Abstract
The degradation of farming lands caused by excessive pesticide usage is a growing concern. One of the most effective strategies for preventing this disaster from worsening is to commence organic pesticide management at a mass level. Although farmers depend highly on synthetic pesticides and fertilizers to obtain higher yields and profitable returns, the adoption of these synthetic inputs have remained surprisingly low in many agricultural contexts, spanning both developing and developed countries. The goal of this study is to utilize the Value-Belief-Norm (VBN) theory as a framework for understanding the critical sociopsychological factors influencing farmers' decision to use organic pesticides. Specifically, this study aims to introduce and assess the impact of a new construct, i.e., the social norm withing the VBN framework. Additionally, this study empirically evaluates the core components of VBN theory and their causal relationship. The data was collected from 322 farmers from Zhoukou, Henan province, China using a survey questionnaire. The findings show that farmers' egoistic values significantly impact the ecological worldview, despite the fact that biospheric values had no discernible effect. The ecological worldview also profoundly influences the farmers' awareness of consequences and their personal norms. Although the study finds awareness of consequences to have no significant effect on personal norms, it has a substantial positive impact on ascription of responsibility. In addition, ascription of responsibility significantly influences farmers' personal norms, which substantially impacts the intention to use organic pesticides. The results also reveal that farmers' intentions significantly impact the usage of organic pesticides. The study's findings can help strengthen essential factors among farmers that can improve their perception of organic agricultural methods, create strategies for managing controlled agrochemicals, and successfully stop environmental degradation by toxic inputs.
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1. Introduction
Food and fiber production necessitate various agricultural practices, most notably the application of chemical fertilizers and pesticides (Savari et al 2023). Farmers' use of chemical pesticides to control diseases and pests in most agricultural sectors during the past 60 years has resulted in significant increases in food yield (Sharifzadeh et al 2018, Rezaei et al 2019). However, chemical pesticides were demonstrated to have detrimental health effects on consumers and farmers and posed as a risk to the global environment and agricultural ecology (Sapbamrer and Thammachai 2021). On the other hand, organic pesticides are a type of pest control substance that is derived from naturally occurring sources such as minerals, plants, or animals and is approved for use in organic farming. These pesticides are intended to manage pests while following the principles of organic farming, which typically prioritize sustainability, environmental protection, and the avoidance of synthetic chemicals (Yazdanpanah et al 2022). Organic pesticides are preferred in organic farming since they are perceived to be less harmful to the environment and non-target organisms than synthetic chemical pesticides (Zhang and Hu et al 2016, Zhang and Wu et al 2016). There are various types of organic pesticides including botanical pesticides, microbial pesticides and mineral-based pesticides. Botanical pesticides are produced from plants and often include natural toxins that repel or eliminate pests (Guo et al 2023). Microbial pesticides utilize beneficial microorganisms, such as bacteria, fungi, or viruses, to focus on specific pests (Elnahal et al 2022). Mineral-based pesticides are naturally occurring minerals that function as pesticides (Singh et al 2022). Organic pesticides and farming practices have gained worldwide attention as a means of achieving an agroecosystem that is highly productive, sustainable, and environmentally pleasant (Sapbamrer and Thammachai 2021, Adebiyi and Olabisi 2022). Although organic pesticide control is one of the most practical organic agriculture strategies, there are certain gaps in the literature that need to be addressed promptly to bring about a rapid advancement in the environment and food safety worldwide. The relevant research gaps in organic farming practices (i.e., the contextual gap, the demographic gap, and the theoretical and empirical gaps) have been discussed in the following paragraphs, along with the corresponding objectives of this study to address those gaps.
The International Federation for Organic Agriculture Movement (IFOAM 2008) described organic agriculture as a production system that relies on ecological processes, biodiversity, and cycles tailored to environmental well-being instead of using harmful inputs that have negative impacts. According to a study published by the US Department of Agriculture (Rex Dufour 2015), organic pest management is a natural approach to control insects that may involve the use of pheromone traps, the release of beneficial insects, the use of trap crops, and other methods that have been certified as organic. Although a few researchers have examined the adoption behavior of organic farming practices, such as organic fertilizer (Wang et al 2021, Li and Wu 2021), there is a dearth of research in the body of literature that assesses farmers' intentions and adoption behavior of organic pesticides. This study aims to bridge this contextual gap in the literature by thoroughly evaluating Organic Pesticide Control Method among farmers.
Agriculture-related non-point source pollution has been identified as a hazard to the environment and a factor in the degradation of water, soil, and air quality in a number of developed nations (Zhang et al 2019). Among the research that examined organic farming production methods, Kleemann and Abdulai (2013) discovered that organic farming enhanced agroecological initiatives among pineapple growers in Ghana. According to Nie et al (2018), organic farmers in Costa Rica use fewer agrochemicals than conventional farmers. Since the 1990s, China, the world's largest developing nation, has experienced difficulties with agricultural non-point source pollution, significantly worsening agroecosystems (Zhang et al 2019). Due to its rapid socioeconomic development and population expansion, China uses the highest amount of chemical inputs (approximately 30% of the worldwide total) to ensure a high food yield to meet the demand (Xie et al 2021). Farmers apply most of those hazardous pesticides by hand, posing a significant danger to human health and the environment (Zheng et al 2018). Pesticide usage is a known health risk in China (Zhang and Hu et al 2016), with an estimated 50,000+ instances of pesticide poisoning per year (Zhang and Wu et al 2016). Despite a large number of risk records, very few studies have focused on the apparent need for organic pesticide management in China, and only a few have addressed the importance of reducing toxic pesticide consumption. This study focuses on Chinese farmers at all levels and different types of crop growers in order to address this demographic gap in the literature.
Despite this growing body of research, a consistent theoretical framework for understanding farmers' pesticide application is limited. Hence, a detailed understanding of farmers' desire to use pesticides safely is vital to policymakers and academics (Wang et al 2018). Furthermore, the empirical analysis of prior studies revealed that theories, such as the Theory of Planned Behavior (TPB) and the Norm Activation Model (NAM), could only explain a limited proportion of the variance among the determinants. Hence researchers recommended using a varied range of theories in order to fully explain the elements in the context of organic farming (Rezaei et al 2019, Nguyen et al 2021). Meanwhile, previous studies have focused on examining aspects of farmers' personalities, pro-environmental behavior, knowledge, and subjective norms (Wang et al 2021, Li and Wu 2021). Specifically, the literature did not consider the impact of psychological variables on non-toxic pesticide usage (Wang et al 2018). For instance, there was a lack of investigation into the evidence of aspects like emotional values, environmental consciousness, and individual and social norms. Researchers also suggested further and thorough investigations to address the complex sociopsychological factors impacting farmers' adoption of environmentally friendly, non-toxic agro-inputs (Rezaei et al 2019). Therefore, this study includes a third element (i.e., Social Norms) to Value-Beliefs-Norm (VBN) theory to fully appreciate the key sociopsychological factors for adopting Organic Pesticide Control techniques as pro-environmental behavior among farmers in China. Specifically, this study focuses on the intention and behavioural action of using organic pesticides by farmers in Zhoukou, Henan Province, China. The region is significant due to the diversity of products grown, such as fruit orchards or vegetable farms, and the potential of organic pesticides to provide effective pest control while aligning with the principles of organic agriculture (Organic Without Boundaries 2023). Our research aims to identify the sociopsychological factors that influence farmers' decisions regarding the adoption of these organic pesticides, utilizing the VBN theory.
The outcomes of this study can aid in fortifying essential factors among farmers that will enhance their perception of organic agricultural practices, formulate techniques for managing restricted agrochemicals, and effectively prevent environmental degradation caused by toxic inputs. The findings may be helpful for environmental and agricultural researchers interested in further exploring and including a wide range of sociopsychological variables that may considerably impact people's pro-environmental behavioral intentions.
The remainder of this paper is structured as follows. Section 2 describes the theoretical framework and related hypotheses. Section 3 explains the survey design and variable measurement. Section 4 presents the methodology and findings. Finally, section 5 concludes the paper with discussions, policy implications, and research limitations.
2. Literature review
2.1. Review of the existing literature
A number of studies have been conducted in identifying the factors influencing farmers' intentions and behavoural actions to use organic pesticides. However, the existing literature has predominantly centered around the theoretical frameworks of the health belief model (HBM) and the theory of planned behavior (TPB). For instance, Kaur et al (2023) examined the perceptions and attitudes of vegetable and fruit growers in India towards biopesticides integrating HBM and TPB. Ataei et al (2021) also integrated TPB and HBM to study farmers intention to use green pesticides in Iran. On the other hand, incorporating TPB and NAM, Rezaei et al (2019) investigated the factors of farmers' intention to use integrated pest management in Iran. Similarly, Nguyen et al (2021) integrated TPB and NAM to inspect the factors influencing Vietnamese farmers' intention toward organic agricultural production. The study by Despotović et al (2019) investigated the intentions of farmers to adopt integrated pest management practices using TPB. The literature review revealed that none of the studies integrated VBN theory to investigate the farmers' intentions and behavioural actions in using organic pesticides in their farming. The current study stands out in its application of the VBN theory, which is a distinct approach compared with existing models that have explored individuals' perceptions and behaviors related to pesticide use. While these models have made significant contributions to understanding these issues, our study integrated the VBN theory to examine the sociopsychological factors influencing farmers' decisions to use organic pesticides, offering a unique perspective.
2.2. Prospects of organic pesticides in china
China, with its extensive agricultural terrain, occupies a significant position in global agriculture (Al Mamun et al 2023). The diverse methods of organic agriculture have led to the fact that China is now one of the top four markets for organic food, following the United States of America, Germany, and France (Donkers 2021). The Chinese government has been taking measures over the past 30 years to enhance pesticide control and ensure the safety of agricultural products. These measures include the enactment of relevant laws and regulations, the establishment of agricultural standards, and the upgrading of the inspection system (Pan et al 2021). As a result, a large number of high-efficiency, low-toxicity, low-residue, and low-risk pesticides have been created, applied, and promoted. Additionally, organic pesticides have received increasing attention in recent years. These efforts have been supported and encouraged by national policies (Wang et al 2022). Prior to 2018, there were 115 organic pesticide active ingredients and over 3,800 registered formulated products in China. These include microbial pesticides, botanical pesticides, biochemical pesticides, natural enemies, and agricultural antibiotics. According to previous reports, the use of organic pesticides comprised 10%–20% of chemical pesticides (Wang et al 2022). As of 2015, China had registered a total of 4,293 organic pesticides with 112 active ingredients. The organic pesticide market in China is projected to grow at a compound annual growth rate of 4.6% from 2020 to 2025 (Wang et al 2018). In 2006, the total organic pesticide consumption reached 145 thousand tons, with nearly 10% of total pesticides being organic. It is expected that China will produce between 300 thousand and one million tons of organic pesticides by 2050, which will be sufficient to meet the needs of chemical pesticide-free agriculture and maintain high yield and quality crop production. It is expected that China will likely enter the phase of pesticide-free agriculture by the year 2050 (Wang et al 2022). Nevertheless, in order to attain high yields and superior crop quality, the development of biopesticides must be expedited, given the country's massive population.
2.3. Theoretical foundation and hypothesis development
Certain pro-environmental practices are theorized to be determined by a combination of values, beliefs, and moral norms, as outlined by the Value-Belief-Norm (VBN) theory (Kaiser et al 2005, Stren et al 1999). Biospheric, altruistic, and egoistic values are the three major types of values (Schwartz 1992). Beliefs encompass three elements: ecological worldview, awareness of consequences, and accepting responsibility (Naznen et al 2023). Personal norms are the only kind that was preliminarily identified as a pro-environmental norm in the original VBN theory. Three value-driven components trigger an ecological worldview as the stream of variables outlined in theory (Hoeksma et al 2017). An ecological worldview encourages people to be aware of the repercussions of their actions, which increases their duty to respond to those consequences in the causal chain (Rezaei et al 2019). Pro-environmental personal norms are directly determined by the extent to which they feel responsible for the negative consequences of their actions (Hoeksma et al 2017). Since organic pesticide control methods are seen as pro-environmental activities, it is vitally important to examine farmers' values, beliefs, and norms to strengthen their willingness to embrace such eco-friendly materials.
In this study, we conceptualized sociopsychological factors as the psychological and social components that play a role in the adoption of organic pesticides by farmers on organic pesticide control. These factors include a range of beliefs, attitudes, and norms influencing farmers' intentions and behavioural actions related to pesticide use. The VBN theory suggests that a farmer's personal values, such as environmental conservation and health consciousness, can affect their preference for organic pest control methods over synthetic alternatives (Stren et al 1999). It is hypothesized that farmers with stronger pro-environmental values will be more likely to use organic pesticides. Additionally, VBN theory posits that the impact of belief is vital (Stren et al 1999) in farmers' decision-making, since it predicts that their beliefs about the potency, safety, and financial feasibility of using organic pesticides in their farming. Specifically, farmers who have a positive outlook on the advantages of organic pesticides are expected to be more likely to use them. Likewise, the influence of social norms, including perceptions of what other individuals (e. g., farmers) and community members consider acceptable or desirable in pesticide use, can significantly impact individual choices (Stren et al 1999). Thus, we expect that the perception of a positive social norm surrounding the use of organic pesticides will increase the likelihood of adoption. Further, the VBN theory advocates that farmers' awareness of the environmental impact of pesticides and their sense of responsibility towards the environment may encourage them to choose organic pest control methods. This inclination towards organic pesticides is likely to be stronger among farmers who have a higher level of environmental awareness.
The selection of the VBN theory as the theoretical framework for this study is grounded in its strong alignment with the specific dynamics of organic pesticide control and the sociopsychological factors involved. This theory is inherently value-based, focusing on how individual values influence beliefs and norms, which, in turn, guide behaviour (Sarkis 2017). In the context of organic pesticide control, where environmental and health-related values are paramount, the VBN theory offers a suitable foundation for understanding how farmers' values shape their attitudes and intentions regarding pesticide adoption. The VBN theory is well-suited for research involving environmental and social issues (Ribeiro et al 2023). Organic pesticide control is a domain where environmental concerns (e.g., reducing chemical pollution) and social norms (e.g., community expectations) significantly influence decision-making (Spina et al 2023). The VBN theory's emphasis on these aspects provides a robust framework to explore these influences. The VBN theory allows for the examination of causal chain relationships among values, beliefs, and norms, providing a structured approach to understanding the sequential psychological processes that lead to specific behaviors (Awais et al 2022). This is particularly relevant in organic pesticide adoption, where a complex interplay of factors determines farmers' choices. Organic pesticide control is a sustainable agricultural practice, and the VBN theory is well-established in the study of pro-environmental and sustainable behaviors (Spina et al 2023). It has been successfully applied to various domains involving sustainability and conservation (Ribeiro et al 2023), making it suitable for investigating the adoption of environmentally friendly pest control methods.
Accordingly, VBN theory was placed as the theoretical foundation for this study. Although VBN theory has been utilized extensively to predict pro-environmental behaviors, researchers have argued that social norms play a significant role in shaping individuals' propensity to engage in pro-environmental behaviors (Choi et al 2015). For instance, using VBN theory, Ghazali et al (2019) found a significant impact of social norms on pro-environmental behavior among different ethnic groups. Integrating VBN theory, Youn et al (2020) also proved that social norms played a substantial role in influencing traditional restaurant diners' intention to choose environmentally friendly restaurants. Therefore, the association between personal standards and pro-environmental conduct is widely documented, this relationship might be even stronger when societal norms are incorporated as an influencing factor (Englis and Phillips 2013, Gabler et al 2013). Although several recent studies have focused only on the impact of personal norms on pro-environmental behaviors (Rezaei et al 2019, Nguyen et al 2021), few researchers have suggested exploring the impact of social norms on the VBN chain (Ghazali et al 2019). Moreover, the advancements in understanding pro-environmental behavior have underscored the importance of interconnected values, such as biospheric and egoistic values, in shaping environmentally responsible actions (Bouman et al 2020). In contrast, altruistic values pertain to concern for others' well-being (Kahana et al 2013). Given this, our study seeks to provide a more comprehensive understanding of the sociopsychological factors that guide individuals' decisions in the context of organic pesticide control by focusing on biospheric and egoistic values and excluding altruistic values.
In the proposed conceptual model, individual-level factors (i.e., ecological worldview, awareness of consequences, and ascription of responsibilities) serve as antecedents to the development of personal norms; while social norms operate as a distinct and external factor influencing personal norms. This nuanced relationship aligns with VBN theory and has been tested in empirical studies (Ghazali et al 2019, Youn et al 2020). In light of this, this study experimentally investigates the extended VBN framework (figure 1), incorporating social norms as an additional component for triggering personal norms inside the causal chain of VBN. The sections below discuss the relationships between the variables in light of the earlier literature.
Figure 1. Research Framework.
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Standard image High-resolution image2.3.1. Biospheric values (BV)
Biospheric values indicate the general consensus of people that nature is valuable and should be protected (Stren et al 1999). A person's biospheric values are mostly concerned with the safety of all components in the ecosystem and all non-human inhabitants (Van Riper et al 2018). Besides a clear association with the well-being of humankind, biospheric values describe individuals' beliefs in maintaining the quality of environmental resources for humankind's benefit (Steg et al 2014). People with high biospheric mindsets should have a greater positive belief in the sustainability of the environment (Thelken and De Jong 2020). Due to their beliefs that safeguarding the environment is the righteous thing to do, people who adhere to biospheric values frequently participate in pro-environmental initiatives (Liobikienė and Juknys 2016). For instance, farmers who value the biosphere can better evaluate the long-term advantages and gains of participating in environmental water conservation initiatives (Valizadeh et al 2020). Biospheric values are found to positively affect people's beliefs in the ecological worldview in the context of energy conservation in a recent study by Al Mamun et al (2022). In light of this discussion, this study proposes the following hypothesis:
H1. Biospheric values positively affect farmers' new environmental paradigm
2.3.2. Egoistic values (EV)
Egoistic values place a strong emphasis on maximizing individuals' personal interests and benefits, such as power and own achievements (De Groot and Steg 2009, Stern 2000). In the majority of earlier studies, egoistic values were found to have a negative association with ecological worldviews (van Riper and Kyle (2014), Hoeksma et al 2017). However, studies also revealed that consumers are open to intake environmentally friendly foods, such as organic foods, in order to gain improved food quality, healthy life, and other personal benefits (Kushwah et al 2019), indicating that egoistic values also drive people to conduct pro-environmental behavior for gaining more personal benefits. Therefore, in this study, farmers' egoistic values are factored into their sense of personal cohesiveness to the environment and their efforts to protect it from obtaining more benefits from a healthy ecosystem. With rapid urbanization, farmers' perspectives of the worth of their land have shifted from their egoistic values (e.g., social security, financial stability, and personal bonding) to an ecological worldview (Kollmuss and Agyeman, 2002).
On the contrary, egoistic values might induce farmers to engage in production practices that jeopardize the sustainability of cultivable land (Kan et al 2022). Although the new environmental paradigm has been shown to be negatively associated with egoistic values, this study has shaped it to be positively associated with an ecological worldview because farmers can sense that organic pesticide is a product that assists them in gaining more profit by safeguarding their arable land. In their study, Choi et al (2015) provided empirical evidence that egoistic values shape ecological worldviews. Hence, this study formulates the following hypothesis:
H2. Egoistic values positively affect farmers' ecological worldview
2.3.3. Ecological worldview (EP)
As defined by the new environmental paradigm, the ecological worldview is considered more comprehensive than pro-environmental norms since it encompasses broader beliefs that are not limited to a specific context (van Riper and Kyle 2014). The ecological worldview develops another belief among people, referred to as 'awareness of consequences' (Stern 2000). Zhang et al (2020) revealed that the ecological worldview substantially impacts farmers' awareness of the consequences of climate change on the agroecosystem. Likewise, Han et al (2016) found that an ecological worldview increases people's awareness of the negative implications of their actions on the objects they care about. Accordingly, the following hypothesis is set forth:
H3a. Ecological worldview positively influences farmers' awareness of consequences
In the VBN theory, an ecological worldview that reflects individuals' fundamental beliefs regarding the actual relationship between humans and the environment is a strong antecedent for forming their personal norms (Stern 2000; van Riper and Kyle 2014). A new environmental paradigm encourages the formation of individual moral norms essential for participating in all sorts of eco-friendly behaviors (Zeiske et al 2020). In their empirical study, Al Mamun et al (2022) discovered that the ecological worldview substantially impacts Malaysians' awareness of the consequences and personal norms regarding energy saving. Similarly, Han et al (2019) provided that their ecological worldview positively influences empirical evidence demonstrating people's sense of obligation to conduct pro-environmental behavior. Based on evidence from earlier studies, this study hypothesizes the following:
H3b. Ecological worldview positively influences farmers' personal norms
2.3.4. Awareness of consequences (AC)
Awareness of consequences is described as personal perceptions of the positive or negative effects of any behavior toward others (De Groot and Steg 2009). Generally, there is a positive relationship between awareness of consequences and ascription of responsibility (Nguyen et al 2021). Farmers might be less likely to take proactive measures to minimize ecological threats if they are not aware of the long-term repercussion of utilizing harmful chemical inputs (Prokopy et al 2019). In contrast, farmers who actively pursue organic agriculture are fully aware of the benefits of these practices and believe that they are responsible for harming the environment by using hazardous agrochemicals (Nguyen et al 2021). According to a recent study by Rezaei et al (2019), farmers who are aware of the advantages of using non-polluting pest management techniques are also aware of the negative effects of using chemical pesticides. As a result, they have a strong sense of responsibility to use eco-friendly pest control techniques. Accordingly, the following hypothesis was proposed:
H4a. Awareness of consequences positively affects farmers' ascription of responsibility
Environmental awareness enhances one's innate capacity for moral duty to engage in eco-friendly behavior (Han et al 2016). Personal obligations are triggered by awareness of the repercussions of one's damaging activities toward the environment and beliefs about one's liability from such results (Pradhananga and Davenport 2022). According to a recent empirical study by Wensing et al (2019), awareness of consequences significantly enhanced farmers' personal norms while taking into account their novel actions in the bio-economy. Nguyen et al (2021) observed that farmers who intend to migrate to organic farming are well-informed about the benefits of organic agriculture and believe they are personally obligated to reduce the adverse environmental consequences of using agrochemicals. Consequently, the following hypothesis was developed:
H4b. Awareness of consequences positively affects farmers' personal norms
2.3.5. Ascription of responsibility (AR)
Ascription of responsibility is an individual's firm belief that their small efforts might avert any negative outcomes from occurring (Hoeksma et al 2017). Han et al (2016) found that AOR significantly influences personal norms to engage in ecologically sustainable initiatives. In the context of organic farming, Fatemi and Rezaei-moghaddam (2020) described farmers' sense of their responsibilities as the level of readiness to accept the negative effects of not using sustainable agricultural practices and recognize their obligations to prevent adverse environmental consequences. More specifically, Nguyen et al (2021) observed that farmers showed a moral commitment and intended to adopt organic agriculture practices to safeguard consumers' health due to their remorse for not doing so in the past. According to Fatemi and Rezaei-moghaddam (2020) and Nguyen et al (2021), farmers' perceptions of their need to engage in environmentally friendly agricultural practices have a big impact on whether they plan to engage in organic farming. In a recent study, Xie et al (2021) also found that farmers were more inclined to use organic fertilizer when they strongly ascribed their responsibility for environmental contamination. According to the arguments, the following hypothesis was postulated in this study:
H5. Ascription of responsibility positively influences farmers' personal norms
2.3.6. Social norm (SN)
Social norms are individuals' evaluations of whether other influential people in their surroundings believe they should or should not participate in a specific initiative (Ajzen 1991). According to Fatemi, Rezaei-moghaddam (2020), social influence refers to how farmers perceive community expectations and pressures to engage in pro-environmental agricultural practices. For farmers who are cautious about the negative environmental implications of conventional farming methods, societal norms are key motivators for them to start organic farming practices (Ambrosius et al 2022; Tran-Nam and Tiet 2022). For instance, farmers internalize utilizing organic practices to avoid reputation loss or social isolation when they notice that their neighbors and friends are using such methods or when they recognize that their coworkers expect them to embrace those (Li and Wu 2021). As a result of peer pressure, farmers are more likely to act in a pro-social manner since they are expected to think about the effects of misusing pesticides amid societal norms that encourage good standards (Wang et al 2018). In their latest study, Tran-Nam and Tiet (2022) investigated the importance of peer influence, including the presence of neighbors who practiced organic farming, and revealed that it helps farmers to understand their moral obligations to adopt organic agriculture. Given the aforementioned findings, this study proposes the following hypothesis:
H6. Social norms positively influence farmers' personal norms
2.3.7. Personal norms (PN)
In the context of this study, 'personal norms' relates to the extent to which a farmer feels obligated to use sustainable agricultural methods as a grower, landowner, or community member when addressing organic practices (Mutyasira et al 2018). Fatemi and Rezaei-moghaddam (2020) characterized moral norms as societal expectations and growers' aspirations of engaging in environmentally friendly practices as their obligations, including avoiding the use of agrochemicals. Ünal et al (2019) asserted that personal norms enable people to form strong intentions to conduct themselves in an ecologically sustainable manner. Personal norm was found to be a significant predictor of farmers' inclination to undertake organic farming by Nguyen et al 2021. In order to avoid potentially negative outcomes, individuals use their own personal norms to choose whether they should participate in a certain behavior (Hoeksma et al 2017). Recent studies have demonstrated the positive influence of personal norms in a range of pro-environmental initiatives among farmers, such as biogas technology (Wang et al 2020), climate change mitigation (Zhang et al 2020), and sustainable agriculture practices (Mutyasira et al 2018). In view of the earlier literature, this study proposes the following hypothesis:
H7. Personal norms positively influence farmers' intention to use organic pesticide control
2.3.8. Intention toward organic pesticide control (IPC) and usage of organic pesticide control (UPC)
The willingness to adopt environmentally friendly practices and products is the foundation for adopting those practices or products in reality (Lanzini et al 2016, Vaz et al 2020). Whether certain conduct will explode depends on one's intention to engage in it (Fatemi and Rezaei-moghaddam 2020). Gaps between intentions and actual adoption in organic initiatives have been highlighted in several prior studies since possessing intentions does not always result in actual execution (Kashif et al 2021). However, recent research by Fatemi and Rezaei-moghaddam (2020) revealed a significant and positive association between farmers' actual adoption of organic agriculture and their intention to adopt it. In light of this, this study aims to assess the following hypothesis:
H8. Intention toward organic pesticide control positively affects farmers' actual usage of organic pesticide control.
All association hypothesized above, presented in figure 1 below:
3. Methods
3.1. Population and sampling
All generations of Chinese landed farmers who grow every crop variety were considered for the study's target population. Since Chinese farmers in rural areas rarely dine out, the survey was more likely to target farmers in second-tier cities who have enough resources to grow crops. Convenience sampling was used to pick participants as it permitted the selection of participants from any region and demographic category who are readily available (Thomas and David 2017). A sample size of 200 is generally recommended, according to Hair et al (2021). Nonetheless, as proposed by Faul et al (2007), the G*power tool was used in this study to precisely estimate the minimal sample size. Based on the parameters of effect size (f2) = 0.15, err prob = 0.05, power (1-err prob) = 0.95, and the number of predictors = 9, the tool indicated that a sample size of at least 153 participants is required. This study collected data that exceeded the minimum sample size to reduce the challenges that a small sample size can generate.
3.2. Data collection
Data were obtained from farmers who participated in 'Practical Skills Training for New Vocational Farmers' in Zhoukou, Henan Province, China. This training program was held in late spring and early summer (March to June) in 2022, with a total of 20 sessions; over 1,000 farmers attended the training program. The data collection team approached the farmers following this training course to share details of their farms and determine their willingness to participate in the survey for this study. Face-to-face interviews with a structured questionnaire were used to obtain data from the participants. The data collection took place from the 1st of February to the 30th of March in 2022. A total of 322 interviews were assessed as complete, comprising all necessary information and being eligible for statistical analysis. It was ensured that the responders' personal information would be treated with the utmost discretion at all times. Participating in this survey remained completely voluntary.
3.3. Measurement items
In order to accomplish the objectives of this study, the survey questionnaire was developed by adapting and slightly amending items from prior studies on similar contexts. To evaluate biosperic values and egoistic values, items were adapted from Han et al (2016). Items to measure Ecological worldview were selected from the study by López-Mosquera and Sánchez (2012). The awareness of consequences was assessed by modifying items from López-Mosquera and Sánchez (2012) and Choi et al (2015). All questions to measure ascription of responsibilities were derived and reformed from López-Mosquera and Sánchez (2012) and Ünal et al (2019). Items for evaluating personal norms were revised from the study by Choi et al (2015) and Ünal et al (2019). Deriving questions from Kim, Kim, Oh and Jung (2016), social norms were gauged. To assess Intention toward organic pest control, items were taken from Chen and Deng (2016) and Maichum and Parichatnon and Peng (2016). Finally, usage of organic pest control was established by measuring questions adapted from Walton and Austin (2011) and Sánchez and López-Mosquera and Lera-López (2015). This study used a 7-point Likert scale to collect responses from the participants. All items used in this study presented in Supporting Materials S1. Survey Instrument.
3.4. Multivariate normality
This study used the statistical tool Web Power to assess the 'multivariate skewness and kurtosis' of all components and datasets to evaluate their non-normality. For both the multivariate skewness value and the multivariate kurtosis value, the analysis revealed a p-value of 0.00, which is significant according to the recommended cutoff value p 0.05 recommended by Cain and Zhang and Yuan (2017). The test results indicated that the dataset used in this investigation was not normally distributed, and there were no issues concerning multivariate normality.
3.5. Data analysis method
PLS-SEM was employed for data analysis because of several distinct features that fit the research design of this study. This technique is particularly suitable for datasets with multivariate non-normality (Hair et al 2017). Additionally, it is appropriate for exploratory studies to gain a comprehensive understanding of hypothesized relationships (Hair et al 2019). PLS-SEM is also recommended for its high accuracy in causal prediction and flexibility in goodness-of-fit standards. Furthermore, this method is applicable to complex research frameworks involving multiple constructs (Hair et al 2017). PLS-SEM is also suitable for small sample sizes. The current study integrated multiple independent constructs and hypothesized several relationships based on non-normal data collected from 322 respondents, a relatively small sample size. Considering these advantages, we opted to use PLS-SEM, specifically SmartPLS (V4.0), to analyze the data.
4. Results
4.1. Demographic data
The demographic features of the respondents (table 1) show that 68.2% are men and 31.4% are women. The majority of the crop growers (38.8%) are between the ages of 41 and 50, 21.4% above 70 years, and19.3% between the ages of 51 and 60. In terms of Land Area, 45.7% of respondents have 1 to 3 Mou of land, 21.7% have 4 to 6 Mou of land, and 21.4% have 7 to 9 Mou of land. Most participants (90.4%) have completed higher school and above, while 8.7% completed Junior college. A large number of respondents (61.5%) have been using land for more than 20 years, followed by 21.7% who have used the same for more than 5 years. The majority of the crop growers have received training 1 to 2 times (53.4%), followed by those who received it 10 or more times (14.9%). In addition, 43.2% of the growers said they had learned organic pest control from their family members, while only 18.6% learned it through a lecture.
Table 1. Demographic characteristics.
| n | % | |
|---|---|---|
| Age | ||
| 18–30 years | 1 | 0.3 |
| 31–40 years | 25 | 7.8 |
| 41–50 years | 125 | 38.8 |
| 51–60 years | 62 | 19.3 |
| 61–70 years | 40 | 12.4 |
| More than 70 years | 69 | 21.4 |
| Total | 322 | 100.0 |
| Education | ||
| High school and below | 291 | 90.4 |
| Junior college | 28 | 8.7 |
| Bachelor's degree and Above | 3 | 0.9 |
| Total | 399 | 100.0 |
| Monthly Expenditure | ||
| less than RMB 1000 | 80 | 24.8 |
| RMB 1001–2000 | 144 | 44.7 |
| RMB 2001–3000 | 80 | 24.8 |
| RMB 3001–4000 | 14 | 4.3 |
| RMB 4001–5000 | 3 | 0.9 |
| above RMB 5001 | 1 | 0.3 |
| Total | 322 | 100.0 |
| Number of Trainings | ||
| 1~2 times | 172 | 53.4 |
| 3~5 times | 45 | 14.0 |
| 6~8 times | 15 | 4.7 |
| 8~10 times | 42 | 13.0 |
| 10 times or more | 48 | 14.9 |
| Total | 322 | 100.0 |
| How to Get knowledge | ||
| Lecture method | 60 | 18.6 |
| Work instruction method | 50 | 15.5 |
| Participatory learning method | 14 | 4.3 |
| Audiovisual technology method | 59 | 18.3 |
| Learning from family members | 139 | 43.2 |
| Total | 322 | 100.0 |
| Gender | ||
| Male | 221 | 68.8 |
| Female | 101 | 31.4 |
| Total | 322 | 100.0 |
| Land Area | ||
| Less than 1 Mu | 1 | 0.3 |
| 1–3 Mu | 147 | 45.7 |
| 4–6 Mu | 70 | 21.7 |
| 7–9 Mu | 69 | 21.4 |
| 10 Mu or More | 35 | 10.9 |
| Total | 322 | 100.0 |
| Length of Land Use | ||
| Less than 5 years | 70 | 21.7 |
| 6 to 10 years | 19 | 5.9 |
| 11 to 15 years | 23 | 7.1 |
| 16 to 20 years | 12 | 3.7 |
| More than 20 years | 198 | 61.5 |
| Total | 322 | 100.0 |
| Types of Crops Produced | ||
| Vegetables | ||
| No | 155 | 48.1 |
| Yes | 167 | 51.9 |
| Total | 322 | 100.0 |
| Fruits | ||
| No | 223 | 69.3 |
| Yes | 99 | 30.7 |
| Total | 322 | 100.0 |
| Food crops | ||
| No food crops | 219 | 68.0 |
| Yes | 103 | 32.0 |
| Total | 322 | 100.0 |
Note. 1RMB = 0.14USD; 1Mu = 0.165Acre.Source: Author's data analysis
4.2. Common method bias
It is recommended that the research model be retained free from Common Method Bias (CMB). Accordingly, we employed Harman's single-factor test to examine the presence of CMB (Chang et al 2010). According to this criterion, a single factor should not account for more than 50 percent of the total variation (Podsakoff et al 2012). The results showed that a single factor accounted for only 31.362% of the variation in this study, which falls within the recommended threshold. Therefore, the model was deemed free from the CMB issue.
4.3. Full collinearity statistics
To minimize collinearity issues, Kock (2015) recommended maintaining Variance Inflation Factor (VIF) values of all constructs below the maximum cutoff of 3.3. The VIF values in this study ranged from 1.099 to 2.472, as depicted in table 2. It was, therefore, reasonably certain that neither the data from a single source were skewed nor the study's data set had any collinearity problems.
Table 2. Full collinearity test.
| Variables | VIF |
|---|---|
| Biospheric Values | 1.211 |
| Egoistic Value | 2.079 |
| Ecological Worldview | 2.472 |
| Awareness of Consequences | 1.099 |
| Ascription of Responsibility | 1.656 |
| Personal Norms | 1.732 |
| Social Norms | 1.816 |
| Intention towards organic pesticide control | 1.918 |
| Usage of organic pesticide control | 1.969 |
4.4. Measurement model (outer model)
The measurement model should be evaluated prior to the structural model, as suggested by Hair et al (2017). Therefore, this study assessed the outer model's consistency and reliability, as well as its convergent validity and discriminant validity, to verify the robustness of the measurement model.
4.5. Internal consistency and convergent validity
We evaluated the internal consistency of the constructs using three criteria: Dijkstra– Henseler's rho, Cronbach's alpha, and composite reliability. For all of these metrics, a value higher than 0.70 indicate adequate internal consistency, as recommended by Hair et al (2019). The results, presented in table 3, demonstrate that Cronbach's alpha (ranging from 0.781 to 0.900), Dijkstra–Henseler's rho (0.787–0.906), and composite reliability (0.858–0.910) had values higher than 0.70, indicating higher internal consistency and reliability of the constructs. Additionally, we examined convergent validity by assessing average variance extracted (AVE), which measures the degree of variance in the constructs associated with latent constructs (Hair et al 2017). The recommended threshold of AVE is higher than 0.50 for each of the constructs. The results are presented in table 3, showing that all AVE values range from 0.602 to 0.770, indicating adequate convergent validity.
Table 3. Validity and reliability.
| Variables | Mean | Standard Deviation | Cronbach's Alpha | Dijkstra-Hensele's rho | Composite Reliability | Average Variance Extracted |
|---|---|---|---|---|---|---|
| Biospheric Values | 5.537 | 1.098 | 0.785 | 0.787 | 0.861 | 0.608 |
| Egoistic Value | 5.560 | 1.180 | 0.859 | 0.859 | 0.905 | 0.703 |
| Ecological Worldview | 5.258 | 1.162 | 0.849 | 0.850 | 0.898 | 0.689 |
| Awareness of Consequences | 5.651 | 0.980 | 0.781 | 0.788 | 0.858 | 0.602 |
| Ascription of Responsibility | 5.210 | 1.157 | 0.885 | 0.886 | 0.921 | 0.743 |
| Personal Norms | 5.243 | 1.115 | 0.868 | 0.870 | 0.910 | 0.717 |
| Social Norms | 5.130 | 1.196 | 0.900 | 0.906 | 0.930 | 0.770 |
| Intention towards organic pesticide control | 5.235 | 1.063 | 0.810 | 0.811 | 0.875 | 0.637 |
| Usage of organic pesticide control | 5.485 | 0.979 | 0.839 | 0.839 | 0.886 | 0.608 |
4.6. Discriminant validity
Discriminant validity was determined by assessing the Fornell-Larcker criterion, Heterotrait-Monotrait (HTMT) ratio, and cross-loadings. According to the Fornell-Larcker criterion, the square root of AVE should be higher than the square roots of the AVEs of all other constructs in the corresponding row and column (Hair et al 2017). The results are presented in table 4, which shows that the values are higher than the correlations of the other constructs in the corresponding row and column, thus meeting the criterion. We also established discriminant validity by examining the HTMT. According to this criterion, the HTMT values should be lower than 0.90 (Henseler and Sarstedt 2013). Table 4 demonstrates that the HTMT values for all constructs (ranging from 0.106 to 0.802) are within the recommended threshold.
Table 4. Discriminant validity.
| BV | EV | EP | AC | AR | PN | SN | IPC | UPC | |
|---|---|---|---|---|---|---|---|---|---|
| Fornell-Larcker Criterion | |||||||||
| BV | 0.780 | ||||||||
| EV | 0.291 | 0.839 | |||||||
| EP | 0.255 | 0.688 | 0.830 | ||||||
| AC | 0.080 | 0.186 | 0.174 | 0.776 | |||||
| AR | 0.174 | 0.449 | 0.538 | 0.181 | 0.862 | ||||
| PN | 0.214 | 0.532 | 0.601 | 0.169 | 0.446 | 0.847 | |||
| SN | 0.261 | 0.490 | 0.555 | 0.283 | 0.544 | 0.444 | 0.877 | ||
| IPC | 0.304 | 0.410 | 0.411 | 0.174 | 0.381 | 0.382 | 0.437 | 0.798 | |
| UPC | 0.379 | 0.407 | 0.414 | 0.199 | 0.323 | 0.404 | 0.397 | 0.652 | 0.780 |
| Heterotrait-Monotrait Ratio (HTMT) | |||||||||
| BV | |||||||||
| EV | 0.355 | ||||||||
| EP | 0.312 | 0.802 | |||||||
| AC | 0.106 | 0.221 | 0.210 | ||||||
| AR | 0.211 | 0.515 | 0.619 | 0.214 | |||||
| PN | 0.260 | 0.617 | 0.698 | 0.204 | 0.507 | ||||
| SN | 0.312 | 0.554 | 0.629 | 0.333 | 0.608 | 0.498 | |||
| IPC | 0.381 | 0.493 | 0.495 | 0.213 | 0.449 | 0.455 | 0.511 | ||
| UPC | 0.468 | 0.479 | 0.490 | 0.244 | 0.375 | 0.473 | 0.458 | 0.789 |
Note: BV: biospheric values, EV: egoistic value, EP: ecological worldview, AC: awareness of consequences, AR: ascription of responsibility, PN: personal norms, SN: social norms, IPC: intention towards organic pesticide control, UPC: usage of organic pesticide controlSource: author's data analysis
According to Chin et al (1997), all factor loadings should be greater than 0.60 to ensure substantial discriminant validity. All the factor loading values for all the items ranging from 0.916 to 0.988 (presented in table 5 in bold and italic font) were higher than the specified threshold. Therefore, the findings of all three types of validity tests used in this study demonstrated that the constructs have a high level of discriminant validity.
Table 5. Loading and cross-loading.
| CODE | BV | EV | EP | AC | AR | PN | SN | IPC | UPC |
|---|---|---|---|---|---|---|---|---|---|
| BV1 | 0.762 | 0.216 | 0.185 | 0.050 | 0.127 | 0.184 | 0.185 | 0.281 | 0.288 |
| BV2 | 0.806 | 0.213 | 0.213 | 0.056 | 0.150 | 0.145 | 0.188 | 0.228 | 0.289 |
| BV3 | 0.791 | 0.207 | 0.200 | 0.094 | 0.104 | 0.163 | 0.178 | 0.223 | 0.291 |
| BV4 | 0.759 | 0.271 | 0.196 | 0.050 | 0.163 | 0.178 | 0.263 | 0.219 | 0.316 |
| EV1 | 0.340 | 0.829 | 0.569 | 0.178 | 0.371 | 0.404 | 0.406 | 0.389 | 0.374 |
| EV2 | 0.233 | 0.862 | 0.579 | 0.135 | 0.371 | 0.463 | 0.381 | 0.326 | 0.321 |
| EV3 | 0.178 | 0.853 | 0.569 | 0.158 | 0.392 | 0.469 | 0.429 | 0.335 | 0.351 |
| EV4 | 0.224 | 0.809 | 0.590 | 0.153 | 0.371 | 0.449 | 0.425 | 0.325 | 0.320 |
| EP1 | 0.249 | 0.559 | 0.821 | 0.128 | 0.422 | 0.459 | 0.394 | 0.313 | 0.311 |
| EP2 | 0.207 | 0.558 | 0.845 | 0.201 | 0.439 | 0.494 | 0.460 | 0.327 | 0.360 |
| EP3 | 0.185 | 0.524 | 0.848 | 0.107 | 0.462 | 0.520 | 0.452 | 0.400 | 0.398 |
| EP4 | 0.206 | 0.634 | 0.804 | 0.141 | 0.460 | 0.519 | 0.528 | 0.324 | 0.308 |
| AC1 | 0.109 | 0.141 | 0.134 | 0.785 | 0.123 | 0.114 | 0.168 | 0.071 | 0.150 |
| AC2 | 0.088 | 0.151 | 0.145 | 0.820 | 0.143 | 0.140 | 0.257 | 0.134 | 0.144 |
| AC3 | 0.011 | 0.092 | 0.106 | 0.737 | 0.121 | 0.116 | 0.191 | 0.148 | 0.149 |
| AC4 | 0.038 | 0.180 | 0.149 | 0.761 | 0.168 | 0.148 | 0.249 | 0.178 | 0.172 |
| AR1 | 0.160 | 0.367 | 0.444 | 0.120 | 0.856 | 0.402 | 0.493 | 0.303 | 0.283 |
| AR2 | 0.139 | 0.425 | 0.481 | 0.148 | 0.881 | 0.399 | 0.480 | 0.354 | 0.269 |
| AR3 | 0.115 | 0.368 | 0.477 | 0.200 | 0.857 | 0.380 | 0.476 | 0.351 | 0.295 |
| AR4 | 0.192 | 0.389 | 0.454 | 0.156 | 0.855 | 0.354 | 0.424 | 0.303 | 0.267 |
| PN1 | 0.203 | 0.429 | 0.522 | 0.152 | 0.369 | 0.857 | 0.400 | 0.355 | 0.380 |
| PN2 | 0.180 | 0.467 | 0.482 | 0.185 | 0.348 | 0.816 | 0.320 | 0.315 | 0.323 |
| PN3 | 0.184 | 0.452 | 0.504 | 0.135 | 0.376 | 0.856 | 0.389 | 0.311 | 0.352 |
| PN4 | 0.157 | 0.458 | 0.528 | 0.104 | 0.416 | 0.859 | 0.393 | 0.311 | 0.313 |
| SN1 | 0.261 | 0.383 | 0.446 | 0.262 | 0.453 | 0.353 | 0.873 | 0.380 | 0.345 |
| SN2 | 0.219 | 0.416 | 0.452 | 0.234 | 0.490 | 0.365 | 0.868 | 0.366 | 0.362 |
| SN3 | 0.224 | 0.460 | 0.548 | 0.281 | 0.480 | 0.403 | 0.877 | 0.411 | 0.381 |
| SN4 | 0.215 | 0.452 | 0.495 | 0.220 | 0.485 | 0.429 | 0.891 | 0.375 | 0.309 |
| IPC1 | 0.198 | 0.338 | 0.310 | 0.102 | 0.305 | 0.306 | 0.326 | 0.781 | 0.466 |
| IPC2 | 0.285 | 0.383 | 0.357 | 0.146 | 0.374 | 0.331 | 0.407 | 0.821 | 0.510 |
| IPC3 | 0.262 | 0.292 | 0.279 | 0.132 | 0.242 | 0.299 | 0.306 | 0.807 | 0.543 |
| IPC4 | 0.221 | 0.299 | 0.363 | 0.171 | 0.297 | 0.284 | 0.354 | 0.782 | 0.558 |
| UPC1 | 0.268 | 0.388 | 0.429 | 0.157 | 0.313 | 0.354 | 0.338 | 0.526 | 0.784 |
| UPC2 | 0.352 | 0.338 | 0.330 | 0.185 | 0.243 | 0.311 | 0.318 | 0.507 | 0.773 |
| UPC3 | 0.273 | 0.281 | 0.248 | 0.117 | 0.231 | 0.318 | 0.270 | 0.483 | 0.770 |
| UPC4 | 0.268 | 0.238 | 0.258 | 0.168 | 0.199 | 0.265 | 0.256 | 0.521 | 0.777 |
| UPC5 | 0.317 | 0.340 | 0.345 | 0.145 | 0.274 | 0.328 | 0.365 | 0.503 | 0.793 |
Note: BV: Biospheric Values, EV: Egoistic Value, EP: Ecological Worldview, AC: Awareness of Consequences, AR: Ascription of Responsibility, PN: Personal Norms, SN: Social Norms, IPC: Intention towards organic pesticide control, UPC: usage of organic pesticide controlSource: Author's data analysis
4.7. Structural model (inner model)
The structural model needs to be assessed using the path coefficient (beta values- β), (p-values), coefficient of determination (r2), and effect size (f2), as recommended by Hair et al (2017). This research uses the bootstrapping method to assess p-values, t-values, and path coefficients to evaluate each association among constructs to test the hypotheses.
4.8. Hypothesis testing
The results of the bootstrapping analysis for the hypotheses are outlined in table 6 and figure 2. In the first place, even though the association between biospheric values and ecological worldview was reported to have a positive β-value of 0.060 and a moderate t-value of 1.361, the p-value of 0.087 indicated that the association was not statistically significant. Hence, the result indicated that hypothesis H1 was refuted. According to Hypothesis H2, egoistic value is positively associated with ecological worldview. The prediction was validated by the bootstrapping result, which recorded statistically significant values (β = 0.671, t = 15.524, p < 0.001). Concurrently, the next two hypotheses regarding associations of ecological worldview with awareness of consequences (H3a) and personal norms (H3b) also established substantial favorable effects. The statistical figures of the association between ecological worldview on awareness of consequences (β = 0.174, t = 2.677, p = 0.004) and ecological worldview on personal norms (β = 0.467, t = 7.241, p < 0.001) supported both the hypotheses. In parallel, the relationship between awareness of consequences and ascription of responsibilities (β = 0.258, t = 5.749, p < 0.000) was reported with all significant values confirming hypothesis H4a.
Table 6. Hypothesis testing.
| Hypo | Direct Effects | CI-Min | CI-Max | Beta | t value | p value | Decision |
|---|---|---|---|---|---|---|---|
| H1 | BV→EP | −0.008 | 0.137 | 0.060 | 1.361 | 0.087 | Rejected |
| H2 | EV→EP | 0.594 | 0.736 | 0.671 | 15.524 | 0.000 | Supported |
| H3a | EP→AC | 0.075 | 0.285 | 0.174 | 2.677 | 0.004 | Supported |
| H4a | AC→AR | 0.084 | 0.294 | 0.181 | 2.790 | 0.003 | Supported |
| H3b | EP→PN | 0.352 | 0.566 | 0.467 | 7.241 | 0.000 | Supported |
| H4b | AC→PN | −0.041 | 0.113 | 0.035 | 0.736 | 0.231 | Rejected |
| H5 | AR→PN | 0.039 | 0.234 | 0.132 | 2.207 | 0.014 | Supported |
| H6 | SN→PN | 0.003 | 0.207 | 0.103 | 1.645 | 0.050 | Supported |
| H7 | PN→IPC | 0.271 | 0.483 | 0.382 | 5.962 | 0.000 | Supported |
| H8 | IPC→UPC | 0.585 | 0.715 | 0.652 | 16.748 | 0.000 | Supported |
Note: BV: Biospheric Values, EV: Egoistic Value, EP: Ecological Worldview, AC: Awareness of Consequences, AR: Ascription of Responsibility, PN: Personal Norms, SN: Social Norms, IPC: Intention towards organic pesticide control, UPC: Usage of organic pesticide controlSource: Author's data analysis
Figure 2. Structural Model.
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In contrast, for hypothesis 4b, despite having a positive β-value (0.035), the association was reported to have a statistically non-significant p-value (0.231). Hence, hypothesis H4b was rejected. Evaluation of the next association between Ascription of responsibilities and personal norms (β = 0.132, t = 2.207, p = 0.014) revealed positive β-values, higher t-values, and significant p-values. As a result, hypothesis H5 was substantially supported. Social norms were reported to have statistically significant association with personal norms (β = 0.003, t = 1.645, p = 0.05). Hypothesis H7 postulated that personal norms are significantly and positively associated with intention toward organic pest control. This hypothesis was supported by all the significant statistical values of this association (β = 0.382, t = 5.962, p < 0.001). Finally, it was found that Intention toward organic pesticide control significantly influenced the Usage of Organic Pesticide Control. This notion was supported by all the statistically significant values (β = 0.652, t = 16.748, p < 0.001). Therefore, hypothesis H8 was supported as well.
Most notably, as recommended by (Kock 2016), the lower level (CI-MIN) and upper level (CI-MAX) confidence intervals for supported hypothesis should not contain the value 0 (zero). The analysis showed that all of the accepted hypotheses met these standards. It also showed that the rejected hypotheses contain 0 (zero value) between the lower-level and upper-level values of the confidence interval.
4.9. The coefficient of determination (R2)
The coefficient of determination (R2) is a statistical measure used to assess how much of the variation in a dependent variable can be explained by a linear model. Significant, moderate, and weak endogenous latent variables have R2 values of 0.75, 0.50, and 0.25, respectively (Hair et al 2019). Six different endogenous constructs of the model under study are presented in table 7 and figure 2. The R2 value of ecological worldview (0.474) suggested that all the related exogenous factors explained only 47.4% of the variation, indicating a weak explanatory power. Accordingly, the R2 values for awareness of consequences (2.7%), ascription of responsibilities (3.0%), personal norms (38.4%), intention toward organic pesticide control (14.3%), and adoption of organic pesticide control (42.4%) indicated low explanatory power through their related exogenous constructs.
Table 7. Coefficient of determination (R2 ).
| Variables | R square | R Square adjusted | Explanatory power |
|---|---|---|---|
| Ecological Worldview | 0.477 | 0.474 | Weak |
| Awareness of Consequences | 0.030 | 0.027 | Weak |
| Ascription of Responsibility | 0.033 | 0.030 | Weak |
| Personal Norms | 0.391 | 0.384 | Weak |
| Intention towards organic pesticide control | 0.146 | 0.143 | Weak |
| Usage of organic pesticide control | 0.426 | 0.424 | Weak |
Note: R2 value interpretation (> = 0.75- Significant, > = 0.50- moderate, > = 0.25- Weak) (Hair et al 2019)Source: Author's data analysis
4.10. The effect size (f2)
The effect size (or f2) is a statistical measure used to determine whether an exogenous factor significantly affects an endogenous variable. This statistic is derived from the unique variance rather than the shared variances (Hair et al 2017). Cohen (1988) states that effects can be classified as substantial (> = 0.35), medium (> = 0.15), and small (> = 0.02). It may be difficult to confirm the applicability of these general principles to make a significant and noticeable effect size because the characteristics of the research framework and study domain are diverse (Hair et al 2021). The results of the effect size assessment for this study are reported in table 8. It is found that egoistic value to ecological worldview (0.788) and intention towards organic pesticide control to usage of organic pesticide control (0.741) have a substantial effect. concurrently, ecological worldview to personal norms (0.220) and personal norms to intention towards organic pesticide control (0.171) have medium effect size, and all other associations have small to trivial effect size.
Table 8. Effect Size (f2 ).
| Food waste composting intention | Effect size | |
|---|---|---|
| BV→EP | 0.006 | Trivial |
| EV→EP | 0.788 | Substantial |
| EP→AC | 0.031 | Small |
| AC→AR | 0.034 | Small |
| EP→PN | 0.220 | Medium |
| AC→PN | 0.002 | Trivial |
| AR→PN | 0.018 | Trivial |
| SN→PN | 0.010 | Trivial |
| PN→IPC | 0.171 | Medium |
| IPC→UPC | 0.741 | Substantial |
Note 1: BV: Biospheric Values, EV: Egoistic Value, EP: Ecological Worldview, AC: Awareness of Consequences, AR: Ascription of Responsibility, PN: Personal Norms, SN: Social Norms, IPC: Intention towards organic pesticide control, UPC: Usage of organic pesticide controlNote 2: f2 score interpretation (> = 0.35- substantial effect size, > = 0.15– medium effect size, > = 0.02- small effect size and <0.02- trivial effect size) (Cohen, 2013).Source: Author's data analysis
4.11. Multi-group analysis
Finally, the model was assessed using multi-group analysis (MGA) to ensure a more complete analysis and interpretation. Because of its focus on subgroup heterogeneity, PLS-MGA is a powerful tool for studying moderation in a wide range of interrelated relationships (Hair et al 2017). Before applying PLS-MGA, measurement invariance was checked to ensure that the investigated effects were legitimate. In this specific test, a method known as the Measurement Invariance of Composite Models (MICOM) was utilized to determine the level of homogeneity that existed between two different groups.
The measurement invariance of composite models (MICOM) portrayed the results of the compositional invariance assessment. The permutation's p-values for all constructs in land size (Group 1. 0–3 Mou; Group 2. More than 3 Mou) and the number of training sessions received (Group 1. 1–5 Times; Group 2. More than 5 Times) are larger than 0.05, indicating that compositional invariance was established. However, the permutation's p-values for 'Egoistic Values' for age (Group 1. 18 to 50 Years; Group 2. More than 50 Years) and 'Personal Norms' for gender (Group 1. Female; Group 2. Male) are less than 0.05. As only one out of nine constructs' p-values is less than 0.05 and the eight remaining constructs' p-values are more than 0.05, this study presumes the fulfillment of compositional invariance for age and gender. This study compares standardized path coefficients across the four groups through MGA in PLSPM.
The findings revealed that all the p-values for the Gender group, Land Size Group, and Training Received group are more than 0.05 (as indicated in table 9). Hence, it was concluded that there were no statistically significant differences between these three groups for any associations. The only difference found in the Age group is the associations between EP to PN, AR to PN, PN to IPC, and IPC to UPC. Hence, it can be stated that the younger group of respondents are more concerned about Ecological Worldview, Personal Norms and have more intention toward organic pesticide control since their β-value is higher. However, the older group is more concerned about ascription of responsibility since their β-value is higher.
Table 9. Multi-group analysis.
| Associations | Multi-group analysis | |
|---|---|---|
| Difference (β value) | p-value | |
| Age (Group 1. 18 to 50 Years; N = 151) (Group 2. More than 50 Years; N = 171) | ||
| BV→EP | 0.001 | 0.476 |
| EV→EP | 0.108 | 0.102 |
| EP→AC | 0.057 | 0.304 |
| AC→AR | −0.001 | 0.481 |
| EP→PN | 0.277 | 0.018 |
| AC→PN | 0.025 | 0.397 |
| AR→PN | −0.212 | 0.038 |
| SN→PN | −0.066 | 0.312 |
| PN→IPC | 0.224 | 0.029 |
| IPC→UPC | 0.248 | 0.000 |
| Land size (Group 1. 0–3 Mou; N = 148) (Group 2. More than 3 Mou; N = 174) | ||
| BV→ EP | 0.017 | 0.419 |
| EV→EP | 0.051 | 0.273 |
| EP→AC | −0.078 | 0.295 |
| AC→AR | −0.054 | 0.358 |
| EP→PN | 0.057 | 0.324 |
| AC→PN | −0.036 | 0.349 |
| AR→PN | 0.167 | 0.081 |
| SN→PN | 0.138 | 0.121 |
| PN→IPC | 0.067 | 0.294 |
| IPC→UPC | −0.079 | 0.151 |
| Gender (Group 1. Female; N = 101) (Group 2. Male; N = 221) | ||
| BV→EP | −0.003 | 0.496 |
| EV→EP | −0.012 | 0.454 |
| EP→AC | 0.014 | 0.445 |
| AC→AR | 0.082 | 0.245 |
| EP→PN | −0.036 | 0.427 |
| AC→PN | −0.003 | 0.486 |
| AR→PN | −0.164 | 0.126 |
| SN→PL | 0.062 | 0.362 |
| PN→IPC | 0.074 | 0.288 |
| IPC→UPC | −0.026 | 0.380 |
| Number of training received (Group 1. 1–5 Times; N = 217) (Group 2. More than 5 Times; N = 105) | ||
| BV→EP | 0.129 | 0.154 |
| EV→EP | −0.057 | 0.270 |
| EP→AC | −0.020 | 0.411 |
| AC→AR | 0.108 | 0.269 |
| EP→ PN | 0.029 | 0.446 |
| AC→PN | 0.011 | 0.464 |
| AR→PN | −0.041 | 0.423 |
| SN→PL | 0.051 | 0.355 |
| PN→IPC | −0.121 | 0.181 |
| IPC→UPC | −0.056 | 0.227 |
Note 1: BV: Biospheric Values, EV: Egoistic Value, EP: Ecological Worldview, AC: Awareness of Consequences, AR: Ascription of Responsibility, PN: Personal Norms, SN: Social Norms, IPC: Intention towards organic pesticide control, UPC: Usage of organic pesticide controlNote 2: 1 Mou = 0.165 Acre Source: Author's data analysis.
5. Discussions
Farmers' beliefs in an ecological worldview were not statistically impacted by their biospheric values. The findings contradict recent studies on farmers' climate change mitigation behavior by Zhang et al (2020) and farmers' soil conservation behavior by Bijani et al (2019). It would be unfair to generalize from this finding that farmers have little concern about environmental safety. Perhaps most Chinese farmers only consider environmental protection in terms of human health protection. To protect their own and their customers' health, they may feel compelled to switch to organic pesticides, a move that would also send a message about their values toward the biosphere.
The study reveals that farmers' egoistic values strongly influenced their views on the ecological worldview. The result corroborates the study of Choi et al (2015) on individuals' adoption of organic practices. This finding indicates that organic pesticide control practices can be seen as more beneficial by the farmers who care about the environment for their own sake and future generations. This may be because farmers are becoming more cognizant of the importance of safeguarding the sustainability of the agroecosystem since they no longer wish to produce unhealthy food with poisonous chemicals. Another possible explanation is that farmers are gaining a deeper understanding of the risks associated with their excessive use of toxic pesticides, which can soon make their arable land infertile. Because of this, they are driven by their egoistic values to believe that using organic pesticide controls is the only option to reestablish the ecological balance and soil fertility.
Concurrently, this study observed that an ecological worldview enhances farmers' awareness of consequences as well as personal norms in a positive way. The outcomes were validated by the findings of recent research conducted by Al Mamun et al (2022) in the context of energy-saving practices. The most likely reason for these findings is that farmers are already facing difficulties due to the excessive use of hazardous agrochemicals and that they are well aware of the possible negative repercussions of doing so (e.g., food quality deterioration, fetal health issues, rapid infertility of cultivable lands, and narrowed irrigation resources). Due to farmers' prior horrible experiences of losing their arable lands, they are becoming more compassionate toward the environment and are consequently truly worried about the detrimental implications of hazardous pesticides. Farmers' moral obligation to mitigate the adverse impacts of environmental contamination is therefore formed as a result of their beliefs of ecological worldview.
In the next part of the analysis, it was discovered that organic pesticide control practices were more likely to be adopted by farmers if they were aware of the potential consequences of not adopting those. Recent study findings by Rezaei et al (2019) in the context of environmentally friendly pest management strategies among farmers supported the notion. This result's likely interpretation is that farmers are encountering soil infertility and are losing fast-cultivable lands due to the heavy use of chemical inputs that also damage the water and the air. In addition, the poisonous pesticides pose a threat to farmers' health when they are physically administering them.
However, the current study found that farmers' awareness of consequences had no significant effect on their own personal norms. This outcome is similar to the findings of recent research on farmers' water conservation strategies by Pradhananga and Davenport (2019). The non-significant correlation shows that farmers' sentiments of personal obligation are not driven by their awareness alone and that there must be additional elements to encourage their moral norms to use eco-friendly pesticides. This outcome is likely because many root-level farmers are still unaware of the negative impacts of toxic pesticides on environmental sustainability, and hence, they are still using hazardous chemicals recklessly to increase their agricultural yields.
Subsequently, it was found that the farmers' sense of responsibility significantly impacts their personal norm to adopt organic pesticide control. The results are consistent with the vast majority of recent studies on organic agricultural methods (Xie et al 2021, Nguyen et al 2021). According to the findings, farmers may embrace organic pesticide control methods on a large scale when they accept their responsibility to safeguard the environment. This result is probably because many farmers are becoming aware of the importance of their role in ensuring the long-term sustainability of the environment and have discovered that organic inputs are more lucrative than chemical ones. Another possible explanation is that farmers believe that preventing environmental damage is not just the job of government entities and that they, too, must do their part to assist the government in achieving its aim of sustainability.
The inclination of farmers to embrace organic pesticide control was afterward discovered to be strongly influenced by their personal norms. In the context of sustainable agro-practices, this outcome is also in line with the findings of a previous study by Mutyasira et al (2018). Ultimately, the researchers concluded that farmers would be more likely to adopt organic agro-techniques if they perceive a moral obligation to do so and acknowledge that it is their responsibility to address environmental risks brought on by harmful agrochemicals. One of the potential explanations is that the stronger relationships that farmers have toward their farming land and other agricultural resources made them morally obligated to save those, as those are the only sources of their income.
Furthermore, the study found that farmers' intentions significantly influenced their decision to actually use organic pesticide management methods. The result is consistent with those of Fatemi and Rezaei-moghaddam (2020), who examined the expansion of organic farming methods. It indicates that by presenting farmers with proper rationale, they may be successfully persuaded to utilize organic pesticide control methods. It might also be argued that the severity of environmental instabilities and natural catastrophes strengthened the demand for environmentally friendly agricultural techniques, driving farmers to essentially establish hazardous chemical-free farming systems. The most important thing to note is that farmers have possibly realized that organic farming and protecting the environment are no longer choices but necessities owing to recurrent ecological disasters.
Finally, there was no statistically significant difference found between any two categories in the groups of gender, land size, and training received, as shown by the results of the multi-group analyses of the four groups. This demonstrates that organic pesticide control is acknowledged as a natural solution by acting as an insect repellant by farmers of all levels, irrespective of the size of their land, their gender, or received training. The only difference in the age group is indicated in the ecological worldview, ascription of responsibility, personal norm, and intention to use organic pesticides. According to the findings, organic pesticide adoption is more likely to occur among farmers under the age of 50 because of their stronger personal norms and beliefs founded on a stronger ecological worldview. This is probably because younger farmers have a higher education and, therefore, have a better understanding of how eco-friendly organic agricultural operations may protect their arable land from deterioration.
6. Implications
6.1. Theoretical implications
This research contributes to the literature on organic agricultural methods by examining individual farmers, a demographic segment previously relatively limited in the context of Organic Pesticide Control. It focuses on the specific agricultural setting of Zhoukou in Henan, China, which has distinctive obstacles and prospects for the adoption of organic pesticides. This contextualization enables us to offer region-specific guidelines and insights. Moreover, farmers' decision-making procedures and intentions to use Organic Pesticide Control techniques were evaluated using a holistic sociopsychological framework. We propose a novel idea by incorporating the concept of social norms into the VBN framework, which broadens the theoretical foundation and provides a more inclusive analysis of farmers' decision-making processes. By examining the distinctive components of the VBN theory, we clarify the interconnections between them, providing a more comprehensive understanding of the factors that influence farmers' decisions to employ organic pesticides. The study's findings scientifically establish a framework of moral determinants for farmers' eco-friendly behaviors, indicating that personal and social values, beliefs, and moral responsibility stimulate farmers' sustainable efforts of organic pesticide control to protect agricultural resources. This study finds that farmers are more likely to choose organic pesticide control methods if they feel a high moral and social obligation to protect the environment from the harmful impacts of chemical pesticides. Whereas previous research has demonstrated that moral theories are more adapted to explain small-ranged pro-environmental activities (e.g., climate change protection and energy saving) (Zhang et al 2020; Al Mamun et al 2022), this study reveals that sociopsychological elements may also be established as credible indicators of broad-ranged values, beliefs, and norms in the domain of agriculture, where the environment is the most crucial element. Farmers' recognition of the consequences of excessive use of chemical pesticides, willingness to take responsibility for their mistakes, and eventual commitment to rectify the situation were all comprehensively depicted using the cognitive chain framework of values, beliefs, and norms. Other sociopsychological theories, such as the theory of interpersonal behavior and the cognitive hierarchy theory (Fulton et al 1996), are consistent with the findings of this study since they also argue that values provide a foundation for beliefs regarding pro-environmental activities. Notably, this research added to the VBN theory by incorporating farmers' green trust, which was proven to be an essential determinant in forming the motivations for using organic pesticides among farmers.
6.2. Practical implications
The study's findings include a broad range of real-life potential benefits for agricultural practitioners, environmental and natural resource preservation authorities, interventionist organizations, and even farming personnel seeking to achieve long-term sustainability in organic farming management. Findings from this research will be useful for all sorts of agriculture sectors and related businesses in minimizing fundamental constraints to the widespread use of organic pesticide control techniques among farmers. The factors and viewpoints explored in this research seem to be highly effective for the development of not just organic pesticide control measures but also other environmentally friendly agricultural practices such as organic fertilizer, soil and water conservation practices, and so on. Accordingly, based on the study findings, some practical implications for assisting the significant stakeholders in applying organic agricultural techniques are presented below.
Since farmers' biospheric values were not likely to impact their ecological worldview, this study concludes that farmers may not be empathetic enough to realize that protecting the environment is within human control. This alarming reality necessitates immediate efforts from all relevant stakeholders to enhance farmers' biospheric values to foster their respect for the environment. Agro-environmental planners and the public affairs departments of the involved organizations should consider that to help spread the good values of organic pesticide control among farmers. To put a stronger focus on organic agricultural inputs, it is necessary to highlight that government's agricultural department officials must emphasize not only the biospheric values of farmers but also grow biospheric values of all agribusiness practitioners and marketers. This is because a diverse range of professionals working together may have immense potential to encourage farmers to develop ecological sustainability views in a broad range. According to the study's findings on egoistic values, farmers do not actually have a self-centered mindset. Instead, they may easily be inspired to adopt a pro-environmental worldview by growing a consciousness that the environment equally belongs to all living creatures on this planet. Marketers and agricultural practitioners should promote how organic pesticide control practices may safeguard the environment and provide a healthier future for humankind.
Given that the ecological worldview has a significant impact on the awareness of consequences and personal norms, agricultural analysts and scientists should be successful in addressing new organic practices so that farmers can easily adopt those to minimize the repercussions of conventional chemical treatments. A strong emphasis on education and training in organic farming practices among farmers of all skill levels is strongly recommended since the study found that awareness of consequences significantly impacts ascription of responsibilities. Based on the findings, policymakers may develop targeted outreach and educational strategies that align with the values and beliefs of farmers. For instance, promoting the environmental benefits of organic pesticides for farmers who prioritize conservation of the environment may be a highly effective strategy. When creating and delivering these training programs, agricultural educators, government partners, and other nonprofit organizations must provide examples from real-world catastrophes of using toxic chemicals to make farmers more inclined to use organic pesticides. To enhance farmers' knowledge, administrators should plan regular conferences, awareness programs, and documentaries highlighting the advantages of organic pesticides and the negative impacts of agrochemicals. Thus, this study emphasized the imperative for policymakers to address the knowledge gaps that hinder farmers' understanding of the efficacy and safety of organic pesticides. By investing in educational programs for farmers and disseminating accurate information about the benefits and appropriate application of organic pesticides, policymakers can enhance farmers' confidence in adopting these alternatives. Such efforts can also help to promote the adoption of more sustainable and environmentally friendly practices. As the study revealed a substantial impact of ascription of responsibility on personal norms, it implies that policymakers and governmental organizations should establish rules and regulations to help farmers realize their obligations toward safeguarding the biosphere for their own benefit because the environment is the source of their livelihood. Farmers' associations and forums can regularly publish all the good organic practices of numerous farmers in different areas. This will help other farmers grow more environmentally conscious and morally obligated to start using organic pesticides as a good practice toward protecting the environment.
Furthermore, the government can impose restrictions on the usage of chemical pesticides and enforce a high price on agrochemicals, increasing farmers' interest in organic pesticides to lower production costs. By establishing clear guidelines and standards for these products, policymakers can foster trust among farmers and consumers. Our research findings suggest that sociopsychological factors impact pesticide adoption in various farming systems. Additionally, the Government Agricultural Departments can release laboratory reports on environmental degradation brought on by the overuse of agrochemicals, indicating that farmers are accountable for this cataclysm. This study's further analysis indicated that personal norms are a crucial facet in the development of intention, implying that broadcasting the suffering of farmers whose livelihoods have been heavily damaged by the heavy use of agrochemicals may instill remorse for using toxic chemicals. This may develop their personal liabilities among other farmers to start organic practices. In order to make farmers feel liable for causing ecological damage and destroying the ecosphere equilibrium, government authorities may introduce legal penalties for the unregulated usage of pesticides. Moreover, recognizing the impact of social norms on personal norms offers valuable insights into devising targeted intervention strategies aimed at driving individuals' intentions regarding organic pest control. This finding addresses the significant beneficial impact of social norms underlining the necessity of mass broadcasting of organic trends, information interchange, and the support for organic movements in society in order to foster among farmers a moral imperative that they too must embrace these organic techniques to avoid being alienated from their community. It also highlights the significance of community-based approaches in promoting environmentally friendly behaviors. By fostering and fortifying positive social norms within communities, individuals can be encouraged to align their personal norms with sustainable practices, thereby creating a conducive environment. Policymakers and agricultural authorities should refer to these findings when designing policies and regulations related to pesticide usage. We also propose that policymakers leverage market support mechanisms, such as subsidies or incentives for organic pesticide products, to foster a positive social norm around the adoption of organic pest control methods. This approach has the potential to alleviate the entry barriers faced by farmers who are interested in transitioning to organic pest management practices. Additionally, using social media to form larger groups and peer support platforms may help spread the wave of applying organic pesticide control practices over the entire group of farmers. Finally, to promote the adoption of organic pesticides, policymakers should encourage collaboration and knowledge sharing between conventional and organic farming communities. This may facilitate a more gradual transition for farmers currently practicing conventional agriculture.
6.3. Limitations and future recommendations
A couple of the study's limitations can be overcome in follow-up research. First and foremost, the data was collected through convenience sampling, which reduced its generalizability. Future studies with a large sample size from various locations and demographic groups may contribute to enhancing the generalizability of the study model. In addition, it is possible that some crucial factors were ignored (e.g., price value, green trust, government subsidies) because the present study only focused on a small subset of the various factors associated with moral and behavioral intention. In order to improve understanding in this field, future studies should include additional constructions. The cross-sectional design of this study further restricted the capacity to assess the behavioral patterns of respondents for a longer period of time. Hence, more longitudinal research is recommended to investigate the constructs' long-term effects and their related interactions with time. Finally, as we collected data from farmers who attended farmer training centers by applying specific selection criteria, it is difficult to accurately determine the alignment of the demographic characteristics of our sample with the broader farmer population in Zhoukou, Henan, China. Further research may benefit from more comprehensive demographic data to improve the external validity of this study's results.
7. Conclusion
The reckless use of agrochemicals has resulted in highly challenging circumstances, despite ecological sustainability being the most crucial matter globally. Rather than using unregulated conventional hazardous chemical pesticides, the goal of this study is to determine the impact of the critical sociopsychological factors that may influence farmers to switch to organic pesticide control practices. Employing VBN theory as a framework, this study surveyed 322 Chinese farmers to assess their level of interest in and use of organic pesticides. Results show that farmers' biospheric and egotistic values positively influence their ecological worldview. Additionally, ecological worldview greatly impacts farmers' awareness of consequences and personal norms. Although awareness of consequences has a substantial positive effect on ascription of responsibility, it did not significantly impact farmers' personal norms. Moreover, the analysis reveals that both ascription of responsibility and societal norms have a substantial impact on personal norms, and personal norms subsequently strongly impact the intentions to use organic pesticides. It was demonstrated that farmers' intentions significantly influenced their actual use of organic pesticide control methods. This study's findings emphasized all the important elements that could lead to the creation of more efficient policies and strategies in China and other developing countries. This research can help the government develop new laws and regulations to limit the use of harmful agrochemicals, which can prevent soil infertility, water pollution, food quality degradation, and other unanticipated consequences.
Data availability statement
All data that support the findings of this study are included within the article (and any supplementary files).
Ethical approval
The research ethics committee of Changzhi University have approved this study (Approval Number: CZ-2022–0010). This study has been performed in accordance with the Declaration of Helsinki.
Consent to participate
Written informed consent was obtained from respondents who participated in the survey.
Consent to publish
All authors approved the manuscript and give their consent for submission and publication.
Authors contribution
Qing Yang, Farzana Naznen and Mohammad Nurul Hassan Reza: Conceptualization, Investigation, Methodology, Writing—Original Draft Preparation. Muhammad Mehedi Masud and Abdullah Al Mamun: Conceptualization, Methodology, Formal Analysis, Writing—Review & Editing.
Funding
This research was funded by UKM - Graduate School of Business, Universiti Kebangsaan Malaysia (Ref. No. GSB-2023-007).
Competing interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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