1. Introduction
In 2022, the No.1 Central Document of China proposed to accelerate the expansion of beef, mutton, and dairy production and further promote the transformation and upgrading of grassland animal husbandry [1]. In accordance with the decision and arrangement of the No.1 Central Document of China in 2022, the Ministry of Agriculture and Rural Affairs further defined the goals and tasks for the industrialization, scale, and standardization of grassland animal husbandry. However, in the process of transformation to industrialization and larger-scale operations, grassland animal husbandry in Inner Mongolia still suffers from many problems, such as a fragile ecological environment, an insufficient processing capacity of agricultural and livestock product enterprises, and a slow income increase in herders [2], which have seriously restricted the healthy development of grassland animal husbandry. In order to eliminate the above-mentioned difficulties in the development of grassland pastoral areas, the People’s Government of the Inner Mongolia Autonomous Region officially proposed the implementation of the pastoral modernization strategy in 2020 [3]. This strategy for the modernization of pastoral areas insists on the orientation of “ecological priority and green development” and closely integrates the characteristics and reality of pastoral areas, which is the concrete practice of the rural revitalization strategy in pastoral areas. In addition, it is important to speed up the construction of a green supply chain of grassland livestock products, especially around the characteristics of the livestock industry and green development requirements, to build a reasonable supply chain interest linkage mechanism of livestock products, enhance the sustainable development ability of the green supply chain of grassland livestock products, and achieve the modernization of pastoral areas.
The construction of a reasonable and stable supply chain interest linkage mechanism is the core of the industrialized operation of livestock products and is the key to achieving the integration of the supply chain of livestock products and the effective operation of the whole livestock industry chain [4]. Relevant studies have shown that two essential features of livestock industrialization are the construction of industrial chains and the design of the interest linkage mechanism, the most important of which is the design of the interest linkage mechanism [5], and that the focus on the problems and contradictions of grassland livestock industrialization is the defect of the interest linkage mechanism. At the same time, the interest linkage mechanism is the main obstacle to achieving sustainable development of the livestock product supply chain [6], which is also a more sensitive social issue in the supply chain of agricultural products [7]. In the context of pastoral modernization, the intervention of green development factors has led to significant changes in the interests of all subjects in the supply chain, gradually revealing irreconcilable defects in the previous interest linkage mechanism and making the construction of a new interest linkage mechanism more complicated. At the same time, compared with the traditional supply chain, green supply chain management requires the enterprises in the supply chain to have a strong innovation ability, informatization level, and cooperation ability [8]. Therefore, it places higher requirements on interest linkage and coordination among the enterprises in the entire supply chain.
Thus, the construction of a green supply chain interest linkage mechanism for grassland livestock products is different from the previous consideration constructing it for only economic benefits. This article combines ecological benefits with economic benefits to construct a green supply chain interest linkage mechanism for livestock products that conforms to the concept of ecological priority and green development. Therefore, the research results can enrich the theoretical system of interest linkage in the supply chain of livestock products on the basis of the concept of green development, better ensure the effective operation of the green supply chain of grassland livestock products, promote the green development of grassland animal husbandry, increase the income of herdsmen, and achieve a win–win situation for the economic and ecological benefits of pastoral areas.
Building on previous research, we focus on the following key research questions: (1) What are the factors influencing the interest linkage mechanism in the green supply chain of grassland livestock products? (2) What is the relationship between the different influencing factors? (3) What is the mechanism of the different influencing factors on the interest linkage of the green supply chain of grassland livestock products? (4) How can a reasonable interest linkage mechanism for the green supply chain of livestock products be built?
An important contribution of this paper is the construction of a conceptual model of interest linkage-influencing factors of the green supply chain of grassland livestock products incorporating the concept of green development based on stakeholder theory and green supply chain theory. Taking Inner Mongolia as the research object, this article collects survey data of 358 participants of a green supply chain of grassland livestock products, systematically and intensively studies the relationship between the influencing factors of interest linkage mechanism, and reveals the influencing mechanism of each influencing factor on the interest linkage of a green supply chain of grassland livestock products. This article proposes countermeasures to build a reasonable interest linkage mechanism for the green supply chain of livestock products.
The remainder of this paper is organized as follows: Section 2 briefly reviews the relevant literature. Section 3 introduces the theoretical foundation and model construction of interest linkage of the green supply chain of grassland livestock products. Section 4 discusses the data sources and scale designing. Section 5 presents the empirical study results. Section 6 states the conclusion and proposes managerial implications and suggestions for future study.
2. Review of the Relevant Literature
Scholars at home and abroad have carried out continuous exploration to improve the interest linkage mechanism in agriculture and animal husbandry, mainly focusing on the workings of the interest linkage mechanism, its influencing factors, and suggestions for its construction.
The earliest research on the linkage of interests between relevant subjects of agricultural industrialization was conducted by academics on the relationship between farmers and herdsmen and leading enterprises, but the concept of “linkage mechanism” was not directly proposed. The scholar Yang et al. (1998) first put forward the expression of “interest linkage mechanism” in the study of the interest distribution mechanism of agricultural industrialization organizations [9]; subsequently, theoretical studies on the interest linkage mechanism of farmers and herdsmen gradually increased. At present, the academic community mainly summarizes the interest linkage methods as contract linkage, share linkage, and cooperative linkage [10].
In terms of research on factors influencing interest linkage, Lan Yong et al. used family ranches and agricultural enterprises as their research perspective and found that default costs, the number of linked farmers, risk capital, guarantee amount, and secondary income share were the main factors affecting the effectiveness of an inter-subject interest linkage mechanism [11]. Shao et al. found that institutional construction plays an important role in building close interest linkages by studying farmers’ professional cooperatives in Changshu City [12]. Wei et al. proposed that the basic production and product marketization characteristics of cooperatives are important factors affecting the interest relationship between cooperatives and members [13]. Wei et al. and Zhu used logistic regression analysis based on multiple interest perspective to propose factors affecting the choice of interest linkage mode from the perspective of farmers and enterprises, respectively [14]. Ge et al. (2015) examined three subjects, namely, herding households, cooperatives and leading enterprises, in grassland pastoral areas, used the industrial chain as a whole as a research perspective, and found that the herders’ literacy, the scale of production and operation of the subject, and the awareness of cooperation have a greater influence on the interest linkage behavior among others [15]. Ge et al. (2017) further pointed out that the choice of logistics methods and distribution channels of livestock products by the subjects of the grassland animal husbandry industry chain will also affect the construction of the interest linkage mechanism [16].
In terms of the policy measures to be implemented to build the interest linkage mechanism and to enhance the performance of the linkage, Wen et al. concluded that fostering and growing family ranches and building a close interest linkage mechanism between herders’ cooperatives and leading enterprises can create a favorable external environment for the development of grassland animal husbandry business entities in Inner Mongolia’s pastoral areas [17]. Qian and Ma further pointed out that cooperatives should be used as a link to build a mechanism for linking the interests of agricultural enterprises and adopted case analysis to verify the effectiveness of this model [18]. Lan proposed measures to build the interest linkage mechanism of agricultural products’ supply chain, that is, to focus on coordinating the distribution of interests between farmers and cooperatives and between farmers and large operators [7]. Wang et al. (2019) proposed the construction of an interest linkage mechanism between new agricultural management subjects and small farmers, including improving agricultural production conditions, stabilizing the basic rural management system and moderate-scale operation [19]. Ruan et al. investigated the radiation-driven status of new agricultural business entities nationwide and analyzed the construction effect of the interest linkage mechanism between new agricultural business entities and farmers, and the study showed that most new agricultural business entities have established interest linkage mechanisms with farmers. However, the sustainability of the interest linkage mechanism varies greatly due to the uneven radiation-driving ability of the agricultural operators [20].
This study is distinct because existing studies mainly analyze the interest linkage mechanism based on the perspective of a single subject, such as farmers and herdsmen, enterprises, or two subjects, but there are only a few papers that analyze the system based on the perspective of the supply chain as a whole. Interest linkage forms a chain of interests in the supply chain, and it is difficult to draw scientific conclusions by focusing only on a few participating subjects in the supply chain. Therefore, this article explores the interest linkage mechanism between all stakeholders from the perspective of the entire supply chain, which is more objective and comprehensive. At the same time, in model construction and empirical research, the previous literature focused on economic factors and economic benefits, but downplayed the green development factors and ignored the ecological benefits to a certain extent, resulting in the lack of practicality and generalizability of research results. This article comprehensively considers economic and ecological benefits and introduces green development factors into the study of interest linkage mechanisms, further enriching the theoretical system of green supply chain interest linkage mechanisms.
In summary, the intervention of green development factors makes it necessary to reconstruct the interest linkage mechanism of livestock industry [21]. To clarify the influencing factors of interest linkage, revealing the relationship between different influencing factors and the mechanism of their influence on interest linkage is an important prerequisite for reconstructing a reasonable and stable interest linkage mechanism. Based on this, under the perspective of pastoral modernization, it is of great significance and value to study the influence mechanism of the green supply chain interest linkage of grassland livestock products under the concept of green development around the characteristics of grassland livestock industry to construct a reasonable and stable interest linkage mechanism of grassland livestock products’ supply chain, and, subsequently, to realize the modernization of pastoral areas.
3. Theoretical Foundation and Model Construction
3.1. Basic Theoretical Assumptions
The formation and construction of the interest linkage mechanism is a complex process that is influenced by various factors, and the mechanism and degree of influence of each factor varies. Based on the stakeholder theory and the green supply chain theory, this paper focuses on the characteristics of the green supply chain of grassland livestock products, combines existing field research, incorporates green factors, and constructs an index system of interest linkage-influencing factors consisting of five potential variables including public policy effect [19,22,23], green business status [24,25], willingness to cooperate [26,27,28], characteristics of decision-making behavior [29,30] and circulation characteristics [31,32].
Public policy effect: Wang et al. (2022) selected technology promotion efforts, publicity power, subsidy mechanisms, and satisfaction when designing policy-oriented coverage variables [33]. On this basis, this article combines the actual research situation to set potential variables of public policy effect, including four observed variables: policy satisfaction, policy input strength, policy publicity strength, and policy awareness.
Green business status mainly includes six observed variables: green awareness level, green business scale, green investment efforts, green business situation, green cost perception, and profit level.
Willingness to cooperate mainly includes three observed variables: existing contractual relationships, cooperation expectation awareness, and cooperation satisfaction.
Characteristics of decision-making behavior include three observed variables: market awareness, market information acquisition channels, and trading frequency.
Circulation characteristics mainly include three observed variables: stability of sales channels, convenience of logistics, and cold chain logistics awareness.
Interest linkage mainly includes four observed variables: interest linkage mode, interest coordination channel, interest distribution dominance, and interest distribution awareness.
Meanwhile, the relationship between potential variables and observed variables is set, and relevant research hypotheses are proposed.
(1) Public policy effect. The various public policies formulated by the government are closely related to the potential interests of business entities in the green supply chain of livestock products and are an important guide for the green development of grassland animal husbandry. The degree of policy investment, publicity, and satisfaction have a significant impact on the green business status of various stakeholders in the supply chain. At the same time, the government influences the green management subjects’ grasp of market information, information source channels, and their willingness to cooperate with each other through the promulgation of policies. Compared with ordinary supply chain subjects, the livestock product enterprises, cooperatives, and herders who receive policy subsidies and support have higher production motivation, tend to seek cooperation among themselves, and increase the intensity of cooperation among themselves. Xu et al. (2021) found that both incentive and restrictive environmental regulations have a significant positive moderating effect on the recognition of agricultural green production policies and willingness to engage in agricultural green production [25]. Zhang et al. (2021) proposed to build a full, end-to-end green supply chain through policy formulation, in order to improve the greening level of the entire supply chain [34]. Wang et al. (2019) showed that the government’s introduction of various forms of support policies is an important guarantee and support for the development of small-scale farmers and cooperatives, and that tax relief, financial subsidies, and risk prevention and control play important roles in completing infrastructure construction, improving production motivation, and reducing disaster risk losses for farmers [19]. Du and Jing showed that government policy orientation plays a normative and constraining role on farmers’ green behavior [35]. Huttunen and Peltomaa showed that government subsidy policies related to green production have a significant positive impact on farmers’ green production transition [36]. Li et al. (2015) concluded that policy incentives are an important influencing factor on the willingness of subjects to cooperate [37]. Accordingly, this paper proposes the following hypothesis:
Public policy effect has a positive impact on green business status;
Public policy effect has a positive influence on willingness to cooperate;
Public policy effect has a positive influence on the characteristics of decision-making behavior.
(2) Green business status. The green management status of each participating subject in the green supply chain of grassland livestock products has an important influence on the existing contractual relationship, cooperation expectation awareness, and cooperation satisfaction of the subject, and the green management status also affects the subject’s decision-making behavior characteristics and the circulation characteristics of livestock products. As rational brokers, each interested subject will consider the expected benefits and costs, and when a decision is beneficial to their own benefits, they will generate positive behaviors and attitudes, thus increasing their behavioral intentions. Fang et al. (2022) found that in order to achieve the goals of green operation and sustainable development, enterprises must strengthen strong cooperation with green suppliers [24]. Yang et al. (2022) used a two-category logit model to analyze the behavior of modern agricultural production system, and the results showed that the level of value perception and capital endowment have positive effects on agricultural production behavior [38]. Zhang et al. (2021) found that the green production behavior of operating agents has an important influence on the choice of organizational models such as the industrial market transaction model and the vertical cooperation model [39]. Based on the above views, the following hypotheses are proposed:
Green business status has a positive effect on willingness to cooperate;
Green business status has a positive influence on the characteristics of decision-making behavior;
Green business status has a positive influence on circulation characteristics.
(3) Willingness to cooperate. The closeness of cooperative relationship between subjects and their awareness and evaluation of cooperative expectation have a significant influence on the choice of interest linkage by each subject in the supply chain. Ge et al. (2017) found that the degree of closeness of cooperative relationships and the perception of future cooperative relationships affect the choice of interest linkage mechanism among various entities in the industrial chain [16]. Shi et al. found a significant relationship between farmers’ willingness to cooperate, cooperative behavior, and contractual choice willingness through a related model based on micro farmers’ perspective [26]. Tian and Zhang conducted a study using SEM (structural equation modeling) and found that the willingness to cooperate among subjects such as cattle farmers, farms, and slaughter and processing enterprises in the industry chain directly determines the organizational efficiency of the beef cattle industry chain and the tightness of the linkage of each link [40]. Based on this, the following hypothesis is proposed:
Willingness to cooperate has a positive influence on interest linkage.
(4) Characteristics of decision-making behavior. The degree of market awareness, market information acquisition channels, and transaction frequency between each subject in the livestock product supply chain directly affect the characteristics of livestock product circulation and the choice of their interest linkage. Ge et al. (2017) pointed out that the behavior of various entities in the industrial chain directly affects the way they cooperate with each other and also affects the logistics characteristics of their livestock products [16]. Li et al. (2009) found that farmers’ degree of awareness of the market has an important influence on their production and planting decision behavior [29]. Zhong et al. (2016) found a significant relationship between farmers’ perceptions of cooperatives and other cooperatives and the formation of cooperative relationships based on an extended study of the theory of planned behavior [41]. Based on the above views, the following hypotheses are proposed:
Characteristics of decision-making behavior have a positive effect on circulation characteristics;
Characteristics of decision-making behavior has a positive effect on interest linkage.
(5) Circulation characteristics. The awareness of business subjects on cold chain logistics, the convenience of logistics, and the stability of their sales channels not only affect the choice of future cooperation methods between each other but also affect the construction of the interest linkage mechanism between subjects. The more convenient the circulation of livestock products and the higher the level of socialized logistics services, the more inclined the supply and demand sides of logistics services are to cooperate, which is conducive to reducing the logistics service costs of the entire supply chain [42]. Sun (2016) pointed out that under the third-party cold chain logistics model, the willingness to cooperate between different market entities is relatively high [31]. Hai and Gao argued that the key to the construction of an agricultural industry chain is to solve its logistics problem, open the production and marketing chain of processing, transportation, storage, and sales of agricultural products, strengthen the connection between them, and then achieve the integration of the industry chain [43]. Through an empirical analysis of the effect of cooperatives on promoting agricultural income, Jiang et al. found that the individual characteristics of farmers, participation in cooperatives, planting, and logistics services, play an important role in promoting agricultural income, so it is necessary to strengthen the active integration of cooperatives into the industrial chain, which can ensure the participation of farmers in the distribution of benefits in the agricultural industrial chain [44]. Accordingly, the following hypotheses are proposed:
Circulation characteristics have a positive effect on willingness to cooperate;
Circulation characteristics have a positive effect on interest linkage.
3.2. Model Construction
In this paper, SEM is used to analyze the influence mechanism of the link of interest. SEM analysis integrates two statistical methods, factor analysis and path analysis, to obtain the direct effect, indirect effect, or total effect of the independent variable on the dependent variable by examining the relationships among the dominant, latent, and interfering variables included in the model.
Based on the above research hypotheses and the principles of structural equation modeling, the conceptual model of structural equation, as shown in Figure 1, is constructed in this paper.
4. Data Sources and Scale Design
4.1. Data Sources and Sample Description
The data used in this paper are collected from field surveys and interviews conducted by the research team in July 2022, and February and March 2023 in six livestock banners (an administrative division of the Inner Mongolia Autonomous Region in China, equivalent to a county-level administrative division) and counties in the Inner Mongolia Autonomous Region. Among them, selected the research area included all pilot banners and counties of pastoral modernization in Inner Mongolia (four in total) as well as two nonpilot banners and counties. Focusing on the composition and characteristics of the green supply chain of grassland livestock products, pastoral households, cooperatives, and leading enterprises were selected to ensure a scientific and reasonable sample selection, and all the participating subjects in the green supply chain of livestock products were covered. After sample verification, data correction and elimination of those samples with incomplete information and illogical data, 358 valid samples were finally obtained. Referring to the method of Ge et al. (2017), a five-point scale was used to unify the findings of different participating subjects in the supply chain into the model [16].
(1) Analysis of herding households’ sample characteristics.
The basic characteristics of the herding households studied in this paper are as follows: Majority of the heads of households are men, 67.54%, who are more familiar with household production and operation. In terms of age structure, the herdsmen aged 36–45 account for the largest number of operators with 35.08%, while herders aged 46–55 rank second with 30.82%. Combined with field research, it is easy to see that the trend of younger herders in banner counties with greater policy support is becoming more and more obvious. In terms of the educational level of herders, the population with junior high school education accounted for the most with 39.02%. In terms of working experience, the percentage of herders who did not work outside the business reached 60.98%. In terms of farming years, the proportion of people with 6–15 years and 16–25 years of experience were 25.90% and 23.93%, respectively. In terms of social experience, the percentages of ordinary herders and herders with multiple social identities (party members, cooperative members, model households, etc.) were similar, accounting for 52.46% and 47.54%, respectively. In terms of herders joining production cooperatives, the sample herders in this study were more inclined to establish stable cooperative relationships in order to expand production and improve market competitiveness, and the proportion of herders joining professional cooperatives and joint-family operations reached 46.75%, as shown in Table 1.
(2) Analysis of sample characteristics of cooperatives.
The basic characteristics of the cooperatives in this research are as follows: The cooperatives in the research, according to their operation types, can be divided into livestock unified breeding; providing services of purchasing production materials; and integration of breeding, processing, and sales. These types account for 76.9%, 3.8%, and 19.2% of the total, respectively. Cooperative formation driven by large households or by village party branches are the main ways to form cooperatives, accounting for 42.3% and 38.5% of the research data, respectively. In terms of the source of funds for the establishment of cooperatives, “self-financing + government project funds” accounted for the largest proportion, with 57.7%. As for the operation mode of cooperatives, the operation mode of “party branch + cooperative + enterprise” is the main mode, accounting for 64.2%. However, the overall scale of cooperative operation is small, with 34.6% of cooperatives with registered capital of less than CNY 2 million, and there is only 15.4% of cooperatives with 46 or more members, which have limited radiation drive, as shown in Table 2.
(3) Analysis of the characteristics of the sample of leading enterprises.
The basic characteristics of the surveyed enterprises are as follows: According to their nature, the surveyed enterprises can be divided into private enterprises and state-owned enterprises, which account for 94.4% and 5.6%, respectively. In terms of the number of years of establishment, 6–10 years of operation accounted for the largest proportion, with 47.1%. The regional categories of enterprises mainly include national, provincial, municipal, and county level, accounting for 11.8%, 29.4%, 23.5%, and 35.3%, respectively. In terms of business type, the leading enterprises of livestock products include production and breeding, slaughtering and processing, integrated operation, and other multi-business types. Among them, the largest proportion of enterprises is that with an integrated operation type of production, processing, and sales, with 33.3%, while the proportion of production and breeding enterprises and slaughtering and processing enterprises are 22.2% and 11.1%, respectively. In addition, this paper investigates the leading enterprises providing services such as forage and agricultural equipment for the special composition of the green supply chain of grassland livestock products, accounting for 16.7%. In terms of enterprise registered capital, the number of enterprises with registered capital of more than CNY 5 million occupies more than 70% of the total number of those included in the research, while the market share of enterprises is mainly divided into two categories, relatively high and very high, accounting for a total of 77.8%. In line with the sample enterprise characteristics required in this paper, the selection of livestock product enterprises with a leading role is shown in Table 3.
4.2. Variable Selection and Assignment
Combined with the above conceptual model on the indicator system of interest-linked influencing factors, while drawing on the research design schemes of scholars such as Ge et al. and Siti et al., this section proposes to use the Likert five-point scale to quantify the question items of relevant explicit variables in segments [16,45], as shown in Table 4.
5. Empirical Study
5.1. Confidence and Validity Analysis
5.1.1. Confidence Analysis
The data were analyzed using SPSS 24.0 software. It was concluded that the alpha reliability coefficients of the six latent variables, including the public policy effect, were mostly in the range of 0.7–0.9, and the overall Cronbach’s alpha for the scale was 0.943, indicating that the data used in this study had good internal consistency and stability, as shown in Table 5.
5.1.2. Validity Analysis
This paper focuses on validity analysis through structural validity, convergent validity, and differential validity. Firstly, the KMO value of this paper is calculated as 0.946, the approximate chi-square value of Bartlett’s spherical test is 4808.114, the degree of freedom (df) is 253, and the significance (Sig.) = 0.000, which indicates that the questionnaire has good structural validity. Secondly, as can be seen from Table 6, the AVE values of each dimension reached above 0.5, and the CR values reached above 0.7, indicating that each dimension has good convergent validity.
Finally, the absolute values of the correlation coefficients among the latent variables are all smaller than the square root of the latent variables’ AVE (the values in the matrix with the diagonal line bolded), indicating that the model has good discriminant validity, as shown in Table 7.
5.2. Structural Equation Model Results Testing and Analysis
5.2.1. Analysis of Model Fit
After calculation, it is seen that the measured results of each index of goodness of fit meet the reference standard, as shown in Table 8. The quantitative feasibility of the indicators is high, and the fitness and fit between the actual observed data and the model are good.
5.2.2. Analysis of Empirical Results
Based on the structural equation model, the hypotheses of this study were tested and the standardized path coefficients of the model as well as the results of the hypothesis testing are as follows.
(1) Hypothesis testing.
Figure 2 shows the standardized path coefficient diagram of the structural equation model of the interest linkage of grassland livestock products’ green supply chain (note: the English initials of each potential variable are shown in Figure 2). The hypotheses of this study were tested using AMOS 24.0 software, and the standardized path coefficients and significance levels of the model were calculated, as shown in Table 9. Among them, Estimate is the unstandardized coefficient, which is used to determine the significance of its path coefficient, and the size of the standardized path coefficient is used to determine the degree of its influence.
From the output results, among the 11 paths of the theoretical model, all the paths passed the significance test, except for the two paths of “Green business status → Characteristics of decision-making behavior“ and “Circulation characteristics → Interest linkage”, which were not significant.
Public policy effect positively affects the green business status of business actors in the supply chain (p < 0.001), and the standardized path coefficient is 0.594, so the research hypothesis of H1a is valid. This is consistent with the findings of scholars Du and Jing [34]. Public policies are oriented toward ecological priority and green development, and continuously improve the green management awareness of business subjects through publicity and investment funds, thereby increasing green investment and expanding the scale of green management. The field research situation also confirms this conclusion, and the government gives priority to the implementation of policies such as agricultural support and protection subsidies, agricultural and livestock production materials purchase subsidies, and tax preferences with demonstration site enterprises, cooperatives, and herding households in order to follow the path of green and high-quality development of grassland animal husbandry, which provides important support and guarantees for production and breeding subjects to increase infrastructure construction, purchase mechanized and intelligent equipment, and improve livestock breeds. Public policy effect has a significant positive effect on willingness to cooperate (p < 0.001), with a standardized path coefficient of 0.362. The support and publicity of relevant policies will directly promote the operation subjects to seek multifaceted cooperation to maximize their own interests; hypothesis H1b is verified. The standardized path coefficient of public policy effect on the characteristics of decision-making behavior is 0.712, which has a significant positive effect (p < 0.001); hypothesis H1c is verified. This indicates that under the guidance and support of relevant government policies, business subjects have clearer awareness of the market business environment, more diversified channels to obtain market information, and positive attitudes toward the establishment of close interest linkages among subjects. At the same time, according to the standardized path coefficient, it can be seen that the public policy effect has a greater degree of influence on the characteristics of decision-making behavior.
The standardized path coefficient of green business status on the willingness to cooperate is 0.360, and the p-value reaches the significance level. This indicates that the green production and operation status of supply chain stakeholders has a positive influence on the choice of inter-subject cooperation, the judgment of cooperation expectation, and the evaluation of cooperation subjects; H2a hypothesis is verified. On one hand, the green production and operation status of each interested subject drives them to abandon the traditional market transaction mode and choose horizontal and vertical cooperation modes to achieve the goal of reducing the transaction cost of the green supply chain of livestock products; on the other hand, each interested subject tends to choose a closely coordinated cooperation mode to better meet its own green development needs so as to continuously improve its market share and competitiveness. Taking the leading enterprises as an example, the publicity of the green management concept is conducive to enhancing their corporate image and reputation, improving their market competitiveness and production enthusiasm, and thus motivating them to continuously innovate their production and cooperation methods. Therefore, the good or bad green operation status of the subject has an obvious promotion effect on the willingness of the subject to cooperate in the green supply chain of grassland livestock products. The green business status positively affects the circulation characteristics of subjects (p < 0.001), and the standardized path coefficient is 0.337; hypothesis H2c is verified. This indicates that the current expansion of the green scale of livestock products and the improvement in the green awareness of the operating subjects put forward higher requirements for the circulation of livestock products, the demand for cold chain logistics under the concept of green development is higher, and each operating subject pays more attention to the construction of its cold chain logistics system so as to maximize its own profit. Among them, the green business status of the subject has a greater degree of influence on willingness to cooperate. However, the p-value of green business status on the characteristics of decision-making behavior did not pass the significance test, and hypothesis H2b did not hold. This is inconsistent with the research conclusion of Ge et al. (2017) [16]; this may be determined by the special nature of livestock production, which relies heavily on the constraints of natural conditions, such as grassland ecology, and changes in green management status may not affect the degree of subjects’ knowledge of the market in a short period of time or may have less impact. Especially for herders, their market trading behavior does not change significantly in the short term because of the addition of green factors.
The willingness to cooperate of the interested subjects has a significant positive influence on the interest linkage of the green supply chain of livestock products, with an influence coefficient of 0.394 (p < 0.001); hypothesis H3 is valid. The existing contractual relationship, the judgment of expected benefits of cooperation, and the satisfaction of cooperation among the stakeholders in the green supply chain of grassland livestock products, to a certain extent, restrict the choice of the overall interest linkage of the supply chain. By comparing the risks and benefits of cooperation with those of separate operation, each stakeholder recognizes the necessity of cooperation and thus continuously enhances the willingness of cooperation among them in order to reduce transaction costs and risks and to obtain higher benefits by forming a close interest linkage among them.
Characteristics of decision-making behavior have a significant positive effect on both circulation characteristics and interest linkage at the 1% significance level, and research hypotheses H4a and H4b are tested. The interested subjects in the green supply chain, such as herders, cooperatives, and leading livestock product enterprises, are engaged in livestock production and operation activities based on market price trends, business environment expectations, and government policy guidance. Especially under the current policy background of green development of livestock industry, each subject tends to form different interest linkages in order to maximize their own interests by continuously trying to broaden sales channels and change product distribution methods to minimize operating costs and risks.
Circulation characteristics had a significant positive effect on willingness to cooperate, and the standardized path coefficient was 0.316. The research hypothesis H5a was verified, but the direct impact on interest linkage failed the significance test, so hypothesis H5b was not valid. This is inconsistent with the research conclusion of Ge et al. (2017) [16]; this may be determined by the special geographical location of the grassland pastoral areas. Taking the herders’ business entities as an example, herders located in remote areas will choose to cooperate with other organizations based on their own logistics transportation convenience and cost pressure, so the circulation characteristics have a positive impact on the willingness to cooperate, but in the long run, with the improvement in logistics infrastructure conditions in pastoral areas, they may prefer self-operated logistics and have insufficient motivation to build interest linkage, so their effect on interest linkage is not significant.
(2) Influence mechanism of each influencing factor on interest linkage.
In order to further analyze the mechanism of each influencing factor on the interest linkage, this paper uses the bootstrap program in the AMOS 24.0 software to test the significance of each path mediation effect (the structural equation model constructed in this paper is the chain multiple mediation model). Among them, the paths of the influence of each factor on the interest linkage are labeled as follows: m1 (public policy effect → willingness to cooperate → interest linkage), m2 (public policy effect → green business status → willingness to cooperate → interest linkage), m3 (public policy effect → green business status → circulation characteristics → willingness to cooperate → interest linkage), m4 (public policy effect → green business status → interest linkage), m5 (public policy effect → green business status → circulation characteristics → willingness to cooperate → interest linkage), m6 (public policy effect → green business status → circulation characteristics → interest linkage), m7 (public policy effect → characteristics of decision-making behavior → circulation characteristics → willingness to cooperate → interest linkage), m8 (public policy effect → characteristics of decision-making behavior → circulation characteristics → interest linkage), m9 (public policy effect → characteristics of decision-making behavior → interest linkage), and m10 (public policy effect → green business status → characteristics of decision-making behavior → interest linkage). The details are shown in Table 10. m1, m2, m3, m7, and m9 paths are significant, and the remaining indirect influence paths are not significant, which is consistent with the previous test hypotheses showing that H5b and H2b are not significant. Additionally, among all the paths, public policy effect indirectly influences the interest linkage to a greater extent through the characteristics of decision-making behavior.
According to the previous hypotheses and the analysis of the empirical results of the mediating path, it can be seen that (1) willingness to cooperate directly and positively affects interest linkage, for reasons that have been analyzed in the previous section and thus will not be repeated here. (2) Although the circulation characteristics cannot directly affect the interest linkage, they can indirectly and positively affect the interest linkage through willingness to cooperate. In other words, the better the circulation characteristics of livestock products, the more the willingness to cooperate in a vertical collaboration way, and the more conducive it is to the formation of interest linkage. (3) Characteristics of decision-making behavior can not only directly affect the interest linkage, but also change the willingness to cooperate with each other through circulation characteristics, thus indirectly affecting the formation of the interest linkage mechanism. When the subject’s characteristics of decision-making behavior are better, i.e., the clearer they know the market information and demand of livestock products, they can promote the diversification of sales channels and distribution methods of livestock products, so that they tend to cooperate with each other to reduce production and distribution costs and establish reasonable and stable interest linkage to maximize overall interests. (4) The green business status can indirectly influence the interest linkage through two paths. First, it indirectly affects the interest linkage through the willingness to cooperate with each other. With the deepening of the concept of green development, each participating body in the supply chain pays more attention to the green business status of the cooperative partners, and the scale of green operation, the degree of green input, and green operation will directly affect the judgment of the expected benefits of the cooperative partners, thus affecting the overall interest linkage. The second path is through a change in the willingness to cooperate through circulation characteristics, thus indirectly affecting the interest linkage. Based on the special characteristics of livestock products, the better the green business status of the subject, the more willing it is to change the circulation characteristics of its livestock products, thus affecting its willingness to participate in cooperation and further influencing the formation of the overall interest linkage mechanism. (5) The public policy effect can indirectly influence the interest linkage through five paths. Firstly, it indirectly affects the interest linkage through willingness to cooperate, and the proportion of indirect effect is 21.01%. Secondly, through the characteristics of decision-making behavior, the indirect effect is 45.91%, which shows that the public policy effect has the strongest influence on the interest linkage by influencing the characteristics of decision-making behavior. Thirdly, by means of the characteristics of decision-making behavior, it influences the circulation characteristics of subjects and changes the cooperation willingness of the interested subjects, thus indirectly influencing the interest linkage; the proportion of indirect effect is 5.58%. The fourth path is improving the willingness to cooperate of subjects by improving their green business status, thus indirectly influencing the interest linkage; the proportion of indirect effect is 12.45%. Fifth, on the basis of improving the green business situation, the circulation characteristics of livestock products of the subject are enhanced, thus affecting the willingness to cooperate with each other and indirectly influencing the construction of interest linkage, with an indirect effect of 3.63%.
6. Conclusions and Prospects
6.1. Conclusions
According to this empirical study, it can be seen that in the implementation of the pastoral modernization strategy, variables such as public policy effect, green business status, characteristics of decision-making behavior, willingness to cooperate, and circulation characteristics all affect the interest linkage of the green supply chain of grassland livestock products in different degrees in a direct or indirect way, and there are also complex interactions among the potential variables. The main findings of this paper are as follows:
(1) Willingness to cooperate has a significant positive effect on the interest linkage mechanism. The highest degree of influence was found in the existing contractual relationship indicator of willingness to cooperate. This is because the existing contractual relationship among the participating subjects in the supply chain directly affects their acceptance of the establishment of the new interest linkage mechanism. The more stable and reasonable the existing contractual relationship is, the clearer the awareness and judgment of the cooperation relationship is, the more they can recognize the importance of cooperation, the more they can enhance the awareness of cooperation among subjects, and thus, the more conducive the formation of the interest linkage mechanism is to the green supply chain of grassland livestock products;
(2) The direct impact of circulation characteristics on interest linkage is not significant, but it can indirectly have a positive effect on the interest linkage through willingness to cooperate. Among the distribution characteristics, the most influential is the stability of sales channels. In order to reduce costs and risks, market players tend to establish cooperative relationships with other players to maximize each other’s profits and indirectly promote the formation of interest-linked relationships;
(3) The characteristics of decision-making behavior can not only directly and positively influence interest linkage but also indirectly and positively influence interest linkage by influencing the willingness of subjects to cooperate through the characteristics of livestock product distribution. Among these characteristics, the degree of market perception is the most significant influence indicator of decision-making behavior characteristics. This means that with the change in the subject’s decision-making behavior characteristics, especially the increase in the subject’s market awareness degree, the judgment and evaluation of the livestock products business environment and future trends will become more objective. This increase in market awareness will improve their choice and understanding of new circulation methods of livestock products, and continuously enhance the awareness and willingness to cooperate for the stabilization of livestock products sales channels, thus promoting the formation of the interest linkage mechanism;
(4) Green business status cannot directly influence interest linkage but can indirectly influence interest linkage via two paths with the help of intermediary factors: one path is indirectly influencing interest linkage by influencing the willingness to cooperate with each other. The second path is changing the willingness to cooperate by affecting the circulation characteristics, which indirectly affects the interest linkage. Among these characteristics, the green business scale is the most significant influence indicator in the green business status of the subject;
(5) The public policy effect cannot directly influence the interest linkage mechanism but can indirectly influence interest linkage via five paths through factors such as green business status, willingness to cooperate, characteristics of decision-making behavior, and circulation characteristics. Among the five influence paths, the public policy effect has the greatest indirect influence on interest linkage through the characteristics of decision-making behavior. Among these characteristics, the public policy effect of government input strength and policy publicity strength are the most influential factors in this variable, which are important ways to strengthen the interest linkage of the green supply chain of grassland livestock products.
6.2. Managerial Implications
Regarding the direction, degree, and path of action of the above influencing factors and related research findings, the following managerial implications are proposed in order to build a reasonable interest linkage mechanism, realize the long-term coordination and sustainable development of the green supply chain of livestock products, and realize the goal of modernization of pastoral areas.
(1) Standardize the cooperative behavior of the subject and enhance the willingness to cooperate between the subjects. The research results show that the existing contractual relationship is the most significant factor affecting the interest linkage in the willingness to cooperate, and the regulation of the cooperative behavior of the subjects is an important prerequisite for establishing a long-term and stable contractual relationship. Therefore, the participating subjects in the green supply chain should adhere to the cooperation principle of “benefit sharing and risk sharing”, establish the goal of maximizing the overall benefit, break the phenomenon of “one voice” of the larger subjects in the supply chain, and realize the reasonable distribution of operating profit so as to improve the cooperation evaluation among the main parties and the willingness to cooperate with each other, forming a reasonable interest linkage.
(2) Strengthen the construction of the livestock products market system and stabilize the circulation channels of livestock products. The empirical results in the previous section show that the circulation characteristics of livestock products in pastoral areas cannot directly affect the interest linkage but can indirectly affect the interest linkage by changing the willingness of cooperation among the subjects. Therefore, the government should pay attention to the construction of the livestock products market system in grassland and pastoral areas, eliminate restrictions of livestock products’ circulation in pastoral areas, optimize the livestock products circulation environment, and broaden and stabilize the livestock products sales channels. Firstly, the government should focus on cultivating organizations that provide the whole chain of socialized services and provide herders and supply chain participants with quality services in the whole chain and process; secondly, the government should improve and perfect the information collection and release system in the process of production, circulation, and marketing of livestock products and provide herders with more accurate, effective, and timely market transaction information so as to better guide the production and circulation of livestock products to form a stable interest linkage mechanism.
(3) Cultivate and improve market awareness in the interested subjects. The empirical results show that the degree of market awareness of subjects has a significant positive impact on their interest linkage. Therefore, the government should increase market awareness training for supply chain participants and leading market participants, especially herders in a disadvantaged position, to grasp market demand and price information in a timely manner and improve their awareness and judgment of the livestock products market environment and product price trends so that relevant stakeholders can make rational choices in the market fluctuations and improve the sustainability of interest linkages.
(4) Strengthen the main body’s awareness of green development and expand the scale of green operations. In the process of promoting a pastoral modernization strategy, green development has become an inevitable trend for the future development of grassland animal husbandry. Only when each business entity is fully aware of the necessity and urgency of green development can it continuously expand its green business scale, improve the green business environment of each business entity in the supply chain, and lay a solid foundation for the formation of a reasonable and stable interest linkage mechanism so as to better enhance the overall competitiveness and sustainable development capacity of the green supply chain of grassland livestock products.
(5) Increase government input and policy publicity to highlight the effect of public policy. The government should actively promote the concept of “ecological priority and green development” through various online and offline channels. At the same time, by increasing policy support, the government can enhance the guiding role of green management for each subject and solve the practical problems faced by them in green management. In addition, the government should also encourage each subject to change its traditional management concept and mode and enhance its awareness of active participation in cooperation so as to promote the formation of a reasonable interest linkage mechanism in the green supply chain of grassland livestock products.
(6) Improve relevant laws and regulations to effectively safeguard the interests of market entities. The government should attach great importance to the construction of a legal and regulatory system to effectively safeguard the interests of the main body. Firstly, the government should implement and improve relevant policies and laws and regulations. In specific legal provisions, the government should clarify the rights and responsibilities of each business entity in the production cooperation process. Secondly, the government should establish a sound and effective supervision mechanism. On the basis of laws and regulations, a supervisory agency for grassland livestock product trading should be established to promote better and more reasonable interest linkage mechanisms between entities.
6.3. Prospects
There are some limitations in this study. First, the interest linkage mechanism is influenced by multiple factors and is a complex system. This article incorporates green development factors and constructs a relatively reasonable indicator system, but other secondary influencing factors will also be ignored. Second, in terms of field research, although there are many research areas and a relatively large sample size, the representativeness of the samples may also be insufficient, making it difficult to fully reflect the overall picture of the research object. This topic will require further research in the future. In the next step, we should continue to explore the possible influencing factors. At the same time, based on mathematical models, such as game theory, we can also explore in detail the value distribution, competition, and cooperation relationship of the green supply chain of livestock products so as to further improve the theoretical system of the green supply chain of livestock products and better achieve the goal of modernization in pastoral areas.
Conceptualization, J.Z., Y.W. and X.Z.; data curation, B.; formal analysis, J.Z. and X.Z.; investigation, J.Z., Y.W. and B.; project administration, J.Z.; software, J.Z. and Y.W.; supervision, X.Z.; validation, Y.W. and B.; writing—original draft, Y.W.; writing—review and editing, J.Z. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
Not applicable.
The authors are grateful to the anonymous reviewers and editorial team for their constructive comments on the study.
The authors declare no conflict of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Distribution of sample characteristics of herding households.
| Variables | Options | Frequency | Percentage |
|---|---|---|---|
| Gender | Male | 206 | 67.54% |
| Female | 99 | 32.46% | |
| Age | Under 25 years old | 1 | 0.33% |
| 26–35 years old | 31 | 10.16% | |
| 36–45 years old | 107 | 35.08% | |
| 46–55 years old | 94 | 30.82% | |
| 56 years old and above | 72 | 23.61% | |
| Academic qualifications | Elementary school and below | 81 | 26.56% |
| Junior high school | 119 | 39.02% | |
| High school | 30 | 9.84% | |
| College | 56 | 18.36% | |
| Bachelor’s degree or above | 19 | 6.23% | |
| Outbound work experience | Yes | 119 | 39.02% |
| No | 186 | 60.98% | |
| Revenue sources | Farming income only | 142 | 46.56% |
| Multiple sources of income | 163 | 53.34% | |
| Years of breeding | 16–25 years | 73 | 23.93% |
| 26–35 years | 64 | 20.98% | |
| 36 years and above | 38 | 12.46% | |
| 5 years and below | 51 | 16.72% | |
| 6–15 years | 79 | 25.90% | |
| Social experience | General pastoralist | 160 | 52.46% |
| Multiple social identities (party members, cooperative members, model households, etc.) | 145 | 47.54% | |
| Production cooperation | Professional cooperatives | 64 | 20.98% |
| Enterprise | 5 | 1.64% | |
| Joint venture | 23 | 7.54% | |
| Single-family operation | 163 | 53.44% | |
| Family ranch | 50 | 16.39% |
Distribution of sample characteristics of cooperatives.
| Variables | Options | Percentage |
|---|---|---|
| Cooperative business type | Unified livestock breeding | 76.90% |
| Livestock breeding + product processing and sales | 19.20% | |
| Purchase of production materials | 3.80% | |
| Cooperative formation method | Driven by capable people or large households | 42.30% |
| Village party branch leaders | 38.50% | |
| Led by leading enterprises | 3.80% | |
| Ordinary herdsmen formed on their own initiative | 11.50% | |
| The main source of funds for the establishment of cooperatives | Self-financed by members | 23.10% |
| Self-financing + government project funds | 57.70% | |
| Self-financing + government funding + corporate input | 19.20% | |
| Cooperative operation mode | Cooperatives + herders | 26.90% |
| Party Branch + cooperative + enterprise | 64.20% | |
| Cooperatives + herders + enterprises | 7.70% | |
| Cooperatives + herders + family ranches | 1.20% | |
| Number of cooperative members | 1–15 people | 30.70% |
| 16–30 people | 26.90% | |
| 31–45 people | 26.90% | |
| 46 and above | 15.40% | |
| Registered capital | Under CNY 2 million | 34.60% |
| CNY 2 million to 4 million | 30.80% | |
| CNY 4 million to 6 million | 15.40% | |
| CNY 6 million to 8 million | 11.50% | |
| More than CNY 8 million | 7.70% |
Distribution of sample characteristics of cooperatives.
| Variables | Options | Percentage |
|---|---|---|
| Nature of business | Private companies | 94.4% |
| State-owned enterprises | 5.6% | |
| Year of business establishment | 0–5 years | 17.6% |
| 6–10 years | 47.1% | |
| 11–15 years | 23.5% | |
| More than 16 years | 11.8% | |
| Enterprise category | National level | 11.8% |
| Provincial level | 29.4% | |
| Municipal | 23.5% | |
| County | 35.3% | |
| Business type | Production and breeding enterprises | 22.2% |
| Slaughter and processing enterprises | 11.1% | |
| All-in-one operation | 33.3% | |
| Sales companies | 16.7% | |
| Veterinary medicine, forage, agricultural |
16.7% | |
| Enterprise registered capital | Under CNY 5 million | 29.4% |
| CNY 5–10 million | 35.3% | |
| CNY 10 million or more | 35.3% | |
| Market share | General | 22.2% |
| Comparatively high | 42.5% |
Variable settings and their assignments.
| Latent Variable | Observed Variables | Variable Assignment |
|---|---|---|
| Public policy effect | Policy satisfaction | Very dissatisfied = 1, dissatisfied = 2, average = 3, satisfied = 4, very satisfied = 5 |
| Policy input strength | Very small = 1, small = 2, average = 3, large = 4, very large = 5 | |
| Policy publicity strength | Very small = 1, small = 2, average = 3, large = 4, very large = 5 | |
| Policy awareness | Very unaware = 1, unaware = 2, average = 3, aware = 4, very aware = 5 | |
| Green business status | Green awareness level | Very unaware = 1, unaware = 2, average = 3, aware = 4, very aware = 5 |
| Green business scale | Herders: grassland area (less than or equal to 46.7 ha = 1, 46.7–93.3 ha = 2, 93.3–140.0 ha = 3, 140.0–186.7 ha = 4, greater than or equal to 186.7 ha = 5) | |
| Cooperative: registered capital (less than 1 million yuan = 1, 1–3 million = 2, 3–5 million = 3, 5–7 million = 4, more than 7 million = 5) | ||
| Leading enterprises: annual sales (less than 1 million yuan = 1, 1–3 million = 2, 3–5 million = 3, 5–7 million = 4, more than 7 million = 5) | ||
| Green investment efforts | Herders: breed improvement rate (less than 25% = 1, 25–50% = 2, 50–75% = 3, 75–90% = 4, greater than 95% = 5) | |
| Cooperatives: variety improvement rate (less than 25% = 1, 25–50% = 2, 50–75% = 3, 75–90% = 4, greater than 95% = 5) | ||
| Leading enterprises: modern machinery and equipment and waste treatment inputs (less than CNY 1 million = 1, CNY 1–3 million = 2, CNY 3–5 million = 3, CNY 5–7 million = 4, more than CNY 7 million = 5) | ||
| Green business situation | Herders: income from the sale of livestock products as a percentage of total income | |
| Cooperatives: livestock products acquisition volume (income) to total acquisition volume (income) ratio | ||
| Leading enterprises: the proportion of sales of livestock products to total sales | ||
| Less than 25% = 1, 25–50% = 2, 50–75% = 3, 75–90% = 4, greater than 95% = 5 | ||
| Green cost perception | Significantly improved = 1, improved = 2, fair = 3, reduced = 4, significantly reduced = 5 | |
| Profit level | Significant decrease = 1, decrease = 2, average = 3, increase = 4, significant increase = 5 | |
| Willingness to cooperate | Existing contractual relationships | Market transactions = 1, verbal agreements = 2, annual orders = 3, signed contracts = 4, share dividends = 5 |
| Cooperation expectation awareness | Strongly disagree = 1, disagree = 2, indifferent = 3, agree = 4, strongly agree = 5 | |
| Cooperation satisfaction | Very dissatisfied = 1, dissatisfied = 2, average = 3, satisfied = 4, very satisfied = 5 | |
| Characteristics of decision-making behavior | Market awareness | Respondents’ judgment on the future trend of livestock product prices and the reasons for it |
| Respondents’ performance in the face of market price fluctuations | ||
| Evaluation of existing benefit distribution methods and reasons | ||
| Forecast of market business environment | ||
| Evaluation of interest coordination and reasons for it | ||
| Five points for all clear answers, four points for four, three points for three, two points for two, one point for one | ||
| Market information acquisition channels | Interview = 1, telephone and fax = 2, email or online trading platform = 3, reference = 4, other = 5 | |
| Trading frequency | Very infrequent = 1, infrequent = 2, average = 3, frequent = 4, very frequent = 5 | |
| Circulation characteristics | Stability of sales channels | Very unstable = 1, unstable = 2, average = 3, stable = 4, very stable = 5 |
| Convenience of logistics | Very inconvenient = 1, inconvenient = 2, no feeling = 3, convenient = 4, very convenient = 5 | |
| Cold chain logistics awareness | Very unimportant = 1, unimportant = 2, indifferent = 3, important = 4, very important = 5 | |
| Interest linkage | Interest linkage mode | Very uncompact = 1, uncompact = 2, fair = 3, compact = 4, very compact = 5 |
| Interest coordination channel | Court negotiation = 1, not settled = 2, through mutual negotiation = 3, through union organization negotiation = 4, through tripartite mechanism of government, union, and employer = 5 | |
| Interest distribution dominance | All on the market decision = 1, enterprise independent decision = 2, decision by mutual agreement = 3, strictly by contract = 4, distribution through intermediary organizations = 5 | |
| Interest distribution awareness | Very unreasonable = 1, unreasonable = 2, average = 3, reasonable = 4, very reasonable = 5 |
Reliability analysis of the linkage of interest scale.
| Latent Variable | Cronbach’s A | Number of Items |
|---|---|---|
| Public policy effect | 0.846 | 4 |
| Green business status | 0.884 | 6 |
| Willingness to cooperate | 0.827 | 3 |
| Characteristics of decision-making behavior | 0.880 | 3 |
| Interest linkage | 0.866 | 4 |
| Circulation characteristics | 0.769 | 3 |
Convergent validity and combined reliability analysis of the linkage of interest scale.
| Potential Variables | Measurement Question Symbols | Factor Loading Factor | AVE | CR |
|---|---|---|---|---|
| Public policy effect | X11 | 0.772 | 0.578 | 0.846 |
| X12 | 0.772 | |||
| X13 | 0.732 | |||
| X14 | 0.764 | |||
| Green business status | X21 | 0.794 | 0.567 | 0.886 |
| X22 | 0.745 | |||
| X23 | 0.778 | |||
| X24 | 0.782 | |||
| x25 | 0.575 | |||
| X26 | 0.819 | |||
| Willingness to cooperate | X31 | 0.762 | 0.609 | 0.824 |
| X32 | 0.768 | |||
| X33 | 0.810 | |||
| Characteristics of decision-making behavior | X41 | 0.864 | 0.705 | 0.877 |
| X42 | 0.833 | |||
| X43 | 0.821 | |||
| Circulation characteristics | X51 | 0.688 | 0.526 | 0.768 |
| X52 | 0.724 | |||
| X53 | 0.761 | |||
| Interest linkage | X61 | 0.897 | 0.617 | 0.865 |
| X62 | 0.756 | |||
| X63 | 0.748 | |||
| X64 | 0.730 |
Results of the discriminant validity test.
| Public Policy Effect | Green Business Status | Willingness to Cooperate | Characteristics of Decision-Making Behavior | Interest Linkage | Circulation Characteristics | |
|---|---|---|---|---|---|---|
| Public policy effect | 0.760 | |||||
| Green business status | 0.515 | 0.753 | ||||
| Willingness to cooperate | 0.611 | 0.636 | 0.780 | |||
| Characteristics of decision-making behavior | 0.634 | 0.454 | 0.598 | 0.840 | ||
| Interest linkage | 0.660 | 0.504 | 0.621 | 0.646 | 0.786 | |
| Circulation characteristics | 0.524 | 0.461 | 0.574 | 0.469 | 0.522 | 0.725 |
Overall model goodness-of-fit.
| Fitting Index | Indicator Meaning | Evaluation Criteria | Model Fitted Values | Fitting Situation |
|---|---|---|---|---|
| CMIN/DF | Cardinality/freedom ratio | <3 | 1.474 | Ideal |
| RESEA | Root-mean-square error of approximation | <0.08 | 0.036 | Ideal |
| IFL | Incremental fitness metrics | >0.9 | 0.978 | Ideal |
| TLI | Tucker–Lewis index | >0.9 | 0.974 | Ideal |
| AGFI | Adjusted goodness-of-fit index | >0.9 | 0.908 | Ideal |
| NFI | Standard fit index | >0.9 | 0.934 | Ideal |
Structural model path coefficients and significance tests.
| Assumptions | Paths | Estimate | p | Standardization Factor | Is It Established | ||
|---|---|---|---|---|---|---|---|
| H1a | Green business status | <--- | Public policy effect | 0.663 | *** | 0.594 | Established |
| H1c | Characteristics of decision-making behavior | <--- | Public policy effect | 0.642 | *** | 0.712 | Established |
| H2b | Characteristics of decision-making behavior | <--- | Green business status | 0.072 | 0.134 | 0.09 | Not established |
| H2c | Circulation characteristics | <--- | Green business status | 0.294 | *** | 0.337 | Established |
| H4a | Circulation characteristics | <--- | Characteristics of decision-making behavior | 0.468 | *** | 0.432 | Established |
| H1b | Willingness to cooperate | <--- | Public policy effect | 0.356 | *** | 0.362 | Established |
| H2a | Willingness to cooperate | <--- | Green business status | 0.316 | *** | 0.360 | Established |
| H5a | Willingness to cooperate | <--- | Circulation characteristics | 0.318 | *** | 0.316 | Established |
| H5b | Interest linkage | <--- | Circulation characteristics | 0.112 | 0.185 | 0.096 | Not established |
| H3 | Interest linkage | <--- | Willingness to cooperate | 0.455 | *** | 0.394 | Established |
| H4b | Interest linkage | <--- | Characteristics of decision-making behavior | 0.552 | *** | 0.438 | Established |
Note: *** indicates p < 0.001.
Analysis of the overall effect of the interest linkage mechanism.
| Parameter | Estimate | Lower | Upper | p-Value | Indirect Effects as a Percentage |
|---|---|---|---|---|---|
| m1 | 0.162 | 0.031 | 0.415 | 0.002 | 21.01% |
| m2 | 0.096 | 0.026 | 0.18 | 0.002 | 12.45% |
| m3 | 0.028 | 0.004 | 0.11 | 0.004 | 3.63% |
| m4 | 0.022 | 0.041 | 0.09 | 0.34 | |
| m5 | 0.003 | −0.004 | 0.018 | 0.422 | |
| m6 | 0.003 | −0.009 | 0.015 | 0.657 | |
| m7 | 0.043 | 0.009 | 0.128 | 0.004 | 5.58% |
| m8 | 0.034 | −0.057 | 0.135 | 0.34 | |
| m9 | 0.354 | 0.143 | 0.62 | 0.001 | 45.91% |
| m10 | 0.026 | −0.038 | 0.103 | 0.419 | |
| m11 (total effect) | 0.771 | 0.634 | 0.951 | 0.001 |
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; Wang, Yali 1 ; Zhang, Xiaomeng 2 ; 1 School of Economics and Management, Inner Mongolia Agricultural University, Hohhot 010010, China;
2 School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China;