecological Welfare Value Realization
Forest New Quality Productive Forces	1.8766 ***	−0.9270 **	1.5962 ***	−0.8141 *	1.2714 ***	−0.6668 ***
	(0.3896)	(0.3532)	(0.3955)	(0.4315)	(0.1793)	(0.1617)
Control Variables	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Spatiotemporal Fixed Effects	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way
Lagged Forest New Quality Productive Forces							1.3421 ***	−0.6630 ***
							(0.1767)	(0.1504)
Constant Term					−0.5830	−0.7110	−1.1798 **	−0.0459
					(0.5744)	(0.5179)	(0.5753)	(0.4897)
Observations	270.0000	270.0000	300.0000	300.0000	270.0000	270.0000	270.0000	270.0000
R2	0.4100	0.3197

, Columns (1) and (2) employ the one-period lag of new quality forestry productivity as an instrumental variable for endogeneity testing. This instrument is correlated with current forestry productivity but does not directly affect the dependent variables in the current period, thereby rejecting the weak instrument hypothesis. This confirms the absence of endogenous relationships among the variables and affirms that the effect of forestry productivity on the transformation efficiency of forest ecological economic and welfare value is not biased by endogeneity. Columns (3) and (4) address the issue of limited sample size in the transformation efficiency of forest ecological economic and welfare value. To correct for potential censoring in the dependent variables, a two-limit Tobit model is employed. Columns (5) through (8) conduct robustness checks by lagging the key explanatory variable by one period, aiming to mitigate issues such as reverse causality. Together, these tests consistently demonstrate that new quality forestry productivity has a significant impact on the transformation efficiency of both forest ecological economic and welfare value. Therefore, the baseline regression results are deemed robust and reliable.

At various stages of the impact of forestry neo-productivity on the efficiency of forest ecological value realization, industrial chain resilience consistently plays an effective regulatory role. The rising level of residents’ informatization facilitates more effective decision-making by forest ecological managers and enhances the skill application of forestry laborers. The human-centered philosophy emphasizes the provision of forest ecological services to meet human well-being, continuously optimizing the efficiency of forest ecological welfare value realization. The measurement of industrial chain resilience follows the study by Zhang Hu [40], focusing on the leading capacity and profitability of high-end industries, aiming to enhance the effectiveness of the forestry industrial chain. The level of residents’ informatization is measured based on the average per capita telecommunications service volume, as suggested by Xu Xiaodong [41]. From columns (1), (3), and (7) of the main effects model in

Table 5. Test results of moderating effects in the mechanism of influence.

Variable	Efficiency of Forest Ecological Economic Value Realization		Efficiency of Forest Ecological Welfare Value Realization				Efficiency of Forest Ecosystem Services Value Realization
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	M1	M2	M1	M3	M2	M4	M1	M2
V1	1.5770 ***	1.4628 ***	−0.8399 ***	−0.9063 ***	−0.7208 ***	−0.7665 ***	−0.2521 *	−0.2668 *
	(0.3303)	(0.2795)	(0.2800)	(0.3046)	(0.2338)	(0.2446)	(0.1356)	(0.1390)
V2			−0.0392	−0.0138		0.0314
			(0.0736)	(0.0730)		(0.0755)
V3	−0.2230	0.2271 *	0.3073		−0.1704	−0.2104 **	−0.0175	0.0403
	(0.4296)	(0.1178)	(0.4375)		(0.1067)	(0.0868)	(0.0584)	(0.0320)
V4				0.3366 **		0.3453 ***
				(0.1395)		(0.1194)
V5		4.9580 ***			−5.2826 ***	−4.8824 ***		0.6362 ***
		(0.5936)			(0.7303)	(0.8614)		(0.1824)
V6						1.4864
						(1.4454)
V7	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
V8	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled
V9	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled
V10	−1.6056 **	−1.9246 **	0.5008	0.7266	0.8326	0.9523	−0.7587 *	−0.7996 *
	(0.7315)	(0.7475)	(0.6569)	(0.6382)	(0.6141)	(0.6391)	(0.4181)	(0.4270)
Observations	300	300	300	300	300	300	300	300
R2	0.6750	0.7207	0.4351	0.4459	0.5325	0.5468	0.3837	0.3887

Note: The models correspond to the abbreviations. M1: Main Effects Model; M2: Model with Moderating Effect of Industrial Chain Resilience; M3: Model with Moderating Effect of Residents’ Informatization; M4: Model with All Moderating Effects. The variables correspond to the abbreviations. V1: Forestry New Quality Productivity Forces; V2: Residents’ Informatization Level; V3: Industrial Chain Resilience Level; V4: Interaction: Forestry × Informatization (Centered); V5: Interaction: Forestry × Resilience (Centered); V6: Triple Interaction: Forestry × Informatization × Resilience (Centered); V7: Control Variables Included; V8: Individual Fixed Effects; V9: Time Fixed Effects; V10: Constant Term.

, it can be seen that residents’ informatization and industrial chain resilience levels do not have significant direct effects on forestry neo-productivity across regions, indicating their appropriateness as moderating variables. Column (2) shows that the centered interaction term between forestry neo-productivity and industrial chain resilience is significantly positive and aligned with the direction of the main effect coefficient. This fully demonstrates that a stable forestry industrial chain strengthens the positive effect of forestry neo-productivity on the efficiency of forest ecological economic value realization. A higher degree of industrial chain resilience implies greater productivity when facing external environmental shocks such as natural disasters. Internal innovation in productivity facilitates the transformation of ecological resources into economic ones, thereby realizing the economic value of ecosystem services and confirming Hypothesis H₂. Column (4) shows that the centered interaction term between forestry neo-productivity and residents’ informatization is significant and in the opposite direction of the main effect coefficient. As residents gain more access to information, it enhances scientific literacy among the labor force and improves the precision of smart forestry monitoring. This mitigates the negative impact of forestry neo-productivity on the efficiency of forest ecological welfare value realization, thus confirming Hypothesis H₃. Column (5) reveals that the centered interaction between forestry neo-productivity and industrial chain resilience is significant and consistent with the direction of the main effect. Improvements in industrial chain resilience promote the orderly allocation of production factors in the forestry sector. While this reduces resource misallocation and directly influences the economic transformation efficiency of ecological capital through forestry neo-productivity, it tends to overlook the output of social welfare for nearby residents, thereby hindering the improvement of Efficiency of Forest Ecological Welfare Value Realization. This also confirms Hypothesis H₂. Column (8) shows that the centered interaction between forestry neo-productivity and industrial chain resilience is significant and in the opposite direction of the main effect coefficient. At the current stage, the development of industrial chain resilience greatly benefits the cultivation of neo-productivity, the optimization of forestry industrial structure, and the improvement of ecosystem services supply. A stable forestry industrial chain operation model helps mitigate the drawback of prioritizing economic value over social welfare in forest ecosystem services, thereby reducing the negative effect of forestry neo-productivity on the efficiency of forest ecosystem services value realization, which again supports Hypothesis H₂. In column (6), which includes both the interaction terms for residents’ informatization and industrial chain resilience, multicollinearity among variables may affect the significance levels. However, empirical results demonstrate that the two can jointly moderate the impact of forestry neo-productivity on the efficiency of forest ecological welfare value realization.

The resilience of the industrial chain and the level of residents’ Informatization have a significant impact on the technological improvement of forest new quality productive forces, but the social and political influences behind them cannot be ignored. First, the resilience of the industrial chain enhances the forestry industry’s ability to adapt to external shocks, promoting the economic transformation of ecological resources and improving the efficiency of realizing forest ecological economic value. However, the enhancement of industrial chain resilience is often accompanied by the centralization of industries, which may lead to the dominance of large enterprises and capital-intensive production units in the development of ecological resources, exacerbating the imbalance in the distribution of resources and benefits. Vulnerable groups, especially local small producers and residents in remote areas, may be excluded from economic benefits and find it difficult to share the dividends brought by forest new quality productive forces, which undoubtedly intensifies social inequality and the impoverishment of ecological welfare. Second, the improvement in residents’ Informatization effectively reduces information asymmetry, enhances public awareness and understanding of ecological protection, reduces the social cost of ecological protection, and increases public support and participation. At the social level, Informatization promotes the dissemination of ecological protection knowledge and stimulates public environmental responsibility and awareness. At the political level, Informatization increases policy transparency and execution efficiency, enabling residents to access policy information in real-time, participate in policy supervision, and ensure policies are more just and efficient. These measures help reverse the negative impact of forest new quality productive forces on the efficiency of forest ecosystem services value realization and promote a win–win situation for ecological protection and economic development. Third, the improvement of industrial chain resilience accelerates the transformation of ecological benefits at the social and political levels by strengthening the dissemination of green technologies, enhancing social responsibility, and promoting stakeholder collaboration. At the political level, policy guidance and green fiscal support have promoted the widespread adoption of green production models, facilitated the accumulation of green capital, and reduced the lag in the transformation of ecological welfare benefits. Overall, the improvement of industrial chain resilience, through enhancing social capital, optimizing resource allocation, and improving policy execution, has promoted the coordinated development of ecological protection and economic growth, reducing the negative impact of forest new quality productive forces on the slow transformation of ecological welfare and achieving the goal of green sustainable development.

4.3. The Impact of Forestry’s New Quality Productivity on the Efficiency of Forest Ecological Value Realization in Different Regions

Forestry’s new quality productivity exerts a complex influence on the efficiency of forest ecological value realization across different regions of China. In the eastern region, the forest vegetation types are rich and diverse. Forest zones are formed along a thermal gradient, featuring unique landscapes ranging from tropical rainforests to coniferous forests. The abundance of forest resources provides a solid foundation for establishing well-structured forest ecosystems. The structure of plantations and secondary forests accelerates the overall development of forest resources. The cultivation of economic forests not only enhances the economic value of timber but also supports ecological benefits such as soil and water conservation. Compared with the national average, the eastern region shows a stronger influence of new quality forestry productivity on the efficiency of ecological value realization. The central region, situated between east and west, enjoys geographic advantages. A higher Gini coefficient than other regions creates favorable conditions for the effectiveness of forestry’s new quality productivity. This contributes to improving both the quality and economic value of forest ecosystem services. Among all regions, the central region exhibits the strongest influence of new quality forestry productivity on the efficiency of forest ecological and economic value realization. The western region, characterized by plateaus and a continental climate, has a more rugged terrain and lower forest coverage. Severe issues such as rocky desertification and desertification are present, and the ecological protection barrier is relatively fragile. Due to significant pressures related to both forest protection and development, the impact of forestry’s new quality productivity on the transformation efficiency of forest ecological value in this region is not significant (

Table 6. Results of regional heterogeneity distribution.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
	East			Central			West
	Ecological Economic Value Efficiency	Ecological Welfare Value Efficiency	Efficiency of Forest Ecosystem Services Value Realization	Ecological Economic Value Efficiency	Ecological Welfare Value Efficiency	Efficiency of Forest Ecosystem Services Value Realization	Ecological Economic Value Efficiency	Ecological Welfare Value Efficiency	Efficiency of Forest Ecosystem Services Value Realization
Forest New Quality Productive Forces	1.6237 ***	−1.0349 **	−0.3370 **	1.7162 ***	0.0241	0.0206	0.8648	−0.3224	−0.0294
	(0.3113)	(0.3504)	(0.1274)	(0.3976)	(0.3391)	(0.0643)	(0.4794)	(0.3107)	(0.0515)
Control Variables	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Spatiotemporal Fixed Effects	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way	Two-way
Constant Term	−2.0419 **	0.6189	−0.8753 *	−0.9919	2.0150 *	0.0817	−3.8164 *	1.8158 *	−0.3892
	(0.8319)	(0.8929)	(0.4784)	(0.9934)	(0.9205)	(0.1215)	(1.7454)	(0.8611)	(0.3223)
Observations	110.0000	110.0000	110.0000	80.0000	80.0000	80.0000	110.0000	110.0000	110.0000
R2	0.7570	0.5642	0.5651	0.8835	0.6683	0.6661	0.6416	0.6325	0.1183

).

5. Conclusions and Recommendations

5.1. Conclusions

Economic and welfare value represent the static evaluation of ecosystem services, while the efficiency of value realization reflects the dynamic speed at which ecosystem values are converted into tangible outcomes. This study reveals that forest new quality productive forces have a significant positive effect on promoting the efficiency of forest ecosystem services value realization. In addition, industrial chain resilience is confirmed as a key moderating variable in the relationship between forest new quality productive forces and the efficiency of forest ecosystem services value realization, while the level of residents’ Informatization weakens the shackles on the transformation of forest new quality productive forces to the efficiency of forest ecological welfare value realization.

This suggests that future policymaking should not only focus on the enhancement of productivity itself but also on the integrity of the industrial system and the cultivation of residents’ digital capabilities to fully stimulate the multiple functions of forest ecosystems. Empirical analysis using the two-way fixed effects model indicates that this effect is particularly prominent in the eastern and central regions but less noticeable in the western regions, where ecological conditions are relatively fragile, indicating that regional differences have an undeniable impact on the efficiency of forest ecosystem services value realization.

The results also show that forest new quality productive forces impose certain constraints on the efficiency of ecological welfare value realization, especially in the eastern regions. This finding highlights the imbalance between economic benefits and social welfare value realization efficiency in the current ecosystem services. Therefore, it is imperative to establish policy tools that are oriented towards social equity and environmental justice. Strengthening inclusive governance mechanisms is urgent, and through participatory governance models, marginalized groups such as rural communities, minorities, and women can be truly involved in decision-making processes regarding forest resource utilization and benefits distribution. This will not only help break the current bottleneck limiting the efficiency of ecological welfare value realization but also promote balanced development of ecosystem services in both the economic and social dimensions. Practices such as community co-management, forest co-construction and sharing mechanisms, and participatory monitoring are effective pathways to incorporate fairness into governance systems.

It is worth noting that although this study is based on the national context of China, its theoretical framework and core conclusions have strong implications for other countries. In Europe, the ecosystem service payment mechanism and social forestry policies are becoming more mature, and the concept of balancing productivity with equity proposed in this study could support the improvement of existing Payment for Ecosystem Services (PES) policies. In regions like Latin America and Southeast Asia, where forest degradation and social inequality are intertwined, the proposed “industrial chain resilience + informatization” pathway offers a new perspective for addressing governance challenges in the implementation of the Reducing Emissions from Deforestation and Forest Degradation (REDD+) program. Additionally, this study could provide empirical references for the United Nations Forum on Forests (UNFF) and the Global Forest Goals (GFGs), integrating ecological, economic, and social triple values into the core of policymaking.

Although some achievements have been made, this study still has several limitations. First, the study relies on regional data, which may overlook the influence of local policies and community factors. Future research should integrate local governance and community participation to provide more representative analysis. Second, the regional division is based on administrative boundaries rather than ecological and geographical characteristics, which may ignore the influence of local ecological differences on the conclusions. Third, although the constructed indicator system is relatively comprehensive, it still lacks the measurement of implicit social benefits in ecological welfare, and future research should complement this with more micro-level survey data for quantitative analysis.

Future research can further expand in three areas: first, integrating local governance structures and community participation with more diverse micro-data to ensure the representativeness and accuracy of the conclusions; second, conducting more refined regional divisions based on ecological and geographical characteristics, enhancing sensitivity to local ecological differences and thereby more accurately assessing the impact of regional differences on forest new quality productive forces and the efficiency of forest ecosystem services value realization; third, refining survey data, particularly for quantitative research based on social welfare and community-level data, to complement the existing deficiencies and improve the accuracy of ecological welfare efficiency assessments.

In summary, while promoting the development of forest new quality productive forces is key, only by simultaneously embedding the concept of equitable governance, strengthening industrial chain resilience, and improving residents’ informationization levels can we achieve a comprehensive improvement in the efficiency of forest ecosystem services value realization. This will ultimately lead to accelerated transformation of sustainable ecosystem service value and an overall leap in ecosystem service functions. Based on the issues identified in this study, the following corresponding solutions are proposed to provide new suggestions and insights for improving the efficiency of forest ecosystem services value realization.

5.2. Recommendations

Balancing the transformation mechanism of forest ecosystem services value realization efficiency and clarifying the driving role of forest new quality productive forces is essential. To address the current issue of the uneven efficiency transformation speed between economic benefits and social welfare in ecosystem services, constructing an inclusive governance mechanism is crucial. To this end, local forest governance committees can be established to enhance the forest management capabilities and decision-making participation of marginalized groups through regular public consultations, capacity-building programs, and information-sharing platforms. Additionally, the development of a participatory monitoring system should be strengthened, using modern technologies to enable local communities to actively participate in the monitoring and management of forest resources, ensuring the sustainable utilization of forest resources. Given the potential negative effects of forestry’s new quality productivity on the efficiency of forest ecological welfare value realization, it is recommended that ecological compensation mechanisms be incorporated into forestry development strategies. Through joint regulation by both government and market forces, equitable distribution of forest ecological services can be ensured. At the same time, efforts should be made to improve both the quantity and quality of market-oriented development for forest ecosystem services. Establishing rational pricing mechanisms and trading systems will allow for the ecological value of forests to be appropriately compensated economically, thereby incentivizing sustainable management and utilization of forest resources.

Optimizing the moderating roles of industrial chain resilience and residents’ informatization to promote holistic enhancement of ecological value realization efficiency is essential. It is advised that regions further optimize the forestry industry chain by strengthening transparency and synergy across the chain, reducing information asymmetry and transaction costs. Real-time data analysis and demand forecasting should be utilized to improve inventory management and reduce resource waste, thereby enhancing the efficiency of the forestry value chain. Regional collaboration should be encouraged to share forestry resources and technologies, improving overall industrial chain resilience. Emphasis should be placed on leveraging the moderating role of industrial chain resilience in the process of forest ecological value realization, particularly in aligning the positive effects of forestry productivity with both the economic and welfare values of forest ecosystem services. Furthermore, the advantages of information disclosure should be fully utilized. Enhancing information education and skills training for residents in forest regions can raise professional competencies and innovation capacities. The continuous cultivation and attraction of interdisciplinary talents proficient in forestry management, ecological conservation, and market operations is crucial. This will enable adaptation to the demands of digital transformation, allowing for the application of digital technologies, artificial intelligence, and big data as tools of new quality productivity to improve forest resource monitoring, management, and value realization.

Decoding the root causes of regional heterogeneity and promoting differentiated development strategies for mutual benefit are essential. As an economically developed region, the eastern area has high forestry productivity, but the main challenge it faces is how to protect the ecological environment while enhancing economic value and improving social welfare. Finland supports the development and transformation of green technology through green technology subsidy funds and a comprehensive forest certification system, promoting the sustainable use of forest resources and gaining international market recognition for forest ecosystem services. The eastern region of China should learn from Finland’s experience, strengthen the promotion of green technology, and improve the market competitiveness of forest ecosystem services. The government can establish green subsidy funds and technology conversion reward mechanisms in the region to encourage the introduction and promotion of green technologies. At the same time, the eastern region should improve the forest ecosystem services certification system and promote the branding and market development of forest ecosystem services.

The central region has significant potential in improving the efficiency of forest ecological welfare value realization, but it also faces problems such as an incomplete industrial chain and information asymmetry. Canada performs efficiently in forest industry chain management. The government promotes the rational allocation of forest resources and information sharing through an industry chain collaboration reward fund. In addition, Canada’s “forestry digital platform” realizes full-chain digital management from forest resource monitoring to market forecasting, enhancing the transparency and efficiency of the industry chain. The central region should learn from Canada by establishing a forestry industry collaboration fund and building a cross-regional forest resource sharing platform to increase information transparency and resource sharing, thereby enhancing the effectiveness of the forestry industry.

The western region faces severe ecological restoration and protection pressures due to fragile ecological conditions. In this regard, Costa Rica’s ecological compensation mechanism provides valuable experience. As a pioneer in global ecological protection, Costa Rica has successfully implemented the Payment for Ecosystem Services (PES) system. This system, through both government and market mechanisms, compensates ecological service providers, motivating farmers and forestry enterprises to protect forests and restore the ecological environment. The western region can draw on Costa Rica’s ecological compensation mechanism by providing financial rewards for ecological restoration and protection areas, and setting up compensation funds with different standards according to the functions of forest ecosystems. This precise ecological compensation system can not only protect the western region’s forest ecosystems but also improve local economic levels and ensure fair distribution of ecological services.