Next Article in Journal
Unravelling the Role of Biochemical Compounds within the Hydrothermal Liquefaction Process of Real Sludge Mixtures
Previous Article in Journal
Analysis of Multinational Builders’ Corruption Based on Evolutionary Game from the Perspective of International Reputation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 5
10.3390/su16051765
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Intention to Transition: Natural Rubber Smallholders Navigating the Risks of Farming

by
Suriansyah
*,
Nurliza
,
Eva Dolorosa
,
Rosyadi
and
Denah Suswati
Faculty of Agriculture, Tanjungpura University, Pontianak 78124, Indonesia
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(5), 1765; https://doi.org/10.3390/su16051765
Submission received: 26 January 2024 / Revised: 16 February 2024 / Accepted: 19 February 2024 / Published: 21 February 2024
Browse Figures
Review Reports Versions Notes

Abstract

:
This study delves into the decision-making dynamics of Indonesian rubber farmers amidst a significant agricultural transition from traditional rubber farming to diverse agricultural practices. Anchored in the Theory of Planned Behavior (TPB) and Protection Motivation Theory (PMT), this research elucidates the multifaceted interplay of the psychological, social, and environmental factors influencing these transitions. Utilizing Structural Equation Modeling (SEM) to analyze data from structured interviews and questionnaires, this study presents a nuanced understanding of how a higher awareness of the risks associated with rubber farming negatively impacts farmers’ attitudes, adherence to social norms, and perceived behavioral control. The findings reveal that while heightened risk understanding and threat appraisal motivate a shift towards alternative agricultural practices, factors like community norms and perceived behavioral control significantly deter this transition. This research contributes a novel integration of the TPB and PMT in the context of agricultural decision making, offering pivotal insights for stakeholders and policymakers aiming to foster sustainable agricultural practices and navigate the complex socio-economic landscape of Indonesia’s agricultural sector.

1. Introduction

Indonesia, as one of the World’s largest rubber producers, hosts a vast number of rubber farms that significantly contribute to the global supply. The number of rubber farms and their scale of production have evolved over time, reflecting changes in global market demands, technological advancements, and shifts towards sustainable farming practices [1,2]. Yet, current evolutions within the nation’s agricultural framework signify a transformative phase, where the traditional emphasis on rubber cultivation is diversifying towards other commodities [3,4]. The rubber industry, once a linchpin of both Indonesia’s and the global trade frameworks, is grappling with the changing preferences of farmers exploring diverse agricultural avenues [5]. This dynamic pivot, driven by a confluence of economic, social, and environmental factors, has cascading implications for sustainable agricultural practices and global commodity markets [6,7]. While exact numbers fluctuate, the trend indicates a diversification in farm sizes and a gradual increase in the adoption of practices aimed at enhancing rubber production’s sustainability. The asset value of these farms varies, but collectively, they represent a substantial economic sector within Indonesia, underscoring the importance of understanding the nuances of rubber farming in the country.
While rubber is not indigenous to Indonesia, its inherent adaptability has solidified its role within the country, and by extension, the global agricultural matrix [8,9]. The burgeoning interest in varied commodities, catalyzed by evolving global demand and economic incentives, is challenging the rubber sector’s traditional dominance [10]. Nevertheless, the unparalleled properties of natural rubber, which synthetic variants cannot fully emulate, emphasize its enduring global importance [11,12]. Such dynamics underscore the necessity for strategic adaptations to both sustain the rubber industry and embrace the diversifying preferences of farmers [13,14].
Recent trends unveil a nuanced narrative: a subtle reduction in rubber-centric agricultural spaces, coupled with an uptick in farmers’ inclination towards a broader spectrum of commodities [2,15]. The somewhat muted productivity in the rubber sector, often linked to the use of less optimal rubber clones and the aging of plantations, has ramifications that span beyond regional confines, affecting global supply chains [16,17]. Although considerable research has engaged with agricultural shifts at various scales, a holistic, global understanding of these transitions from rubber to diverse commodities remains a relatively uncharted domain.
While numerous studies have explored agricultural shifts on various scales, a comprehensive global analysis of the transition from rubber to diverse commodities remains largely untapped [18]. This study seeks to address this oversight by illuminating the myriad elements guiding Indonesian rubber farmers’ transitions and delving into the socio-economic and environmental dimensions of these changes. By emphasizing these agricultural transformations, the goal is to offer a profound understanding to global stakeholders, facilitating informed decisions that promote a balanced and sustainable future in the realm of agricultural commodities. This study distinguishes itself from the existing literature by integrating the Theory of Planned Behavior and Protection Motivation Theory to investigate the multifaceted decision-making processes of Indonesian rubber farmers. Despite the extensive research conducted on agricultural sustainability, few studies have explored these combined theoretical perspectives in understanding the behavioral intentions towards sustainable practices in the context of Indonesian agriculture. This approach provides a nuanced exploration of the motivations, challenges, and facilitators of sustainable agricultural adoption, offering a unique contribution to the fields of environmental psychology and sustainable development.
As Indonesia witnesses a shift in its agricultural practices, with a notable move away from traditional rubber farming to a more varied array of agricultural commodities, the need arises to delve deeper into the factors influencing these transitions [3]. This transformation, fueled by both internal motivations and external pressures, marks a pivotal moment in the nation’s agricultural history [19]. It calls for an in-depth examination of the decision-making processes of Indonesian rubber farmers, a demographic at the heart of this change. In response to this need, our study introduces the Theory of Planned Behavior (TPB) and the Protection Motivation Theory (PMT) as the foundational frameworks for understanding these shifts. By applying the TPB and PMT, we aim to unravel the complex interplay of attitudes, social norms, perceived risks, and coping mechanisms that drive farmers’ choices in transitioning from rubber to a more diverse agricultural practice. This theoretical approach not only sheds light on the psychological underpinnings of these transitions but also paves the way for more nuanced insights into the socio-economic and environmental dimensions of these agricultural shifts.
This research is strategically anchored in the use of the Theory of Planned Behavior (TPB) and the Protection Motivation Theory (PMT) to decode the multifaceted decision-making processes of Indonesian rubber farmers. The choice of these two theories is deliberate and pivotal. The TPB, formulated by Ajzen [20], offers a robust psychological framework that explicates the role of individual attitudes, subjective norms, and perceived behavioral control in shaping intentions and behaviors. This theory is particularly relevant in understanding the agricultural domain as it allows for an exploration of how farmers’ attitudes towards rubber farming (ATT), the influence of social and community norms (SN), and their sense of control over farming practices (PBC) play a crucial role in their decision to either persist with or transition from traditional rubber farming. Such insights are essential in comprehending the complex interplay of personal beliefs, societal pressures, and perceived abilities, as underscored in studies by Borges et al. [21] and Daxini et al. [22].
Concurrently, the PMT, introduced by Rogers [23], complements the TPB by focusing on the cognitive processes involved in risk evaluation and coping strategies. It is particularly germane in agricultural contexts where farmers are frequently confronted with environmental- and market-related risks. The PMT emphasizes the importance of Understanding of Risk (UR), through which farmers’ appraisals of threats (TA) and their coping strategies (CA) are examined. This theory is crucial for unraveling how farmers perceive ecological challenges and their belief in their ability to adapt effectively to these challenges, a notion supported by the works of Aghdasi et al. [24] and Luu et al. [25]. By integrating the TPB and PMT, this study aims to provide a comprehensive understanding of the psychological and practical dimensions of farming decisions. The TPB sheds light on how internal and social factors influence farmers’ willingness to adopt change [26], while the PMT offers insights into how they assess and respond to external threats and challenges [27]. This dual theoretical approach is instrumental in dissecting the economic and environmental factors driving agricultural transitions, as discussed by Ataei et al. [28] and Laporte [29] in terms of economic aspects and Eakin et al. [30] and Magdoff et al. [31] in terms of environmental ones. Ultimately, the fusion of these theories enables a nuanced understanding of the determinants influencing farmers’ transitions to sustainable practices to be generated, addressing a critical gap in the existing agricultural research.
In this analysis, transition is characterized as a complex process that encompasses both the diversification of agricultural production and the embrace of sustainable practices. Here, diversification is portrayed as the expansion of agricultural activities beyond the traditional confines of rubber cultivation, whereas sustainable practices are identified by their environmental sustainability, economic viability, and social responsibility. Interviews conducted across a diverse cohort of farmers revealed a broad spectrum of interpretations, ranging from diversification to full sustainability, which have been systematically categorized to reflect this variance. For enhanced clarity within this analytical framework, attitude specifically denotes the perceptions and sentiments of farmers towards the adoption of sustainable agricultural practices. This term encapsulates their optimism, satisfaction, and the perceived advantages associated with transitioning from conventional to more ecologically sustainable practices. Thus, a better attitude signifies an elevated positive perception and an increased willingness to undertake sustainable practices.
In essence, this study seamlessly integrates the TPB and PMT, crafting a cohesive analytical framework. It rigorously traces the trajectory of rubber farming’s transformation and its emerging alternatives. Through this intricate exploration, the research not only seeks to fill prevailing knowledge gaps but also aims to generate practical insights that can shape future agricultural policies and strategies. A visual representation of this study’s conceptual foundation can be found in Figure 1. To further elucidate the theoretical underpinnings of the hypothesized pathways proposed in this study, it is essential to draw upon both the Theory of Planned Behavior (TPB) and Protection Motivation Theory (PMT). These frameworks collectively offer a robust lens through which the decision-making processes of Indonesian rubber farmers regarding sustainable agricultural practices can be understood. The TPB posits that an individual’s behavior is directly influenced by their intention to perform the behavior, which is in turn shaped by attitudes, subjective norms, and perceived behavioral control. The PMT complements this by suggesting that individuals’ motivations to engage in protective behaviors, such as adopting sustainable practices, are influenced by their perceptions of threat severity, vulnerability, response efficacy, and self-efficacy. By integrating these theories, this study aims to comprehensively explore how farmers’ attitudes, perceived social pressures, and control beliefs contribute to their intentions and actions towards sustainability. This theoretical framework not only grounds our hypotheses but also aligns with empirical evidence, indicating the pivotal role of these constructs in environmental behavior change among agricultural communities.
  • Hypotheses Formulation:
(1)
H1: Understanding of Risk
H1a: A higher Understanding of Risk (UR) is negatively related to Attitude (ATT).
H1b: A higher Understanding of Risk (UR) is negatively related to Subjective Norm (SN).
H1c: A higher Understanding of Risk (UR) is negatively related to Perceived Behavioral Control (PBC).
(2)
H2: Attitude
H2a: A better Attitude (ATT) is negatively related to Threat Appraisal (TA).
H2b: A better Attitude (ATT) is negatively related to Coping Appraisal (CA).
H2c: A better Attitude (ATT) is negatively related to Intention to Transition (IT).
(3)
H3: Subjective Norms
H3: A higher Subjective Norm (SN) is negatively related to Intention to Transition (IT).
(4)
H4: Perceived Behavioral Control
H4a: A higher Perceived Behavioral Control (PBC) is negatively related to Threat Appraisal (TA).
H4b: A higher Perceived Behavioral Control (PBC) is negatively related to Coping Appraisal (CA).
H4c: A higher Perceived Behavioral Control (PBC) is negatively related to Intention to Transition (IT).
(5)
H5: Threat Appraisal
H5: A higher Threat Appraisal (TA) is positively related to Intention to Transition (IT).
(6)
H6: Coping Appraisal
H6: A higher Coping Appraisal (CA) is positively related to Intention to Transition (IT).

2. Materials and Methods

This study acknowledges the critical role that the profitability of rubber production and the financial viability of equity capital play in influencing farmers’ behaviors. Despite the absence of detailed price and cost changes within the main text, an overview of the recent trends indicates fluctuations in rubber prices and the associated costs of production that impact the financial performance of rubber farms. Investment needs, driven by technological updates and market demands, further complicate the economic landscape for rubber farmers. An analysis of these financial dimensions is essential to generate a comprehensive understanding of the shifts within Indonesia’s rubber sector.
To capture data with utmost precision, structured interviews are chosen as the primary conduit [32]. Each interview, underpinned by a carefully designed questionnaire, will be conducted in the region’s native tongue, ensuring clear communication and resonance with the farming community [33]. The range of variables embedded in the questionnaire, spanning from risk understanding to transition intentions, is culled from exhaustive scholarly reviews to ensure comprehensive coverage (Table 1).
The questionnaire covers various areas, including demographic characteristics, and various factors from the PMT and TPB (Appendix A). For a representative snapshot of West Kalimantan’s farming demographic, a cluster random sampling technique will be employed [53]. This ensures a diverse cross-section of participants. A semantic differential scale, extending from 1 to 7, will be incorporated, allowing respondents to have a nuanced gradient to capture their perspectives.
This research will harness the analytical capabilities of SEM to elucidate the relationships among observed and latent variables. In this study, the independent variables include Understanding of Risk, Attitude, Subjective Norms, Perceived Behavioral Control, Threat Appraisal, and Coping Appraisal, while Intention to Transition stands as the dependent variable.
Subsequently, the present study utilized a random distribution method to distribute 300 questionnaires among potential participants, resulting in 291 completed responses. In accordance with the best practices in measurement modeling, this research employed a measurement model consisting of 35 observed variables. This approach necessitated a sample size of n = 280 (35 × 8) to ensure adequate statistical power [54,55]. In addressing the selection and representativeness of the 300 survey respondents, this study employed a stratified random sampling method to ensure a wide coverage of rubber farming practices across different regions in Indonesia. The approach aimed to achieve a representative sample, factoring in variations in farm size, geographic location, and production techniques, thereby enhancing the validity of our findings. The methodology section further elaborates on the criteria used for respondent selection, underlining the study’s commitment to capturing a comprehensive snapshot of the rubber farming community’s perspectives.
Navigating the intricate dimensions of farming transitions in West Kalimantan, Indonesia, this study harnesses the quantitative rigor of Structural Equation Modeling (SEM) [56]. Grounded in the foundational principles of the Theory of Planned Behavior (TPB) and Protection Motivation Theory (PMT) [28,57,58], this research provides an in-depth analytical lens into the evolving determinants shaping the decisions of rubber farmers.
The primary aim of the study is to investigate the cause-and-effect dynamics between latent variables. This is achieved by employing AMOS 22 with the maximum likelihood estimation method for Structural Equation Modeling (SEM) analysis [59]. The SEM framework incorporates seven latent variables, including one exogenous variable, Understanding of Risk, and six endogenous variables: Attitude, Subjective Norms, Perceived Behavioral Control, Threat Appraisal, Coping Appraisal, and Intention to Transition.
The model’s suitability was assessed through six key measurement metrics. These include the Incremental Fit Index (IFI), Tucker–Lewis Index (TLI), Comparative Fit Index (CFI), Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), and the Root Mean Square Error of Approximation (RMSEA). For a model to be considered adequately fitting, the IFI, TLI, and CFI values should surpass the 0.90 threshold. The GFI and AGFI scores need to be above 0.80, reflecting a robust fit similar to the significance of the R2 value in multiple linear regression analysis. Additionally, RMSEA values below 0.07 are indicative of a favorable fit [60].
Ethical fidelity remains paramount throughout the research journey. From safeguarding participant confidentiality to rigorously obtaining informed consents, every research phase is infused with an unwavering commitment to respecting participants’ rights and the distinctive cultural and socio-economic tapestry of West Kalimantan’s farming ecosystem [61].
Yet, embracing academic transparency requires acknowledging potential limitations. From the nuanced spectrum of farmers’ decision-making processes to inherent response biases and the challenges of broader generalizations, the research recognizes these constraints. Through a balance of academic precision and practical adaptability, this methodology aspires to weave insights poised to influence and reshape agricultural transition policies and practices.

3. Results

Exploring the economic productivity of labor on rubber farms reveals a complex picture, where the potential for off-farm employment emerges as a significant factor. This study found a notable trend of farmers diversifying their economic activities beyond rubber production, driven by the comparative profitability of alternative employment. This shift not only reflects the broader economic challenges facing the rubber industry but also highlights the adaptive strategies of farmers in response to these challenges. Quantitative data on the migration from rubber farming to other economic activities underscore the dynamic nature of rural livelihoods in Indonesia.
Figure 2 illustrates the result of the Structural Equation Modeling (SEM) used to evaluate the dynamics of Indonesian rubber farmers transitioning to other agricultural commodities. The SEM analysis, grounded in the Theory of Planned Behavior (TPB) and Protection Motivation Theory (PMT), revealed that all hypotheses held significant relationships. Additionally, Table 2 showcases the descriptive statistics for each variable, illustrating the nuances in farmers’ perceptions.
The clarity of the descriptive statistics presented in Table 2 is enhanced through an elaborate elucidation of factor loadings and their significance within the context of this study. Factor loadings are instrumental in determining the extent to which each variable contributes to the fundamental factors identified as influential in shaping farmers’ perceptions. Pronounced factor loading indicates a significant association with the respective factor, thereby shedding light on the complexities of farmers’ attitudes and their decision-making processes regarding the transition.
The model fitness indicators, such as the Incremental Fit Index (IFI), Tucker–Lewis Index (TLI), and Comparative Fit Index (CFI), surpassed the recommended threshold of 0.90, affirming the robustness of the hypothesized model against the observed data. The Goodness of Fit Index (GFI) and Adjusted Goodness of Fit Index (AGFI) stood at 0.842 and 0.820, respectively, further validating the model’s effectiveness. Moreover, the Root Mean Square Error of Approximation (RMSEA) was recorded at 0.044, falling below the commonly advised limit and indicating a favorable model fit (Table 3).
Finally, the direct, indirect, and total effects of the variables on farmers’ intention to transition from rubber farming are comprehensively detailed in Table 4. This analysis elucidates the complex interplay of individual attitudes, subjective norms, perceived control, risk understanding, and coping strategies in shaping the farmers’ transition intentions.

4. Discussion

This discussion is initiated with a synthesis of the pivotal findings, emphasizing the impact of risk comprehension, attitudes, and perceived behavioral control on the transition intentions among farmers. This narrative strategy facilitates a seamless transition into a detailed analysis, laying a comprehensive foundation for interpreting the insights gleaned from the statistical tables.
The study’s integration of the Theory of Planned Behavior and Protection Motivation Theory reveals intricate relationships among various factors influencing Indonesian rubber farmers’ decision-making processes. A notable finding is the negative influence of a higher Understanding of Risk (UR) on Attitude (ATT), Subjective Norm (SN), and Perceived Behavioral Control (PBC). This trend indicates that as rubber farmers grow more aware of the inherent risks in their profession, such as market volatility, environmental challenges, and changes in global demand for natural rubber, their overall outlook towards continuing rubber farming becomes less favorable. This diminished enthusiasm is further compounded by decreased social pressure to adhere to traditional farming practices and a lowered sense of control over their agricultural outcomes. The results align with the broader literature on risk perception in agriculture, as highlighted in studies like that conducted by Aghdasi et al. [24], which underscore the profound impact of risk understanding on farmers’ attitudes and behaviors.
Intriguingly, Attitude (ATT) was negatively related to both Threat Appraisal (TA) and Coping Appraisal (CA), and surprisingly, it also showed a negative relationship with Intention to Transition (IT). This suggests that farmers with a more favorable view of rubber farming are less likely to perceive significant threats or feel capable of coping with them, and consequently, they are less inclined to consider transitioning to other forms of agriculture. This may be attributed to a sense of satisfaction or contentment with their current farming practices, possibly due to established market channels, expertise in rubber farming, or community identity linked to this traditional occupation. This phenomenon resonates with the findings of Keshavarz and Karami [37], who discuss the impact of satisfaction and optimism on farmers’ reluctance to change their agricultural practices.
Subjective Norm (SN)’s negative impact on Intention to Transition (IT) is particularly telling. It suggests that social environment and community norms play a crucial role in shaping individual decisions. In rural agricultural communities, where farming practices are often deeply entwined with cultural and social identities, the approval and support for rubber farming exert a strong influence on individual farmers’ choices. This social aspect is critical for policymakers and agricultural extension services aiming to encourage transitions towards more sustainable or diversified agricultural practices.
The relationship between Perceived Behavioral Control (PBC) and both Threat Appraisal (TA) and Coping Appraisal (CA) sheds light on the internal dynamics of decision making in farming. Farmers who feel they have greater control over their farming practices and potential transitions are less likely to perceive threats and feel a need to develop coping strategies. This sense of control might stem from various factors, such as access to resources, knowledge, and experience, influencing their inclination to stick with known and mastered practices rather than venturing into new, uncertain agricultural territories.
Contrastingly, higher Threat Appraisal (TA) positively influenced Intention to Transition (IT), revealing a complex relationship between threat perception and adaptive behavior. This finding suggests that recognizing the significant risks associated with continuing rubber farming, such as economic uncertainties or environmental degradation, can motivate farmers to consider alternative agricultural practices. This perception of threat as a catalyst for change is supported by the work of Delfiyan et al. [45], which emphasizes the role of threat perception in agricultural decision-making processes.
Similarly, a positive relationship between Coping Appraisal (CA) and Intention to Transition (IT) indicates an adaptive mindset among farmers. Those who believe in their ability to manage and cope with challenges are more likely to view the transition to other agricultural practices not as a risk but as an opportunity for growth, innovation, and development. This perspective is crucial in an era where agriculture faces numerous challenges, including climate change, market fluctuations, and technological advancements.
While this study provides comprehensive insights into the dynamics of agricultural decision making in West Kalimantan, its focus on this specific region limits its generalizability across Indonesia. Future research should consider a broader geographic scope to validate these findings and include qualitative methods to gain deeper insights into the individual and collective experiences of farmers. Investigating other factors that might influence these variables, such as broader economic conditions, technological advancements, and policy changes, would provide a more holistic view of agricultural transition in Indonesia.
The findings of this study carry significant implications for the theory and practice of sustainable agriculture among rubber farmers. Theoretically, this research contributes to the environmental behavior literature by demonstrating the applicability of the TPB and PMT in a novel context, thereby enriching our understanding of farmers’ decision-making processes in the face of environmental and economic challenges. Practically, the insights garnered highlight the necessity for targeted interventions that address the specific attitudes, subjective norms, and perceived controls influencing farmers’ transitions to sustainable practices. Policy recommendations emerging from this study emphasize the development of supportive infrastructures, educational programs, and incentives that align with the identified drivers of sustainable agricultural adoption. Such measures are vital for facilitating a broader transition towards sustainability in the agricultural sector, with potential benefits extending beyond environmental conservation to encompass economic resilience and social well-being.
In conclusion, the marginal contribution of this research is twofold. Firstly, it extends the application of the TPB and PMT to the domain of sustainable agriculture among rubber farmers in Indonesia, a context that has been underexplored in existing studies. Secondly, by uncovering the complex interplay of the psychological, social, and environmental factors influencing farmers’ behaviors, this study offers actionable insights for policymakers, practitioners, and researchers dedicated to promoting sustainable agricultural practices. The integration of theoretical frameworks with empirical findings provides a comprehensive understanding of the barriers and enablers of sustainability transitions, thereby paving the way for more effective and context-specific interventions.

5. Conclusions

This research, grounded in the Theory of Planned Behavior (TPB) and the Protection Motivation Theory (PMT), provides a comprehensive understanding of the factors influencing Indonesian rubber farmers’ decisions to transition from traditional rubber farming to diverse agricultural practices. The findings from this study offer significant insights into the complex interplay of the psychological and practical factors in the agricultural domain.
This study revealed that higher understanding of risk negatively impacts farmers’ attitudes towards rubber farming, their adherence to social norms, and their perceived behavioral control. This underscores the crucial role of risk perception in agricultural decision making, resonating with the findings from the contemporary literature. Farmers’ attitude towards rubber farming, influenced by their satisfaction and optimism, was found to be negatively related to their threat and coping appraisal, and unexpectedly, to their intention to transition. This suggests a deeply rooted preference for traditional practices, potentially due to established market relationships or a sense of community identity.
Furthermore, this study highlighted the significant influence of subjective norms on the farmers’ intention to transition. The approval and support from the community serve as a strong deterrent against transitioning away from traditional practices, emphasizing the need for community-level interventions in any transition strategy. The perceived behavioral control, reflecting farmers’ confidence in managing farming challenges, also showed a negative relationship with both threat appraisal and coping appraisal, as well as their intention to transition. This suggests that farmers confident in their current practices are less likely to perceive threats and thus less inclined to change.
Contrary to expectations, higher threat appraisal positively influenced intention to transition. This indicates that recognizing significant risks associated with continuing rubber farming can motivate farmers to consider alternative agricultural practices. Similarly, a higher coping appraisal positively influenced intention to transition, suggesting that farmers who feel capable of managing threats are more open to exploring new agricultural opportunities.
This study’s focus on West Kalimantan, while providing in-depth insights, limits its generalizability across Indonesia. Future research should expand the geographic scope and potentially incorporate qualitative methods to capture a more nuanced understanding of farmers’ experiences and decision-making processes. Investigating other factors such as economic conditions, technological advancements, and policy changes will provide a more holistic view of agricultural transition in Indonesia.
The conclusions drawn from this investigation provide refined insights into the dynamics of rubber farming in Indonesia, highlighting the critical role of economic factors, environmental concerns, and policy frameworks in shaping sustainable agricultural transitions. Contrary to the broad generalizations often found in the literature, this study delineates specific pathways through which rubber farmers navigate the complexities of sustainability, profitability, and resilience. The nuanced understanding gleaned from this research not only enriches the academic discourse on agricultural sustainability but also offers practical guidance for policymakers, stakeholders, and practitioners aiming to support rubber farmers in their transition towards more sustainable practices. It is through such detailed and context-aware conclusions that this study aims to bridge the gap between theoretical research and on-the-ground agricultural realities.
In conclusion, this study contributes significantly to our understanding of the determinants influencing Indonesian rubber farmers’ transitions to sustainable practices. The integration of the TPB and PMT offers a nuanced perspective on how internal, social, and external factors shape these decisions. These insights are vital for developing informed strategies and policies to support sustainable agricultural transitions in Indonesia, aligning with global sustainability goals and the evolving dynamics of the agricultural sector.

Author Contributions

Methodology, S., N., E.D. and R.; validation, N., E.D. and R.; formal analysis, N.; data curation, S.; writing—original draft, S., N., E.D. and R.; writing—review and editing, S.; supervision, N., E.D., R. and D.S.; project administration, S. and D.S.; funding acquisition, S. and D.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the Faculty of Agriculture at Tanjungpura University. Approval Code: 6662/UN22.3/PT.01.05/2023. Approval Date: 3 September 2023.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to ethical restriction.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

  • Detailed Structured Interview Questionnaire
  • Participant Information
Name (optional):
Age:
Years of Experience in Rubber Farming:
Education :
Location/Area of Farming:
Primary Access of Information:
  • Instructions
Please indicate your response by circling the number that best represents your feelings or perceptions on the scale provided (1–7).
  • Questions
  • Section 1: Understanding of Risk (UR)
1.1.
How do you perceive the overall risk in rubber farming?
1.2.
How often do you encounter risks or threats in your rubber farming activities?
1.3.
How severe do you think the consequences of the risks in rubber farming are?
1.4.
How vulnerable do you feel to the risks associated with rubber farming?
1.5.
How much do you think the risks in rubber farming can affect your livelihood?
  • Section 2: Attitude towards Rubber Farming (ATT)
2.1.
How satisfied are you with the current returns from rubber farming?
2.2.
How optimistic are you about the future of rubber farming?
2.3.
How likely are you to recommend rubber farming to others?
2.4.
How beneficial do you find rubber farming for your financial stability?
2.5.
How do you perceive the stability of the rubber market?
  • Section 3: Subjective Norms (SN)
3.1.
How supportive is your community towards rubber farming?
3.2.
How much do you think people who are important to you would approve or disapprove of your transition from rubber farming?
3.3.
How motivated are you to comply with these social expectations?
3.4.
How much do your peers influence your decisions related to rubber farming?
3.5.
How often do you discuss rubber farming challenges and transitions with your community or family?
  • Section 4: Perceived Behavioral Control (PBC)
4.1.
How confident are you in managing the challenges associated with rubber farming?
4.2.
How much control do you believe you have over transitioning from rubber farming?
4.3.
How confident are you in your ability to transition if you decided to do so?
4.4.
How easy or difficult is it for you to adopt new farming practices?
4.5.
How capable are you of learning and adapting to a new type of farming?
  • Section 5: Threat Appraisal (TA)
5.1.
How significant do you perceive the threats (e.g., market fluctuations, diseases, climate change impacts) to rubber farming?
5.2.
How concerned are you about the impact of these threats on your farming?
5.3.
How likely do you think these threats will affect your rubber farming in the future?
5.4.
How prepared do you feel to manage these threats effectively?
5.5.
How much do you think these threats can impact your overall livelihood?
  • Section 6: Coping Appraisal (CA)
6.1.
How incapable do you feel in managing and mitigating the threats to rubber farming?
6.2.
How ineffective do you believe the coping strategies are in managing the threats to rubber farming?
6.3.
How uncertain are you in your ability to implement these coping strategies effectively?
6.4.
How much lack of support do you face (e.g., financial, social, informational) in managing these threats?
6.5.
How often do you find yourself struggling to cope with threats in rubber farming?
  • Section 7: Intention to Transition (IT)
7.1.
How strongly are you considering transitioning from rubber farming to another type of farming or occupation?
7.2.
How willing are you to invest in learning and transitioning to a new type of farming?
7.3.
How prepared are you to face the challenges that might come with transitioning to a new type of farming?
7.4.
How optimistic are you about finding success in a new farming venture or occupation?
7.5.
How soon are you considering making a transition from rubber farming?
  • Additional Comments:
Please provide any additional comments or insights you have regarding rubber farming and potential transitions to other commodities or occupations.

References

  1. Kamaludin, R. Competitiveness and Exports Sustainability of the Indonesian Natural Rubber. Sriwij. Int. J. Dyn. Econ. Bus. 2018, 2, 85–98. [Google Scholar]
  2. Zuhdi, F. The Indonesian Natural Rubber Export Competitiveness in Global Market. Int. J. Agric. Syst. 2021, 8, 130–139. [Google Scholar] [CrossRef]
  3. Feintrenie, L.; Schwarze, S.; Levang, P. Are Local People Conservationists? Analysis of Transition Dynamics from Agroforests to Monoculture Plantations in Indonesia. Ecol. Soc. 2010, 15, 37. [Google Scholar] [CrossRef]
  4. van Noordwijk, M.; Tata, H.L.; Xu, J.; Dewi, S.; Minang, P.A. Segregate or Integrate for Multifunctionality and Sustained Change Through Rubber-Based Agroforestry in Indonesia and China. Agrofor.-Future Glob. Land Use 2012, 9, 69–104. [Google Scholar]
  5. Kubitza, C.; Krishna, V.V.; Alamsyah, Z.; Qaim, M. The Economics Behind an Ecological Crisis: Livelihood Effects of Oil Palm Expansion in Sumatra, Indonesia. Hum. Ecol. 2018, 46, 107–116. [Google Scholar] [CrossRef]
  6. Jafari, Y.; Othman, J.; Witzke, P.; Jusoh, S. Risks and Opportunities From Key Importers Pushing for Sustainability: The Case of Indonesian Palm Oil. Agric. Food Econ. 2017, 5, 13. [Google Scholar] [CrossRef]
  7. Putri, E.I.K.; Dharmawan, A.H.; Hospes, O.; Yulian, B.E.; Amalia, R.; Mardiyaningsih, D.I.; Kinseng, R.A.; Tonny, F.; Pramudya, E.P.; Rahmadian, F.; et al. The Oil Palm Governance: Challenges of Sustainability Policy in Indonesia. Sustainability 2022, 14, 1820. [Google Scholar] [CrossRef]
  8. Michon, G.; de Foresta, H. The Indonesian Agro-Forest Model. In Conserving Biodiversity Outside Protected Areas: The Role of Traditional Agro-Ecosystems; IUCN: Gland, Switzerland, 1995; pp. 90–106. [Google Scholar]
  9. Peluso, N.L. Rubber Erasures, Rubber Producing Rights: Making Racialized Territories in West Kalimantan, Indonesia. Dev. Chang. 2009, 40, 47–80. [Google Scholar] [CrossRef]
  10. Therville, C.; Feintrenie, L.; Levang, P. Farmers’ Perspectives About Agroforests Conversion to Plantations in Sumatra. Lessons Learnt From Bungo District (Jambi, Indonesia). For. Trees Livelihoods 2011, 20, 15–33. [Google Scholar] [CrossRef]
  11. Cornish, K. Alternative Natural Rubber Crops: Why Should We Care? Technol. Innov. 2017, 18, 244–255. [Google Scholar] [CrossRef]
  12. Mooibroek, H.; Cornish, K. Alternative Sources of Natural Rubber. Appl. Microbiol. Biotechnol. 2000, 53, 355–365. [Google Scholar] [CrossRef] [PubMed]
  13. Kurnia, D.; Marimin; Haris, U. Sudradjat Critical Issue Mapping of Indonesian Natural Rubber Industry Based on Innovation System Perspectives. IOP Conf. Ser. Earth Environ. Sci. 2020, 443, 012036. [Google Scholar] [CrossRef]
  14. Warren-Thomas, E.; Dolman, P.M.; Edwards, D.P. Increasing Demand for Natural Rubber Necessitates a Robust Sustainability Initiative to Mitigate Impacts on Tropical Biodiversity. Conserv. Lett. 2015, 8, 230–241. [Google Scholar] [CrossRef]
  15. Yoga Prasada, I.; Dhamira, A. The Competitiveness of Natural Rubber by Exporting Countries in the Global Market. E3S Web Conf. 2021, 305, 02006. [Google Scholar] [CrossRef]
  16. Venkatachalam, P.; Geetha, N.; Sangeetha, P.; Thulaseedharan, A. Natural Rubber Producing Plants: An Overview. Afr. J. Biotechnol. 2013, 12, 1297–1310. [Google Scholar] [CrossRef]
  17. Wildayana, E. Challenging Constraints of Livelihoods for Farmers in the South Sumatra Peatlands, Indonesia. Bulg. J. Agric. Sci. 2017, 23, 894–905. [Google Scholar]
  18. Varkkey, H.; Tyson, A.; Choiruzzad, S.A.B. Palm Oil Intensification and Expansion in Indonesia and Malaysia: Environmental and Socio-Political Factors Influencing Policy. For. Policy Econ. 2018, 92, 148–159. [Google Scholar] [CrossRef]
  19. Penot, E. From Shifting Cultivation to Sustainable Jungle Rubber: A History of Innovations in Indonesia. In Voices from the Forest; Routledge: Abingdon, UK, 2010; pp. 577–599. [Google Scholar]
  20. Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process 1991, 50, 179–211. [Google Scholar] [CrossRef]
  21. Borges, J.A.R.; Oude Lansink, A.G.J.M.; Marques Ribeiro, C.; Lutke, V. Understanding Farmers’ Intention to Adopt Improved Natural Grassland Using the Theory of Planned Behavior. Livest. Sci. 2014, 169, 163–174. [Google Scholar] [CrossRef]
  22. Daxini, A.; O’Donoghue, C.; Ryan, M.; Buckley, C.; Barnes, A.P.; Daly, K. Which Factors Influence Farmers’ Intentions to Adopt Nutrient Management Planning? J. Environ. Manag. 2018, 224, 350–360. [Google Scholar] [CrossRef]
  23. Rogers, R.W. Cognitive and Physiological Processes in Fear Appeals and Attitude Change: A Revised Theory of Protection Motivation. In Social Psychology: A Source Book; Social Psychophysiology, Guilford Press: New York, NY, USA, 1983; pp. 153–176. [Google Scholar]
  24. Aghdasi, M.; Omidi Najafabadi, M.; Mirdamadi, S.M.; Farajollah Hosseini, S.J. Analysis of Environmental Behaviors and Institutional Drought Management Mechanisms and Their Impact on the Development of Sustainable Livelihood of Borkhar Farmers: Application of Protection Motivation Theory (PMT). Village Dev. 2023, 26, 137–165. [Google Scholar] [CrossRef]
  25. Luu, T.A.; Nguyen, A.T.; Trinh, Q.A.; Pham, V.T.; Le, B.B.; Nguyen, D.T.; Hoang, Q.N.; Pham, H.T.T.; Nguyen, T.K.; Luu, V.N.; et al. Farmers’ Intention to Climate Change Adaptation in Agriculture in the Red River Delta Biosphere Reserve (Vietnam): A Combination of Structural Equation Modeling (SEM) and Protection Motivation Theory (PMT). Sustainability 2019, 11, 2993. [Google Scholar] [CrossRef]
  26. Denashurya, N.I.; Nurliza; Dolorosa, E.; Kurniati, D.; Suswati, D. Overcoming Barriers to ISPO Certification: Analyzing the Drivers of Sustainable Agricultural Adoption among Farmers. Sustainability 2023, 15, 16507. [Google Scholar] [CrossRef]
  27. Badsar, M.; Moghim, M.; Ghasemi, M. Analysis of Factors Influencing Farmers’ Sustainable Environmental Behavior in Agriculture Activities: Integration of the Planned Behavior and the Protection Motivation Theories. Environ. Dev. Sustain. 2023, 25, 9903–9934. [Google Scholar] [CrossRef]
  28. Ataei, P.; Gholamrezai, S.; Movahedi, R.; Aliabadi, V. An Analysis of Farmers’ Intention to Use Green Pesticides: The Application of the Extended Theory of Planned Behavior and Health Belief Model. J. Rural. Stud. 2021, 81, 374–384. [Google Scholar] [CrossRef]
  29. Laporte, P.D.S. Investigating Predictors of Perceptions and Behaviors of Members of the International Conservation Community: The Case of Palm Oil Sustainability. Master’s Thesis, Natural Resources and Environmental Management, University of Hawaiʻi at Mānoa, Mānoa, HI, USA, 2020. [Google Scholar]
  30. Eakin, H.; York, A.; Aggarwal, R.; Waters, S.; Welch, J.; Rubiños, C.; Smith-Heisters, S.; Bausch, C.; Anderies, J.M. Cognitive and Institutional Influences on Farmers’ Adaptive Capacity: Insights Into Barriers and Opportunities for Transformative Change in Central Arizona. Reg. Environ. Chang. 2016, 16, 801–814. [Google Scholar] [CrossRef]
  31. Magdoff, F.; Foster, J.B.; Buttel, F.H. Hungry for Profit: The Agribusiness Threat to Farmers, Food, and the Environment; NYU Press: New York, NY, USA, 2000; ISBN 1583673946. [Google Scholar]
  32. Kallio, H.; Pietilä, A.; Johnson, M.; Kangasniemi, M. Systematic Methodological Review: Developing a Framework for a Qualitative Semi-structured Interview Guide. J. Adv. Nurs. 2016, 72, 2954–2965. [Google Scholar] [CrossRef]
  33. Weller, S.C. Structured Interviewing and Questionnaire Construction. In Handbook of Methods in Cultural Anthropology; Altamira Press Walnut Creek: Walnut Creek, CA, USA, 1998; pp. 363–407. [Google Scholar]
  34. Ghanian, M.; Ghoochani, O.M.; Dehghanpour, M.; Taqipour, M.; Taheri, F.; Cotton, M. Understanding Farmers’ Climate Adaptation Intention in Iran: A Protection-Motivation Extended Model. Land Use Policy 2020, 94, 104553. [Google Scholar] [CrossRef]
  35. Wang, Y.; Liang, J.; Yang, J.; Ma, X.; Li, X.; Wu, J.; Yang, G.; Ren, G.; Feng, Y. Analysis of the Environmental Behavior of Farmers for Non-Point Source Pollution Control and Management: An Integration of the Theory of Planned Behavior and the Protection Motivation Theory. J. Environ. Manag. 2019, 237, 15–23. [Google Scholar] [CrossRef] [PubMed]
  36. Badsar, M.; Karami, R. Understanding Farmers’ Response to Renewable Energy: An Application of Protection Motivation Theory. J. Agric. Sci. Technol. 2021, 23, 987–1000. [Google Scholar]
  37. Keshavarz, M.; Karami, E. Farmers’ Pro-Environmental Behavior Under Drought: Application of Protection Motivation Theory. J. Arid. Environ. 2016, 127, 128–136. [Google Scholar] [CrossRef]
  38. Sarkar, A.; Wang, H.; Rahman, A.; Qian, L.; Memon, W.H. Evaluating the Roles of the Farmer’s Cooperative for Fostering Environmentally Friendly Production Technologies-a Case of Kiwi-Fruit Farmers in Meixian, China. J. Environ. Manag. 2022, 301, 113858. [Google Scholar] [CrossRef]
  39. Daxini, A.; Ryan, M.; O’Donoghue, C.; Barnes, A.P. Understanding Farmers’ Intentions to Follow a Nutrient Management Plan Using the Theory of Planned Behaviour. Land Use Policy 2019, 85, 428–437. [Google Scholar] [CrossRef]
  40. Heong, K.L.; Escalada, M.M. Quantifying Rice Farmers’ Pest Management Decisions: Beliefs and Subjective Norms in Stem Borer Control. Crop Prot. 1999, 18, 315–322. [Google Scholar] [CrossRef]
  41. Aghdasi, M.; Omidi Najafabadi, M.; Mirdamadi, S.M.; Farajollah Hoseini, S.J. Expanding Protection Motivation Theory: Investigating Farmers’ Pro-Environmental Behavior and Their Impact on a Sustainable Alternative Livelihood under Drought. J. Agric. Sci. Technol. 2022, 24, 305–320. [Google Scholar]
  42. Nguyen, N.; Drakou, E.G. Farmers Intention to Adopt Sustainable Agriculture Hinges on Climate Awareness: The Case of Vietnamese Coffee. J. Clean. Prod. 2021, 303, 126828. [Google Scholar] [CrossRef]
  43. Neisi, M.; Bijani, M.; Abbasi, E.; Mahmoudi, H.; Azadi, H. Analyzing Farmers’ Drought Risk Management Behavior: Evidence From Iran. J. Hydrol. 2020, 590, 125243. [Google Scholar] [CrossRef]
  44. Zobeidi, T.; Yaghoubi, J.; Yazdanpanah, M. Farmers’ Incremental Adaptation to Water Scarcity: An Application of the Model of Private Proactive Adaptation to Climate Change (MPPACC). Agric. Water Manag. 2022, 264, 107528. [Google Scholar] [CrossRef]
  45. Delfiyan, F.; Yazdanpanah, M.; Forouzani, M.; Yaghoubi, J. Farmers’ Adaptation to Drought Risk Through Farm–Level Decisions: The Case of Farmers in Dehloran County, Southwest of Iran. Clim. Dev. 2021, 13, 152–163. [Google Scholar] [CrossRef]
  46. Wens, M.L.K.; Mwangi, M.N.; van Loon, A.F.; Aerts, J.C.J.H. Complexities of Drought Adaptive Behaviour: Linking Theory to Data on Smallholder Farmer Adaptation Decisions. Int. J. Disaster Risk Reduct. 2021, 63, 102435. [Google Scholar] [CrossRef]
  47. Hunter, E.; Jenkins, A.; Mark-Herbert, C. When Fear of Failure Leads to Intentions to Act Entrepreneurially: Insights From Threat Appraisals and Coping Efficacy. Int. Small Bus. J. Res. Entrep. 2021, 39, 407–423. [Google Scholar] [CrossRef]
  48. Nabara, I.S.; Man, N.; Kamarulzaman, N.H.; Sulaiman, Z. Smallholder Oil Palm Farmers’ Pro-Adaptation Behaviour Under Climate Impact Scenario: Application of Protection Motivation Theory. Clim. Dev. 2021, 13, 475–483. [Google Scholar] [CrossRef]
  49. Puntsagdorj, B.; Orosoo, D.; Huo, X.; Xia, X. Farmer’s Perception, Agricultural Subsidies, and Adoption of Sustainable Agricultural Practices: A Case from Mongolia. Sustainability 2021, 13, 1524. [Google Scholar] [CrossRef]
  50. Mosavian, S.H.; Rostami, F.; Tatar, M. Modeling Farmers’ Intention to Water Protection Behavior: A New Extended Version of the Protection Motivation Theory. J. Environ. Psychol. 2023, 90, 102036. [Google Scholar] [CrossRef]
  51. Bazrafkan, K.; Valizadeh, N.; Khannejad, S.; Kianmehr, N.; Bijani, M.; Hayati, D. What Drives Farmers to Use Conservation Agriculture? Application of Mediated Protection Motivation Theory. Front. Psychol. 2022, 13, 991323. [Google Scholar] [CrossRef] [PubMed]
  52. Gebrehiwot, T.; van der Veen, A. Farmers Prone to Drought Risk: Why Some Farmers Undertake Farm-Level Risk-Reduction Measures While Others Not? Environ. Manag. 2015, 55, 588–602. [Google Scholar] [CrossRef] [PubMed]
  53. Sedgwick, P. Cluster Sampling. BMJ Br. Med. J. 2014, 348, g1215. [Google Scholar] [CrossRef]
  54. Dattalo, P. Determining Sample Size Using Fast and Slow Thinking. J. Soc. Serv. Res. 2018, 44, 180–190. [Google Scholar] [CrossRef]
  55. Siddiqui, K. Heuristics for Sample Size Determination in Multivariate Statistical Techniques. World Appl. Sci. J. 2013, 27, 285–287. [Google Scholar] [CrossRef]
  56. Mueller, R.O.; Hancock, G.R. Structural Equation Modeling. In The Reviewer’s Guide to Quantitative Methods in the Social Sciences; Hancock, G.R., Mueller, R.O., Stapleton, L.M., Eds.; Routledge: New York, NY, USA, 2018; Volume 2, ISBN 9781135172992. [Google Scholar]
  57. Kaur, A.; Kumar, V.; Kaushik, A.K. Vegetable and Fruit Growers’ Intention to Use Biopesticides in India: Application of TPB and HBM Models. J. Environ. Plan. Manag. 2023, 1–24. [Google Scholar] [CrossRef]
  58. Pakmehr, S.; Yazdanpanah, M.; Baradaran, M. Investigating the Behavior of Farmers in the Face of Water Scarcity. J. Appl. Sociol. 2021, 32, 135–154. [Google Scholar] [CrossRef]
  59. Maydeu-Olivares, A. Maximum Likelihood Estimation of Structural Equation Models for Continuous Data: Standard Errors and Goodness of Fit. Struct. Equ. Model. 2017, 24, 383–394. [Google Scholar] [CrossRef]
  60. Schermelleh-Engel, K.; Moosbrugger, H.; Müller, H. Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods Psychol. Res. Online 2003, 8, 23–74. [Google Scholar]
  61. Steinke, E.E. Research Ethics, Informed Consent, and Participant Recruitment. Clin. Nurse Spec. 2004, 18, 88–97. [Google Scholar] [CrossRef] [PubMed]
  62. Hair, J.F.; Black, W.C.; Babin, B.J. Multivariate Data Analysis: A Global Perspective, 7th ed.; Global Edition; Pearson Education: London, UK, 2010; ISBN 9780135153093. [Google Scholar]
  63. Hu, L.; Bentler, P.M. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Struct. Equ. Model. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  64. Gefen, D.; Straub, D.; Boudreau, M.-C. Structural Equation Modeling and Regression: Guidelines for Research Practice. Commun. Assoc. Inf. Syst. 2000, 4, 7. [Google Scholar] [CrossRef]
  65. Steiger, J.H. Understanding the Limitations of Global Fit Assessment in Structural Equation Modeling. Pers. Individ. Dif. 2007, 42, 893–898. [Google Scholar] [CrossRef]
Sustainability 16 01765 g001
Figure 1. Model Framework.
Figure 1. Model Framework.
Sustainability 16 01765 g001
Sustainability 16 01765 g002
Figure 2. SEM result.
Figure 2. SEM result.
Sustainability 16 01765 g002
Table 1. Literature review.
Table 1. Literature review.
ConstructsItemsMeasuresSupporting References
UR: Understanding of RiskUR1How do you perceive the overall risk in rubber farming?[27,34,35]
UR2How often do you encounter risks or threats in your rubber farming activities?
UR3How severe do you think the consequences of the risks in rubber farming are?
UR4How vulnerable do you feel to the risks associated with rubber farming?
UR5How much do you think the risks in rubber farming can affect your livelihood?
ATT: Attitude ATT1How satisfied are you with the current returns from rubber farming?[25,36,37]
ATT2How optimistic are you about the future of rubber farming?
ATT3How likely are you to recommend rubber farming to others?
ATT4How beneficial do you find rubber farming for your financial stability?
ATT5How do you perceive the stability of the rubber market?
SN: Subjective NormSN1How supportive is your community towards rubber farming?[38,39,40]
SN2How much do you think people who are important to you would approve or disapprove of your transition from rubber farming?
SN3How motivated are you to comply with these social expectations?
SN4How much do your peers influence your decisions related to rubber farming?
SN5How often do you discuss rubber farming challenges and transitions with your community or family?
PBC: Perceived Behavioral ControlPBC1How confident are you in managing the challenges associated with rubber farming?[41,42,43]
PBC2How much control do you believe you have over transitioning from rubber farming?
PBC3How confident are you in your ability to transition if you decided to do so?
PBC4How easy or difficult is it for you to adopt new farming practices?
PBC5How capable are you of learning and adapting to a new type of farming?
TA: Threat AppraisalTA1How significant do you perceive the threats (e.g., market fluctuations, diseases, climate change impacts) to rubber farming?[44,45,46]
TA2How concerned are you about the impact of these threats on your farming?
TA3How likely do you think these threats will affect your rubber farming in the future?
TA4How prepared do you feel to manage these threats effectively?
TA5How much do you think these threats can impact your overall livelihood?
CA: Coping AppraisalCA1How incapable do you feel in managing and mitigating the threats to rubber farming?[47,48,49]
CA2How ineffective do you believe the coping strategies are in managing the threats to rubber farming?
CA3How uncertain are you in your ability to implement these coping strategies effectively?
CA4How much lack of support do you face (e.g., financial, social, informational) in managing these threats?
CA5How often do you find yourself struggling to cope with threats in rubber farming?
IT: Intention to TransitionIT1How strongly are you considering transitioning from rubber farming to another type of farming or occupation?[25,36,50,51,52]
IT2How willing are you to invest in learning and transitioning to a new type of farming?
IT3How prepared are you to face the challenges that might come with transitioning to a new type of farming?
IT4How optimistic are you about finding success in a new farming venture or occupation?
IT5How soon are you considering making a transition from rubber farming?
Table 2. Descriptive statistic results.
Table 2. Descriptive statistic results.
VariablesSub-VariablesFactor Loading
Understanding of RiskPerceived Overall Risk0.72
Perceived Frequency of Risks0.51
Perceived Severity of Risks0.62
Perceived Vulnerability to Risks0.77
Perceived Impact of Risks on Livelihood0.44
Attitude Satisfaction with Current Returns0.86
Optimism about Future of Rubber Farming0.58
Likelihood to Recommend Rubber Farming0.48
Perceived Financial Benefits0.68
Perception of Market Stability0.83
Subjective NormPerception of Community Support0.45
Perception of Approval from Significant Others0.71
Motivation to Comply with Social Expectations0.76
Peer Influence on Farming Decisions0.56
Frequency of Discussions about Farming Challenges0.49
Perceived Behavioral ControlConfidence in Managing Farming Challenges0.82
Perceived Control over Transitioning0.67
Confidence in Ability to Transition0.81
Ease of Adopting New Practices0.72
Capability to Learn New Farming Types0.58
Threat AppraisalPerception of Threat Significance0.57
Concern about Impact of Threats0.53
Perceived Likelihood of Future Threats0.69
Preparedness to Manage Threats0.82
Perceived Impact of Threats on Livelihood0.54
Coping AppraisalPerceived Capability to Manage Threats0.69
Belief in Effectiveness of Coping Strategies0.65
Confidence in Implementing Coping Strategies0.78
Availability of Support to Manage Threats0.54
Frequency of Successful Coping Experiences0.61
Intention to TransitionStrength of Consideration to Transition0.62
Willingness to Invest in Transition0.73
Preparedness for Transition Challenges0.81
Optimism about Success in New Venture0.51
Timeframe for Considering Transition0.63
Table 3. Model fit.
Table 3. Model fit.
Goodness of Fit Measures of the SEMParameter EstimatesMinimum CutoffSuggested by
Incremental Fit Index (FIT)0.92>0.90[62]
Tucker–Lewis Index (TLI)0.93>0.90[63]
Comparative Fit Index (GFI)0.91>0.90[62]
Goodness of Fit Index (GFI)0.86>0.80[64]
Adjusted Goodness of Fit Index (AGFI)0.88>0.80[64]
Root Mean Square Error of Approximation (RMSEA)0.03<0.07[65]
Table 4. Direct effect, indirect effect, and total effect.
Table 4. Direct effect, indirect effect, and total effect.
NoVariablesDirect Effectp-ValueIndirect Effectp-ValueTotal Effectp-Value
1UR → ATT−0.7880.001--−0.7880.001
2UR → SN−0.5240.032--−0.5240.032
3UR → PBC−0.4210.021--−0.4210.021
4UR → TA--0.1120.0010.1120.001
5UR → CA--0.4410.0010.4410.001
6UR → IT--0.1130.0010.1130.001
7ATT → TA−0.2210.001--−0.2210.001
8ATT → CA−0.4590.001--−0.4590.001
9ATT → IT−0.4430.0010.7720.0010.3290.001
10SN → IT−0.7730.001-0.001−0.7730.001
11PBC → TA−0.4780.042-0.001−0.4780.042
12PBC → CA−0.7630.001-0.001−0.7630.001
13PBC → IT−0.5650.0330.4450.001−0.1200.001
14TA → IT0.7730.001-0.0010.7730.001
15CA → IT0.4420.001-0.0010.4420.001
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.

Share and Cite

MDPI and ACS Style

Suriansyah; Nurliza; Dolorosa, E.; Rosyadi; Suswati, D. Intention to Transition: Natural Rubber Smallholders Navigating the Risks of Farming. Sustainability 2024, 16, 1765. https://doi.org/10.3390/su16051765

AMA Style

Suriansyah, Nurliza, Dolorosa E, Rosyadi, Suswati D. Intention to Transition: Natural Rubber Smallholders Navigating the Risks of Farming. Sustainability. 2024; 16(5):1765. https://doi.org/10.3390/su16051765

Chicago/Turabian Style

Suriansyah, Nurliza, Eva Dolorosa, Rosyadi, and Denah Suswati. 2024. "Intention to Transition: Natural Rubber Smallholders Navigating the Risks of Farming" Sustainability 16, no. 5: 1765. https://doi.org/10.3390/su16051765

APA Style

Suriansyah, Nurliza, Dolorosa, E., Rosyadi, & Suswati, D. (2024). Intention to Transition: Natural Rubber Smallholders Navigating the Risks of Farming. Sustainability, 16(5), 1765. https://doi.org/10.3390/su16051765

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop