The Impact of the Governance Fragmentation of Forestry Communities on the Economic Performance of State-Owned Forest Enterprises in Northeast China: An Empirical Analysis Based on the Transaction Cost Perspective

Abstract

The 2015 reform of state-owned forest regions (SOFRs) in Northeast China required state-owned forest enterprises (SOFEs) to transfer their governmental and social roles to local authorities. This transition, however, created fragmented governance within forestry communities due to the absence of cooperative mechanisms between SOFEs and local governments. This study examines the economic effects of this governance fragmentation on SOFEs and explores the underlying mechanisms. The research combines new institutional economics and transaction cost theory to develop hypotheses and employs empirical analysis using fixed-effects models on data from 39 SOFEs, belonging to two forest industry groups from 2015 to 2022, collected through surveys and field investigations. The findings indicate that governance fragmentation has a significant negative impact on the economic performance of SOFEs. The high transaction costs incurred by SOFEs in achieving community co-governance with local governments are identified as a key mediating mechanism. These costs lead to resource dispersion and diminished trust between SOFEs and local governments. The economic impact of this governance fragmentation varies based on the economic conditions of the SOFEs, their operational scales, and the clarity of geographical management boundaries with local governments. To mitigate the adverse effects of governance fragmentation, the study suggests proactive institutional designs to reduce transaction costs. These findings offer new insights into the corporate social responsibilities of Chinese SOFEs and suggest improvements in the governance structures of forestry communities in SOFRs in Northeast China. Additionally, the study expands the application of transaction cost theory in public affairs governance and enhances quantitative research on the economic impact on enterprises.

1. Introduction

In the 1950s, the central government of China invested in the construction of 87 state-owned forest enterprises (SOFEs) in the provinces of Heilongjiang, Inner Mongolia, and Jilin to support national industrial construction and meet the demand, in economic development, for forest resources such as timber. Initially, SOFEs not only vertically operated the forestry industry but also engaged in horizontal integration [1], and operated under the principle of “zhengqi heyi”, which means the integration of government entities and business corporations. SOFEs took on all social affairs management and government administrative functions and were the core organizational entities within state-owned forest regions (SOFRs) in Northeast China. While this integration of functions strengthened national political power, reduced management costs, and restored the national economy under the planned economic system, it also burdened enterprises with heavy social burdens and exacerbated the overconsumption of forest resources [2]. In 1992, China officially established a socialist market economy system and promoted the market-oriented reform of state-owned enterprises. Consequently, SOFEs began to explore the establishment of a modern corporate system, but this reform did not change the fundamental nature of SOFEs performing social functions, and social welfare spending remained a huge burden for SOFEs. By the early 21st century, 60 out of the 84 SOFEs had depleted most of their mature forests, and almost all SOFEs were in financial arrears [1]. Entering the 21st century, under the influence of the Natural Forest Protection Program (NFPP), SOFEs gradually began to reduce timber production and transition towards forest conservation. With a sharp decline in timber revenue, some enterprises attempted to transfer part of the social service system to local governments. In 2015, the Central Committee of the Communist Party of China and the State Council issued the “Guiding Opinions on Reform of State-owned Forest Regions”. One of the important reform elements was to gradually separate government functions from these enterprises according to local circumstances (“yindi zhiyi”). Under the promotion of the central government, the administrative powers of the forestry communities previously held by SOFEs gradually transferred to local governments, bringing an end to the decades-long system of “zhengqi heyi”.

After the reform, SOFEs were positioned as ecological public interest state-owned enterprises, with their primary goal being the protection of state-owned forest resources. However, this does not mean that the economic benefits of the enterprises are unimportant. Maximizing the commercial value of market-oriented operations within SOFEs is also one of the key objectives of the reform of the SOFRs. Enhancing the economic efficiency of SOFEs will contribute to better ecological forest management, improve the living standards of employees, and reduce dependence on national NFPP funding. Many scholars have analyzed the impact of factors such as forest certification [3], managers’ personal characteristics [4], and government investment in science and technology [5] on the economic performance of forest enterprises. However, relatively less attention has been paid to institutional factors like their governance structure. Han et al. [6] regarded SOFEs as “social firms”, where a company’s objective is to improve the well-being of local communities by increasing economic, environmental, and social outcomes, and proved that there was no significant trend in the pure technical efficiency of enterprises during the reform period, although there was some improvement in pure technical efficiency within the framework of profit maximization. This reminds researchers that SOFEs cannot be simply regarded as market-oriented enterprises, but rather to comprehensively consider their social and political attributes.

Current research on the reform of SOFRs in Northeast China mainly focuses on the implementation process of the reform and its outcomes in terms of economy and ecology [7,8,9]. Some studies have noticed the impact of the reform on forestry communities and residents’ livelihoods [10,11,12]. However, the transformation of forestry community governance architecture, the changes in the roles of SOFEs in forestry community governance, and the impacts on SOFEs have not attracted widespread attention from scholars. Before the reform, SOFEs were the sole entities in regional governance, undertaking functions such as social services, social management, social security, and urban construction that should have been provided by the government or society. Relieving SOFEs of their heavy social burdens is not an easy task. In practice, SOFEs are in superior conditions compared with local governments, in terms of administrative level, management capacity, and personnel quality [13]. The limited financial resources of local governments constrain their ability to fulfill social service functions in forestry communities [14]. Therefore, during the reform’s transition period, SOFEs had to replace local governments and to continue to bear the actual responsibilities, substantive work, and personnel costs of providing public services and managing communities, while local governments could enjoy a free ride from SOFEs in the governance process. However, SOFEs do not have the legal qualifications to participate in the specific agenda of the governance of forestry communities now, facing operational dilemmas of “taking governance responsibility without management authority”, which restrict the effectiveness of collaborative governance between SOFEs and government. In other words, the role SOFEs play in forestry community governance does not receive formal recognition from the authorities, and mechanisms for cooperative governance and mechanisms for the coordination of regional governance rights and responsibilities have not been established between SOFEs and local governments, let alone the sharing of the costs of governance. Moreover, after the management of forestry communities was localized, the power and responsibilities of social governance, which were previously exercised by SOFEs, have been fragmented among different functional government departments. In the process of participating in the governance of forestry communities, SOFEs need to coordinate with multiple government functional departments, which further increases the difficulties and challenges faced by SOFEs in governance agendas due to the involvement of different policies, regulations, and procedures. Especially for forestry communities, which were established based on the natural distribution of forests, the phenomenon of geographical distribution across administrative boundaries is particularly prominent. Dealing with cross-domain affairs caused by the mismatch between administrative management scales and ecological issues has become a common challenge for SOFEs and local governments to face together. In short, SOFEs and local governments, as the co-management institutions of forestry communities, are relatively decentralized in terms of governance authorities, governance responsibilities, and other governance elements such as concepts, mechanisms, and information, and they face a pronounced problem of governance fragmentation.

The term “fragmentation” implies that the governance field is marked by a patchwork of public and private institutions, which differ in nature, constituencies, spatial scope, subject matter, and objectives [15]. Research on institutional fragmentation originated in international law, and can be traced back to the mid-19th century when international law fragmentation began to be studied, as did the overlap and conflicts between international treaties [16]. Currently, fragmentation has become a common governance issue, leading to a rich body of research outcomes in fields such as government administration [17] and resource management [18]. The consequences of fragmentation, whether they are positive or negative, have not yet been unanimously agreed upon by academics. Some scholars argued that governance fragmentation facilitates small-scale multilateral cooperation, enabling faster, more innovative, and further-reaching decision-making among participants [16]. However, other scholars pointed out that under a fragmented governance architecture, the boundaries of participants are not always clear, which may result in conflicting decisions, increased redundancy, and hindrances to the formation of common visions, aspirations, and actions. It follows that organizational diversity itself does not necessarily lead to efficiency [16]. Back to the SOFRs in Northeast China, scholars have noticed that the governance fragmentation of forestry communities has led to a decline in regional public services and the living standards of residents [11], but research conducted from the economic perspective, like the impact on the economic performance of enterprises, has not yet received attention. The stripping of functions is expected to alleviate the burden on SOFEs to some extent and allow them to concentrate more on ecological protection and industrial transformation. Simultaneously, a fragmented governance architecture may strengthen the connection between the forest regions and the locals, while more communication with governments could also enhance SOFEs’ political resources, aiding them in acquiring more economic resources [19]. However, the broad and dispersed polycentric governance systems resulting from addressing fragmentation could lead to high transaction costs when simultaneously accommodating various interests [20]. As non-legitimate and non-authoritative governance entities, governance affairs, including supplying public services undertaken by SOFEs may greatly increase communication and coordination costs between SOFEs and local governments. The transaction cost theory in new institutional economics has become a good tool for investigating economic organizations, including horizontal diversification, multinational corporations, strategic alliances, supply chain relationships, and public–private partnerships [21], as well as for analyzing development policies and evaluating the effectiveness of institutional arrangements in resource management [22], and has been widely applied in fields like fisheries co-management [23], forest management [22], and environmental governance [20]. From the perspective of transaction costs, an imbalance between costs and benefits can undermine institutional effectiveness and even lead to institutional collapse [20]. A sound institutional framework can reduce the waste of management resources and market inefficiency through better management measures [24], thereby promoting economic performance. In other social science research fields, such as public affairs management, however, the importance of transaction costs has yet to receive widespread attention. So, what impact does the governance fragmentation of forestry communities have on the economic performance of SOFEs? Is the transaction cost for SOFEs when participating in co-governance with local governments the key mechanism for the impact of governance fragmentation? This study will conduct empirical econometric analysis to address these above two questions with collected panel data from 2015 to 2022. The focus of the research is, on the one hand, to scientifically construct an indicator that can measure the fragmentation level of governance architecture for forestry communities, and to analyze its impact on the economic performance of SOFEs; on the other hand, it is to analyze whether the transaction costs paid by SOFEs under fragmented governance architecture are the key mediator variable.

This study holds significant theoretical and practical implications. The analysis of the governance fragmentation dilemma in forestry communities during the reform transition period and their economic impacts on SOFEs will enrich the research landscape related to forestry reform from a social governance perspective and fill gaps in the existing literature, while also helping to reveal the lingering effects of the 20th-century planned economic system on the construction of the market economy in China and deepening scholarly understanding of the unique corporate responsibilities and operational mechanisms of Chinese SOFEs. Furthermore, by focusing on the interaction between SOFEs and government within a regional governance architecture and viewing social management and public service provision as a “commodity”, this study delves into the forms and influences of transaction costs that SOFEs incurred to achieve co-governance under a fragmented governance architecture and its economic impact on enterprises, which will contribute to the field of transaction cost economics by expanding the applications of the theory in the field of public governance. In terms of practical significance, the insights gained from this study will assist SOFEs in better handling the relationship between their economic and social responsibilities, promote the improvement of the governance architecture in forestry communities, and reduce the political and social dependence of forestry communities and local governments on SOFEs. This will foster a conducive environment for co-governance between governments and SOFEs, facilitating the deep transformation of SOFEs and achieving their high-quality economic performance.

This paper is divided into six sections. Following this introduction, the Section 2 provides an overview of the institutional background of SOFEs participating in community governance in SOFRs in Northeast China and a literature review on governance fragmentation and transaction cost economics, based on which the research hypotheses are formulated. The Section 3 outlines the data sources, research methods, and selection of model variables, with a particular focus on the measurement of governance fragmentation. The Section 4 presents the regression results. The Section 5 and Section 6, respectively, discuss and summarize the findings.

2. Institutional Background and Research Hypotheses

2.1. Institutional Background of SOFEs Participating in Community Governance

Referring to forestry reform in China, many scholars have studied the marketization reform in China’s collective forest regions and related forestry sectoral policies and organizational forms [25,26]. However, there is less attention from policymakers and researchers on the reforms affecting China’s state-owned forests (SOFs) in the commercially significant Northeast, and their changes are both distinct and more recent when compared with the collective forests [27]. The area of SOFs accounts for 40% of the total forest area in China [28] and represents the most primitive and essential parts of China’s natural forest resources. In the 1950s and 1960s, China established a large number of SOFEs as developers of SOFs. In terms of the organizational management system of SOFs, this was divided into provincial-level forest industry groups (intermediate management institutions between the national government and SOFEs), local-level SOFEs, and smaller forest farms (the smallest units of SOF management). SOFEs, along with the forest farms and forestry communities they manage, constitute the SOFRs in Northeast China.

Since 1949, the SOFRs in Northeast China have cumulatively produced over 1.23 billion m³ of timber, making significant contributions to China’s economic construction and industrial production. Economically, these SOFEs were taken as “workshops” of the “national factory”, performing production tasks set by central planners [12]. At the same time, they provided ample employment opportunities for workers and their family members. In the realm of social life, SOFEs played the role of working units (danwei) providing comprehensive social welfare to their workers [29], such as housing, hospitals, education, etc., establishing a strong dependency relationship between individuals and their working units. So, politically, SOFEs were also key intermediary organizations and sites by which society is governed by the state and wielded significant social, economic, and political power in communities reliant on forestry, as the main governing bodies in forest regions [12].

Since the market-oriented reform of China’s economic system in 1979, the structural adjustment of state-owned enterprises aimed at transforming into modern corporations, thereby inevitably transferring their management functions in the regional social and political fields to local governments. However, SOFEs, most of which were established in remote mountains, often served as the only capable service providers in the region [29]. So, it was extremely difficult for SOFEs to divest their political and social functions to local governments. Nevertheless, this was also the task that SOFEs needed to gradually accomplish after the cessation of commercial logging of natural forests in SOFRs in Northeast China in 2014, which led to a loss of timber sales revenue. In this process, the community faced challenges such as unemployment and welfare decline [30], while collective interests became increasingly complex and fragmented, further raising governance difficulties in forestry communities. At the same time, SOFEs and local governments also face severed governance concepts, uncoordinated governance rules, blurred boundaries of management rights and responsibilities, unmatched management scope and capabilities, as well as inefficient information and data communication, leading to increased vulnerability and fragmentation during the co-governance of forestry communities. The current policy funding of NFPP covers employee and resident relocation, housing construction, and social safety net support [28], reflecting that the maintenance of social stability in forestry communities has remained one of the core goals of SOFEs. The integration of historically shaped political characteristics with the marketization goals of enterprises is often a unique feature of Chinese forestry cases. This complexity adds to the interest and challenges of conducting research in Chinese forest regions.

2.2. Governance Fragmentation of Forestry Communities and Economic Performance of SOFEs

The fragmentation issue of the international forest governance institutional system, characterized by the lack of coherence and coordination among various elements of the constantly expanding and proliferating international forest regime complex, has garnered significant attention from scholars [31]. However, further discussion is needed to delve into details at the regional level. In forestry communities, there is a significant overlap and coverage between the forest resource system and the socio-economic system, expanding the governance responsibilities of SOFEs and local governments beyond the realm of forest management.

Biermann et al. [32] focused on the overarching system of organizations, regimes, and other forms of principles, norms, decision-making procedures, regulations, and institutions in a given political issue area, calling it “governance architecture”, and proposed an explanatory framework for governance fragmentation. This framework has been widely applied in the field of Earth system governance, such as global climate governance [33], global environmental governance [34], as well as fragmentation issues in specific governance areas, such as forest governance [35], ocean governance [36], and energy security governance [37]. The “governance fragmentation of forestry communities” mentioned in this study is based on this concept of governance architecture, referring to the regional fragmented governance situation between SOFEs and local governments in forest governance and social governance areas in forestry communities, due to uncoordinated management norms, principles, concepts, institutions, and systems. Zürn and Faude [38] argue that fragmentation is not necessarily destructive, but rather a process of institutional or functional differentiation, which is an important feature of all modernity but inevitably poses challenges to governance. The crucial issue lies not in fragmentation per se, but in the lack of coordination between fragmented or differentiated institutions and governance entities, leading to a decline in the quality of institutions and resulting in additional consequences, such as actors exploiting fragmented institutions to pursue their narrow interests [32]. In terms of local sustainability, the decline in institutional quality will marginalize residents, affecting their livelihoods [18]. From the perspective of regional governance, a poor-quality institution system may also make it more difficult to achieve collaborative efforts to address economic and social challenges crossing organizational and geographical boundaries [39]. Additionally, the regional partnerships formed by multiple entities in the process of local public service will lack the funding and formal authority needed to counteract the strong centrifugal forces fostered by existing professional and departmental “silos”, leading to disunited public service and wastage of time [39]. The decline in institutional quality will also generate additional legitimacy issues [40].

In the field of new institutional economics, whether it be economic institutions, political institutions, or just governance levels, there is a wealth of theoretical and empirical research on the impact of institutions on economic performance [41,42]. Existing studies widely argue that a better quality institutional and governance system usually has a positive impact on economic performance, because higher quality institutions will facilitate more efficient utilization and allocation of resources [24] and help optimize collective and individual economic decisions [42], thereby enhancing the economic output of economic entities. Sound institutions can also promote economic performance by reducing resource wastage and market inefficiencies like rent-seeking behaviors through the adoption of advanced technologies and management measures [24]. Based on extensive discussions in the literature, it can be inferred that the fragmented governance architecture of forestry communities implies a decline in the quality of regional institutions, which in turn will constrain the economic performance of SOFEs. Hence, the first research hypothesis is proposed from the perspective of the direct effect of the governance architecture:

Hypothesis 1:

The governance fragmentation of forestry communities has a negative impact on the economic performance of SOFEs.

2.3. Governance Fragmentation of Forestry Communities, Transaction Costs, and Economic Performance of SOFEs

Coase [43,44], Alchian and Demsetz [45], North [46], Williamson [47], and many other scholars introduced institutional elements into the production function, proposing a novel perspective on the determination of economic performance by institutions, and forming the important New Institutional Economics school in the history of economics. The origins, causes, and consequences of transaction costs have long been one of the key concerns of new institutional economists [47]. In market trading, Coase [43] first proposed the existence of transaction costs, defining them as “the costs of using the price mechanism, including the costs of discovering relevant prices as well as the costs of negotiation and contracting”, to illustrate that markets were not as frictionless as assumed in classical economics. Subsequently, Williamson [47] identified uncertainty, frequency of exchange, and the degree to which investments are transaction-specific as the principal dimensions for describing transactions, and advocated that effective organizational forms of economic activities should align transaction attributes with governance mechanisms to reduce transaction costs. In the current wide-ranging academic research, there is still no unified consensus on the definition and classification of transaction costs [48], which vary depending on the specific research content. Due to the difficulty in operationalizing and quantifying the concept, there are few direct empirical estimates of transaction costs [49], but this situation is gradually improving with a deeper understanding of the concept of transaction costs.

In this study, if the “governance”—including social management, forest governance, and public services—provided by SOFEs and local governments is regarded as a “good”, then the costs required to achieve the exchange of this “good” can be seen as transaction costs. Local governments hold administrative powers and occupy a proactive position in the production and exchange of this kind of “good”, while SOFEs are in a subordinate position, having to cooperate and fulfill obligations. Therefore, the transaction costs focused on in this study mainly refer to all of the time, energy, and money that SOFEs expend to achieve co-governance with local governments in forestry communities. These costs include information searching costs, negotiation and communication costs, transportation costs, organizing and supervision costs, and opportunity costs.

To prevent ambiguity, there are four aspects that need to be further clarified.

Firstly, the production and exchange of this “good” are non-market, relying instead on relevant institutional arrangements for regional governance, as a kind of public good. Compared to contracts in the business domain, these institutional arrangements regulate who will be the producer (who can participate in governance) and how to trade (how to achieve co-governance).

Secondly, in the process of reaching the exchange of this “good”, both SOFEs and local governments have a limited ability to absorb information and make decisions and are, therefore, in a state of bounded rationality.

Thirdly, SOFEs have accumulated a wealth of local knowledge, collective authority, and local trust in the long-term management of forestry communities, which are difficult to transfer through institutional adjustments. Therefore, they can be viewed as a resource with high asset specificity that the SOFEs owned in the “production” process, leading to the high structural dependence of local governments during co-governance.

Fourthly, the relevant financial support for local governments to manage forestry communities has not arrived promptly after the reform. Facing limited resources and vague management responsibilities, local governments have an opportunistic tendency in the process of reaching the exchange of this “good”, preferring to take a free ride rather than exert their own efforts. As Ostrom [50] pointed out, “Whenever one person cannot be excluded from the benefits that others provide, each person is motivated not to contribute to the joint effort, but to free-ride on the efforts of others”.

There is an increasing body of literature indicating the effectiveness of local-level institutional arrangements in managing common resources in developing countries [22]. However, under the fragmented governance architecture in forestry communities, the bounded rationality of governance entities, the structural dependence of local governments on SOFEs, and free-riding behavior have led to an increase in information costs and communication costs for SOFEs in dealing with governments. The fragmented governance architecture may also lead to insufficient incentives, a decline in cooperation cohesion, and excessive monitoring costs and principal-agent costs due to speculative behavior or to prevent speculative behavior, resulting in serious resource waste and reducing economic efficiency [51]. The cost savings from the marketization of public services achieved by SOFEs participating in the co-governance of communities are often offset by transaction costs involved in contract specification, tendering, monitoring, and compliance processes [39]. Therefore, despite the support of national finances, the high transaction costs faced by SOFEs participating in co-governance will still dissipate their work energy, consume reform dividends, lead to a reduction in resources tilted towards production, and thereby affect the economic output of SOFEs. At the same time, this will also weaken the trust between SOFEs and local governments, increase cooperation uncertainty, and hinder the construction of a favorable investment environment.

Based on the above literature analysis, a theoretical framework can be constructed as shown in Figure 1, and the second research hypothesis is proposed from the perspective of the mediating effect of transaction costs:

Hypothesis 2:

The governance fragmentation of forestry communities results in high transaction costs for SOFEs participating in co-governance activities, and thereby has a negative impact on the economic performance of SOFEs.

3. Methodology

3.1. Variables

3.1.1. Dependent Variable

Ameer and Othman [52] measure the economic performance of enterprises from the perspective of shareholders using indicators such as return on assets, gross profit, and cash flow. However, for Chinese SOFEs, which are not fully market-oriented state-owned enterprises, they often have a strong reliance on the national budget, and corporate profits cannot accurately reflect their efficiency and performance. The public welfare nature of SOFEs also means that they often do not focus on returns and do not need to weigh costs and benefits as highly as other market-oriented enterprises. Therefore, this study focuses more on the output value to reflect their economic performance over a period of time. Referencing Wang et al. [53], this study chooses the total output value of the forestry industry of SOFEs as the indicator. In the “China Forestry Statistical Yearbook” (renamed as “China Forestry and Grassland Statistical Yearbook” after 2018), the total output value of the forestry industry of SOFEs is a measure of the total value formed by the activities of the primary, secondary, and tertiary industries of forestry, which can reflect changes in SOFE economic performance, as these enterprises mainly focus on the development and utilization of resources related to forests.

3.1.2. Independent Variable

Zelli [15] pointed out the need to establish a set of standards for assessing and comparing the degree and impact of fragmentation in governance architectures. Currently, many studies measure the level of governance fragmentation through structural analysis of governance networks [54] or through institutional text analysis [55]. This study combines the two approaches, investigating both the specific content of forestry community governance and the structured distribution of governance issues among governance entities.

Field research in SOFRs in Northeast China revealed that the collaborative governance mechanisms, including cost sharing and coordination of rights and responsibilities between SOFEs and local governments, have not been properly established. The gradual process of transferring working responsibilities and items to local governments related to operating social functions can be seen as the dismantling of holistic governance with SOFEs as the main body. The governance affairs of forestry communities are gradually dispersed into two main entities of SOFEs and local governments. Consequently, the questionnaire includes an annual table that collects the transfer times of 16 social functions (the social functions undertaken by different SOFEs in forestry communities are initially different and the 16 items presented in the questionnaire are a collection of the main functions undertaken by SOFEs via self-report; the final collected and statistically analyzed data on these items varies depending on the specific SOFE), such as forestry police, procuratorates, courts, education, hospitals, fire-fighting teams, elderly care, residential property management, urban construction, heating supply, water supply, electricity supply, street cleaning, social insurance agencies, community management, and street offices, to SOFEs. Meanwhile, the questionnaire also includes a scale to measure the degree of transfer of functions. For each category of functions, 10 options are designed, including “signed agreement, administrative power transferred, institutional framework transferred, personnel transferred, assets transferred, archives transferred, government responsible for the work, government funding, SOFE responsible for the work, SOFE funding”. These options aim to reflect the extent of function transfer and the actual party responsible for governance. By combining the annual table with the degree of transfer of functions, the transfer degree $A_{it}$ of governance matters of SOFEs to local governments each year can be obtained. Furthermore, the retention degree $B_{it}$ of governance matters still undertaken by SOFEs can be obtained, where $A_{it}+B_{it}=1$. Based on this, the absolute value of the difference between $A_{it}$ and $B_{it}$ can be obtained as ${Gov\_dalet}_{it}$, as shown in Formula (1):

$${Gov\_dalet}_{it}=\left|A_{it}-B_{it}\right|$$

(1)

The larger the value of ${Gov\_dalet}_{it}$, the more centralized the governance matters are towards one party, either SOFEs or local government, implying a higher degree of involvement in governance by one party and correspondingly less involvement by the other (since ${Gov\_dalet}_{it}$ is the absolute value of the calculated difference, there is no further distinction as to which party is more involved in governance, which is not related to the degree of governance fragmentation that this study aims to measure), and indicating a lower degree of governance fragmentation in forestry communities. Meanwhile, the smaller the value of ${Gov\_dalet}_{it}$, the more dispersed the governance matters are among the entities, with both SOFEs and local governments participating in forestry community governance. Cases where the cooperative mechanisms are not well established, indicate a higher level of governance fragmentation in forestry communities. Therefore, ${Gov\_dalet}_{it}$ is a negative indicator of the level of governance fragmentation in forestry communities. By reverse transformation, the measurement indicator for governance fragmentation ${Gov\_frag}_{it}$ can be obtained, as shown in Formula (2):

$${Gov\_frag}_{it}=\left({Gov\_dalet}_{max}-{Gov\_dalet}_{it}\right)∕\left({Gov\_dalet}_{max}-{Gov\_dalet}_{min}\right)$$

(2)

where ${Gov\_dalet}_{max}$ and ${Gov\_dalet}_{min}$ represent the maximum and minimum values of ${Gov\_dalet}_{it}$, respectively.

3.1.3. Mediating Variable

Adhikari and Lovett [22] measured the transaction costs of household involvement in forest management by using the average time spent by each family on various community forestry activities. Similarly, Chen et al. [56] measured government efficiency in terms of local government quality by the “average number of days per year that enterprises interact with the government”, where a higher value indicated higher transaction costs for enterprises.

Before the reform, forestry communities were relatively closed and independent, with less interaction with local authorities. During the reform process, however, the once closed forestry communities gradually opened up, leading to increased interaction between SOFEs and local governments. Many of these interactions revolved around advancing the stripping of governmental and social functions and forestry community governance. Therefore, in measuring transaction costs, this study focuses on the time costs that SOFEs need to bear to achieve community co-governance with local governments. Drawing from existing research, the questionnaire measures the time costs SOFEs spend through the “average number of days of interaction between SOFEs and local governments (monthly in the current year)”. A higher value of this indicator represents higher transaction costs spent by SOFEs.

3.1.4. Control Variables

Liao and Gao [57] divided the influencing factors of economic performance in resource-based industries into fundamental factors and indirect effect factors. The former includes productive factors such as capital investment, labor utilization, and natural resource development, while the latter includes factors such as technological progress, optimization and upgrading of industrial structure, industrial agglomeration, market competition, and government environmental regulation. Therefore, this study, in conjunction with the actual situation of SOFRs in Northeast China, selects capital investment from NFPP, technology investment, labor input, enterprise industrial structure, forest management circumstances, forest resource endowment, regional economic development, and total population of forestry communities as control variables to study the impact of governance fragmentation of forestry communities on the economic performance of SOFEs.

SOFEs participate in forest governance and social governance in forestry communities and engage in close interaction with local governments in seeking capital investment and other resources. Benham and Benham [49] pointed out that the influencing factors of transaction costs include negotiation skills, local knowledge, personal networks (social capital in relationship governance), and political relations. In addition, based on field observations, the transaction costs borne by SOFEs in participating in co-governance under fragmented governance architectures are closely related to the content and form of governance, the special geographic distribution of forestry communities, the scale of forestry population, and the development of social services. Therefore, in the model verifying the impact of governance fragmentation of forestry communities on the transaction costs borne by SOFEs, the selected control variables include the capital investment from NFPP, the regional economic development level, the regional population density, the total population of forestry communities, the development level of the regional service industry, and SOFEs’ forest resource endowment.

3.2. Data

The primary data used in this study mainly come from a questionnaire survey conducted on the SOFEs located in SOFRs in Northeast China in 2023 and 2024, including two big forest industry groups at the provincial level; these being, Jilin Changbai Mountain Forest Industry Group Co., Ltd., Yanji, China (hereinafter abbreviated as “JLCB Co., Ltd.”, managing 18 SOFEs in Jilin Province (Antu Forest Management Office is excluded due to its different nature from other enterprises in history)) and Longjiang Forest Industry Group Co., Ltd., Harbin, China (hereinafter abbreviated as “LJ Co., Ltd.”, managing 23 SOFEs, most of which are located in Heilongjiang Province and a small portion in Jilin Province). Questionnaires were distributed to all 41 SOFEs managed under the two forest industry groups, covering their activities in promoting the transfer of governmental functions and social functions, and interactions between government and enterprises from 2015 to 2022, since the reform of SOFRs began. In subsequent data processing, additional telephone follow-ups and content confirmation were conducted for where responses were ambiguous. In the end, 39 questionnaires were collected from SOFEs, with an effective sample size of 312 after interpolating for a small number of missing values. This study has also conducted field research on typical SOFEs since 2022, and enterprise discussions and semi-structured interviews with representatives were conducted on topics such as the degree and bottlenecks of enterprise transformation, the current situation, and difficulties in forestry community governance. These efforts have contributed 13 classic cases to enrich the relevant study.

Due to time and resource constraints, conducting a comprehensive questionnaire survey of all SOFEs in SOFRs in Northeast China and obtaining research data is currently unfeasible. Therefore, samples from two forest industry groups, JLCB Co., Ltd. and LJ Co., Ltd., were selected. Since the original development background, construction history, and social operating mechanism of forestry communities are generally similar across SOFRs in Northeast China, and the direction of enterprise reform and industrial development is also roughly the same after the reform, the two selected forest industry groups meet the requirements of representativeness and typicality for the study. On the other hand, for the starting timing point and process of separating government functions and social functions and transferring them to local governments, there is a significant difference for the forest industry groups, resulting in a variation in the degree of governance fragmentation of forestry communities at the current stage and increasing the variability of independent variables in the sample. Consequently, studying the data of the two forest industry groups together not only expands the sample size but also avoids many irrelevant factors and highlights the effects of institutional change.

In addition to the data collected through questionnaire surveys, this study also utilizes data from the “China Forestry Statistical Yearbook” (renamed to the “China Forestry and Grassland Statistical Yearbook” after 2018) covering the years 2015 to 2022, as well as the “China County Statistical Yearbook”. Furthermore, information on the reform progress of SOFEs is also referenced from their self-reported assessments to the National Forestry and Grassland Administration in 2019, 2020, and 2021. The meanings and basic characteristics of relevant variables are shown in

Table 1. The definitions of variables and their basic characteristics (N = 312).

Category	Symbol	Variable and Meaning	Unit	Mean	Std. Dev.
Dependent variable	Eco_perform	The total output values of the forestry industry of SOFEs	104 CNY	91,003.763	54,185.695
Independent variable	Gov_frag	The degree of governance fragmentation of forestry communities	no unit	0.595	0.281
Mediating Variable	Tran_cost	Average number of days of interaction between SOFEs and local governments (monthly in the current year)	day/month	8.067	6.312
Control Variables	NFPP_invest	Capital investment from the NFPP for SOFEs	104 CNY	19,247.481	5859.140
	Tec_invest	Technology investment (annual forestry technology investment of SOFEs)	104 CNY	8.940	52.021
	Employees	Labor input (annual number of employees on duty of SOFEs)	people	3177.083	1255.627
	Structure	Industrial structure of SOFEs (tertiary industry output value of SOFE/total forestry industry output value of SOFEs)	no unit	0.407	0.197
	Per_maintain	Forest management situation (per capita managed forest area of SOFEs)	ha/person	430.169	242.171
	Forestland	Forest resource endowment (area of forest land of SOFEs)	ha	219,346.552	106,318.124
	PerGDP local	Regional economic development (per capita GDP of the region)	CNY/person	39,946.869	13,983.131
	Areapopulation	Total population of forestry communities	people	34,666.143	60,202.298
	Popu_density	Regional population density (total regional population/total administrative area)	people/sq	104.906	318.105
	Tertiaryindustry	Development of the regional service industry (local tertiary industry output value/total local industry output value)	no unit	0.456	0.128

(N = 312).

3.3. Methods

The empirical model of this study is based on panel data from 2015 to 2022 to examine the direction and magnitude of the impact of the governance fragmentation of forestry communities on the economic performance of SOFEs. Considering the unobserved heterogeneity, this study employs a fixed-effects model with fixed effects for time, enterprise, and Co., Ltd. dimensions to mitigate the bias caused by omitted control variables. The econometric regression model is set as follows:

$${Eco\_perform}_{it}={\alpha }_0+{\alpha }_1{Gov\_frag}_{it}+{\alpha }_2{Z}_{it}+{\delta }_i+{\mu }_t+\xi +{\epsilon }_{it}$$

(3)

In Equation (3), ${Eco\_perform}_{it}$ represents the total output values of the forestry industry of SOFE i at time t; ${Gov\_frag}_{it}$ represents the degree of governance fragmentation at time t in the forestry community which was originally managed by SOFE i; and $Z_{it}$ is the control variable vector. ${\alpha }_0$ is the intercept term; ${\delta }_i$ represents the individual fixed effect of SOFE i that does not change over time and its impact on economic performance; ${\mu }_t$ represents the year fixed effect, controlling for the effects of time trends; $\xi$ represents the Co., Ltd. fixed effect at the group level to which SOFE i belongs. ${\epsilon }_{it}$ is a random disturbance term. To eliminate the significant differences in the dimensionality of the variables, this study has taken the logarithm of the core variables. The processed regression model is as follows:

$$ln{Eco\_perform}_{it}={\beta }_0+{\beta }_1{Gov\_frag}_{it}+{\beta }_{2}ln{Z}_{it}+{\delta }_i+{\mu }_t+\xi +{\epsilon }_{it}$$

(4)

In Equation (4), the coefficient ${\beta }_1$ is the core estimation parameter to identify the net effect of the governance fragmentation of forestry communities on the economic performance of SOFEs. Other variables are consistent with Equation (3).

In addition to the direct effects, this study will also examine whether the transaction costs incurred by SOFE i in participating in co-governance at time t (${Tran\_cost}_{it}$) is the mediating variable based on the previous analysis, in order to explore the potential mechanisms through which the governance fragmentation of forestry communities may affect the economic performance of SOFEs. Based on the significance testing of the coefficient ${\beta }_1$ of ${Gov\_frag}_{it}$ in regression model (4), the linear regression model is constructed for the effect of the governance fragmentation of forestry communities (${Gov\_frag}_{it})$ on the mediating variable ${Tran\_cost}_{it}$, as well as the regression model for the impact of governance fragmentation (${Gov\_frag}_{it}$) and the mediating variable (${Tran\_cost}_{it}$) on the economic performance of SOFEs. The existence of the mediating effect can be examined by the significance of the regression coefficients ${\gamma }_1, {\beta }_1^{\prime }, {\beta }_2^{\prime }$. The regression models take the following form:

$${Tran\_cost}_{it}={\gamma }_0+{\gamma }_1{Gov\_frag}_{it}+{\gamma }_2{Z}_{it}^{\prime }+{\delta }_i+{\mu }_t+\xi +{\epsilon }_{it}$$

(5)

$$ln{Eco\_perform}_{it}={\beta }_0^{\prime }+{\beta }_1^{\prime }{Gov\_frag}_{it}+{\beta }_2^{\prime }{Tran\_cost}_{it}+{\beta }_3^{\prime }ln{Z}_{it}+{\delta }_i+{\mu }_t+\xi +{\epsilon }_{it}$$

(6)

In Equation (5), $Z_{it}^{\prime }$ represents the control variable vector of the impact of governance fragmentation of forestry communities on transaction costs incurred by SOFEs. Other variables are consistent with Equation (3).

4. Results

4.1. Descriptive Statistics

JLCB Co., Ltd. gradually transferred related matters such as forestry police, procuratorates, courts, education, heating supply, water supply, and electricity supply for forestry communities to local governments starting from 2005. By 2020, most SOFEs had completely stripped government functions and social functions except for hospitals and fire-fighting teams, and forestry community governance was basically centered on local governments, with SOFEs not needing to participate in many tasks. However, LJ Co., Ltd. managed the region with the greatest difficulty in the reform of separating government and social functions from SOFE management in SOFRs, with the largest number of employees and operating the biggest volume of social functions among all forest industry groups before the reform. It was not until 2015, when the reform of SOFRs was initiated, that the stripping began to slowly progress, so this is why the starting point for our questionnaire data collection is set as 2015. As for now, due to the limited financial resources of local governments, the actual work of many social functions is still undertaken by SOFEs, apart from the transfer of forestry police, procuratorates, courts, education, and electricity supply for forestry communities, although nominally local governments are the governing subjects and have taken away all administrative powers.

During the period of 2015–2022, the average total output values of the forestry industry of SOFEs of LJ Co., Ltd. exhibited an initial increase followed by a decline, as shown in Figure 2. The year 2018 marked a clear turning point, showing significant fluctuations in the output values of SOFEs during the reform and adjustment period. The SOFEs of JLCB Co., Ltd. showed relatively stable average total forestry industry output values, with a slight decrease in 2018. Overall, LJ Co., Ltd. had a much larger business scale compared to JLCB Co., Ltd., but by 2022, the average output value of JLCB Co., Ltd.’s enterprises had surpassed LJ Co., Ltd. Liu et al. [58] summarized the characteristics of economic development of SOFEs in the province of Inner Mongolia as significant differences in average annual growth rate, large fluctuations, and strong economic vulnerability. These characteristics are also observed in the selected regions in this study.

Due to JLCB Co., Ltd. starting the separation of government functions and social functions from enterprise management relatively early, the average monthly interaction days between SOFEs and local governments in the baseline year of 2015 were higher compared to LJ Co., Ltd. However, when LJ Co., Ltd. gradually transferred public institutions such as forestry police, procuratorates, courts, and education to local government management from 2018 onwards, the average monthly interaction days between SOFEs and local governments significantly increased, indicating the official beginning of forestry community co-governance. In 2019, JLCB Co., Ltd. and LJ Co., Ltd. had similar average monthly interaction days between SOFEs and local governments, but in the following three years, LJ Co., Ltd. surpassed JLCB Co., Ltd.

Figure 3 reveals the annual average level of governance fragmentation in forestry communities previously managed by SOFEs of these two forest industry groups. Theoretically, the level of governance fragmentation should follow an inverted U-shaped curve with its opening facing downwards throughout the entire reform period. The inverted U-shaped curve indicates the transition of governance functions and responsibilities from SOFEs to local governments and an ideal state where governments, not SOFEs, bear all the relevant community governance responsibilities and work after the complete and final separation of government and social functions from SOFEs. During this process, the level of governance fragmentation shows an initial upward trend followed by a decline. It can be observed that the governance fragmentation level of the communities under LJ Co., Ltd.’s SOFEs shows an upward trend each year, with a noticeable increase after 2018. This indicates that as administrative and social functions are transferred to the government, the actual participants in relevant management and service activities gradually involve both the enterprises and local governments, leading to an increase in the level of fragmentation. In 2020, LJ Co., Ltd. finished the transfer of 2151 administrative powers of forestry community governance from the SOFEs to local governments, and passed the national acceptance that year, marking a turning point reflecting the transfer of governance leadership. There was also a significant decrease in the average governance fragmentation level in 2019 for JLCB Co., Ltd., possibly due to significant progress in the functional transfer work completed in that year before the reform acceptance in 2020. The trend line of JLCB Co., Ltd. in Figure 3 shows a distinctly different pattern compared to the trend line of LJ Co., Ltd. because LJ Co., Ltd. was in the early stage of functional transfer and did not reach the inflection point until 2020, while JLCB Co., Ltd. reached the inflection point since 2016 and entered the later stage of substantive work transfer, with the local governments taking the dominant governance position. This can further explain why, in the later stage of the average monthly interaction, the number of days of interaction between SOFEs and local governments for LJ Co., Ltd. exceed those of JLCB Co., Ltd. in Figure 2.

4.2. Baseline Regressions

In order to avoid the interference of outliers on the research results, a two-tailed winsorization at the 2.5% quantile is applied to the sample data of each variable.

Table 2. Baseline regression results of the impact of governance fragmentation of forestry communities on the economic performance of SOFEs.

	(1)	(2)	(3)	(4)	(5)
	lnEco_perform	lnEco_perform	lnEco_perform	lnEco_perform	lnEco_perform
Gov_frag	−0.529 ***	−0.323 ***	−0.233 **	−0.494 ***	−0.494 ***
	(0.111)	(0.092)	(0.094)	(0.117)	(0.117)
lnNFPP_invest		0.199 *	0.546 ***	0.480 ***	0.480 ***
		(0.107)	(0.152)	(0.151)	(0.151)
lnTec_invest		−0.008	0.002	0.008	0.008
		(0.005)	(0.013)	(0.010)	(0.010)
lnEmployees		0.639 ***	0.888 ***	0.724 ***	0.724 ***
		(0.089)	(0.146)	(0.172)	(0.172)
lnStructure		−0.069	−0.059	0.022	0.022
		(0.062)	(0.096)	(0.077)	(0.077)
lnPer_maintain		0.247 ***	0.121	0.214	0.214
		(0.064)	(0.200)	(0.138)	(0.138)
lnForestland		0.043	−5.912	−5.507 *	−5.507 *
		(0.087)	(3.723)	(2.946)	(2.946)
lnPerGDP local		0.080	−0.146	0.505 ***	0.505 ***
		(0.085)	(0.140)	(0.151)	(0.151)
lnAreapopulation		0.016	0.045	0.062	0.062
		(0.044)	(0.079)	(0.108)	(0.108)
_cons	11.554 ***	1.241	71.366	61.099 *	61.099 *
	(0.067)	(1.348)	(45.461)	(35.775)	(35.775)
Enterprise FE	Y	N	Y	Y	Y
Year FE	Y	N	N	Y	Y
Co., Ltd. FE	Y	N	N	N	Y
N	312	312	312	312	312
adj. R2	0.622	0.404	0.538	0.665	0.665

Note: ***, **, and * are significant at the 1%, 5%, and 10% statistical levels, with standard errors in parentheses.

reports the regression results of models without controlled variables (column 1), without controlling for fixed effects (column 2), and with stepwise control of enterprise, year, and Co., Ltd. fixed effects (columns 3–5). The study finds that regardless of the model specification, the estimated parameter of the core explanatory variable Gov_frag is significant. Additionally, the Hausman test result for the random effects model and the fixed-effects model yield Prob > chi² = 0.0000, rejecting the null hypothesis. Therefore, in the subsequent analysis, we will rely on the regression results based on the fixed-effects model.

From the regression results in column (5), with other control variables included, it can be observed that the estimated coefficient of the core explanatory variable Gov_frag is significantly negative at the 1% level. This indicates that, holding other conditions constant, an increase in the level of governance fragmentation of forestry communities leads to a decline in the total output value of the forestry industry of SOFEs, which confirms the validity of Hypothesis 1 and shows that the governance fragmentation of forestry communities has overall decreased the economic performance of SOFEs. There is a significant positive correlation between the capital investment from the NFPP for SOFEs (lnNFPP_invest) and SOFEs’ economic performance at the 1% level, demonstrating the important support role of national investment in the economic output of SOFEs during forestry reform. At the same time, labor input (lnEmployees) is significantly positive at the 1% level, showing that the increase in labor input significantly promotes SOFEs’ economic performance with other conditions unchanged, and the reform of SOFEs has not changed the labor-intensive nature of their forestry industry. This is consistent with the research findings of Liu [59] that labor and capital, as representative productive factors, are the main factors affecting the forestry economic performance in the state-owned forest regions of China. Ning et al. [60] previously estimated the total factor productivity (TFP) of SOFEs in SOFRs in Northeast China, and found that the growth of TFP was mainly attributed to technological progress. However, in this study, the coefficient of technology investment (lnTec_invest) is positive but not significant, indicating that forestry technology investment does not significantly promote SOFEs’ economic performance. The reasons can be attributed to two aspects: one is the time lag effect of technology investment, which requires a long time to be absorbed and transformed into actual production, and the other is that most SOFEs often use national subsidies for forest management and worker livelihood instead of investing in technology and industry [61]. Therefore, the threshold for technology investment to have an effective impact on economic performance has not yet been reached, as evidenced by the existence of a minimum threshold of R&D investment level that positively affects enterprise economic performance in Wang’s [62] research. Moreover, through on-site investigations, it has also found that many SOFEs lack subsequent financial support for the maintenance and updating of related technologies and equipment after making a substantial one-time technological investment, which also limits the effectiveness of technology investment. Surprisingly, the forest resource endowment (lnForestland) of SOFEs has a negative impact on the economic performance of SOFEs, and passes the significance test at the 10% level. The reason may be that SOFEs, after the SOFR reform, have transformed into protectors of forest resources rather than good users, causing the forests to be “dormant” and hard to effectively convert into valuable assets. So, as the area of forest land increases, the need for management and protection also improves, which to some extent adds more pressure on the development of SOFEs. Finally, it should be noted that a significant positive driving effect of regional economic development (lnPerGDP_local) on the economic performance of SOFEs, because regional economic development is more diverse and stable compared to state-owned forest regions [14]. Thus, the integration of forestry industry chains with the development of other local regions is a key issue that SOFEs need to explore in the future.

The preceding text has theoretically analyzed the mediating mechanism of governance fragmentation of forestry communities on the economic performance of SOFEs from the perspective of transaction costs. In this part, this study uses a mediating effect model for empirical testing to verify this mechanism, and the regression results are shown in

Table 3. The transaction cost mechanism of the impact of governance fragmentation of forestry communities on the economic performance of SOFEs.

	(1)	(2)	(3)	(4)
	Tran_cost	Tran_cost	lnEco_perform	lnEco_perform
Gov_frag	4.661 ***	4.095 ***	−0.404 ***	−0.421 ***
	(0.479)	(0.540)	(0.122)	(0.124)
Tran_cost			−0.027 ***	−0.017 **
			(0.009)	(0.008)
lnNFPP_invest		−3.316 ***		0.415 ***
		(1.182)		(0.154)
lnTec_invest				0.007
				(0.010)
lnEmployees				0.702 ***
				(0.170)
lnStructure				0.014
				(0.074)
lnPer_maintain				0.225
				(0.140)
lnForestland		17.363		−5.276 *
		(17.595)		(2.917)
lnPerGDP local		−2.705 **		0.470 ***
		(1.044)		(0.148)
lnAreapopulation		−0.722		0.053
		(0.558)		(0.104)
Popu_density		−0.004
		(0.029)
Tertiaryindustry		−5.154 **
		(2.369)
_cons	5.209 ***	−135.080	11.693 ***	59.563 *
	(0.300)	(222.325)	(0.075)	(35.487)
Enterprise FE	Y	Y	Y	Y
Year FE	Y	Y	Y	Y
Co., Ltd. FE	Y	Y	Y	Y
N	312	312	312	312
adj. R2	0.843	0.850	0.632	0.668

Note: ***, **, and * are significant at the 1%, 5%, and 10% statistical levels, with standard errors in parentheses.

. The results in columns (1) and (2) confirm the significantly positive impact of governance fragmentation of forestry communities (Gov_frag) on transaction costs (Tran_cost) at the 1% significance level. In columns (3) and (4), the mediating variable of transaction costs (Tran_cost), along with other variables, is placed back into the regression model of the impact of governance fragmentation of forestry communities on the economic performance of SOFEs. The results show that the core explanatory variables of governance fragmentation of forestry communities (Gov_frag) and transaction costs (Tran_cost) both have a significantly negative impact. Compared with the results in Table 2, the coefficient of the variable of governance fragmentation of forestry communities (Gov_frag) has decreased, indicating that the transaction costs that SOFEs need to pay to participate in co-governance are the mediating mechanism for the negative impact of governance fragmentation of forestry communities on the economic performance of SOFEs, thus verifying Hypothesis 2. The regression results in column (2) of Table 3 further indicate that the more funds SOFEs receive from the NFPP (lnNFPP_invest), the lower the transaction costs involved in interacting with local governments, possibly because SOFEs with more investment from NFPP have more sufficient funds to participate in community governance and avoid too much communication and negotiation with local governments on governance funding sources. On the other hand, the better local economic development (lnPerGDP_local), correspondingly the higher fiscal revenue of local governments, which may reduce the dependence on SOFEs in providing public services in forestry communities, thereby reducing the degree of SOFEs participation in co-governance and the subsequent transaction costs. The results also indicate that the proportion of the local tertiary industry in local total output value (Tertiaryindustry) has a significant negative impact on SOFEs’ transaction costs at the 5% level, possibly because the more developed that the local service industry is, the more beneficial it is for SOFEs to provide public services to forestry communities through market-oriented means, thereby reducing the transaction costs of interaction with local governments.

4.3. Sensitivity Analyses

This study will conduct robustness tests by winsorizing data at a higher percentile and changing the regression method. Further, we will discuss the impact of different economic and social contexts on the research results through subgroup analysis.

4.3.1. Two-Tailed Winsorization at the 5% Quantile

This study further conducts a wider two-tailed winsorization at the 5% quantile of the sample data for each variable to avoid the interference of a wider range outliers on the research conclusions, as shown in

Table 4. Robustness test 1: two-tailed winsorization at the 5% quantile.

	(1)	(2)	(3)	(4)	(5)	(6)
	lnEco_perform	lnEco_perform	Tran_cost	Tran_cost	lnEco_perform	lnEco_perform
Gov_frag	−0.523 ***	−0.469 ***	4.576 ***	3.978 ***	−0.396 ***	−0.396 ***
	(0.110)	(0.116)	(0.466)	(0.526)	(0.120)	(0.124)
Tran_cost					−0.028 ***	−0.017 **
					(0.009)	(0.009)
lnNFPP_invest		0.502 ***		−3.337 ***		0.439 ***
		(0.161)		(1.145)		(0.163)
lnTec_invest		0.010				0.009
		(0.010)				(0.010)
lnEmployees		0.734 ***				0.711 ***
		(0.175)				(0.173)
lnStructure		0.021				0.015
		(0.078)				(0.076)
lnPer_maintain		0.227				0.237
		(0.147)				(0.148)
lnForestland		−6.877 **		18.302		−6.724 **
		(3.022)		(18.432)		(3.022)
lnPerGDP local		0.535 ***		−3.186 ***		0.492 ***
		(0.155)		(1.122)		(0.152)
lnAreapopulation		−0.044		−0.895		−0.057
		(0.114)		(0.781)		(0.108)
Popu_density				0.005
				(0.026)
Tertiaryindustry				−4.807 *
				(2.720)
_cons	11.549 ***	78.241 **	5.147 ***	−140.589	11.692 ***	77.771 **
	(0.066)	(36.956)	(0.294)	(232.518)	(0.074)	(36.987)
Enterprise FE	Y	Y	Y	Y	Y	Y
Year FE	Y	Y	Y	Y	Y	Y
Co., Ltd. FE	Y	Y	Y	Y	Y	Y
N	312	312	312	312	312	312
adj. R2	0.624	0.670	0.838	0.845	0.634	0.673

Note: ***, **, and * are significant at the 1%, 5%, and 10% statistical levels, with standard errors in parentheses.

. The columns (1) and (2) are the robustness tests of the direct effects of the governance fragmentation of forestry communities on the economic performance of SOFEs, while columns (3) to (6) correspond to the robustness tests of the mediation mechanism model studied earlier. The results of the robustness tests show that there were no significant changes in the size, direction, and significance of the coefficients, indicating the baseline regression results are robust and reliable.

4.3.2. Changing the Regression Method

Considering the long-term and dynamic effects of economic performance and the potential endogeneity issues of the model, we use system GMM for regression by introducing lagged dependent variables as instrumental variables and forming dynamic panel data. The consistency of the system GMM estimator depends on two conditions: the disturbance term is not autocorrelated, which can be judged by observing the AR (2) statistic; and the validity of the instrumental variables, which some studies in the literature judge by using the Sargan test [63]. However, the Sargan statistic provided by official commands assumes that the disturbance term is independently and identically distributed, which is too strict and often not in line with reality [64]. Therefore, this study uses an unofficial command “xtabond2” when estimating the system GMM and reports the heteroscedasticity-robust Hansen statistic to judge the validity of the instrumental variables.

Table 5. Robustness test 2: using system GMM regression method.

	(1)	(2)	(3)
	lnEco_perform	Tran_cost	lnEco_perform
L. lnEco_perform	1.036 ***		0.964 ***
	(0.123)		(0.128)
L. Tran_cost		0.756 ***
		(0.074)
Gov_frag	−0.417 ***	2.088 **	−0.221 *
	(0.095)	(0.994)	(0.117)
Tran_cost			−0.028 *
			(0.015)
lnNFPP_invest	0.107	−0.063	0.295 *
	(0.166)	(1.713)	(0.155)
lnTec_invest	0.001		−0.013
	(0.017)		(0.017)
lnEmployees	0.818 ***		0.497 *
	(0.272)		(0.264)
lnStructure	−0.181 ***		−0.168 **
	(0.065)		(0.074)
lnPer_maintain	−0.322 **		−0.214
	(0.130)		(0.130)
lnForestland	−0.103	0.235	−0.026
	(0.220)	(1.014)	(0.174)
lnPerGDP local	−0.265 **	−0.030	−0.252 **
	(0.127)	(0.630)	(0.109)
lnAreapopulation	−0.200	−0.127	−0.220 **
	(0.135)	(0.586)	(0.106)
Popu_density		−0.001
		(0.000)
Tertiaryindustry		1.433
		(2.038)
AR (1)	0.001	0.006	0.001
AR (2)	0.587	0.009	0.529
AR (3)	\	0.404	\
Hansen_overid	0.160	0.178	0.477
N	273	273	273

Note: ***, **, and * are significant at the 1%, 5%, and 10% statistical levels, with standard errors in parentheses. The p-values for the first-, second-, and third-order Arellano–Bond sequential autocorrelation tests (AR (1), AR (2), and AR (3)) are reported. The Hansen overidentification test (Hansen-overid) also reports a p-value.

reports the regression results of the direct and mediation effect using the system GMM method. All the Hansen statistics for overidentification tests are not significant, indicating the effectiveness of the instrumental variables. In columns (1) and (3), the null hypothesis is accepted by observing the AR (2) results, indicating that there is no autocorrelation in the disturbance term, and the model specification and estimation method are reasonable. In column (2), the null hypothesis cannot be accepted because the p-value of AR (2) is 0.009. While the p-value of AR (3) is 0.404, so the null hypothesis is not rejected when the dependent variable is lagged for three periods, and it is reasonable to use the system GMM method for estimation now.

As shown in column (1) in Table 5, after transforming the regression model, the negative impact of governance fragmentation of forestry communities (Gov_frag) on the economic performance of SOFEs is significant at the 1% level. In column (3), it can be further seen that after adding the mediation effect, the negative impact of the governance fragmentation of forestry communities (Gov_frag) on the economic performance of SOFEs still passes the significance test at the 10% level, and that the mediating variable of transaction costs (Tran_cost) also has a significant negative impact on the economic performance of SOFEs at the 10% level, once again proving the robustness and reliability of the baseline models for hypothesis verification. In all the regression results of columns (1), (2), and (3), the regression coefficients of the lagged dependent variables are significantly positive, suggesting the economic performance and transaction costs of SOFEs have dynamic trends over time, which confirms that the setting of the dynamic panel model is also reasonable.

4.3.3. Subgroup Analyses

The sample can be divided into low-output and high-output groups based on the difference between the total output value of the forestry industry of SOFEs and its average value (91,003.76 10⁴ CNY), to consider the impact of the changing economic foundation of SOFEs on the research results. It can also be divided into large-scale and small-scale groups according to the difference between the total operating area of the SOFEs and its average value (252,126.5 ha), to consider the impact of different social contexts on the research results. Additionally, based on whether there was a clear boundary line (such as rivers, railways, bridges, roads, etc.) for the geographical management scope between SOFEs and local governments in history, the SOFE sample can be grouped into borderless and bounded groups, which is also an important distinction based on the characteristics of the social context. The subgroup regression results on the impact of governance fragmentation of forestry communities on the economic performance of SOFEs are shown in

Table 6. Subgroup Analyses.

	(1) By the Total Output Value of the Forestry Industry of SOFEs		(2) By the Total Operating Area of SOFEs		(3) By Geographical Management Boundary in History
	Low-Output SOFEs	High-Output SOFEs	Small-Scale SOFEs	Large-Scale SOFEs	Bounded SOFEs	Borderless SOFEs
Variables	lnEco_perform	lnEco_perform	lnEco_perform	lnEco_perform	lnEco_perform	lnEco_perform
Gov_frag	−0.437 ***	0.172	−0.391 ***	−0.830 ***	−0.543 ***	−0.200
	(0.132)	(0.121)	(0.134)	(0.196)	(0.154)	(0.227)
lnNFPP_invest	−0.300	0.205 *	0.768 ***	0.123	0.348 **	0.515
	(0.221)	(0.109)	(0.237)	(0.222)	(0.176)	(0.475)
lnTec_invest	0.017 *	−0.010	0.019	−0.000	0.014	0.006
	(0.009)	(0.009)	(0.012)	(0.018)	(0.014)	(0.015)
lnEmployees	0.250	0.144	0.760 ***	0.692 **	0.720 ***	0.615
	(0.217)	(0.112)	(0.204)	(0.269)	(0.184)	(0.425)
lnStructure	−0.028	0.027	0.083	−0.135	0.046	−0.189
	(0.086)	(0.036)	(0.105)	(0.114)	(0.086)	(0.195)
lnPer_maintain	−0.106	0.284 **	−0.103	0.252	−0.003	1.065 ***
	(0.208)	(0.112)	(0.228)	(0.224)	(0.122)	(0.351)
lnForestland	−6.817 **	3.861 *	−7.244 *	1.411	−0.305	−20.88 **
	(3.255)	(2.158)	(3.995)	(3.462)	(3.040)	(9.076)
lnPerGDP local	0.744 ***	0.020	0.536 **	0.349 **	0.470 **	0.668
	(0.196)	(0.094)	(0.231)	(0.174)	(0.182)	(0.413)
lnAreapopulation	0.141	−0.032	0.079	−0.011	0.149	−0.007
	(0.103)	(0.092)	(0.123)	(0.214)	(0.130)	(0.155)
Constant	85.804 **	−40.925	78.677	−18.045	−0.128	245.656 **
	(40.146)	(26.567)	(48.099)	(43.122)	(36.441)	(118.467)
Enterprise FE	Y	Y	Y	Y	Y	Y
Year FE	Y	Y	Y	Y	Y	Y
Co., Ltd. FE	Y	Y	Y	Y	Y	Y
N	170	125	192	120	232	80
adj. R2	0.496	0.782	0.560	0.761	0.669	0.673

Note: ***, **, and * are significant at the 1%, 5%, and 10% statistical levels, with robust standard errors in parentheses.

.

In column (1), it can be observed that for the low-output group, the governance fragmentation of forestry communities has a more significant negative impact on the economic performance of SOFEs at the 1% level. This may be because SOFEs with poor economic performance have limited available economic resources, and the already scarce human, material, and financial resources are further dispersed under a fragmented governance architecture, leading to a more significant negative impact on their industries. The forestland area (lnForestland) shows contrasting results in the grouped regression of total output value of the forestry industry, which promotes the economic performance of high-output SOFEs but hinders the economic performance of low-output SOFEs. The reason may be that the SOFEs with poor economic performance have limited investment in tourism infrastructure and production facilities, making it difficult to effectively monetize forest resources. On the contrary, larger forest areas result in higher forest management costs, which hinder the increase in economic output of SOFEs. The regression result in column (2) shows that the influence of a fragmented governance architecture is more evident for SOFEs with larger operating scales. This could be due to the fact that, as the operating scale of SOFEs expands, the number of governance affairs related to forests and communities may increase, causing the SOFEs’ energy to be more dispersed and resulting in their relatively poor economic performance under a fragmented governance architecture. The result in column (3) indicates that for SOFEs that had clear geographical boundaries separating them from local government management in the past, their economic performance is more negatively affected by governance fragmentation, passing the significance test at the 1% level. This can be attributed to the psychological division between the SOFEs and local governments caused by the distinct boundaries under the previous separation management, resulting in difficulties for SOFEs and local governments to establish a trust-based, long-term, and stable cooperative relationships. Therefore, SOFEs that had previously experienced clear geographical management boundaries with local governments show a more pronounced effect of governance fragmentation after the reform, and their future community integration processes may be relatively slow compared with other SOFEs without such boundaries.

5. Discussion

In this section, the industrial transformation of SOFEs after the cessation of commercial logging in natural forests and the specific forms of transaction costs incurred by SOFEs in forestry community co-governance and the manifestations of their impact will be further discussed to deepen the understanding of the research results.

5.1. Industrial Transformation of SOFEs

After the logging ban, SOFEs actively developed industries such as forest cultivation, forest health and wellness, forest tourism, forest food, and non-timber forest product processing, adapting to local conditions and transitioning towards a forest-based economy, carbon sequestration economy, bioeconomy, etc. [65]. Li et al. [66] pointed out that, since 2014, increased NFPP funding has promoted the development of ecological industries and products such as forest tourism, timber products, and flowers, as well as the cultivation of preparatory resources. The proportion of the tertiary industry has gradually increased, accelerating the industrial restructuring in forest areas. However, regression results in this study suggest that the current economic performance of SOFEs still mainly relies on labor input and government investment through NFPP. There is a negative correlation between forest resource endowment and economic performance of SOFEs, and the relationship between enterprise industrial structure and economic output of SOFEs has not passed the significance test. Similar findings were also observed in Shen et al.’s [67] study, where the contribution of the forestry tertiary industry to economic performance in the NFPP area was not apparent despite its continuous increase in proportion. These results indicate that after the traditional timber economic chain has been cut off in SOFRs in Northeast China, the new pillar industries for economic performance have yet to be fully developed.

Many SOFEs have the dream of developing their vast forests into ecological tourism industries, as described by Zhu et al. [68], so it is necessary to establish a conversion system from ecological resources to assets and then to capital for fully realizing the value of forest ecological products. However, in fact, the establishment of this conversion system is not easy, and SOFESs face strict constraints from the ecological environment department and the land and resources department regarding the utilization of forest land. Lo [69] pointed out in his research that the construction of infrastructure projects required for tourism development may lead to deforestation and the permanent occupation of forest land, which is not allowed under forest protection policies. Moreover, in terms of marketization, fierce competition caused by highly homogeneous products, combined with the remote location of towns and inadequate transportation infrastructure, severely hinders the number of visitors to these forest regions [69]. The extent to which eco-tourism projects developed with significant capital investment can contribute to the development of SOFEs remains unknown. Under strict forest protection regulations, how to rationally utilize forest resources and realize the economic value of ecological products is a crucial issue for SOFEs to explore during industrial transformation.

5.2. Transaction Costs Incurred by SOFEs in Forestry Community Co-Governance and Their Impact

As mentioned earlier, high transaction costs not only disperse the manpower, material resources, and financial resources of SOFEs but also weaken the trust relationship between SOFEs and local governments, thereby exerting a negative impact on the economic performance of SOFEs.

In reality, SOFEs and local governments need to constantly liaise and coordinate in areas such as community services, regional administrative management, and forest governance. Many tasks are assigned to SOFEs by local governments through the distribution of documents, so SOFEs need to obtain relevant documents on site and participate in various forms of meetings. These activities of handling affairs, communication, and meetings consume a significant amount of time and resources for SOFEs, and they occur frequently every year. “We attend quite a few meetings organized by the local government. We have to go at least three times every half month, not to mention the roads for getting document. It’s over 30 km to go to the county seat, and we have to make a round trip” (2023, employee 01 from TB Forest Enterprise). Similar findings were also identified in the research conducted by Adhikari and Lovett [22], where the highest transaction costs in family involvement in community forestry co-governance were the energy and time expended during lengthy discussions in meetings and assemblies, as well as the prolonged mediation procedures aimed at resolving conflicts related to actual users of community forestry resources. Moreover, during co-governance, SOFEs need to coordinate multiple government departments, resulting in increased communication costs and decreased management efficiency, as described by one interviewee: “Nowadays, we (referring to SOFE) face great work pressure. When we need to communicate and coordinate with the local government, it is not as smooth as before the functional transfer. It is possible that one department is available, while another department not” (2022, employee 01 from WH Forest Enterprise). In particular, forestry communities were established based on the natural distribution of forests, making it very common for them to span across different cities and counties, and some SOFEs even operate across provinces. SOFEs need to engage with different governments separately and follow different procedures and standards in terms of administrative management, law enforcement, project approval, and many other aspects, which result in prolonged project cycles and increased operating costs for SOFEs. “The project was assigned to our company as a whole, but we had to separately go to three or four counties to complete the formalities, and the requirements and standards were different in each place, which wasted a lot of our time” (2023, employee 01 from LJ Co., Ltd.).

The long-term division between forestry communities and local jurisdictions has formed implicit “barriers” with limited communication and weak connections to the outside world for forestry communities, creating a closed regional economy and a small-scale society [14]. In the inherent concept of local governments, SOFEs and their subordinate forestry communities do not belong to the jurisdiction of local governments. Even after the reform, it has been difficult for local governments to develop a proactive mindset regarding serving forestry communities and to establish good cooperative relationships with SOFEs. Under the fragmented governance perception of local governments, the dissatisfaction of SOFEs with local government investment, construction, and other aspects has been gradually accumulating, as they feel they have not received fair treatment, leading to a further weakening of the trust relationship between the SOFEs and local governments. As described by interviewees, “The local governments doesn’t treat us as a company; they think the forestry community affairs shouldn’t be under their control… They may include you in the official planning now, but when it comes to fund allocation, they prioritize their own projects” (2022, employee 02 from WH Forest Enterprise) and “Even if they (referring to local governments) have the money, they will invest their own affairs. For example, we built a sewage treatment plant before, costing a lot of our time to communicate and negotiate with local governments. It was really exhausting.“ (2023, employee 01 from FZ Forest Enterprise).

The high transaction costs faced by SOFEs participating in forestry community co-governance largely stem from the path dependence effects of historical institutions during the transitional period of reform. The old governance system has been dismantled, but the new one has not yet been formed. The inertia from both ideology and institutions has always constrained SOFEs from completely divesting themselves of social functions and transitioning towards marketization. For one thing, local governments maintain deep-rooted control thinking and a government-centric administrative manner. They retain a dismissive and neglectful attitude towards the governance role of SOFEs, failing to recognize their value and provide them with the necessary governance space. For another thing, during the transitional period of reform, SOFEs have not completely reversed the behavioral rules and ideological concepts of taking full responsibility for forestry community affairs. Many SOFE employees occasionally exhibit nostalgia for a unified management system when faced with difficulties in work or cooperation with local governments. At the same time, due to the responsibility ambiguity and information asymmetry caused by policy burdens, the central government takes responsibility for the losses of SOFEs, known as the soft budget constraint of state-owned enterprises [70], including the payment of a portion of the social management costs through the NFPP fund. At this point, market prices and corporate profits cannot accurately reflect the operational efficiency and degree of marketization of SOFEs, and they also do not need to calculate costs and benefits like highly marketized enterprises, which is a common understanding between SOFEs and local governments. Therefore, due to SOFEs’ soft budget constraint and their paternalistic care in the forestry communities, SOFEs and local governments cooperate with each other in a distorted manner despite facing high transaction costs, resulting in a highly fragmented governance architecture in community co-governance, rather than a rupture of cooperation.

The high transaction costs and this kind of fragmented forestry community governance architecture poses significant challenges to the legitimacy and sustainability of SOFEs. On the one hand, power is concentrated in government departments, and they always act as judges, supervisors, and evaluators. When SOFEs cooperate with local governments as required or serve residents in need, they not only need to invest a lot of time and effort but, more importantly, lack the authority and capability to solve problems and face legitimacy challenges. SOFEs can only serve as informal intermediaries between local governments and residents. Leaving aside the impact on SOFEs, the results of forestry community co-governance are also unsatisfactory and inefficient. On the other hand, the reform of SOFRs aims to make SOFEs independent and market-oriented, operating on a self-sustaining basis. As a result, economic profitability becomes one of the key objectives that they must consider [71]. Moreover, SOFEs no longer bear the governmental or societal functions on paper after the reform, making it impossible for NFPP funding to continuously sustain relevant expenditure calibers for public management of SOFEs. Once the state ceases to provide such financial backing, the transaction and management costs associated with SOFEs’ co-governance participation will be exposed, jeopardizing the sustainability of their development. Our previous research findings demonstrate that for SOFEs with weak economic conditions or a large operating scope, a fragmented governance architecture is highly detrimental to improving their economic output. Consequently, behind the fragmented governance architecture and the high transaction costs, lies the threat that SOFEs face in terms of governance legitimacy and economic sustainability, which is a key challenge faced by local governments, community residents, and SOFEs together in forestry community governance.

6. Conclusions and Suggestions

6.1. Conclusions

This study attempts to investigate, for the first time, the economic impact of governance fragmentation after the SOFR reform of SOFEs. This study conducts a theoretical analysis using the new institutional economics and transaction cost theory and verifies hypotheses by applying a fixed-effects model with data collected on the economic output of SOFEs in Northeast China and the status of governance fragmentation of forestry communities from 2015 to 2022. The main findings are as follows.

(1) The fragmented governance architecture between SOFEs and local governments for forestry communities has a significant negative impact on the economic performance of SOFEs.

(2) The high transaction costs incurred by SOFEs in achieving community co-governance with local governments have been proven to be a key mediation mechanism by which governance fragmentation of forestry communities affects the economic performance of SOFEs. High transaction costs lead to the dispersion of resources and efforts, making it difficult for SOFEs to concentrate on forest management and industrial production, as well as weakening trust relationships between SOFEs and local governments. These results are further confirmed through a series of robustness checks.

(3) In addition, the impact of the governance fragmentation of forestry communities on the economic performance of SOFEs varies in terms of SOFEs’ own economic situation, their operating scales, and whether there was a clear geographical management boundary with local governments.

6.2. Suggestions

The diversification of governance entities is an inevitable trend of the times and a practical requirement for achieving good governance. Under the current high transaction costs, a key reason why collaborative governance among diverse governance entities in SOFRs in Northeast China can be sustained is that SOFEs can cover some of the expenses from the NFPP funds they receive from the state. However, once SOFEs lose financial support and face the high transaction costs caused by a fragmented governance architecture, their collaborative governance relationship with local governments in forestry communities may deteriorate, potentially leading to the collapse of the forest governance system. Therefore, mitigating the negative consequences of fragmentation may require more proactive institutional design to reduce transaction costs.

(1) Local governments should incorporate forestry communities into their governance scope and take on the responsibility of administrative management and public service provision in these communities through the central adjustment of the NFPP funding channels for affairs and personnel that have been transferred to the governments. Local governments should also incorporate SOFEs and forestry communities into local development plans, including increasing investment in enterprises, and covering forestry communities in regional educational groups and medical consortia. This will help alleviate the development burden on SOFE and improve the level of forestry community construction. Additionally, local governments should utilize information technologies such as big data, artificial intelligence, and the Internet of Things to establish more flexible and efficient communication channels within forestry communities. This will enable online operations for tasks such as information dissemination, policy consultation, permit processing, public services, and neighborhood assistance, and achieve the sharing of information resources with SOFEs.

(2) Local governments need to recognize the advantages of SOFEs in forestry community governance, including their local knowledge and community authority. They should strengthen communication with SOFEs by establishing joint meetings and other means, and grant SOFEs the autonomy and coordination capabilities that are consistent with governance responsibilities, so as to facilitate the integration of SOFEs as important governance partners into the local social governance system, unleashing synergies to their fullest potential. Introducing market mechanisms is one of the important means to enrich the supply of regional public goods. For public service products that the government is unable to provide or provides inefficiently, they can be delegated to SOFEs or other non-governmental organizations, but relevant costs should be shared through means such as purchasing socialized services. More importantly, it is necessary to develop clear cooperation agreements, clarify responsibility attributions and establish effective monitoring indicators, to prevent from the risk of local government free riding and ensure the realization of regional governance responsibilities on the basis of consistent rights and responsibilities.

(3) To handle relevant affairs across administrative boundaries in forestry communities, it is essential to integrate the governance resources of neighboring local governments and establish joint governance plans to address conflicts arising from crossing geographical boundaries, administrative boundaries, and functional boundaries. Holding regular joint meetings can ensure the coordination and consistency of different governments in policy formulation and implementation. Alternatively, the establishment of specialized cross-departmental or cross-regional coordinating committees may be considered to specifically oversee, coordinate, and integrate the affairs involving multiple departments and regions within the stated-owned forest regions. Utilizing information technologies can also reduce information barriers and resource wastage.

6.3. Implications and Limitations

Top-down reform cannot take into account all the details at the initial stage of design, so “acting according to circumstances (yindi zhiyi)” becomes a good tool for promoting implementation of the reform. However, when dominant departments with power demand cooperation from weaker departments and overlook the actual situation of the latter, it may lead to the reform having unexpected consequences. This empirical study on the governance fragmentation of forestry communities and its impact on SOFEs’ economic performance will remind policymakers and analysts of the flaws in the forestry community co-governance system during the transition period of SOFRs. Furthermore, it is of great importance to have a correct understanding of the transaction costs in SOFEs participation in co-governance, especially for enterprises with weak economic foundation, cause the SOFR reform should not harm the benefits of SOFEs and their local residents. If the cooperative mechanisms and cost-sharing mechanisms for co-governance of forestry communities are not properly established after the separation of governmental functions and social functions from enterprises, it may affect the sustainability of enterprise development and threaten the legitimacy and efficiency of governance, as we have analyzed.

However, due to limitations in data availability, this study still has the following limitations.

(1) In terms of data volume, this study only utilizes data from 39 SOFEs belonging to two forestry industry groups that could be collected at present. Regarding the sample structure, although this study concludes on the basis of empirical observations that local governments are free-riders in forestry community co-governance, due to constraints in data availability, this research did not analyze and calculate the transaction costs incurred by local governments to achieve co-governance of forestry communities, nor does it compare them with transaction costs incurred by SOFEs. Additionally, in terms of indicator selection, despite using interview materials to corroborate the forms and impacts of transaction costs in the study, inevitable subjectivity still exists, which is also influenced by data availability. In the future, if possible, we hope to collect more data from SOFEs in Northeast China and collect additional data from government or third parties to ensure a more representative sample, which will contribute to further demonstrating the importance of transaction costs in collaborative governance of public affairs. On the other hand, our next step will be to develop a wider range of alternative and operational indicators to measure governance fragmentation and transaction costs to enrich the quantitative data.

(2) This study also has limitations in terms of cross-industry comparisons. Although SOFEs in Northeast China exhibit distinct characteristics and incomparability in terms of the content, scope, and scale of fulfilling social functions compared to state-owned forest farms in other regions, they bear great similarities to large-scale state-owned enterprises which were also historically operated under the principle of “zhengqi heyi” in areas such as agricultural reclamation and oil fields in China. Compared to forest regions, the progress and achievements in the transfer of social functions from state-owned enterprises in agricultural reclamation areas and oil fields have been faster and greater. However, due to limitations in data availability, this study has not yet conducted comparative analyses in this regard. In the future, meaningful conclusions may be drawn by analyzing the reform progress, the community governance structures post-reform, and their impacts on economic performance of enterprises across various industries and fields.

(3) Lastly, it must be acknowledged that this study also has limitations in its research dimensions. Governance fragmentation, besides its economic impacts, may also have implications for environmental sustainability, residents’ welfare, and long-term social stability. Conducting research in these areas contributes to a comprehensive understanding of the social, economic, and ecological effects of regional governance architecture. Due to constraints in length and data availability, this study did not explore or discuss these aspects. In the future, we hope to develop more indicators to delve deeper into the impacts of governance fragmentation on the level of regional public service, the quality of public safety, the satisfaction and welfare of residents, and the sustainability of forest resource protection. By enriching the dimensions of the research, this will provide theoretical foundations and data support for optimizing the governance system of forestry communities.