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Journal of Resources and Ecology >

2024 , Vol. 15 >Issue 3: 683 - 697

DOI: https://doi.org/10.5814/j.issn.1674-764x.2024.03.015

Tourism Environmental Behavior and Farmer’ Participation in Tourism

Influencing Factors of Farmers’ Self-organized Participation in Collective Actions in Rural Tourism of China

  • LUO Wenbin , 1 ,
  • CHU Xuelian 1 ,
  • TANG Pei 1 ,
  • GAO Yunhong 1 ,
  • SU Mingming , 2, *
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  • 1. College of Tourism, Hunan Normal University, Changsha 410081, China
  • 2. School of Ecology and Environment, Renmin University of China, Beijing 100872, China
*SU Mingming, E-mail:

LUO Wenbin, E-mail:

Received date: 2023-07-31

  Accepted date: 2023-12-31

  Online published: 2024-03-13

Supported by

The Key Research Project Funded by Hunan Provincial Department of Education(2022A0053)

The National Natural Science Foundation of China(42171232)

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Abstract

Farmers’ self-organized participation in collective actions is critical to optimize governance efficiency and ensure positive outcomes of rural tourism. To identify the underlying mechanisms, the Institutional Analysis and Development (IAD) intellectual decision extension model is selected. A mixed method approach is adopted with a questionnaire survey of 239 households and 20 semi-structured interviews in the suburban of Changsha City, Hunan Province of China. Household livelihood capital, characteristics of household head, tourism market environment, institutional rules as entry and exit rules, cognitive reform and level of land consolidation are found with significant effects. Theoretical and practical implications are discussed and future research directions are put forward.

Key words： rural tourism; farmer; self-organization; collective action; IAD intellectual decision extension model; influencing factors

Cite this article

LUO Wenbin , CHU Xuelian , TANG Pei , GAO Yunhong , SU Mingming . Influencing Factors of Farmers’ Self-organized Participation in Collective Actions in Rural Tourism of China[J]. Journal of Resources and Ecology, 2024 , 15(3) : 683 -697 . DOI: 10.5814/j.issn.1674-764x.2024.03.015

1 Introduction

As the most basic unit of governance in the national governance system, rural areas have received extensive attention from the government and the academia in terms of governance efficiency and structural optimization. The rural revitalization strategy of China puts forward the requirement of effective governance, aiming to innovate rural governance and strengthen the construction of grassroots democracy (Liu, 2020; Li et al., 2021; Zhang and Wang, 2021). Tourism, with its potential to strengthen industrial linkages at rural areas, is particularly useful to improve collective economy, improve farmers’ livelihood, reduce poverty and promote rural revitalization (Kim et al., 2016; Lor et al., 2019; Su et al., 2019; Li et al., 2021). Currently in China, the management of rural tourism are dominated by the government or business enterprises, farmers’ role is not highly revealed. With enhanced connections with external markets facilitated by rural tourism, farmers have much higher endeavor for wider participation and benefit sharing (Liu and Liu, 2016). Besides, farmers’ self-organized participation could promote the integration of internal self-generated rules of traditional rural society and the external legal system, optimize rural governance structure and enhance governance efficiency (Chen, 2019), which could in turn facilitate the sustainable development of rural tourism.
In reality, actors of collective actions are mostly disadvantaged groups of the society (Du et al., 2019). For rural residents, collective actions could create a sense of belonging and a common identity, and empower them to solve problems from a local perspective, which could support the satisfaction of local communities’ needs and enhance rural sustainability (Ostrom, 2000; Wang et al., 2018). However, collective actions in rural tourism still face governance dilemmas such as disorderly competition in the tourism market, inefficient collective actions, and issues of “free-riding”, “tragedy of the commons” and “anti-tragedy of the commons” (Hardin, 1968; Heller, 1998).
The government and the market, as executive forces, play important roles in the effective allocation of rural resources (Su et al., 2019; Liu, 2020), but the existing government-led or market-led development models tend to ignore the important roles of farmers and weaken their enthusiasm and participation. As important means of addressing efficiency and managing public affairs (Ostrom, 1990), farmers’ self-organized collective actions enable them to gain a greater voice among other stakeholders such as government and enterprises, ensure their proper sharing of benefits, enhance their supports for development and promote conservation behaviors (Hwang et al., 2012). Therefore, encouraging and supporting farmers’ self-organized participation in collective actions of rural tourism would reinforce farmers’ role in rural revitalization and sustain high-quality development of rural tourism.

2 Literature review

2.1 Rural governance and tourism governance

First used for management and political activities related to public affairs at the national level, the term of governance is no longer restricted to national political issues since 1990s, but becomes a system of social governance at different scales (Liu and Wu, 2014). As an important component of social governance, rural governance is crucial to the economic, environmental and social sustainability of rural areas (Goodwin, 1998). Previous research have looked into various issues of rural governance, including local participation in rural governance (Romano, 2019), rural governance and economic development (Chapple and Montero, 2016), rural environmental governance (Dang and Tran, 2020), governance reform (Antonio and Nicolas, 2019), urban-rural governance gap (Krishna, 2015) and so on. Despite that the collaborative multi-actor governance could solve difficulties in tourism development and bring positive socio-economic benefits to the declining rural communities (Keyim, 2018), many challenges still exist in practice (Ballesteros and Hernández, 2019).
China has large and diverse rural areas with a large rural population, many studies explored issues along the evolution of rural governance structure and governance model with practical relevance (Liu and Liu, 2016; Wang, 2018; Jiang et al., 2019; Liu, 2020). After the national rural governance reform, rural governance in China had expanded to a pluralistic actor system, including the government, farmers, the market and many other actors (Du, 2019). Various governance forms had been developed based on local practices (Xiao, 2014). However, problems still existed such as low level of farmers’ participation, insufficient institutional development, low governance efficiency and reduced effectiveness of villagers’ self-governance (Gao and Li, 2021).
With tourism being developed extensively in rural areas in China, many rural tourism destinations were challenged by governance issues, such as community participation and benefit sharing in tourism, restrictions on the property rights of land and other resources (Su et al., 2019). Therefore, tourism governance became an important area of rural governance. Among various actors including the government, the market and rural organizations, rural residents and their roles in tourism governance have received much attention in recent years. In particular, rural tourism may be ineffective if rural residents bear negative views toward tourism (Riensche et al., 2019). Therefore, promoting farmers’ autonomous governance (Zhou et al., 2021) and supporting their endogenous development (Sun et al., 2020) were identified as critical for rural places. In this context, research on farmers’ self-organization and collective actions in rural tourism deserve more attention, which would support both theoretical research and practical development of rural tourism and the revitalization of rural places. Engaging IAD intellectual decision extension model, this study aims to understand how farmers’ self-organized participation in collective actions of rural tourism is formed as intervened by both internal and exogenous factors.

2.2 Collective action and self-organization

As important analytical theories of public governance, collective action and the institutional theory of autonomous organization and governance have been studied extensively. Olson (1971) states that collective action is a cooperative form of action performed by individual actors with collective intentions to act in part, which is driven by common interests and requires simultaneous participations of members with the aim of achieving their common goals (Thomas et al., 2016). As important methods to solve rural governance and development problems, collective actions can effectively coordinate rural public goods, manage rural common resources, promote public service improvements (Liu and Ravenscroft, 2016, 2017; Takayama et al., 2018), thus promote sustainable rural development.
Self-organizational behavior refers to how occupants of public resources adopt a coordinated strategy to obtain higher gains or reduce common losses (Yan et al., 2019). Self-organized groups voluntarily combine based on relationships and trust, and set their own rules to govern their behaviors (Ostrom, 1990). In contrast to the top-down and outside-in traditional governance approach, self-organization takes a bottom-up and inside-out development approach. Though seemingly opposed, both approaches are unified and form the governance structure in rural areas (Yan et al., 2019).
The theory of self-organizational governance remains essentially a collective action issue (Liu et al., 2020). Both theories of collective actions and self-organizational governance pursue maximum outcomes through shifting from independent action to coordinated strategies with intra-organizational spontaneity. However, collective actions can occur in any organizational form, while farmer self- organizational behavior is only for farmers’ autonomous governance (Liu et al., 2020). Therefore, this study defines farmers’ self-organized collective actions of rural tourism as farmers’ collective behaviors to participate in series of rural tourism development initiatives including infrastructure development, service provision, operation and management in accordance with certain institutional rules in order to maximize the economic, social, and environmental benefits of tourism.
With rural development and social change, participation in tourism has become an important choice for community development (Schmidt et al., 2016). Community participation in tourism has been extensively researched in rural contexts to extend benefits to the poor and support sustainable rural development (Davidson and Sahli, 2015; Kim et al., 2016; Su et al., 2019; Wondirad and Ewnetu, 2019). Factors influencing farmer participation in rural tourism have been analyzed quantitatively (Bello et al., 2018), but the nature and mechanism of such participation behaviors (self-organized or external organized) are not fully understood. It is argued that self-organized collective actions, as an important component of the social capital in the sustainable livelihood framework, could enable effective governance of village affairs and promote harmonious relations among farmers (Mbaiwa and Stronza, 2010). In addition, the quality and sustainability of rural tourism is highly dependent on the support and participation of local farmers (Wan and Li, 2013). Therefore, the necessity and importance of studying the self-organized collective action of farmers in rural tourism is supported (Hwang et al., 2016).
Current research on self-organized collective actions has been expanded from conceptualization to the classification and influencing factor analysis (Markelova et al., 2009; Hwang and Stewart, 2017; Orsi et al., 2017), but limited studies strived to extend this theory to rural tourism. Particularly, with previous studies concentrated on single influencing factor of farmers’ behaviors in rural tourism, such as social capital and leadership, there is a need for a systematic analysis with multiple factors.

2.3 Institutional Analysis and Development (IAD) intellectual decision extension model

The Institutional Analysis and Development (IAD) framework developed by Ostrom (2009) has been widely used as a classic and effective framework to illuminate patterns of interactions between individual choices and a variety of institutional contexts and to evaluate outcomes (Ostrom, 2009; Bernstein et al., 2019; Grossman, 2019; Yao et al., 2021). IAD framework responds to a wider conceptualization of institution as organizations with diverse types and in different contexts (Ostrom, 2011; Grossman, 2019). In particular, it is designed to be open for theoretical constructions and applications on specific institutional issues and comparative analysis, which explains its wide application, particularly for issues concerning common resources management (Ostrom, 2011; Grossman, 2019; Yao et al., 2021).
As outlined by IAD Framework, individual’s rational choice is influenced by exogenous variables, an action stage, actors, interaction patterns, outcomes and evaluation criteria. The exogenous variables include natural material conditions, community attributes, application rules, which influence the action stage where actors made actions on the condition of certain action scenarios (Yu et al., 2017; Yao et al., 2021). In IAD framework, the action stage, composing of the action scenario and actors, provides the fundamental platform where actors observe and analyze information, take actions, engage in interaction patterns, and produce corresponding action outcomes under the influence of exogenous variables (Yao et al., 2021).
To further unveil the black box of actors’ decision- making process in the action stage, an extended framework to the original IAD with a series of internal factors incorporated to illustrate their influences and interactions is developed (Ostrom, 2005; Yu et al., 2017; Cao and Zhang, 2018; Yao et al., 2021). The intellectual decision extension model of IAD framework argues that, in addition to influences of exogenous variables such as natural physical conditions, institutional rules and socio-cultural environment, decisions are made also based on actors’ internal conditions as perceptions, expectations, feedbacks and adjustments of gaps between expected and actual results (Ostrom, 2005; Cao and Zhang, 2018; Yao et al., 2021). By depicting both internal and external factors’ influences with a focus on the action stage, the IAD extension model demonstrates the strength and feasibility to generate a more comprehensive understanding of actors’ decision-making mechanism responding to a dynamic multi-factor action scenario (Yu et al., 2017; Cao and Zhang, 2018; Yao et al., 2021).
Drawing from the above discussion, the IAD intellectual decision extension model is engaged to examine the process of farmers’ self-organized participation in collective actions of rural tourism and to compare influences of various factors. Drawing from previous studies, it is proposed that farmers’ self-organized participation in collective actions of rural tourism is jointly influenced by internal factors and exogenous factors (Cao and Zhang, 2018; Yao et al., 2021). Internal factors include farmers’ family condition, cognition reform and perception of external action status, while exogenous factors include tourism market environment, institutional rules and land consolidation (McGinnis, 2011; Cao and Zhang, 2018; Luo et al., 2019; Yao et al., 2021; Ren et al., 2022). Based on the proposed framework (Fig. 1), this study aims to explore how farmers’ self-organized participation in collective actions of rural tourism is formed as intervened by both internal and exogenous factors. Practical implications would then be discussed to enhance such participation, support effective rural governance and the sustainable development of rural tourism.
Fig. 1 The IAD intellectual decision extension model of farmers’ self-organized participation in collective actions of rural tourism

3 Research hypothesis

Drawing from the proposed framework (Fig. 1), the following research hypothesis are made.
First, as a livelihood strategy, tourism related decisions are influenced by the ownership and status of diverse livelihood capitals, including farmers’ knowledge and skill sets, labor, social influence and many more (Polski and Ostrom, 1999; Xu et al., 2019). Farmers with higher levels of physical, human, social and financial capital usually have a higher propensity to participate in tourism, while natural capital sometimes plays the opposite role (He et al., 2017). In addition, acting as the decision maker for major family issues, characteristics of the household head were found to have significant effects on rural households’ willingness and actions to join cooperatives or self-organized collectives (Karli et al., 2006). Accordingly, the following hypotheses are proposed.
Hypothesis H1: Farmers’ household livelihood capital and characteristics of household head influence farmers’ self-organized participation in collective actions of rural tourism.
Domestic scholars have paid more attention to livelihood capital in recent years, but the research on the relationship between livelihood capital and farmers’ decision-making behaviors is still relatively limited. Currently, scholars are mostly concerned with livelihood capital and farmers’ decision-making on retreat participation (Zhang, 2019), and decision-making on the transfer of agricultural land (Wang et al., 2021; Chen et al., 2022). Since the 1970s, foreign scholars have begun to pay attention to impacts of livelihood capital on the farmers’ decision-making behaviors. Early studies mainly focused on impacts of material capital and human capital on farmers’ decision-making, such as investment decisions, labor allocation, crop selection (Katherine et al., 2009). Furthermore, more research attention has been accorded to impacts of different types of livelihood capitals on the farmers’ decision-making behaviors (Newton et al., 2016; Etana et al., 2020). In terms of research regions, many research explored the relationship between livelihood capital and farmers’ decision-making behaviors in poverty-stricken areas and ecologically fragile areas (Erich et al., 2022).
In this context, about the relationship between the livelihood capital and famers’ self-organized participation, we can put forward the following hypothesis:
Hypothesis H1a: Physical capital influences farmers’ self-organized participation in collective actions of rural tourism.
Hypothesis H1b: Human capital influences farmers’ self-organized participation in collective actions of rural tourism.
Hypothesis H1c: Financial capital influences farmers’ self-organized participation in collective actions of rural tourism.
Hypothesis H1d: Natural capital influences farmers’ self- organized participation in collective actions of rural tourism.
Hypothesis H1e: Social capital affects farmers’ self- organized participation in collective actions of rural tourism.
Hypothesis H1f: Characteristics of household head influence farmers’ self-organized participation in collective actions of rural tourism.
Second, the cognitive reform variable refers to perceptions and attitudes changes brought by rural tourism development. Farmers, as rational economic men, make participation decisions based on their satisfactions with the current status of rural tourism development and thus anticipate its future development trends, and compare their actual and expected benefits and risks (Latip et al., 2018). Accordingly, the following hypothesis is proposed.
Hypothesis H2: Cognitive reform affects farmers’ self- organized participation in collective actions of rural tourism.
Third, the tourism market environment, including the resource endowment of rural destinations, environmental quality, scale of tourism market development and locational conditions of farmers’ assets, is recognized as an important factor to influence community participation in tourism (Saufi et al., 2014). With a better tourism environment, farmers would be more confident to invest in tourism and participate in collective actions in tourism. Accordingly, the following hypothesis is proposed.
Hypothesis H3: Tourism market environment affects farmers’ self-organized participation in collective actions of rural tourism.
In order to avoid farmers’ free-riding actions during tourism development, mechanisms need to be in place to guarantee the implementation of collective actions and regulate farmers’ behaviors (Kim et al., 2021). Properly designed institutional rules not only guarantee reasonable interests sharing, but also promote cooperation among farmers (Ostrom, 2011). Accordingly, the following hypothesis is proposed.
Hypothesis H4: Institutional rules influence farmers’ self- organized participation in collective actions of rural tourism.
Last, in rural destinations, farmers’ participation in rural tourism is influenced by types of land consolidation, such as land transfer, shareholding and subcontracting (Ying et al., 2020). In addition to direct participation in tourism service provision and business operation, land transfer and leasing are also important income sources at rural destinations. At the same time, land consolidation optimizes the use of rural land, improves rural infrastructure, enhances landscape quality and overall rural environment (Bonadonna et al., 2020), thus encourages farmers to participate in rural tourism. Accordingly, the following hypothesis is proposed.
Hypothesis H5: Land consolidation affects farmers’ self- organized participation in collective actions of rural tourism.

4 Methods and data

4.1 Study area

This research focuses on the suburb of Changsha City, the Capital of Hunan Province, in the central-south region of China. After initial field investigations and interviews with village residents, seven villages with relatively higher level of tourism development and community participation were shortlisted. As shown in Fig. 2, Guangming Village, Huangnipu Village, Jinchi Village, Datang Village and Shenhe Village locate on the west side of Changsha, all of which are within the Guangming Grandview Park Area, a famous rural tourism area developed by Wancheng County Government. Xifu Village and Xunlonghe Village locate on the east side of Changsha within the Rural Tourism Area developed by Changsha County Government.
Fig. 2 Location map of the study area
Among the sample village, Guangming was selected as one of “2019 National Forest Villages”, “2021 Chinese Beauty Leisure Villages” and “Hunan Provincial Rural Revitalization Demonstration Villages”. Xunlonghe Village was selected as one of “2019 China Beautiful Leisure Villages” and Xifu Village was listed among the second batch of “National Rural Tourism Priority Villages”. Therefore, all sample villages are representative rural tourism villages and results of the case study can be used for reference by other similar rural areas.
Within 30 minutes’ drive from Changsha, all selected villages have relatively higher level of tourism development serving for urban residents of Changsha. Among them, Guangming, Xifu and Xunlonghe are listed as National Important Villages of Rural Tourism of China. With similar development path of renovating residential houses into tourism accommodations through “government investment and villagers’ self-financing”, farmers’ self-organized participations in collective actions of rural tourism are prevalent in all above-mentioned villages. As shown in Table 1, current participation can be categorized into land use, village improvement, tourism development and tourism related operations.
Table 1 Existing farmers’ self-organized participations at study villages
Type of participation Farmers’ self-organized participations
Land use Land transfer Transfer land to the village to be used by tourism enterprises for project development
Land reform Transfer land to the village for land arrangement
Village improvement Environmental improvement Participate in environmental improvement actions in the village
Beautification of rural environment Participate in rural environment beautification through landscaping their own yards to support overall village environment
Tourism development Tourism project development Participate and support tourism project development of the village collectives or tourism enterprises
Festivals and events Support festivals and events organized in the village, participate in folk cultural performances
Tourism related operation Bed and Breakfast operation Invest in renovation of houses and operate B&B business
Local product sales Take initiatives to hand over local products to the village collective for unified pricing and sales
Labor share Support each other during tourism peak season

4.2 Questionnaire design and data sources

Widely used for collecting data on farmers’ attitude, perceptions and behaviors (Cao and Zhang, 2018; Yao et al., 2021), a resident questionnaire was designed based on the proposed framework and research hypothesis with measurements of dependent and independent variables as shown in Table 2.
Table 2 Definition of influencing variables of farmers’ self-organized participation in collective actions of rural tourism
Variable Description of the values Literature sources
Farmers’ participation in decision-making 1=participating, 0=not participating
(1) Farmers’ household livelihood capital and characteristics of household head (HOV) DFID, 2000;
Fang et al., 2014;
Su et al., 2019
① Physical capital
Number of rooms 1=3 rooms and below, 2=4 rooms, 3=5 rooms, 4=6 rooms, 5=7 rooms and above
② Human capital
Labor force share 1= [0, 0.2), 2= [0.2, 0.4), 3= [0.4, 0.6), 4= [0.6, 0.8), 5= [0.8, 1)*
Whether there are party members or village committee members in the family 1=yes, 0=no
③ Financial capital
Household income per year 1= less than 30000 yuan, 2=30000-49999 yuan, 3= 50000-69999 yuan, 4=70000-99999 yuan, 5=100000 yuan and above
Credit opportunities 1=very difficult, 2= difficult, 3=fair, 4=easy, 5=very easy
④ Natural capital
Arable land area Numerical value
⑤ Social capital
Social networks 1=very low, 2=low, 3=fair, 4=high, 5=very high
Social trust 1=very low, 2=low, 3=fair, 4=high, 5=very high
Social prestige 1=very low, 2=low, 3=fair, 4=high, 5=very high
Social participation 1=very low, 2=low, 3=fair, 4=high, 5=very high
⑥ Characteristics of household head
Age of household head 1=under 20 years old, 2=20-30 years old, 3=31-45 years old, 4=46-60 years old, 5=over 60 years
Gender of household head 1= male, 0=female
Education level of household head 1=below primary school, 2=primary school, 3=junior high school, 4=high school or secondary school, 5=college or above
(2) Cognitive reform variables (CR) McGinnis, 2011;
Cao and Zhang, 2018
Satisfaction 1=very dissatisfied, 2=dissatisfied, 3=fair, 4=satisfied, 5=very satisfied
Change in income 1=much less, 2=less, 3=little change. 4=some improvement, 5=great improvement
Risks 1=very high, 2=high, 3=fair, 4=low, 5=very low
(3) Tourism market environment variables (TME) Wei, 2019;
Zheng et al., 2021;
Ren et al., 2022
Close to the road 1=yes, 0=no
Distance from the central scenic area 1=very far, 2=far, 3=fair, 4=close, 5=very close
Number of visitors 1=very small, 2=small, 3=fair, 4=large, 5=very large
Infrastructure 1=very poor, 2=poor, 3=fair, 4=good, 5=very good
Tourism resources 1=very poor, 2=poor, 3=fair, 4=good, 5=very good
Village Environment 1=very poor, 2=poor, 3=fair, 4=good, 5=very good
(4) Institutional rule variables (IR) Ostrom, 2009;
Cao and Zhang, 2018
Resource ownership 1=yes, 0=no
Entry and exit mechanism 1=yes, 0=no
Punitive measures 1=yes, 0=no
Social security 1=yes, 0=no
(5) Land consolidation variables (LC) Crecente et al., 2002;
Luo et al., 2019
Whether to carry out land transfer 1=yes, 0=no
Is the land used for tourism development 1=tourist land, 0=non-tourist land
Land consolidation impact perception 1=very low, 2=low, 3=fair, 4=high, 5=very high

Note: *: “[” means to equal or bigger than; “)” means to smaller than. “Farmers’ participation in decision-making” in the fisrt line is dependent variable; The others below are independent variables.

In order to verify the applicability of the questionnaire and ensure data validity, a pre-test was conducted in June 2019 at the study site with 107 valid questionnaires obtained among 110 collected. Accordingly, the resident questionnaire was modified to improve readability and validity for the formal survey.
Official field research was conducted from July 2019 to January 2020. The research team with graduate and undergraduate students collected questionnaires at seven villages according to the stratified sampling method. The Guangming Grandview Park Area is centered around Guangming Village, so 90 questionnaires were randomly distributed in Guangming Village. 40 questionnaires were distributed in Xifu and Xunlonghe villages and 20 questionnaires were distributed respectively in the rest four villages. Finally, 250 questionnaires were collected, of which 239 were valid, with an efficiency rate of 95.6%.
In addition to the questionnaire survey, face-to-face semi-structured interviews were conducted with village committee members, party members, owner and staff of local tourism enterprises and farmers in the villages, to get well-around perspectives of the research topic and support the quantitative analysis of the questionnaire survey. Finally, 20 interviews were conducted and each interview took about 30 to 60 minutes.

4.3 Research methodology

A binary logistic model is used for hypothesis testing. The dependent variable is defined as y. y=0 refers to that farmers choose not to participate; y=1 refers to that farmers choose to participate. Assume that the linear function of whether farmers self-organize to participate in collective actions of rural tourism is $f\text{(}x\text{)}={{\beta }_{\text{0}}}+{{\beta }_{\text{1}}}{{x}_{\text{1}}}+{{\beta }_{\text{2}}}{{x}_{\text{2}}}+\ldots +{{\beta }_{p}}{{x}_{p}}$, then the probability of farmers’ participation is ${{P}_{i}}=\frac{\text{exp(}f\text{(}x\text{))}}{\text{1}+\text{exp(}f\text{(}x\text{))}}$, and the probability of non-participation is (1-Pi), and the occurrence ratio is $odds=\frac{{{P}_{i}}}{1-{{P}_{i}}}$, which is $\text{ln(}odds\text{)}=$ $\text{ln}\frac{{{P}_{i}}}{\text{1}-{{P}_{i}}}=f\text{(}x\text{)}$obtained after logarithmic transformation. Referring to the definition of independent variables in Table 1, the form of the function is set as:
$\begin{align} & \ln \frac{{{P}_{i}}}{1-{{P}_{i}}}={{\beta }_{0}}+{{\beta }_{1}}HOV++{{\beta }_{2}}CR+{{\beta }_{3}}TME+ \\ & \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ {{\beta }_{4}}IR+{{\beta }_{5}}LC+\mu \\ \end{align}$
where Pi denotes the probability of farmers’ self-organized participation in collective actions of rural tourism; HOV represents “farmers’ household livelihood capital and characteristics of household head” variables; CR represents “cognitive reform” variables; TME represents “tourism market environment” variables; IR represents “institutional rules” variables; LC represents “land consolidation” variables; and μ is a random disturbance term.

5 Research findings

5.1 Sample characteristics

The overall sample character is shown in Table 3. Majority of respondents are aged between 31 and 60 years. More than half respondents have higher than senior high school education and 67.78% respondents have not received any training. 61.51% households have an annual income of more than 70000 yuan, which is relatively high compared with nearby rural regions. Family income sources are quite diverse, including income directly from tourism and indirectly from other related employments and land reuse in tourism projects.
Table 3 Sample characteristics of the resident questionnaire survey
Variables Number Percentage (%)
Gender Male 124 51.88
Female 115 48.12
Age Lower than 20 4 1.67
20-30 48 20.08
31-45 69 28.87
46-60 79 33.05
Above 60 39 16.32
Annual household income
(yuan)		 lower 30000 26 10.88
30000-49999 28 11.72
50000-69999 38 15.90
70000-99999 57 23.85
100000 above 90 37.66
Education Primary school or below 49 19.71
Junior high school 76 28.85
Senior high or equivalent 60 25.96
College and above 54 25.48
Training No training 162 67.78
Tourism related training 52 21.76
Agricultural training 20 8.37
Other trainings 5 2.09
Income sources* Tourism service 31 12.97
Employment in tourism 28 11.72
Land rental 37 15.48
Other jobs in company 65 27.20
Government subsidy 6 2.51
Farming (planting or breeding) 54 22.59
Worker in cities 131 54.81
Business (operating shops) 62 25.94

Note: * The item of “income source” is multiple choice.

5.2 Model testing

SPSS 20.0 is used to perform model tests. Due to the large number of independent variables, the “forward step (conditional)” regression method is used to reduce the interference between variables. After 10 iterations, the results are shown in Table 4 and Table 5. The overall model holds at the 0.01 level of significance, indicating that the model is reasonable. The Cox & Snell R2 is 0.652, which is greater than 0.6. The Nagelkerke R2 is 0.890, which is greater than 0.8. Thus, the overall fit of the logistic model is validated.
Table 4 Comprehensive test of model coefficients
Item Chi-square df Sig.




Steps 4.405 1 0.036
Block 252.414 10 <0.001
Models 252.414 10 <0.001
Table 5 Summary of models
Steps -2 log-likelihood value Cox & Snell R2 Nagelkerke R2
10 63.168e⃰ 0.652 0.890

Note: e⃰: The estimation terminates at iteration number 9 because the range of change in parameter estimation is less than 0.001.

5.3 Regression results

After 10 iterations, variables with significant influences are included in the regression model and insignificant variables are removed. Table 6 and Table 7 illustrates the overall regression results of the model. Among groups of independent variables, 11 subdivided variables pass the significance test and are integrated into the logistic stepwise regression model (Table 6). Meanwhile, 19 insignificant variables are removed from the model (Table 7).
Table 6 Total regression results of the model
Independent variable Subdivided variables B S.E Wald df Sig.
Household livelihood capital and characteristics of household head Labor force share 2.129 0.456 21.773 1 <0.001
Whether there are party members or village committee members in the family 1.741 0.869 4.016 1 0.045
Social networks 1.891 0.536 12.431 1 <0.001
Age of household head -2.334 0.631 13.700 1 <0.001
Cognitive reform Satisfaction 1.938 0.615 9.923 1 0.002
Change in income 1.795 0.673 7.104 1 0.008
Tourism market environment Tourism resources 2.301 0.648 12.587 1 <0.001
Village environment 2.656 0.632 17.672 1 <0.001
Institutional rules Entry and exit mechanism 1.982 0.798 6.161 1 0.013
Land consolidation Land use 1.555 0.784 3.931 1 0.047
Constants -40.190 7.425 29.302 1 <0.001
Table 7 Insignificant variables
Independent variable Subdivided variables Score df Sig.
Household livelihood capital and characteristics of household head Number of rooms 0.033 1 0.856
Household income 0.380 1 0.538
Credit opportunities 0.108 1 0.742
Arable land area 0.077 1 0.781
Social trust 0.001 1 0.981
Social prestige 0.074 1 0.786
Social participation 1.021 1 0.312
Gender of household head 1.147 1 0.284
Education level of household head 0.035 1 0.851
Cognitive reform Risks 0.066 1 0.797
Tourism market environment Close to the road 0.660 1 0.417
Distance from the central scenic area 2.137 1 0.144
Number of visitors 1.990 1 0.158
Infrastructure 0.243 1 0.622
Institutional rules Resource ownership 0.406 1 0.524
Punitive measures 0.170 1 0.680
Social security 0.698 1 0.403
Land consolidation Whether to carry out land transfer 0.001 1 0.981
Land consolidation impact perception 0.912 1 0.340

5.4 Analysis of significant influencing factors

5.4.1 Household livelihood capital and characteristics of household head

Among variables of “household livelihood capital and characteristics of household head”, human capital, social capital and the age of household head have impacts on farmers’ self-organized participation in collective actions of rural tourism. Thus, H1 is partially supported.
Among the human capital variables, “labor force share” and “whether there are party members or village committee members” have significant positive effects on farmers’ self-organized participation (coefficients of 2.129 and 1.741). Thus, hypothesis H1e is partially supported.
Among social capital variables, “social network” is significantly and positively correlated with farmers’ self-organized participation (coefficient of 1.891). Thus, hypothesis H1a is partially supported. As rural communities emphasize “geographical relationship” and “kinship” (Lu and Li, 2018), farmers form a network of interpersonal circles based on their proximity to each other. When individuals are located at the center of the social network, they receive more information and have less uncertainty when making decisions. As experiences of serving on the village committee is an important social capital in rural areas, the survey results show that farmers with such experiences are more motivated to participate in collective actions of rural tourism and have a wider range of participation.
As a labor-intensive industry, rural tourism involves a series of activities such as tourism operation, service provision, resource utilization and protection. All such activities require both quantity and quality of human capital. The factors of “labor force share” reflects the proportion of the working population relative to the total household size and its higher value indicates that the household has more surplus labor. In the Chinese rural governance system, village committee members and party members usually take the leading position with higher responsibility in village issues. As revealed by semi-structured interviews, village committee members and party members usually take the lead in rural tourism participation to encourage other residents. For example, the first batch of B&B developments in Guangming and Xifu villages were led by party members and village committee members.
The household head is usually the decision maker for household issues. It is identified that the age of household head has a significant negative effect on farmers’ self-organized participation (coefficient of -2.334), indicating that the older the household head is, restricted by his conservative attitude and lower education level, the weaker his or her willingness to participate in collective actions of rural tourism might be. Therefore, hypothesis H1f is partially supported.

5.4.2 Cognitive reform

Among variables reflecting farmers’ cognitive change, satisfaction with tourism (coefficient of 1.938) and changes in household income due to tourism (coefficient of 1.795) positively affect farmers’ self-organized participation in collective actions in tourism. Thus, hypothesis H2 is partially supported. The survey results show that most farmers are satisfied with the current status of rural tourism, and more than half respondents agree that tourism development has increased their income. Furthermore, most respondents have an open and friendly attitude towards tourists, indicating that they are generally supportive of tourism development in their villages.

5.4.3 Tourism market environment

Among variables reflecting “tourism market environment”, both tourism resources (coefficients of 2.301) and living environment (coefficients of 2.656) demonstrate significant positive effects on farmers’ self-organized participation in collective actions of rural tourism. Thus, hypothesis H3 is partially supported.
This research show that farmers involved in tourism generally have high evaluations of the quality of tourism resources. Majority of respondents believe that the local tourism is not well developed at present, but has potential for future development. Farmers not involved in tourism usually do not have high recognition of resources provision of their villages for tourism development, thus they are not willing to participate.
Majority of respondents acknowledge the quality improvement of living environment in the village, which is resulted from village improvement projects initiated by Changsha City since 2006 to improve infrastructure, transportation, village landscape in the suburban area. Therefore, it can be concluded that in addition to enhance tourist experiences, improvements in the living environment could also increase farmers’ confidence in tourism development and prompt them to participate in the collective actions of rural tourism.
As one farmer aged 70 years commented:
“Tourism is important to our village. Now we have better living environment, the roads are paved, rivers are clean, garbage are classified. That is very good. Currently tourism is still of small scalel, but I think we have potential to develop and residents will benefit more from tourism. But we lack of funding for development.”

5.4.4 Institutional rules

Among several variables of “institutional rules” (shown in Table 2), the entry and exit mechanism (coefficient of 1.982) is found to be positively related to farmers’ self-organized participation in collective actions of rural tourism. Thus, hypothesis H4 is partially supported.
With the mean value of 0.32, farmers’ awareness of ways to participate in tourism participation is low, indicating the current lack of information channels. In addition, an evident information gap is identified between tourism participants and non-participants. As revealed by interviews, local B&B owners clearly indicate their awareness of procedures for joining the B&B development cooperative and the related cooperation rules before operating the B&B. However, most non-tourism participants are not aware of the existence of the B&B development cooperative.

5.4.5 Land consolidation

Land is the basic resource for rural development and a critical component of rural tourism. Among variables of “land consolidation”, whether land is used for tourism development (coefficient of 1.555) positively influences farmers’ self-organized participation in collective actions of rural tourism. It is found that farmers with land used for tourism development are more willing to join rural tourism on their own initiation. Therefore, hypothesis H5 is partially supported.
Despite that most villages have carried out land improvement projects, a few village groups and relocated farmers are not included the latest land preparation due to remote geographical locations. According to interviews, such unprepared lands are usually transferred to village cooperatives at villagers’ voluntary participation and used for tourism development, such as fruit picking farms. As commented by a village committee member, farmers are usually willing to invest land with relatively low agricultural benefits in tourism and take the initiative to participate in relevant collective actions.

5.4.6 Summary of the influencing mechanism

Based on IAD intellectual decision extension model, Figure 3 illustrates influences of internal and external factors on farmers’ self-organized participation in collective actions of rural tourism. Such participation is found to be intrinsically constrained by social capital and externally regulated by institutional rules. Therefore, farmers’ ability to obtain information and their understanding of relevant rules significantly affect farmers’ self-organized participation. Farmers, with higher evaluation of tourism resources of the village, have demonstrated higher sense of local identity and satisfaction and confidence to participate in rural tourism. The tourism uses of land, the most important livelihood resource, directly affect farmers’ positive response to tourism development, which also leads to their self-organized participation in rural tourism.
Fig. 3 IAD intellectual decision extension model of farmers’ self-organized participation in collective actions of rural tourism
For the degree of influence, tourism market environment demonstrates a higher degree of influence compared with institutional rules and land consolidation. It indicates that creating a favorable tourism market environment not only could increase destination attractiveness to tourists, but also could encourage farmers’ self-organized collective actions in tourism.

6 Discussion

6.1 Theoretical implications

Rural tourism triggers more actors into rural governance and encourages farmers’ self-organized and collective behaviors either facilitated by external organizations or formed spontaneously. As a new phenomenon that facilitates farmers’ participation and improves the quality and efficiency of rural governance, farmers’ self-organized collective actions of rural tourism are influenced by a variety of factors in a collective manor. Responding to the urgent need to understand its formation process and influencing mechanisms, as shown in Fig. 4, this study engages the IAD intellectual decision extension model and strives to construct a systematic research framework to measure influences of internal and external factors on farmers’ self-organized participation decisions. Engaging both qualitative and quantitative methods, this study not only qualitatively summarizes the overall formation process of farmers’ self-organized collective action in rural tourism destinations, but also quantitatively analyzes the direction and magnitude of influences of different factors on farmers’ participation decisions.
Fig. 4 Theoretical model of farmers’ self-organized participation in collective actions of rural tourism
It is revealed that among internal factors, social and human capital and farmers’ cognitive reform have positive influences on farmers’ self-organized participation decisions, which are consistent with results of related studies (He et al., 2017; Hwang and Stewart, 2017; Liu et al., 2018; Xu et al., 2019). Different from previous studies, physical, financial and natural capital have no evident influence. Such difference may be caused by specific situations of the study area as revealed through the questionnaire survey and interviews. In terms of physical capital, the average number of rooms owned by surveyed farmers is around three. As revealed in resident interviews, most farmers do not have extra rooms to invest in tourism. For natural capital, most farmers have already transferred their lands and receive income by collecting land rental, so the use of arable land is not easily changed. In terms of financial capital, supported through the national poverty alleviation strategy, village collectives and party organizations provide direct assistances to poor households and include them in tourism organizations. Therefore, the financial capital owned by farmers does not exhibit a significant impact on their participation in decision-making.
External factors, as the tourism market environment, institutional rules and land consolidation variables exhibit positive influences on farmers’ participation decisions. Consistent with previous studies, the higher the farmers’ cognitive evaluation of their village’s tourism resources and living environment, the more active they would participate in tourism (Yang et al., 2005; He and Ning, 2020). In addition, farmers with better understanding of the mechanisms for tourism participation demonstrates higher initiation to participate (Kala and Bagri, 2018) and farmers with land used for tourism show higher evaluation of tourism, thus higher willingness to participate (Kim et al., 2021).
Results reveal that all researched villages have formed self-organized collectives under the impetus of rural tourism development and national policies in land transfer and environmental management. Such synergistic governance between external-organization and internal self-organizations promotes the development of rural tourism and effective rural governance at the study area. Moreover, supported by the local government and village committees and guided by management regulations of enterprises and farmers’ self- organizations, the embedment of legal rules to existing rules of self-government is enhanced. Since China has a traditional rural governance mechanism characterized by geographic and kinship ties and rural ethics for more than 2000 years, modern legal systems have encountered various obstacles in the embedding process into the rural society (Chen, 2019). In this context, internally developed self-organizations can help embed such “foreign rules” into traditional rural governance structure and improve the quantity and quality of farmers’ participation (Zhang, 2020).
Therefore, it is argued that rural tourism not only could enhance rural livelihoods and ensure equitable sharing of resources and opportunities (Su et al., 2019), but also serves as the endogenous impetus for the reconstruction and modernization of rural governance (Zhou and Yao, 2019). Such changes to rural governance would in turn reinforce farmers’ sense of participation and prompt their self-organization to form rural tourism collectives. In this way, a virtuous cycle could be formed (Huang et al., 2020; Xiang, 2021).

6.2 Practical implications

Drawing from the above research results, following suggestions are proposed to encourage farmers’ self-organized participation in collective actions of rural tourism in the study area from external and internal perspectives. Such suggestions may also be of reference to other rural areas with tourism development in China and other regions.
In addition to its relevance to tourism attractiveness of the village, tourism resources and living environment could enhance farmers’ confidence to participate in tourism. Therefore, landscaping projects can be engaged to further improve the village environment. In addition, identification of new tourism resources, in particular from cultural and social aspects, and value interpretation of such resources can be further enhanced.
Second, institutional rules play important roles in shaping farmers’ participation decisions. Therefore, institutional arrangements to encourage farmers’ self-organizations and facilitate co-governance of different stakeholders would be further developed. First, responding to the information gap examined in the study, different communication channels, including traditional village meetings and online platforms, should be built up to facilitate effective information dissemination and support the expression of farmers’ voices. Second, rules and regulations should be set up to guide operations and efficacy of such self-organizations. Moreover, collaboration of such self-organizations with other actors, including the government and tourism enterprises, should be realized. In this way, a decentralized and multi-actor governance model for rural areas can be constructed to serve the needs for rural tourism and other development initiatives.
In addition, although influences of land use factors on farmers self-organized behavior is not substantial in this study, the surveyed villages still have land use problems such as abandoned land transfer projects, delayed land rent payments and idle land. Such issues could discourage farmers from participating in tourism. Therefore, it is suggested measures as setting up flexible arrangements of land transfer projects, standardizing procedures for land transfer and tourism land use, can be established by the local government to resolve such land use issues.
Among internal factors, the age of household head is the only factor with negative effects on farmers’ participation decisions. Survey results show that rural households heads are generally of an elder age cohort with capacity constraints to participate in tourism. Considering their important roles in family decisions, communication through various channel can be organized to enhance their understanding of tourism and reduce their concerns for participation. Moreover, responding to limited trainings obtained by farmers, technical trainings of various types can be arranged to enhance their capacity for tourism participation.
Moreover, as shown in the research, current village residents are predominantly elders and females, which are common for rural areas in China (Su et al., 2019). Measures should be developed to improve the overall human capital of the study area. For example, education and training opportunities of tourism service skills and related professional skills can be provided to enhance their capacity to work in the tourism sector. It is particularly so for women, who serve in tourism widely. On the other hand, a supportive platform can be established by the local government to attract investments to rural tourism related projects from local talents or external enterprises. With more jobs and development opportunities, young residents can be attracted back to the village, which would enhance the overall human capital. Moreover, catering for the needs of young residents to settle down in rural areas, supportive services need to be developed, particularly in education and medical care (Su et al., 2019).

7 Conclusions

Rural tourism was traditionally developed and managed by external organizations such as the local government, government agencies and business enterprises (Romano, 2019). Local farmers usually faced many obstacles to participate (Su et al., 2019). Prompted by rural tourism, some farmers began to take initiatives to set up rural tourism organizations to facilitate tourism participation in a collective mode, which is a new phenomenon that should be further researched and would potentially become an important trend of development in rural China.
Therefore, this study engages the IAD intellectual decision extension model to analyze influences of internal and external factors on farmers’ self-organized participation in collective actions of rural tourism. On-site interviews and questionnaires were used for data collection and the hypotheses proposed were tested using a binary logistic regression model. The results indicated that farmers’ participation decisions were jointly influenced by a series of internal and external factors and the direction and magnitude of each factor varies. Research results verify the feasibility of the IAD intellectual decision extension model in understanding farmers’ self-organizational behaviors and the formation mechanism in rural tourism participation. Practical implications are generated to enhance farmers’ self-organizational behaviors and improve rural governance for rural destinations in China and elsewhere.
Farmers’ decision making is a dynamic and complex process with a wider variety of influencing factors (Maart-Noelck and Musshoff, 2013; Xie and Wu, 2019). Though, strived to integrate internal and external factors in the assessment framework, this study could not exhaust all. Additional factors influencing farmers’ self-organized behavior could be further assessed, such as tourism development stages, farmers’ personal characteristics, physical environment and local culture. In particular, influences of different types of institutional rules in addition to boundary rules examined in this study could be further assessed. Comparative research can be conducted in different regions at different development stages to improve the generalizability of research findings and shed lights on other occasions. In addition, from a longitudinal perspective, the formation and evolution process of such behavior over time could be explored in future research. Moreover, this study was primarily taken from farmers’ perspectives. Considering the multi-actor involvement in rural tourism, future research could draw in different types of actors and explore farmers’ self-organization behavior and the multi-actor governance for the sustainability of rural tourism and the revitalization of rural areas.

Acknowledgements

The authors gratefully acknowledge the references consolidation and words modification work from Liu Yangjie and Zhou Yinjie and the mapping modification from Kang Zhiwen.

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