An increase in the world’s population has created a significant need for agricultural products in terms of quality and quantity (Lahlali et al., 2022); hence, the effort to ensure food security against population growth has increased the demand for food (Hawkins et al., 2019), leading to exceeding use of chemical fertilizers and pesticides along with the significant increase in crop yields in the 20th century (Bagheri et al., 2021). The dark side of this movement was applied dramatically to polluted soil, water, and environment, leading to ecological and environmental problems and human health risks (Rodrigues et al., 2022; Sehrawat et al., 2022). Residues of chemical compounds in the environment have caused resistance of weeds, pest, and disease species to chemical toxic materials, severe soil destruction and erosion, water pollution, and threat to human health (in terms of skin diseases, different cancer types, neurological diseases, diabetes, respiratory diseases, fetal insufficiency and diseases, congenital malformation, fertility problems, and genetic problems; Recena et al., 2006; Fianko et al., 2011; Chen et al., 2013; Fan et al., 2015; García-García et al., 2016; Jallow et al., 2017; Bondori et al., 2019, 2021, 2023; Bagheri et al., 2019b, 2021, 2022; Imani et al., 2021; Asante et al., 2023; Bawa, 2023; Dias et al., 2023; Imani et al., 2023; Terfe et al., 2023). However, in recent decades, consumers have become more aware and concerned about the side effects of agrochemicals, which have been highlighted in various studies [Lahlali et al. (2022) on fungicides; Carvalho (2017); Damalas and Eleftherohorinos (2011) on pesticides; Govindasamy et al. (1997) on pesticides, herbicides, fungicides, and insecticides; Önder et al. (2011); Bishnoi (2018) on chemical fertilizers; and Zhang et al. (2018) on chemical inputs used in agriculture]. As public concerns about the impact of chemicals on food safety and environmental protection increased, environmentally friendly management methods, such as biological control and biofertilizers, emerged (Dukare et al., 2019; Wang et al., 2022). As noted by Goulet (2021), the category of biological inputs is broader than the definition of biocontrol; biological inputs include both biocontrol agents and biofertilizers.

From the perspective of ecologists, biological control is known as the best alternative to pesticides (Wu et al., 2005; Bagheri et al., 2016) and one of the key components of integrated pest management strategies (Abdollahzadeh et al., 2015). Biological control means using natural enemies of external origin for permanent pest control (Shafiee et al., 2018; Gholifar et al., 2019). This strategy strengthens the ability and willingness of farmers to control all types of pests ensuring the effectiveness of reducing the population of harmful living organisms and increasing the safety of plants (Sharifzadeh et al., 2017). The most obvious benefit of this type of control is related to food security, human health, and environmental protection by controlling the population of agricultural pests, disease vectors, and invasive species (Rodrigues et al., 2022). Wheeler (2008) and Bagheri et al. (2021) stated that substances used in biological control do not produce residues or create toxic hazards. Therefore, they are not harmful to the environment and health. Moreover, biological control does not affect other organisms (non-target species) that are profitable for the agro-environment. In other words, it can be claimed that biological control has become a useful tool to reach sustainability in the agricultural sector (Rodrigues et al., 2022). While this newly replaced method for pest control can bring many benefits, it has not been successful in practice and sufficiently accepted by producers (Abdollahzadeh et al., 2015); still, many farmers are reluctant to use this method. Usually, they prefer chemical control operations instead of biological control (Safa et al., 2019).

No doubtfully, chemical inputs play an important and determining role in increasing the production rate of agricultural products and farmers’ income in Iran. However, in parallel with this beneficial effect, the widespread and indiscriminate use of such inputs is considered one of the most important barriers to Iran’s environmental sustainability. According to the latest report of the environmental performance index published in 2022, Iran has been ranked 133 showing a score of 34.50 among the 180 countries in the world, and more specifically, it ranked 45, 31, and 113 (worst performance) in agricultural sector, pesticide usage, and sustainable nitrogen management index, respectively, which indicates inappropriate environmental performance in this area (Wolf et al., 2022). As such, today, the fundamental challenge is how to change the behaviors and attitudes of farmers in using chemical inputs in such a way that could provide human health and, furthermore, prevent environmental pollution.

The gradual integration of new methods, considering the agricultural production system, requires not only the environmental dimension but also the social one (Purvis et al., 2019). Therefore, a deep and accurate understanding of farmers’ behavior is essential to accept biological control (Abdollahzadeh et al., 2015; Sharifzadeh et al., 2017). The success of any intervention in terms of activities and programs related to sustainable agriculture (like acceptance of biological control) depends on the use of social-psychological patterns and models (Safa et al., 2019). This study, therefore, was aimed to investigate the factors affecting farmers’ behavior and willingness to accept biological control. Many studies have been conducted on the acceptance of integrated pest management strategies, in general (Habibzadeh Shojaei and Sharifzade, 2014; Sabzian et al., 2015; Bagheri et al., 2019b; Imani et al., 2021), and biological control methods, in particular (Niyaki et al., 2010; Gangadhar et al., 2012; Abdollahzadeh et al., 2015; Ashoori et al., 2015; Shahani, 2020; Bagheri et al., 2021). The main framework of research in these studies was based on the behavioral models, in which the willingness of individuals to accept a particular behavior through different perceptual and cognitive-social processes is explained. Among a variant of environmental psychology theories, which are often used to investigate the factors affecting environmental performance, the Norm Activation Model (developed by Schwartz, 1977), Theory of Planned Behavior (developed by Ajzen, 1991), and Value-Belief-Norm theory (introduced by Stern, 2000) are more popular. Although these theories have been applied to predict the intention toward engaging in environmental behaviors, previous empirical studies have revealed that the technology acceptance model (TAM), in comparison with the rational action or planned behavior model, can account for a significant proportion of the variance (typically approximately 40%) in explaining the adoption behavior (Jokar et al., 2017).

The technology acceptance model (TAM) has been used in several studies, including those investigating biological inputs and organic farmers. Bagheri et al. (2021) used the technology acceptance model (TAM) to measure the acceptance and use of biological inputs by cereal farmers and found that attitudes and perceived usefulness were influential variables in their intention and behavior. In another study, Bagheri et al. (2016) also investigated the use of TAM in the adoption of biological control in the case of rice stem borer and found a positive correlation between perceived usefulness and perceived ease of use with farmers’ willingness to adopt biological control. Using the TAM, Silva et al. (2017) also investigated the intention of bean growers for integrated production in the central region of Brazil and showed that perceived usefulness had a positive effect on attitude and attitude influenced behavioral intentions. In the study of soil conservation behavior among cereal farmers, based on the extended TAM, Ahmadi Firouzjaie et al. (2023) found that perceived usefulness had a direct effect on perceived ease of use. The results also showed that behavioral intention is the most important factor explaining soil conservation behavior. Farmers’ perceived ease of use is recognized as one of the most important factors influencing intention. Naspetti et al. (2017) applied an extended version of TAM to examine attitudes and intentions toward sustainable production strategies among dairy farmers and found that perceived usefulness was the significant determinant of behavioral intention. Hendrawan et al. (2023) used TAM to explain smallholder farmers’ behavior in relation to the use of information and communication technology. Their results indicated that perceived usefulness was more important than perceived ease of use in farmers’ daily activities. Hannus and Sauer (2021), in their research study, used the conceptual framework of TAM to investigate farmers’ intentions to use sustainability standards and came to the conclusion that ease of use was the most effective factor in influencing farmers’ intentions. Chen et al. (2024), in their TAM-based study of farmers’ intentions to adopt live-streaming e-commerce, showed that TAM is quite capable of assessing farmers’ intentions to adopt live-streaming e-commerce. In addition, their results suggested that government support positively influenced perceived usefulness, social learning, and improved perceived ease of use and platform support positively influenced both perceived ease of use and usefulness. McCormack et al. (2022) investigated the ability of TAM to predict farmers’ adoption of an online nutrient management plan. They proposed that perceived usefulness and perceived ease of use were positively and significantly related to farmers’ intention to adopt and use the technology in the future. However, perceived usefulness, which captures the perceived benefits in terms of usefulness, was the main driver of technology adoption. Accordingly, in our research, the important factors affecting the acceptance of biological inputs have been investigated using the TAM model, which measures farmers’ behavior and willingness to accept the use of biological inputs at the same time and, in this respect, differs from the same research study.

The results of the research, as shown in Table 3, indicate that only 18.2% of the respondents were female, 81.8% were male, and 52.6% of the respondents were married. While the majority of the respondents were younger than 45 years of age, the average age of the respondents was close to 32 years. The results also showed that the highest frequency of respondents was among those with less than 10 years of farming experience (53.6%) and the lowest among those with more than 20 years of farming experience (13.3%). In terms of educational level, the data showed a range starting with illiterate respondents (7.3%), those with primary education (14.6%) and secondary and post-secondary education (045.6%) and is over with higher educated respondents (32.5%).

Below is a description of the model variables (Table 4). It should be noted that all the statements used to measure each variable have been prioritized based on their ranking mean.

As shown in Table 4, regarding the ease of using biological inputs, the statements “Consuming manure in the fields is preferable due to creating pores in the soil and making plowing easy,” “Access to biological inputs is easy,” and “Learning how to use biological inputs is easy” were prioritized with an average of 4.10, 4.06, and 3.70, respectively. In total, farmers’ viewpoint regarding the ease of using biological inputs was relatively moderate (x̅=3.61). Examination of the farmers’ perception regarding the usefulness of biological inputs remarked that the statements “Using biological methods is useful for nature and human health” by an average of 4.00, “Using biological control methods is economically beneficial” by an average of 3.90, and “Using biological methods prevents entering pesticides/herbicides to human food chain” by an average of 3.89 were prioritized over the others. The ranking mean value of perceived usefulness of biological inputs is estimated to be 3.8 indicating a moderate value. As shown in Table 4, the attitude of farmers regarding the use of biological inputs was relatively moderate (x̅=3.85). Detailed examination of the statements composed of this variable revealed that the statements “In my opinion, it is wise to use biological methods in pest control,” “I do not believe that herbicides and fertilizers to control weeds are harmless because they diminish the land’s fertility over the years “, and “I pay attention to conserve the environment for the future generations during performing farming operations” ranked first by the average of 4.20, 4.11, and 4.02, respectively. The intention of respondents regarding the use of biological inputs was relatively moderate (x̅=3.73). Among the items administered to measure this variable, the statements “I intend to help conserve the environment by using organic manure and biological fertilizers” by an average of 3.76, “I intend to use fully decomposed animal manure to increase the health of agricultural crops” by an average of 3.75, and “I intend to reduce the cost of purchasing pesticides/herbicides and chemical fertilizers by substituting organic and biological fertilizers” showing an average of 3.73 were mostly agreed by farmers. The findings also showed that the respondents have a tendency to use biological inputs, including fully decomposed animal manures and resources that are usually found in the farm, such as straw and stubble, dry fodder, leaves, and crop residues. Furthermore, they have a willingness to reduce the cost of purchasing chemical fertilizers and pesticides/herbicides by replacing them with biological inputs. Prioritized viewpoints of farmers regarding the behavior to use biological inputs revealed that the statements of “I use organic inputs (green manure, animal manure, and compost) in my farm,” “I perform manual weeding to control weeds in my farm instead of using pesticides/herbicides,” and “I use green manure to prevent soil erosion in my farm” ranked first among the others by an average of 4.01, 3.84, and 3.83, respectively. The total average of the farmers’ behavior using biological inputs showed a moderate value (x̅=3.81), which is in tune with the other model constructs.

Today, more than 300 dangerous chemical inputs, including various fertilizers with the purpose of soil fertility and different types of toxic compounds, are used in farms to control pests, diseases, and weeds (Mansourian et al., 2023). While near less than 1% of the consumed volume of pesticides reaches pests, 99% is released into the environment, causing soil and water pollution (Shah Pasand et al., 2021). The adverse impacts of fertilizers and pesticides on environment, food security, and human health have led to more attention to apply alternative methods, emphasizing safe and chemical-free products (Imani et al., 2021). The per capita consumption of toxic compounds as the ingredients of fertilizers is reported to be 400 grams per person in Iran; moreover, the cancer disease incidence statistics, as an index of unhealthy farming style, are higher in areas, where farming practices depend on a higher level of using chemical pesticides (Khosravi and Tohidfar, 2015; Bondori et al., 2020). Usage of fertilizers and pesticides is a topic, which has a longer tradition of research, while topics such as usage of biological control methods are areas of more recent interest. It is clear that farmers are at the forefront of agricultural practices, and the choice of farming style depends on their decision, which is, in turn, a function of different factors. Therefore, the present survey research sought to determine if factors affect farmers’ behavior and their willingness to accept consuming biological inputs; and if so, what mechanisms explain the relationship between them. Therefore, the research model was developed based on the technology acceptance model (TAM). The results presented that the average of attitude, intention, and behavior of farmers regarding the use of biological inputs was relatively moderate, which is in tune with the results of the study by Bagheri et al. (2021). Referring to the correlation findings, a positive and significant relationship between the perceived ease of use and the perceived usefulness of biological inputs was obtained. The higher the perceived ease of use, the more likely the farmers perceive the biological inputs that are beneficial and profitable. This result is in line with the findings by Salarvand (2014), Shahani (2020), and Bagheri et al. (2016, 2021). A positive and significant association was found between the variables of perceived ease of use, the perceived usefulness of biological inputs, and the attitude to use. These results are in agreement with the findings by Salarvand (2014) and Flett et al. (2004). Between the factors of perceived usefulness, perceived ease of use, attitude, and intention (willingness) to use, positive and significant correlations were found which appear to be in line with the studies by, Salarvand (2014), García-García et al. (2016), Shahani (2020) and Bagheri et al. (2016, 2021). The model also highlighted a direct and significant relationship between perceived usefulness, attitude, intention (willingness), and the behavior of accepting biological inputs, confirming the studies by Salehi et al. (2010), Salarvand (2014), and Bagheri et al. (2016, 2021). Moreover, the results that were obtained approved all the hypotheses aforementioned in previous sections. The findings indicated that behavioral intention (willingness) and attitude were recognized as the most important variables affecting farmers’ behavior in accepting biological inputs. Perceived usefulness and perceived ease of use had a direct, positive, and significant effect on the attitude regarding the use of biological inputs. These two factors could predict the attitude of farmers toward using biological inputs. This is consistent with the study by Salarvand (2014), Bagheri et al. (2016, 2021), and Shahani (2020). In addition, the SEM model also suggests that intention and attitude showed a direct, positive, and significant influence on the farmers’ behavior in accepting biological inputs. Totally, these two variables could predict 80% of the behavior variations. When farmers are inclined to use technology and hold a desirable attitude toward that, they are more likely to accept and use it. Referring to the results of the structural equations, it was observed that the perceived usefulness, perceived ease of use, and attitude had a direct, positive, and significant effect on the tendency of farmers to use biological inputs. Therefore, as improvement occurs in the understanding of farmers regarding the usefulness and ease of using biological inputs or in their attitude over time, there will be desirable changes in the extent and acceptance of these inputs in their farming. Similar results were observed in the studies by Salarvand (2014), Momvandi et al. (2018), Valizadeh et al. (2020), and Bagheri et al. (2021), in which the factors influencing the adoption of biological inputs have explained by the TAM model.

The recent drought in Iran has led the government to ban rice cultivation in many areas and impose many restrictions. Under these circumstances, the strategy of farmers to maintain a certain level of income has led to a higher yield per hectare, which is associated with the intensive use of pesticides and chemical inputs to ensure profitability and, usually, in exchange for the loss of environmental safety.

In general, this study not only described the behavior, intention, attitude, and perception of farmers regarding the ease and usefulness of biological inputs but also examined a model which has introduced important factors affecting the acceptance of biological inputs. In addition, in the presence of different categorization variables, the causal relationships between different constructs of the model were examined. In conclusion, the TAM model has the power to predict farmers’ behavior and willingness to accept biological inputs so that attitude and willingness variables could predict behavior, and in turn, willingness could be predicted by attitude, perceived usefulness, and ease of use variables. While the existence of a causal relationship between variables is independent of how farmers are categorized, the contribution of model variables as the predictors of each path is quite different for each group of farmers.

As far as the adoption of new technologies is concerned, the suggestion to be drawn from our analysis is that the most effective means of encouraging farmers to accept the use of safe and healthy inputs is to plan and implement education and extension programs that will lead to a more desirable attitude and willingness to use such products among farmers rather than their continued reluctance. Other actions include training in biological control for agricultural advisors and input suppliers. In addition, in the context of a transition to biological inputs (including biocontrol agents and biofertilizers), it is crucial to promote the coexistence of chemical and biological inputs and work toward a gradual substitution. Meanwhile, significant attempts should be made by agricultural service centers to change farmers’ attitudes, as farmers are reluctant to use biological inputs. Other, more desirable, actions can encourage the adoption and use of biological inputs through subsidies, insurance, and information campaigns that network farmers’ groups. Government initiatives to develop monitoring and control tools to manage the public health aspects of rice produced by farmers are of great importance to enforce their acceptance. At the same time, promoting the benefits of using biological inputs for crop health can make farmers more receptive to using biological inputs on their farms. Strictness should be applied to the health of agricultural products, and at the same time, emphasis should be placed on the benefits of using biological inputs for the health of products in order to influence farmers’ attitudes. In addition to these proposals, which are essentially instrumental, it is important to emphasize interactive interventions, which focus on involving farmers in extension programs to change their farming system in favor of producing healthy crops and protecting the environment. An example of this type of activity can be promoted in demonstration farms, where the usefulness and ease of use of biological inputs are made visible.

This study had some limitations that should be addressed in future research. The first limitation was related to the lack of generalizability of the results. The study was conducted among a sample of farmers engaged in rice production in one district; therefore, the representation of farmers’ behavior in using biological inputs is limited. Given the differences among farmers living in different regions as well as a large research area of the country, a comprehensive study should be developed to investigate farmers’ behavior and willingness to use biological inputs in agricultural practices. Second, due to the lack of long-term perspective in using cross-sectional data, which do not reflect the real and dynamic nature of farmers’ behavior, future research should maintain a longitudinal perspective in the study. Third, the categorization of farmers was not been considered as a study objective in this study, so it is highly recommended that future studies focus on the study problems, dealing with structural equation and modeling in the presence of at least one categorizing factor to concentrate on a specific group of farmers.

The data analyzed in this study is subjected to the following licenses/restrictions: the study respondents were assured about the confidentiality of collected data. Requests to access these datasets should be directed to MF, m.forouzani@asnrukh.ac.ir.

Ethical approval was not required for the study involving humans in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and the institutional requirements.

MF: Conceptualization, Formal analysis, Methodology, Project administration, Supervision, Writing – original draft. AB: Data curation, Formal analysis, Investigation, Software, Writing – original draft. AM: Conceptualization, Data curation, Writing – review & editing.