Abstract
Introduction:
The agroforestry economy provides a crucial pathway to global poverty alleviation, environmental protection, and the synergistic development of rural revitalization. Family-run forests, forestry cooperatives, and leading enterprises are increasingly becoming the main drivers in the operation of agroforestry, each playing a significant role.
Methods:
This study selected the organizations managing agroforestry in Fujian Province for a case study and employed the Data Envelopment Analysis and Tobit Regression Model to quantitatively measure their relative operational efficiency. The paper also explored the impact mechanisms of factors such as organizational legitimacy, density, and niche on operational efficiency.
Results:
(1) The operational efficiency of agroforestry management organizations in the same region exceeds that of traditional households, demonstrating the advantages of organized management. (2) The study found that government subsidies do not significantly enhance operational efficiency, suggesting that subsidy policies may have issues with timeliness and fail to reflect the actual needs of production activities promptly, thus affecting the effectiveness of capital factors. (3) Organizational legitimacy has a significant positive effect on improving operational efficiency, outweighing the influence of organizational niche and density. (4) The organizational niche is also confirmed to have a positive impact on operational efficiency.
Discussion:
(1) It is essential to strengthen institutional development and the promotion of a contract spirit to foster the in-depth development of organized management. (2) A diversified subsidy mechanism is recommended to reduce the time lag in providing farmers with financial subsidies and enhance the timeliness and effectiveness of subsidy policies. (3) The importance of enhancing organizational legitimacy is emphasized, by leveraging the intermediary role of farmer experts to strengthen legitimacy. (4) The training of organizational legal representatives and the rural financial service system should be improved to broaden each organization's niche, thereby further enhancing the operational efficiency of agroforestry management organizations.
1 Introduction
The varying goals of economic development and resource conservation have made agroforestry, or multipurpose forestry, one of the effective choices for coordinating environmental protection with economic development and the alleviation of poverty (Yusuf et al., 2018). It is particularly crucial to promote regional economic development sustainably. Organizational operators such as family-run forests or farms, cooperatives, and leading enterprises are among the significant factors affecting the success of agroforestry operations (Husgafvel et al., 2018). China places great emphasis on the role of these organizations in the allocation of agroforestry resource elements and actively encourages their development through policies such as tax incentives. Fujian, as the province with the highest forest coverage in China, has seen a continuous increase in the number of newly registered operational entities. Whether favorable policies and industrial environments can be translated into actual benefits for the development of agroforestry, and what the nature of the operational effectiveness of the agroforestry management entities is, remain unanswered questions. The answers for these questions can be found through the measurement of the operational efficiency of agroforestry management organizations and the analysis of influencing factors.
Based on existing global research, the under-forest economy has attracted considerable attention. Beyond the general inquiry into the developmental pathways of the under-forest economy, there is an emerging trend in research that emphasizes the mechanisms of operational entity formation, types, and management models within the under-forest economy, with an increasing focus on the evaluation of operational benefits. This includes studies on the categorization and comparison of operational entities (Che, 2020; Huiqi and Jin, 2018), the transition of operational entities from small forest owners or farmers to community entities (Ayana et al., 2017), and discussions on the motivations and feasibility of diversifying entities such as family-run forests and cooperatives (Dai et al., 2021; Onyema et al., 2018). Additionally, comparative studies are available on the role of these entities in refining the forestry management system and their impact on increasing the incomes of farmers (Liu, 2021; Wu et al., 2022). In terms of management models, scholars have also analyzed various approaches, including market-led and government-regulated management models of the under-forest economy (Huiqi and Jin, 2018), as well as diverse models such as under-forest cultivation and under-forest product processing (Jiang et al., 2019; Triwanto, 2022).
Despite a focus on overall efficiency (Du et al., 2016; Wu et al., 2020), subsidy use (Lin et al., 2017), and cultivation efficiency (Su and Bao, 2019) within the under-forest economy, a dearth of research is available on the operational efficiency of management organizations within this economy. Conversely, extensive studies on entities such as cooperatives and family farms, using Stochastic Frontier Analysis and DEA methods (Ma and Wang, 2020; Zhu, 2017; Tong and Li, 2022), have identified internal factors such as human capital and management practices as determinants of efficiency. Nevertheless, these studies have largely ignored the influence of factors related to the external environment. This research fills the gap by examining operational efficiency from an organizational ecology perspective, enhancing our understanding of the multifaceted role of the under-forest economy in economic, social, and ecological balance and broadening the scope of efficiency factor research in large-scale agriculture.
This research contributes to the field in three key ways. First, it addresses the gap in assessing the operational efficiency of organizations that manage the under-forest economy, with a case study in northwest Fujian, employing the DEA method at the organizational decision-making unit level, an area previously unexplored. Second, it expands the understanding of factors influencing the efficiency of large agricultural operations by examining aspects of organizational ecology—such as organizational legitimacy, density, and niche—beyond traditional internal factors such as human capital and land size (Tong and Li, 2022; Zhang et al., 2022; Xu et al., 2020; Hannan and Freeman, 1977; Jing and Liu, 2013; Cui and Sun, 2020), thus broadening the research horizon. Third, this study innovatively quantifies organizational ecology indicators, offering practical guidance for research aligned with China's context and rectifying the misuse of proxies for ecological niches in existing quantification studies (Zhang and Kong, 2018; Cui et al., 2020).
The cities of Nanping, Sanming, and Longyan in Fujian are the areas with the richest forest resources. They are also comprehensive pilot areas for forestry reform and development in China and Fujian Province. These cities are typical representatives because they are areas of concentrated growth of family-run forestry farms and cooperatives in Fujian. Therefore, based on the design of an index system, this study selected the management organizations in these three areas as the subjects of research to investigate their operational efficiency. This study analyzed the reasons for the differences in the operational outcomes from three major modules: organizational legitimacy, organizational density, and organizational ecological niches, providing policy references for optimizing the external environment of organizational operations. The remaining sections of this article include the impact mechanism of organizational ecology on the operational efficiency of organizations managing the under-forest economy, research methods and data sources, and empirical analysis, along with conclusions and policy recommendations.
2 Theoretical analysis of the impact of organizational ecology on the operational efficiency of under-forest economy management organizations
Organizational ecology essentially refers to the environmental system that can influence the development of organizations. Organizations and their populations evolve and develop within their respective environmental systems. The organizational environment is a collection of external relationships between organizations and populations, representing the combination of all materials and conditions outside the population itself (Hannan and Freeman, 1977; Fei, 2006). Within this context, organizational legitimacy and organizational niche are the core components of the organizational environment, that is, the organizational ecology.
2.1 Mechanisms of influence and hypothesis proposal of organizational legitimacy
Organizational legitimacy can be categorized into three levels: cognitive, regulatory, and normative legitimacy. Cognitive legitimacy refers to the public's recognition of an organization's matters and behaviors, which can be represented by the extent of public awareness and familiarity with the organization. Regulatory legitimacy primarily stems from the rules and regulations established by relevant departments such as the government and industry associations. Normative legitimacy indicates the degree to which organizational behavior conforms to established social standards or values (Cui et al., 2020). Organizational legitimacy is related to the organization's ability to smoothly and broadly acquire the resources necessary for its development (Hannan and Freeman, 1977; Zhang and Kong, 2018). It can prevent social resistance or sabotage against the organization's products or systems; accelerate the inflow of resources such as people, finances, and materials (Cui and Sun, 2020; Zhang and Kong, 2018; Cui et al., 2020); and stabilize the organization's operational efficiency and survival. Therefore, when organizational legitimacy is enhanced, it is more conducive to the organization's selection of the most suitable geographical location in the initial stage, capturing a favorable policy and resource environment for the startup. This allows the organization to orient itself toward the market demand, improving revenue. In addition, the organization can leverage the advantages of transportation, logistics, and industrial chains to reduce organizational resource costs, optimize the ratio of benefits to costs, and enhance operational efficiency. The enhancement of regulatory legitimacy reduces the cost of acquiring fundamental resources, such as land and transportation, and increases the supply of personalized resources, such as organizational rewards. This is beneficial for expanding the resource pool of organizations managing the under-forest economy, changing the relative prices of L (Labor) and K (Capital), affecting the input behavior of production factors, and influencing the outcome of organizational operational efficiency. The strengthening of normative legitimacy is advantageous for attracting high-quality partners, accelerating the flow of production factors, broadening the channels through which organizations managing the under-forest economy acquire resources, reducing inter-organizational friction, lowering transaction costs, and thus enhancing operational efficiency. In summary, this paper proposes the following first original hypothesis H1.
H1: By controlling for other influencing factors, the strength of organizational legitimacy positively promotes the improvement of operational efficiency in organizations managing the under-forest economy.
2.2 Mechanisms of influence and hypothesis proposal of organizational density
Organizational density represents the number of organizational entities with similar organizational structures, resource use methods, and business operations that develop together within a certain range (geographical area or individual volume); organizational density is the basic and most quantitative characteristic of a population (Hannan and Freeman, 1977; Godsoe et al., 2017). Some scholars examined the relationship between organizational density and organizational legitimacy, demonstrating that legitimacy increases consistently at a diminishing rate (Kamp and Peli, 1995). Furthermore, they found that the intensity of inter-organizational competition also rises at a diminishing rate as organizational density increases. This study is contextualized within the initial development phase of emerging forest-based economic entities in China, where such organizations are currently in a low-density developmental stage (Han et al., 2018; Wang and Wei, 2022). Against this backdrop, the core focus of this paper is to investigate how organizational density influences operational efficiency among forest-based economic organizations in their initial development phase. Analyzing the effect of organizational density on operational efficiency under the current low-density context not only requires grounding in classic organizational ecology theories (Kamp and Peli, 1995) but also necessitates integrating applied research findings of organizational ecology theories tailored to the Chinese context. Extant literature has confirmed that organizational density typically affects operational efficiency indirectly by influencing resource utilization efficiency through two key pathways: organizational legitimacy and organizational competitiveness (Cui et al., 2020). Specifically, low organizational density is often associated with a low founding rate during the early stages of population development. At this stage, low social recognition, coupled with inadequate organizational and industrial maturity, constrains resource acquisition and utilization (Suchman, 1995), and thus increases input costs, thereby inhibiting improvements in operational efficiency. Conversely, low organizational density can mitigate the intensity of inter-organizational competition, enabling organizations to access and utilize resources at lower costs, enhance input-output efficiency, and consequently foster efficiency gains (Cui and Sun, 2020; Liang et al., 2017). In contrast, high organizational density exerts the opposite effects. Collectively, these findings indicate that the impact of organizational density on operational efficiency is a complex relationship.
Based on this theoretical foundation, organizational density is regarded as a critical variable influencing the operational efficiency of forest-based economic organizations, though the direction of this effect remains undetermined. This study primarily focuses on examining the potential correlation between operational efficiency and organizational density in forest-based economic organizations, and elaborates on the potential relationship between the two variables from the perspective of input-output efficiency. Consequently, this paper only posits that “organizational density exerts a significant impact on operational efficiency” without prespecifying the positive or negative direction of this effect, thereby proposing the first hypothesis (H2).
H2: When controlling for other influencing factors, a significant correlation exists between organizational density and the operational efficiency of organizations managing the under-forest economy.
2.3 Mechanism of influence and hypothesis proposal of organizational niche
Organizational ecology posits that the organizational niche represents the specific position an organization occupies within its population or community, determining the N-dimensional resource set essential for the organization's survival and development (Hannan and Freeman, 1977; Godsoe et al., 2017). Some scholars believe that the core of an organizational niche resides in the size of the resource pool that an organizational entity can occupy. This resource pool can be quantified through two dimensions: niche width and niche overlap. The former reflects the scope of resources accessible to the organization, while the latter indicates the intensity of competition with other organizations (Freeman and Hannan, 1983). Other scholars directly adopted the traditional definition from organizational ecology, defining an organizational niche as “the position and span occupied by a firm in a multi-dimensional resource space, which determines the range of resources that the firm can acquire and configure.” This definition aligns with the two core dimensions that the reviewers requested us to distinguish, namely “resource availability” and “organizational niche width” (Van Witteloostuijn and Boone, 2006).
Due to constraints on the availability of research data, this study selects “the number of financial industry organizations within a 5-kilometer radius (unit: count)” as the core indicator for measuring “resource availability” and “the diversity of organizations affiliated with the organizational legal person” as the core indicator for assessing “organizational niche width.” Based on this, the present study concurs with the traditional perspective of organizational ecology that an organizational niche is jointly constituted by resource availability and organizational niche width. However, it is important to emphasize that forest-based economic operation organizations are not merely biological population concepts but also social organizational forms. Their survival and development inevitably involve interactions with other organizations and the broader social environment.
Thus, taking the indicator “the number of financial industry organizations within a 5-kilometer radius” as an example, financial resources serve as a representative measure of organizational available resources. The spatial agglomeration of financial institutions can shorten the geographical distance between agricultural operation entities and financial services. When combined with service models such as relationship-based lending, this agglomeration significantly improves the availability of credit funds for agricultural operation entities, thereby influencing organizational operational efficiency through the “factor substitution effect” and “productivity effect” (Song et al., 2025). Concurrently, if an enterprise only occupies a narrow niche width, its capacity to acquire available resources will remain constrained even under conditions of equivalent environmental abundance (Cui and Sun, 2020). This conclusion is consistent with practical observations: within the same social environment, organizations exhibit varying levels of operational efficiency due to differences in their resource acquisition capabilities. Taking “the diversity of organizations affiliated with the organizational legal person” (a measure of organizational niche width) as an example, diversified or large-scale organizations (e.g., Texas Instruments, USA) typically occupy broader niches, enabling them to integrate and utilize more resources. Consequently, these organizations possess greater environmental resilience and are better equipped to withstand external environmental challenges (Abbott et al., 2016).
Drawing on existing literature, for Under-Forest Economy Management Organizations, the scope of available resources directly determines their capacity to utilize understory resources and develop competitive advantages. Audience recognition is a prerequisite for sustaining operations, as these enterprises are deeply embedded within local ecological and social systems. Against this backdrop, ecological niche breadth encompasses both resource scope and audience appeal. Traditional organizational ecology theory posits that in a macro selection environment characterized by perfect competition and resource scarcity, a broader ecological niche width is associated with weaker organizational “focus appeal strength,” which may reduce organizational survival rates or performance (Hannan and Freeman, 1977). However, the under-forest economic organizations examined in this study are still in a “low-density and weakly segmented” stage, where resource redundancy is prevalent. At this stage, expanding the ecological niche primarily provides a buffer through resource redundancy, rather than immediately triggering a sharp increase in competitive intensity. Thus, the diminishing appeal effect is offset by the resource complementarity effect. In addition, these organizations achieve non-equity vertical integration through “order + stewardship” arrangements: a single legal entity covers multiple nodes, including cultivation, primary processing, and sales, thereby internalizing transaction costs without changing the ownership structure. This avoids the structural complexity costs associated with “multiple products and markets” in Hannan's model. The specific explanatory mechanisms are elaborated as follows. Thus, the establishment and growth of an organization are closely linked to its organizational niche. Two primary pathways exist through which the organizational niche influences the operational efficiency of management organizations in the under-forest economy. First, a differentiation in organizational niches leads organizations to make strategic choices toward a path of specialized or diversified development before their establishment. These choices regarding organizational structure or form along with site selection will determine the richness and configuration process of production factors, thereby affecting operational efficiency. For instance, when an organization is founded, the decision-making layer, which is based on the initial environmental resource set the organization relies on, determines the main business to be involved in. Thus, the business can conduct product production, primary processing, distribution services, deep processing, and technological research and development and correspondingly select from the available organizational forms such as family farms, family forests, or professional cooperatives. The organization's position within the industrial chain also varies, affecting operational efficiency. Second, when changes occur in the organizational niche, organizational business strategies need to be adjusted accordingly. Adjustments may include expanding the scale of operations through land transfer, introducing new varieties or technological equipment as additional capital inputs, altering the position in the supply chain, and targeting new markets. These changes in the configuration of production factors at different stages affect operational efficiency. In summary, it is anticipated that the broader the organizational niche, the larger the resource set an organization occupies, and the higher its operational efficiency. Therefore, this paper proposes the third original hypothesis H3.
H3: When controlling for other influencing factors, the organizational niche is positively correlated with the operational efficiency of organizations managing the under-forest economy, meaning the larger the resource set an organization possesses, the higher its operational efficiency.
3 Materials and methods
3.1 Research method and index system construction
Current literature indicates that researchers have used two main approaches to analyzing factors influencing efficiency as the dependent variable. The first approach involves using a Super-Efficiency model coupled with a spatial econometric model to measure efficiency and influencing factors separately (Wu et al., 2021; Xu et al., 2021; Lin et al., 2021). The second approach employs a DEA model combined with a Tobit model for the same purpose (Feng and Xu, 2021). From the themes of the literature, one can observe that the former is more suitable for research in the fields of the environment and economic development, while the latter is more applicable to research in the social environment and economic development fields. Therefore, this study opted to construct a two-stage DEA-Tobit analytical model. The DEA model was used to assess the operational efficiency of organizations managing the under-forest economy. While the Tobit regression was used to analyze the factors influencing the differences in operational efficiency among these organizations.
3.1.1 Compatibility of the DEA-TOBIT two-stage analysis model with organizational ecology research
The DEA-TOBIT two-stage analysis model integrates Data Envelopment Analysis (DEA) with Tobit Regression, achieving an organic linkage between “efficiency measurement” and “identification of influencing factors.” In the first stage (DEA stage), the model requires no predefined production function form. Through a multi-input-multi-output indicator system, it objectively calculates the relative efficiency values (e.g., technical efficiency, scale efficiency) of decision units (such as different organizations or organizational populations), precisely capturing efficiency differences in resource allocation and operational management (Banker et al., 1984). In the second stage (Tobit stage), given that the efficiency values measured by DEA fall within the [0, 1], these efficiency values constitute a constrained dependent variable, and traditional OLS regression is prone to bias. Tobit regression, however, constructs a truncated regression model to effectively identify the direction and magnitude of environmental factors and organizational characteristics on organizational efficiency (Tobin, 1958). This two-stage logic provides a precise methodological tool for analyzing the “efficiency-driven mechanisms” in organizational evolution.
Existing organizational ecology research often employs methods like event history analysis to examine factors influencing organizational birth and demise. However, such approaches cannot directly measure organizational efficiency, making it difficult to quantify the “marginal effect of efficiency differences on organizational survival probability.” The introduction of the DEA-TOBIT model addresses this methodological gap. On one hand, the efficiency measurement in the DEA stage provides “quantifiable efficiency indicators” for organizational ecology research, enabling researchers to incorporate ‘efficiency' as a mediating or moderating variable within the organizational ecology framework. On the other hand, the regression analysis in the Tobit stage further links the transmission pathway from “influencing factors - organizational efficiency - organizational survival,” constructing a more comprehensive theoretical model. - organizational survival" transmission pathway, constructing a more comprehensive theoretical model.
3.1.2 Construction of an index system for measuring the operational efficiency of organizations managing the under-forest economy
Following the general principles of efficiency formation, this study used the output-to-input ratio of organizations managing the under-forest economy to measure their efficiency, thereby constructing an index system (Lin et al., 2017; Su and Bao, 2019; Ma and Wang, 2020; Zhu, 2017; Tong and Li, 2022). The output indicators focused on both quantity and quality, including the annual total output value of the under-forest economy (in 10,000 yuan) and the number of brand marks for under-forest economy products (count), with the latter encompassed quality indicators such as the number of trademarks obtained (count) and the number of green variety certifications (count). From the perspective of input, labor, land, and capital are the most fundamental factors related to production, while the input of technological elements plays a crucial role in improving the efficiency of the allocation of these basic production factors. Therefore, the following input indicators were designed: labor wage (in 10,000 yuan) and the number of management personnel comprehensively reflect the input of human resources; the land use area (hectares) invested in by the organization serves as the land input indicator; and the capital input indicator is represented by the annual investment in capital (in 10,000 yuan) for the under-forest economy, which refers to the total capital invested in the production process of the under-forest economy, excluding the costs of technology usage fees and wages for employees. This includes expenses on land, seedlings, construction of facilities and production tools, utilities, fertilizer, transportation, insurance, and interest. For the input of technological elements, the indicators include the cost of technology introduction (in 10,000 yuan) and the number of management personnel training sessions (person-times). Although all decision-making units operate under the same overall level of social science and technology, the degree of use of technology in terms of new equipment, new technology, new varieties, and professional talent varies among organizations, leading to different levels of input and operational efficiency.
3.1.3 Construction of the organizational ecology index system
This study draws from existing literature to select representative indicators from the aspects of organizational legitimacy, organizational density, and organizational niche. First, organizational legitimacy (XL) encompasses three indicators: cognitive, regulatory, and normative legitimacy. Notably, the application of organizational ecology theory to under-forest economic organizations constitutes a valuable scholarly endeavor, as prior research in this specific domain has been devoid of rigorous quantitative research designs. To capture organizational legitimacy in a more comprehensive manner, this study operationalizes organizational legitimacy by measuring the degree of recognition from diverse stakeholder groups. However, given the inherent social attributes of under-forest economic organizations, these three legitimacy indicators may exhibit a progressive hierarchical relationship within a specific social system context. It is important to clarify that the primary objective of this paper is not to precisely quantify the net effect of subsidies on operational efficiency, but rather to validate the applicability of organizational ecology theory in the under-forest economic context. Specifically, this study aims to examine whether a “threshold effect” exists in the relationship between organizational legitimacy and operational efficiency. Consequently, indicators of organizational legitimacy are constructed and presented from these three stakeholder perspectives. Drawing from Scott's perspective (Scott, 2001), cognitive legitimacy was measured by the extent of public awareness of an organization, using a scale from “few people are aware of the organization” to “an increasing number of people cooperate with the organization” as the indicator XL1. Regulatory legitimacy is based on the rules and regulations set by the government and industry associations and is quantified by the level of key resource support such as economic subsidies received by the organization. Hence, the annual subsidy amount (in 10,000 yuan) was used as the quantified indicator XL2. Normative legitimacy reflects the alignment of organizational behavior with societal values, for which there is currently a lack of quantifiable indicators. Drawing on scholarly conceptualizations of organizational legitimacy, this study employs the number of cooperative agreements signed (XL3) as an indicator to reflect the alignment between an organization's behaviors and the social values of external organizations or individuals. These cooperative agreement partners include horizontal counterparts within the same industry, financial institutions, and vertical entities such as Chinese herbal medicine processing plants and cold-chain logistics enterprises.
Second, an organizational density indicator XD was developed. Organizational density, viewed from the perspective of biological populations, primarily refers to the number of organizations with similar characteristics within a given area. Variations in the number of organizations will affect the level of organizational legitimacy and the extent of inter-organizational resource competition, which in turn affects the survival curve of the organization. This is manifested in the number and scale of the population within the industry, determining the intensity of competition and the potential for cooperation faced by the organization (Cui and Sun, 2020; Liu et al., 2016). This, in turn, influences the organization's ability to access and allocate limited resources. Therefore, this study designed the number of existing agricultural, forestry, animal husbandry, and fishing industry organizations within a 5 km radius (count) as the representative indicator of organizational density, denoted as XD.
Third, an organizational niche indicator, XN, was developed. Scholars commonly use the term ecological niche to denote the niche of an organization, emphasizing the size of the resource set an organizational entity can occupy. The resource set can be measured by the niche width and overlap, representing the organization's range of resources and the degree of competition with other organizations, respectively. Existing studies often substitute indirect factors for the size of the resource set, such as the human capital of the legal representative of the organization (Liu et al., 2016). This study employed more direct indicators: XN1 reflects the diversity of organizations in which the legal representative serves, providing a more comprehensive reflection of the resources possessed by the organization; XN2 represents the number of financial industry organizations within a 5 km radius (count), directly indicating the availability of financial resources for the organization. However, no specific indicator is currently available for organizational overlap, and it is expected that future research will delve deeper into this aspect. In summary, for the empirical analysis in this study, the operational efficiency of organizations managing the under-forest economy was taken as the dependent variable (Y), with organizational legitimacy, organizational density, and organizational niche as the independent variables (X). Considering the availability of data, the specifics are as shown in Table 1.
Table 1
| Dependent variable | Independent variables | Target index | Selected index | Symbol | Description |
|---|---|---|---|---|---|
| Operational efficiency of understory economic management organizations (Y) | Organizational legitimacy (XL) | Cognitive legitimacy | Familiarity of the periphery with the organization | XL1 | 0 = only a few people have ever known = weak 1 = the number of people who know the organization increases from few to many = general 2 = the increasing number of people comes to learn of or cooperate with the organization = strong 3 = many people are familiar with the organization = very strong |
| Regulatory legitimacy | Amount of government subsidies obtained by the organization (in 10,000 yuan) | XL2 | This variable refers to whether the operating entity has obtained an accumulated amount of support for infrastructure, seedlings, and other projects. | ||
| Normative legitimacy | Number of contracts signed by leaders of an organization (count) | XL3 | Number of contracts signed with similar business organizations, technological, financial, and other units, indicates the degree of social recognition of their business. | ||
| Organizational density (XD) | Number of similar organizations in the area | Number of existing agricultural, forestry, animal husbandry, and fishing industry organizations within a 5 km radius (count) | XD | Number of competitors within a 5 km range is used to represent organizational population density. | |
| Organizational niche (XN) | Available resources of the organization | Degree of diversity of legal representatives participating in organizational forms | XN1 | The more types and numbers of operational organizations a legal representative is involved in, the greater the breadth of resources the organization can access and use, and consequently, the greater the width of resource possession. This is represented by an ecological niche that increases progressively, denoted by 0, 1, and 2. | |
| Number of financial organizations within 5 km (count) | XN2 | The amount of scarce financial resources nearby is used to represent the size of organizational resource sets. |
Index system of organizational ecology.
Furthermore, the organizational niche indicators constructed in this study do not account for the influence of organizational niche overlap. This is attributable to the fact that the research context is set in the initial low-density development stage of forest-based economic organizations, which are primarily distributed in rural areas endowed with abundant forest resources. Due to the substantial spatial distance between these organizations, the degree of organizational niche overlap is relatively low. Therefore, this study temporarily excludes the effect of organizational niche overlap and focuses exclusively on the core impact of resource aggregation.
In addition, the design of control variables is crucial. In regression analysis, in addition to the key explanatory variables, it is necessary to control for other potential influencing factors to highlight the explanatory power of the core indicators of organizational ecology on the operational efficiency of organizations. Drawing on existing research, this study controlled for the following 10 variables: organizational type, organizational age (years), number of organization shareholders in the year of the survey (count), area of forest land owned by the organization (hectares), average tenure of regular employees (years), years of education of core management personnel, age (years), whether there is experience in non-agricultural employment, whether they are local township personnel, and regional dummy variables.
3.2 Data sources
The policy orientation of the National Social Science Foundation of China (NSSFC), which emphasizes addressing practical socioeconomic issues and promoting the coordinated development of ecology and economy, has effectively guided the design of this study. Specifically, this orientation has directed the research focus toward the operational efficiency of underforest economic organizations—entities closely linked to ecological conservation and rural revitalization. Meanwhile, funding support from the NSSFC has been crucial for the implementation of this research, particularly facilitating fieldwork and data collection in Fujian Province. The funded expenses include the distribution of questionnaires, interviews with local stakeholders (e.g., underforest economy operators, staff of local agriculture and forestry departments), and data verification processes. For this research, the data on the production and operation of organizations managing the under-forest economy and the environmental data for these organizations is primarily composed of two parts. First, the national and provincial (Fujian Province) statistical yearbooks of forestry were used to collect background information on the management of the under-forest economy and the cultivation of new types of management entities, collected on family-based organizations, specialized cooperative organizations, and corporate enterprise organizations in Fujian Province. These data were used to determine the overall scope of the sample of under-forest economic management organizations. Second is the survey data. Data were collected through a preliminary questionnaire survey conducted in Wuyi City to ensure the scientific validity of the research instrument. The revised questionnaires were then distributed to 206 leaders of under-forest economic organizations across 12 counties, including Wuyi, Guangze, Qingliu, and Changting. This resulted in 132 valid responses. The sample included 48 family-based (36.4%), 64 specialized cooperative (48.5%), and 20 corporate (15.1%) organizations, mirroring the composition of such entities in Fujian Province.
4 Results
4.1 Calculation results of the operational efficiency of the understory economic management organization
Using the Input-BCC model, the relative efficiency of under-forest economic management organizations was evaluated. According to DEA principles, 45 organizations (34.10% of the total) achieved optimal resource allocation efficiency (an efficiency score of 1). The average overall efficiency for all such organizations was 0.65, with an average pure technical efficiency of 0.82 and scale efficiency of 0.78. These figures gain context when compared with the operational efficiency of under-forest economic farmers in the same region, as cited from a previous study (Han et al., 2018), which found average comprehensive efficiencies of 0.2, 0.26, and 0.79 for farmers—significantly lower than organized entities—highlighting the value of organized operations. Analysis of the 132 organizations revealed distinct efficiency differences, with specific values detailed in Table 2.
Table 2
| Index | Comprehensive efficiency | Pure technical efficiency | Scale efficiency | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Number | Rate (%) | Average | Number | Rate (%) | Average | Number | Rate (%) | Average | |
| Above-average DMU | 68 | 51.52 | 0.939 | 84 | 63.64 | 0.995 | 83 | 62.88 | 0.96 |
| Subaverage DMU | 64 | 48.48 | 0.339 | 48 | 36.36 | 0.506 | 49 | 37.12 | 0.461 |
Distribution of operational efficiency of understory economic management organizations in northwestern Fujian Province.
Table 2 indicates that within all management organizations, 68, 84, and 83 decision-making units, respectively, exceeded the average for overall, pure technical, and scale efficiencies, with specific averages of 0.939, 0.995, and 0.96, respectively. Conversely, 64, 48, and 49 sample organizations fell below these averages, with averages of 0.339, 0.506, and 0.461, respectively. The significant variation in operational efficiency among the 132 sample organizations provides a solid basis for research into the factors influencing these differences in efficiency.
This study reveals the current efficiency status and potential for improvement of organizations managing the under-forest economy in northwest Fujian. Table 2 indicates that there was a 35% growth potential in the overall comprehensive efficiency of these organizations, but the analysis showed that 60.6% of the 132 decision-making units had reached the highest level of pure technical efficiency, indicating optimal allocation of input factors. This improvement in efficiency is closely related to the promotion of organized management, which has facilitated scientific decision-making by expanding market information channels and enhancing management standardization. Therefore, the study emphasizes that promoting organized management in the under-forest economy can effectively optimize resource allocation and thereby enhance production efficiency.
4.2 An empirical analysis of the impact of organizational ecology on the operational efficiency of under-forest economic management organization
Using Stata 13 software, the effects of six core explanatory variables on the operational efficiency of organizations managing the under-forest economy were estimated. The final regression results are presented in Table 3.
Table 3
| Variable attribute | Variable | Specific variable declaration | Estimation coefficient Standard deviation |
|---|---|---|---|
| Key explanatory variable | XL1 | Familiarity of the periphery with the organization | 29.51*** [0.0271] |
| XL2 | Amount of government subsidies obtained by the organization | −0.03 [0.0002] | |
| XL3 | Number of objects to which an organization contract is signed | 0.81** [0.0034] | |
| XD | Number of agricultural, forestry, mining, and fishery organizations within 5 km | −0.05** [0.0002] | |
| XN1 | Degree of diversity of legal person participation in organizational forms | 6.44*** [0.0194] | |
| XN2 | Number of financial organizations within 5 km | 0.51** [0.0023] | |
| Control variable | region1 | Nanping City = 1, others = 0 | 14.84*** 0.0446 |
| region2 | Longyan City = 1, others = 0 | 2.04** [0.0156] | |
| region3 | Sanming City = 1, others = 0 | 4.71 [0.0648] | |
| Fnjy | Whether key managers have non-farm employment experience | 6.8* [0.0431] | |
| Edu | Years of education for key managers | −2.13 [0.0176] | |
| Age | Age of key managers | −7.57** | |
| [0.0246] | |||
| Wy | Average working years of long-term employees | −0.74 [0.0092] | |
| Town | Whether the legal person is a township person | 14.53* [0.0935] | |
| Type | Organization type | 3.45 [0.0297] | |
| ogage | Existed years for the organization in the interviewed year | 1.14 [0.0103] | |
| Gd | Number of existing shareholders | 0.35 [0.007] | |
| Fs | Organization owns forest land area | 0.35 [0.0044] | |
| _cons | −13.22 [0.1212] |
Estimation results of the effect of organizational ecology on the operational efficiency of understory economic management organizations.
Tobit regression Number of obs = 132 LR chi2(15) = 132.29 Prob > chi2 = 0.0000 Log likelihood = 24.519497 Pseudo R2 = 1.5891 *** p < 0.01, ** p < 0.05, and * p < 0.1.
Initially, within the organizational legitimacy indicators, the dimensions of cognitive legitimacy and normative legitimacy had a significant positive effect on the operational efficiency of organizations managing the under-forest economy, while the impact of normative legitimacy was not significant. Data from Table 3 show that the level of familiarity of the surrounding community with the organization (XL1) and the number of contract partners the organization has signed agreements with (XL3) significantly promoted the operational efficiency of organizations managing the under-forest economy, which is consistent with Hypothesis 1 (H1). From the estimated values, a 1% change in XL1 led to a 29.51% increase in organizational operational efficiency, highlighting the importance of enhancing the familiarity of the surrounding community with the organization. The surrounding community of an organization was not only the primary source of its production factors but also the initial market for its product output. When the cognitive legitimacy of the surrounding community toward the organization is enhanced, the organization can better align with the market, conducting business with market demand as a guide, which is beneficial for the organization to realize its value. Additionally, the strengthened cognitive legitimacy of the organization can significantly reduce the resistance encountered in the diversion of production factors, allowing for better satisfaction of foundational production factors such as forest land resources and high-quality labor. Furthermore, the number of contract cooperation partners that organizations managing the under-forest economy have (XL3) also significantly promotes their operational efficiency. It is possible that the more formal relational contracts an organization has, the more its behavior tends to align with established social standards or prevailing social values, that is, the higher the level of normative legitimacy of the organization. This is advantageous for the organization as it can reduce the transaction costs associated with contracts, making it easier to find cooperative partners. Different organizations can form complementary resources and advantages along the industry chain, implementing new strategies such as intensive processing, technological research and development, cooperative strategies, and professional services to leverage the synergistic effects between organizations, thereby enhancing their operational efficiency.
Second, the impact of government subsidies (XL2) on organizational operational efficiency was not significant, which is inconsistent with Hypothesis 1. The possible reason for this may lie in the fact that, due to real-world constraints, the amount of government subsidies as the sole indicator of the organization's regulatory legitimacy might not be comprehensive. However, an even more important reason might be that the current financial subsidies for organizations managing the under-forest economy are primarily awarded through a competitive process. That is, before receiving government subsidies, these organizations must complete the initial investment and production and meet the required standards and other criteria to stand out among the many competing organizations and qualify for project subsidies. Therefore, subsidies may lag behind the production of the under-forest economy, thereby constraining the positive impact function of government subsidies. This result effectively alleviates concerns regarding endogeneity associated with regulatory legitimacy (XL2). Specifically, Fujian's forest-based economy subsidy policy adopts a “construction-first, subsidy-later” approach, implying that regulatory legitimacy (XL2) can only be achieved when XL1 and XL3 are sufficiently robust. If regulatory legitimacy (XL2) were plagued by severe reverse causality, XL2 should have exhibited a significant positive effect. The current findings thus substantially mitigate endogeneity concerns.
Third, organizational density significantly affects the management efficiency of the under-forest economy, which is inconsistent with Hypothesis 2. Data indicate that, at the 5% confidence level and when controlling for other variables, the number of agricultural and related organizations within a 5 km radius (XD) has an inhibitory effect on the enhancement of organizational operational efficiency. The potential reason is that as the number of such organizations within a 5 km range increases, so does the competitive pressure among them, leading to fiercer competition for established resources. Especially when the number of organizations is excessive, this can elevate the scarcity of resources, increase the price of resources, and thus inhibit the improvement of operational efficiency. The findings suggest a need to balance the growth of such organizations to maintain efficiency, with the optimal density threshold a topic for further research.
Fourth, the ecological niche width positively influences the organizational efficiency, which is inconsistent with Hypothesis 3. Analysis shows that the diversity of organizational forms (XN1) in which legal representatives participate significantly boosts efficiency at the 1% confidence level, with each unit increase in XN1 leading to a 6.44-unit efficiency gain. This suggests that the breadth of an organization's ecological niche, determined by the diversity of its participation, affects the size of the resource set it can access. Higher diversity in organizational forms leads to access to a greater number of organizations and, more importantly, allows the legal representatives to occupy different resource sets through various organizational forms. This improves both the types and the size of resources available, further broadening the organization's ecological niche. This reduces transaction costs for resource acquisition and encourages strategic cooperation, market expansion, and brand development, ultimately improving operational efficiency. Additionally, the number of financial institutions within a 5 km radius (XN2) positively influences the organizational efficiency at the 5% confidence level. The rationale is that a greater number of financial institutions translate to richer financial resources available to the organization. As financial resources are a key element of production, organizations with easier access to capital can pursue diverse main business strategies. This leads to a wider range of resources within the industry chain, allowing for adjustments in organizational size, market expansion, brand cultivation, and the development of technical talent, which in turn positively influences operational efficiency.
Finally, the impact of control variables on organizational efficiency varies significantly for different variables. Table 3 shows a positive correlation between regional characteristics and organizational efficiency. It may be that economic environments vary by region, leading to disparities in the total volume and methods of resource acquisition by sampled organizations, which in turn affects their operational efficiency. Consequently, enhancing the operational efficiency of these organizations necessitates region-specific policy approaches. Then, the employment of core managerial staff in non-agricultural sectors (fnjy) and their status as local township residents (town) are two indicators that significantly promote operational efficiency at the 10% significance level. The fnjy indicator suggests that the organizational legal representative possesses an extensive social network and rich management experience, which supports the formulation and execution of strategic initiatives. Meanwhile, the town indicator enhances the organization's perceived legitimacy, positively influencing operational efficiency and complementing the understanding of the ecological impact on the operational efficiency of organizations managing the under-forest economy.
4.3 Robustness test
Current data analysis often involves methods such as modifying key explanatory variables, adjusting control variables, and conducting placebo tests. It is believed that the coefficients of key variables have economic significance, while others are predictive and not a primary focus. This study focused on the regression coefficients of core explanatory variables, with modifications such as replacing the subsidy amount (XL2) with a binary indicator for subsidy receipt. The diversity of organizational forms (XN1) and the number of financial institutions (XN2) are represented by continuous variables such as the current number of shareholders and forest land area. Control variables were incrementally included, covering organizational characteristics, management traits, and regional attributes. The robustness check process is shown in Table 4.
Table 4
| Variable | Original regression result | Robustness test results | |||
|---|---|---|---|---|---|
| STEP1 | STEP2 | STEP3 | STEP4 | ||
| XL1 | 0.000(***) | 0.000(***) | 0.000(***) | 0.000(***) | 0.000(***) |
| XL2 | 0.182 | 0.584 | 0.531 | 0.318 | 0.383 |
| XL3 | 0.019(**) | 0.061(*) | 0.049(**) | 0.031(**) | 0.034(**) |
| XD | 0.023(**) | 0.061(*) | 0.056(*) | 0.032(**) | 0.022(**) |
| XN1 | 0.001(***) | 0.000(***) | 0.000(***) | 0.000(***) | 0.001(***) |
| XN2 | 0.027(**) | 0.091(*) | 0.084(*) | 0.019(**) | 0.015(**) |
Robustness test results of key explanatory variables.
*** p < 0.01, ** p < 0.05, and * p < 0.1.
A comparison of the robustness test results in Table 4 with the original regression coefficients revealed that the significance coefficient of the XL1 indicator remained highly consistent with the post-robust regression of the original regression coefficient. This indicates that the familiarity of surrounding groups with the organization has a significantly positive impact on its operational efficiency, a factor that should be fully considered in policy formulation. The significance coefficient for the XL2 indicator post-robust regression was 0.584, while the original coefficients from stepwise regression were 0.113, 0.176, and 0.182, suggesting a stable, yet insignificant relationship between government subsidies and organizational operational efficiency within this study. The stepwise regression coefficients for the XL3 indicator showed slight fluctuations, but the significance coefficient post-robust regression remained significant at the 10% confidence level, indicating that XL3 has a notably clear impact on the operational efficiency of the sample organizations. Similarly, the indicators XD, XN1, and XN2 maintained significance at the 1–10% confidence levels post-robust regression, demonstrating good stability. In summary, the impact of organizational ecology on the operational efficiency of organizations managing the under-forest economy is relatively insensitive to changes when variables are added, deleted, or substituted, meaning that the significance levels and directional effects of various indicators XL1, XL2, XL3, XD, XN1, and XN2 on the dependent variable y are quite stable. Therefore, the robustness tests confirmed the established and stable relationship between organizational legitimacy and ecological niche on the operational efficiency of organizations managing the under-forest economy.
5 Conclusions
Driven by green development policies, the under-forest economy and the related management organizations are rapidly evolving to address the different goals of the needs for economic growth and environmental constraints. Fujian's practices stand as a quintessential example of agroforestry in East Asia, inherently aligned with the core objective of global agroforestry: achieving the coordinated development of ecological conservation and economic benefits. From an organizational ecology perspective, this study focuses on under-forest economic organizations in northwestern Fujian, systematically analyzing strategies for enhancing their operational efficiency and exploring the mechanisms through which organizational ecology factors influence such efficiencys. Using the DEA-Tobit method, it was found that organizational legitimacy and ecological niche positively affect operational efficiency, while organizational density has the opposite effect. Specifically, the impact order is as follows: organizational legitimacy > ecological niche > organizational density. Moreover, the third-level indicators within each module significantly influenced operational efficiency, providing a clear direction for enhancing the efficiency of organizations managing the under-forest economy. Importantly, this study verifies that organizational innovation constitutes an effective pathway to enhance the sustainable efficiency of agroforestry systems, ultimately providing a replicable “Chinese solution” for the sustainable utilization of agroforestry resources in geographically analogous regions worldwide. Based on this research, the following specific policy recommendations are proposed.
First, organizations managing the under-forest economy demonstrate significant advantages in resource allocation, leading to improved overall operational outcomes. In northwestern Fujian, the average values for comprehensive, pure technical, and scale efficiencies of these organizations were 0.65, 0.82, and 0.78, respectively. Among 132 decision-making units, 60.6% had achieved optimization of pure technical efficiency, which is closely associated with scientific decision-making and broadened market information channels of organized operations. This indicates that promoting organized management can enhance the production efficiency of the under-forest economy. Notably, this study quantitatively analyzes the synergy degree between ecological efficiency and economic efficiency in the operational efficiency of Fujian's underforest economic organizations. By contextualizing this finding within the “strong sustainability” theory in sustainable economics (i.e., the irreplaceability of ecological capital), this research provides an empirical case from the mountainous areas of southeastern China for Target 15 of the United Nations Sustainable Development Goals (SDGs) (Life on Land), highlighting the reference value of regional practices for global ecological conservation issues. To this end, we recommend advancing institutional development and popularizing the contract spirit to foster organized management. For example, managers should further deepen systemic reforms to leverage market mechanisms and promote the diversification of organizational forms. Enhancing the application of information technology and establishing a more comprehensive credit system can help to popularize the contract spirit, reduce transaction costs between organizations, and facilitate cooperative endeavors.
Second, government subsidies aimed at incentivizing the use of organizations designed to manage the under-forest economy do not significantly affect operational efficiency. This may be true because the current competitive allocation of subsidies, which requires organizations to meet standards and compete for eligibility before receiving funds post-verification, leads to timeliness issues in financial support. In light of this, this study suggests reforming the subsidy mechanism by implementing a diverse range of subsidy methods to ensure timely capital infusion and optimized resource allocation. For instance, Nanping City has implemented targeted support policies for diverse forest-based operators within industrial parks, including family farms, specialized cooperatives, and leading enterprises. These policies cover key areas such as fiscal subsidies, technical training, and market access assistance. Such a policy framework not only optimizes the forest-based economic ecosystem and enhances policy credibility but also significantly improves the operational efficiency of participating entities. Specifically, we recommend subsidy managers should design a multifaceted subsidy scheme that includes different forms, such as interest-free loans for special funds in the under-forest economy with a 3–5 year term and matching funds for outstanding cooperative projects. These should be combined with the existing competitive subsidies to form a subsidy system that meets the needs of various operational entities. These diversified subsidy approaches can help prevent delays in providing financial support and fully leverage the core role of capital in enhancing organizational operational efficiency.
Third, organizational legitimacy (XL) significantly enhances organizational efficiency, notably through the indices of XL1 and XL3. This finding underscores the importance of enhancing organizational legitimacy, which will ultimately facilitate the empowerment effect of underforest economic organizations on smallholder farmers. Such empowerment directly addresses the universal demand for rural poverty alleviation and development in developing countries worldwide, thereby highlighting the equity-oriented value proposition of this research. Therefore, farmer experts should be leveraged as bridges to foster peer exchange and better align with agricultural operational needs. In addition, data showed that core managers in northwestern Fujian's under-forest economy organizations were typically born and educated in the 1960s and are characterized by their diligence and eagerness to learn. Therefore, recommendations include allocating funds for their advanced formal education, granting expert qualifications through professional diplomas, and inviting local production experts to give knowledge-sharing lectures. Additionally, a farmer expert title or skill assessment system should be established that could elevate organizational recognition, expand cooperative avenues, mitigate information asymmetry, and effectively channel scarce resources such as talent and capital toward the organization.
Fourth, a broader organizational ecological niche significantly positively influences the operational efficiency of organizations. The empirical results showed that with a greater diversity of organizational forms in which the legal representatives participate, the greater the number of financial service organizations within a 5 km radius, the wider the ecological niche, and the larger the resource set, which in turn promote the improvement of operational efficiency. Similarly, Sanming City has proactively coordinated multiple stakeholders, including agricultural and forestry departments, financial institutions, research institutes, and business entities, to establish a collaborative platform. This leadership-driven initiative has effectively addressed resource constraints encountered by forest-based economy operators—such as funding shortages and outdated technologies—while concurrently enhancing the governance efficiency of the industrial chain. Therefore, to support the development of the under-forest economy, it is important to focus on retraining legal representatives regarding organizational development and management skills to broaden the ecological niche. Financial reform should be actively promoted, and the rural financial service system should be improved to provide a variety of financing methods to serve the under-forest economy. For example, based on the compensation list and accounts of ecological public welfare forests, local governments and financial institutions should jointly develop a “credit whitelist,” reduce financing costs, and form a rural financial ecosystem. This will effectively transform financial services into the “lifeblood” needed for economic development, benefiting organizations in occupying a larger resource set.
Additionally, organizational density (XD), which refers to the number of agriculture, forestry, animal husbandry, and fishery organizations within a 5 km radius, exerts an inhibitory effect on the operational efficiency of an organization, with a complex impact that merits future research, particularly concerning the cultivation of the optimal number of organizations managing the under-forest economy. Regarding issues such as Niche width and the dynamics of organizational populations, partiality of memberships in categories and audiences, although these aspects were not included within the framework of this study, they represent crucial perspectives for examining the operational efficiency of under-forest economic management organizations. They also constitute important directions for future research on such topics.
In summary, studying the development of the under-forest economy from the perspective of organized management holds significant practical implications for rural revitalization, especially against the backdrop of promoting the rejuvenation of industry, talent, ecology, organization, and culture, tapping into regional resource advantages through organized management and encouraging “migrant workers to return to their hometowns for entrepreneurship” which can truly make a difference and lead to genuine rural revitalization. Meanwhile, it is imperative to encourage underforest economic organizations to establish vertical alliances with downstream market entities, including forest medicinal material and decoction piece manufacturers, cold chain logistics enterprises, and e-commerce platforms. By acquiring market legitimacy through formal business-to-business (B2B) contracts, these organizations can mitigate the uncertainty associated with specialized asset investments, thereby facilitating in-depth improvements in vertical integration efficiency.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the [patients/participants OR patients/participants legal guardian/next of kin] was not required to participate in this study in accordance with the national legislation and the institutional requirements.
Author contributions
ZW: Resources, Writing – original draft, Software, Methodology, Validation, Conceptualization, Formal analysis, Data curation, Investigation, Visualization. YW: Writing – review & editing, Formal analysis. QZ: Writing – review & editing, Data curation. JL: Software, Visualization, Funding acquisition, Writing – review & editing, Validation. YW: Project administration, Writing – review & editing, Supervision.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was funded by National Social Science Fund Project (Grant no. 22CGL003).
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
operational efficiency, organizational ecology, organizational legitimacy, organization's niche, under-forest economy
Citation
Wang Z, Wang Y, Zhang Q, Lin J and Wei Y (2026) The impact of organizational ecology on the operational efficiency of under-forest economic management organizations: a case study of Fujian Province. Front. For. Glob. Change 9:1714115. doi: 10.3389/ffgc.2026.1714115
Received
27 September 2025
Revised
05 January 2026
Accepted
30 January 2026
Published
18 February 2026
Volume
9 - 2026
Edited by
Jang-Hwan Jo, Wonkwang University, Republic of Korea
Reviewed by
César García-Díaz, Pontifical Javeriana University, Colombia
Anna Neya Kazanskaia, Neya Global, Thailand
Updates
Copyright
© 2026 Wang, Wang, Zhang, Lin and Wei.
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*Correspondence: Junjie Lin, t2054@ndnu.edu.cn; Yuanzhu Wei, 275292658@qq.com
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.