Abstract
Animal welfare plays a key role in achieving sustainable development goals and addresses the growing concerns of citizens and consumers about animals and their products. This study, using the extended Theory of Planned Behavior (TPB), aims to examine the social and psychological factors influencing pro-animal behavior among dairy farmers. Despite its importance, this topic has been less explored in the research literature of sustainability. Data for the research were collected through a cross-sectional survey and a closed-ended questionnaire from two groups of traditional (n = 122) and factory (n = 208) dairy farmers in Iran. A random sampling approach was used to select the samples. SPSS26 and SEM-PLS3 software were used for data analysis, assessment of measurement and structural models, hypothesis testing, and model validation. The results showed that attitude (Beta = 0.43; Sig = 0.0001), perceived behavioral control (Beta = 0.31; Sig = 0.0001), and subjective norms (Beta = 0.11; Sig = 0.01) had statistically significant and positive impacts on pro-animal behavior. According to the results, awareness of the consequences of pro-animal behavior had a statistically significant and positive impact on attitude towards pro-animal behavior (Beta = 0.54; Sig = 0.0001) and perceived behavioral control (Beta = 0.30; Sig = 0.0001). Additionally, perceived behavioral control (Beta = 0.12; Sig = 0.006) and subjective norms (Beta = 0.17; Sig = 0.0001) had a positive and significant impact on attitude towards pro-animal behavior. In general, the independent variables in the validated model of present study could account for 48 percent of pro-animal behavior variance as the dependent variable. This study, by extending and applying the TPB to analyze pro-animal behavior, not only contributes theoretically to the sustainability literature but also provides practical and valuable insights to facilitate the development of pro-animal behaviors and improve animal welfare for stockmen, decision-makers, and responsible organizations.
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Introduction
FAO statistics in 2023 show that there are more than 32 billion live livestock and poultry species worldwide1. Also, reports from this organization show that livestock farming contributes about 40 percent to the world’s agricultural gross domestic product. Furthermore, the lives of more than 1.3 billion people worldwide depend on the livestock sector2. Since ancient times, animals have played a key role in human life in different ways. In other words, animals have always served as a means to ensure human welfare and meet various needs, a trend that continues to this day3,4. Currently, livestock and poultry farms are commonly found worldwide, fulfilling the diverse needs of societies5,6,7,8. Management practices and husbandry activities have changed over time. Modern livestock farming methods have increased production in livestock farms and have led to economic growth, but they have also generated problems related to animal welfare9.
The question is raised: to what extent do humans consider the welfare and essential needs of animals, given that animals fulfill many human needs and support human welfare? According to source10, four key principles are essential for ensuring animal welfare: providing adequate food and water, ensuring appropriate living conditions, maintaining health, and supporting proper behavior11,12,13. These principles imply that animals should be free from hunger and thirst, discomfort, pain, injury, disease, fear, and distress, and should be able to express normal behavior14.
Dairy farms, especially industrial ones, involve frequent human-animal interaction for purposes like milk production and calf rearing. These practices often lead to animal suffering; for example, the early separation of calves from their mothers causes stress and health issues such as mastitis in cows15,16,17. Overall, the farming environment significantly influences animal welfare18,19,20. On the other hand, the treatment of animals by livestock farmers is influenced by ethical principles and society’s perception of the livestock industry. In this regard, increasing awareness of the sentience of animals has led to increased attention to animal welfare by various groups, such as policymakers and consumers21.
In some dairy farms, cows are forced to stand for extended periods, preventing natural behavior and increasing fatigue and lameness22. Diseases like mastitis are also prevalent, often linked to poor hygiene in bedding and milking equipment23,24. Adequate food and clean water are vital for animal welfare, yet research shows that some farms fail to meet these basic needs25,26. Proper nutrition, guided by animal nutrition experts, helps prevent issues like milk fever, caused by calcium loss after birth27,28. These conditions suggest an exploitative human-animal relationship, where animal welfare is often neglected in favor of human interests, violating key welfare principles29,30,31,32. This neglect stems from speciesism human perspectives that reduce animals to mere resources, disregarding their moral status as sentient beings33,34, which results in inappropriate treatment6,35,36.
Animal welfare is important for several reasons. Mammals, in particular, are sensitive beings capable of feeling pain and negative emotions37,38,39. Many people believe animals have intrinsic value and deserve moral consideration and respect, not just as means to human ends40,41. Concern for animal welfare is especially growing in regions like the European Union, where public awareness is rising42,43,44. As a result, stockmen in these areas are expected to adopt farming practices based on scientific knowledge and research to address these concerns45,46,47. In order to ensure animal welfare, organizations such as World Organization for Animal Health (WOAH) and the Food and Agriculture Organization (FAO) have taken useful measures that can serve as a beacon for different countries towards animal welfare48,49. Animal welfare is closely linked to achieving Sustainable Development Goals (SDGs), as research indicates it positively impacts several of them50,51,52. Enhancing animal welfare can lead to higher productivity, lower mortality, and fewer disruptions, offering economic advantages for stockmen53,54. Given the major role of animal products in human diets, safeguarding animal welfare also contributes to human health23,24,55,56,57.
To achieve animal welfare, numerous studies58,59,60 have been conducted. Most of these studies focus on providing technical solutions and pay less attention to the role of stockmen behavior and its antecedents61. Nonetheless, there are few studies that examines role of stockmen behavior and its determinants in animal welfare. Borges et al.62 investigated factors influencing the intention to improve environmental quality among Brazilian pig farmers using the theory of planned behavior. They found that attitude, subjective norms, perceived behavioral control, and self-identity positively and significantly influenced environmental enrichment intentions. Jafari-Gh et al.63 studied the welfare of intensively raised dairy cattle in Iran using both animal-based and stockperson-based indicators. While stockmen paid attention to feeding, issues such as lameness, hock lesions, tail damage, and dirty legs were prevalent. Kauppinen et al.64 applied the original theory of planned behavior to examine pro-animal behavior among Finnish stockpersons. Their study revealed a weak positive link between attitudes, perceived behavioral control, and animal welfare indicators, while agricultural consultants, as subjective norms, had a negative influence. The findings suggested that concern for animal welfare was largely driven by stockmen’s own well-being. Lastly, Matore65 assessed attitudes and knowledge about animal welfare, finding low levels of both, along with low levels of pro-animal behavior.
Each of the cited studies has addressed aspects of animal welfare, and the present study aims to fill existing research gaps. For instance, Jafari-Gh et al.63 focused only on welfare indicators in farms without exploring psychological factors influencing them, which the current study addresses. Borges et al.62 measured farmers’ “intentions” toward certain welfare aspects, whereas the present study evaluates actual stockmen behavior across multiple dimensions (feeding, housing, health, behavior). Similarly, Kauppinen et al.64 limited their welfare indicators to environment-based ones and used basic statistical methods like regression and correlation, while this study applies Structural Equation Modeling for more precise analysis. Finally, unlike Matore65, who only assessed variable levels, the current study examines the relationships between research variables in depth. Stockmen, due to their close relationship with animals, are the ultimate factor in ensuring animal welfare66. Understanding the factors influencing their behavior toward animals can play a crucial role in enhancing animal welfare67. Therefore, it is essential that the scientific community focuses not only on technical studies related to animal welfare but also on social and psychological research.
To the best of our knowledge, studies on the social, psychological, cultural, and moral aspects of animal welfare are limited. Thus, the results of present study can serve as a valuable resource for policymakers and provide a foundation for future research in this field to gain a comprehensive understanding of the determinants of animal welfare across different societies. In other words, this study goes beyond the technical and environmental discussions of animal welfare and focuses on the social, psychological, cultural, and moral determinants. Through this, the present research contributes to the development of knowledge in the field of sustainability and animal welfare.
Specifically, the aim of the present study is to investigate the factors influencing pro-animal behavior among Iranian livestock farmers. To pursue this aim, an extended version of the theory of planned behavior and structural equation modeling were used. On the other hand, this study seeks to examine the differences between traditional and industrial livestock farming in terms of their effects on pro-animal behavior and other research variables. It should be mentioned that management practices, goals, values, and the level of attention to animal welfare differ in different types of livestock farming68,69. Therefore, examining the differences between these two types of livestock farming can provide broad insight and accurate information both in practical and theoretical terms. Finally, the results of this study presents practical solutions for developing pro-animal behavior.
Theoretical background and development of hypotheses
Animal welfare
Various studies70,71,72 propose or define principles and dimensions for ensuring and assessing animal welfare. One of the earliest important documents on animal welfare is the Brambell Report73, which examined the welfare of animals in intensive breeding systems. It emphasized humans’ ethical obligation to treat animals well, recognizing that animals clearly perceive hardship and adversity. The report argued that animal welfare requires fulfilling both physical and psychological needs and stressed that those who work with animals must understand their status and develop proper husbandry skills. Another significant document from the Farm Animal Welfare Council14 reinforced these ideas, stating that since humans raise animals for various purposes, they are responsible for meeting animals’ physical and psychological needs. This report outlined five conditions animals should be free from to achieve welfare: hunger and thirst, inadequate housing, pain/injury/disease, restrictions on natural behavior, and fear and stress. Additionally, it introduced a classification of animal lives into three types: “a life not worth living,” “a life worth living,” and “a good life,” advocating that animals should at least have “a life worth living” during their lifetime. Another key contribution to animal welfare is the Welfare Quality Assessment Protocol for Dairy Cattle74. This project defines specific dimensions to assess animal welfare, particularly for dairy cattle, emphasizing the importance of observable conditions of both the animals and the farm. The protocol’s core principles for achieving and evaluating welfare include good feeding, good housing, good health, and appropriate behavior, each broken down into detailed subcategories to guide comprehensive welfare assessment (Table 1).
The World Organization for Animal Health (OIE) provides one of the most important and comprehensive definitions of animal welfare, describing it as the physical and mental state of an animal throughout its life and at death. Good welfare means the animal is healthy, comfortable, well-fed, and in a safe environment free from pain, fear, and stress. It also includes the ability to express necessary behaviors for its physical and mental well-being. Achieving welfare involves disease prevention, veterinary care, proper housing and feeding, a stimulating and safe environment, humane treatment, and humane slaughter. Welfare depends on the animal’s condition but is also influenced by human behaviors and farming practices48. Dawkins75 offers a simpler definition by asking two questions: “Are the animals healthy?” and “Do the animals have what they want?” The Dairy Cow Welfare Assessment Project further outlines four dimensions of animal welfare, which researchers have applied in various assessments, summarized in Table 2 along with related literature.
Determinants of pro-animal behavior (PaB) using extending the TPB and hypothesis development
Stockmen’s behavior plays a crucial role in ensuring animal welfare, and understanding the factors influencing pro-animal behavior requires a multifaceted approach. This study uses the Theory of Planned Behavior (TPB) as its theoretical framework. Ajzen originally developed the TPB by adding perceived behavioral control to the Theory of Reasoned Action87,88. According to TPB, subjective norm, attitude, and perceived behavioral control predict behavioral intention, which in turn influences actual behavior89,90. A stronger intention increases the likelihood of behavior occurrence91,92. Social pressure from close contacts enhances intention93,94, as does a favorable evaluation of the behavior95,96,97. Perceiving the behavior as easy to perform also strengthens intention98,99. Both original and extended versions of TPB have been widely used in research100,101. For instance, study102 applied the original TPB to explain individual behavior, while study103 used an extended version to measure green product purchase intentions. TPB has also been applied to understand behaviors related to organic product purchasing104, use of organic fertilizers105, and avoiding single-use plastics106. The next section will explain the relationships between TPB’s main constructs and its theoretical development.
Attitude towards pro-animal behavior
The attitude variable refers to an individual’s positive or negative evaluation of a behavior or idea107,108. In fact, an individual’s attitude reflects how valuable or important a phenomenon or behavior, such as animal welfare, is to them109,110. Attitude can influence behavior in various domains. Tian et al.111 concluded that environmental attitudes have a positive and significant impact on employees’ green behavior. Dhir et al.112 also found that consumer attitude plays a positive role in environmental-friendly behavior. Furthermore, Munoz et al.67 show that livestock management practices that positively or negatively impact animal welfare are influenced by attitudes among Australian sheep farmers. Platto et al.113 show that attitude has a positive and significant effect on future behavior of livestock farmers for considering animal welfare in China. Based on the above studies, it can be concluded that attitude plays a decisive role in determining behavior. Therefore, it can be hypothesized that:
Hypothesis 1
Stockmen attitudes towards PaB have a positive and significant impact on their PaB.
Awareness of behavioral consequences
The variable of awareness of behavioral consequences is an important factor in norm activation theory and value-belief-norm theory114,115. This variable refers to the extent of an individual’s awareness of the consequences of their behavior, such as pro-animal behavior116,117. Liobikienė and Poškus118 found that awareness of behavioral consequences has a positive impact on selfish protective behavior (private sphere behavior). Fang et al.119 conducted a multi-group comparative study showing that in one group, awareness of behavioral consequences has a positive and significant impact on protective behavior, while in the other group, there is no significant relationship between these two variables. Therefore, adding this variable to the TPB can help in its development. Moreover, Han120 showed that awareness of behavioral consequences has a positive and significant impact on attitude toward green purchasing. Studies by Rastegari Kopaei et al.121 and Savari et al.122 also show that awareness of behavioral consequences has a positive and significant impact on attitude. Furthermore123,124,125, found that increasing awareness of behavioral consequences strengthens attitude and perceived behavioral control. Therefore, it is hypothesized that:
Hypothesis 2
Awareness of behavioral consequences has a positive and significant impact on attitude towards PaB.
Hypothesis 3
Awareness of behavioral consequences has a positive and significant impact on PaB.
Hypothesis 4
Awareness of behavioral consequences has a positive and significant impact on perceived behavioral control about PaB.
Perceived behavioral control towards pro-animal behavior
Perceived behavioral control refers to the perceived ease or difficulty of performing a behavior like pro-animal behavior by an individual107,126. In other words, this variable assesses the feasibility of a behavior from an individual’s perspective127. Esfandiar et al.128 state that perceived behavioral control increases the use of waste bins (binning behavior) among tourists. Also, Kauppinen et al.64 claim that perceived behavioral control has a positive and significant effect on the occurrence of animal welfare indicators among Finnish dairy farmers. Other studies showed that perceived behavioral control and self-efficacy has a positive effect on environmentally friendly behavior129,130,131,132. Therefore, it is hypothesized that:
Hypothesis 5
Perceived behavioral control has a positive and significant impact on attitude towards PaB.
Hypothesis 6
Perceived behavioral control has a positive and significant impact on PaB.
Subjective norm on pro-animal behavior
Subjective norm refers to the perceived social pressure from close ones to perform or refrain from performing a behavior107,133,134. In fact, this variable shows the extent to which an individual perceives the expectations of their close ones to perform or not perform a behavior135. It is important to note that subjective norms also influence psychological constructs such as attitude and perceived behavioral control136,137. For example, Ogiemwonyi et al.138 found that subjective norms have a positive and significant impact on green purchasing behavior. Moreover, Lind et al.139 show that subjective norm has a positive and significant effect on the acceptance of mastitis prevention methods among Swedish dairy farmers. Furthermore, Van Tonder et al.140 showed that subjective norms, in addition to having a positive impact on consumers’ green buying behaviors, also have a positive and significant impact on consumers’ green attitudes. López-Mosquera et al.141 concluded that subjective norms strengthen the attitude and perceived behavioral control of visitors to urban parks in terms of paying for park conservation. Park and Ha142 also demonstrated that subjective norms can predict attitudes and perceived behavioral control related to recycling. Based on this, it is hypothesized that:
Hypothesis 7
Subjective norms have a positive and significant impact on attitude toward PaB.
Hypothesis 8
Subjective norms have a positive and significant impact on PaB.
Hypothesis 9
Subjective norms have a positive and significant impact on perceived behavioral control about PaB.
In balance, the relationships between the variables and the extended TPB can be summarized as Fig. 1.
Theoretical framework of the study.
Methodology
Research type
Given the objectives of present study, a cross-sectional survey method was used. A cross-sectional survey is a type of quantitative research in which a set of data is collected at a specific point in time through questionnaires and interviews143. This research is also considered applied because various groups, such as policymakers, stockbreeders, and specialists, can benefit from the results of this study.
Study area
This study was conducted in Fars Province, located in the southwest of Iran (Fig. 2). Fars is one of the key provinces in the country for livestock production, playing an important role in ensuring national food security and creating employment144. The province has 5,650,000 goats and sheep, ranking first in the country, as well as producing 57,950 tons of red meat (ranking second) and 644,700 tons of raw milk (ranking fourth) in the country. One of the key contributors to red meat production and the main source of raw milk in this province is dairy cows, with a population of 345,275. Dairy farms in Fars Province play a vital role in providing raw milk for dairy industries and calves for fattening, contributing significantly to the province’s and the country’s food security. Given the critical importance of this province in food production, especially animal products, collecting data and providing suitable analysis in this area can guide policymakers and stakeholders in this vital sector.
Study site. Adobe Photoshop software version 23.0.1 (https://www.adobe.com/products/photoshop.html).
Statistical population and sampling method
The statistical population studied includes all factory and traditional dairy farmers in Fars province. According to the statistics obtained from the Agricultural Jihad Organization of Fars province, the number of dairy farmers in the province is 17,211. For estimating the sample size, the Krejcie and Morgan table was used. Therefore, based on the total number of dairy farmers in Fars province, the sample size was calculated to be 379 dairy farmers. A stratified random sampling method with proportional allocation was used for sampling. Since farms vary in terms of area, number of livestock, and type of management, they were divided into two strata: traditional and factory. Then, 330 dairy farmers were randomly selected from five counties of Shiraz (n = 80), Marvdasht (n = 120), Zarqan (n = 37), Beyza (n = 39), and Kavar (n = 54), proportionate to the population of dairy farmers in each county.
Data collection tools
Based on existing literature in the fields of animal welfare and environmental psychology, the relevant variables were extracted, and a questionnaire was designed to collect data. The content and face validity of the questionnaire were confirmed by six experts in the fields of animal sciences, psychology of sustainability, and animal welfare before data collection. To assess the reliability of the questionnaire, a pilot study was conducted in Kharameh County, Fars province. In this pilot study, 30 dairy farmers were randomly selected from various villages in Kharameh. After collecting the pilot study data, Cronbach’s alpha coefficient was calculated for each variable/construct. It is worth noting that during this process, some items were revised if necessary. These revisions included rephrasing, editing, or removing certain items. Finally, after preparing the final version of the questionnaire, it was used to collect the main data. After completing the final survey, the reliability of the instrument and data was re-examined using composite reliability and rho-a measures. To assess the validity of the questionnaire and the main data, convergent and discriminant validity measures were used. For convergent validity, the Average Variance Extracted (AVE) criterion was used, and for discriminant validity, Fornell-Larcker, Heterotrait-Monotrait ratio (HTMT) and variance inflation factors (VIFs) criteria were applied. Additionally, to measure the questions for all variables, a five-point Likert scale (1 = very low to 5 = very high) was used.
Conceptual and operational definitions of variables
In this section, conceptual and operational definitions of the constructs are presented. However, the detailed items/questions used for assessing each variable have been presented in Appendix 1.
Subjective norm: This variable refers to the social pressure perceived by stockmen from their relatives to ensure animal welfare. This concept is measured using five questions on a five-point Likert scale (1 = very low to 5 = very high).
Awareness of behavioral consequences: This variable includes stockmen’ awareness of the negative consequences of their actions on animal welfare. This variable is assessed using six questions on a Likert scale (1 = very low to 5 = very high).
Attitude: Attitude reflects the favorable or unfavorable evaluation of stockmen regarding the adherence to animal welfare. It is measured using nine questions on a five-point Likert scale (1 = very low to 5 = very high).
Perceived behavioral control: Behavioral control indicates the perceived ease or difficulty by stockmen in adhering to animal welfare, measured using six questions on a five-point Likert scale (1 = very low to 5 = very high).
Pro-animal behavior: This concept measures animal welfare. Animal welfare refers to the physical and mental condition of an animal during its life and death. An animal experiences good welfare when it is healthy, comfortable, well-fed, and in a safe environment free from pain, fear, and stress. Moreover, an animal that can exhibit behaviors necessary for its physical and mental conditions is mentioned to have good welfare. Animal welfare requires disease prevention, appropriate veterinary care, management of housing, nutrition, a stimulating and safe environment, humane behavior, and humane slaughter. While animal welfare depends on the animal’s condition, behaviors such as animal care, farming practices, and human behavior can affect animal welfare." This variable assesses the fulfillment of animal needs in four dimensions: nutrition (food-water), environment, health, and appropriate behavior. In the present study, twelve questions (8 for food, 4 for water) are used to assess the nutrition dimension, 15 questions for the environment, 16 questions for health, and 16 questions for behavior, all measured on a five-point Likert scale.
Data analysis
In this study, descriptive statistics and mean comparison tests were conducted using SPSS software. For assessing the measurement model, evaluating the structural model, and testing hypotheses, PLS software was used. The measurement model indicates the extent to which the designed items measure the intended variable. Additionally, the structural model examines the relationships between the research variables (latent constructs), through which the hypotheses are also tested.
Statement
All participants were briefed on data protection concerns by the enumerators and provided verbal consent at the start of each interview. Informed consent was acquired from every individual participant involved in the study. All materials and methods were carried out in line with the relevant guidelines and regulations, and this research received approval from a committee at Shiraz University, Iran. The study was approved by the institutional review board at Shiraz University, Iran. All procedures conducted in studies involving human participants adhered to the ethical standards set by the institutional research committee and complied with the 1964 Helsinki declaration and its subsequent amendments or similar ethical standards.
Results
Demographic characteristics of respondents
Table 3 shows the demographic characteristics of the stockmen under study. According to this table, the number of traditional farms was 122, and the number of factory farms was 208. The average age of the stockmen was about 49 years, with most stockmen falling in the age range of 40–60 years. The average experience of the stockmen in livestock farming was 23.18 years, and most of them (N = 177) had less than 20 years of experience. The results indicate that the highest frequency of education level was related to high school (N = 153), while the lowest frequency (N = 28) was for illiterate stockmen.
Comparison of variables among different groups of stockbreeders
In this section, the mean values of the variables were compared between two groups of traditional and factory stockmen. In other words, this section determines whether the difference in means of the variables between traditional and factory stockmen is significant. According to Table 4, there is a significant difference between the two groups of traditional and factory farms in terms of awareness of the consequences of pro-animal behavior (T = -2.44; P = 0.016). Based on the results of testing this hypothesis, the mean value of awareness of the consequences among factory stockmen (Mean = 27.96) is higher than the mean value of awareness of the consequences among traditional stockmen (Mean = 27.22). Furthermore, the results showed that there was no significant difference between traditional and factory stockmen in terms of subjective norm (T = -1.24; P = 0.215). However, there was a significant difference between traditional and factory stockmen in terms of perceived behavioral control (T = -5.33; P = 0.0001). Accordingly, with respect to perceived behavioral control, with a mean of 24.25, factory stockmen had a higher rank compared to traditional stockmen, which had a mean of 22.66.
Also, there was a significant difference between the two farming systems with respect to the attitude toward pro-animal behavior (T = -2.03; P = 0.043). In other words, the mean attitude in factory stockmen was 44.25, which is higher than the mean of attitude for traditional stockmen (43.17). There was also a significant difference in the mean pro-animal behavior between the two farming systems (T = -2.41; P = 0.01). The mean of pro-animal behavior in factory farming was 234.13, while in traditional farming it was 229.66.
Measurement model
In order to assess reliability in present study, the Cronbach’s alpha coefficient, composite reliability, and homogeneity reliability (Rho) indices were used. The minimum acceptable value for each of these indicators is 0.70. In the current study, the values for these three indices were found to be higher than the acceptable threshold (ranging from 0.74 to 0.90) (Table 5). Therefore, the research tool is considered to have the necessary reliability. Additionally, for assessing validity, both convergent and discriminant validity were examined. For convergent validity, factor loadings and the average variance extracted (AVE) were used, while for discriminant validity, the Fornell-Larcker criterion, the HTMT (Heterotrait-Monotrait ratio), and variance inflation factors (VIFs) were applied. The factor loadings of all the items in the study ranged from 0.48 to 0.83. It should be noted that, ideally, factor loadings should be greater than or equal to 0.70. However, in some cases, since items with factor loadings less than 0.70 are statistically significant, it is better to retain them in the analysis. In the present study, the minimum acceptable factor loading value was 0.48 (Table 5). Since this factor loading was statistically significant and removing it could harm the content validity of the latent construct, it was retained in the analysis. The AVE values ranged from 0.50 to 0.65, which is higher than the recommended value of 0.50 suggested by statistical sources (see Hair et al. 2010). Therefore, the constructs in this study are confirmed to have convergent validity. In summary, regarding attitude and perceived behavioral control (PBC), we initially had and reported nine and six items (respectively) (Appendix), but the factor loading for item 5 of attitude and item 6 of PBC were well below the threshold. If we included these items, index estimates for the key psychometric indices of the model such as Cronbach’s alpha, rho-A, composite reliability (CR), and AVE decreased as a result. Also, maintaining these items in the analysis could increase the inner and outer VIF values. Ultimately it was appropriate based on best practices in structural equation modeling, not to include these items in the final model, thereby allowing us to report more valid indicators of construct validity and improving model fit. With respect to pro-animal behavior (PaB), as noted earlier we started with 59 items to measure this construct in a comprehensive way. However, the nature of the analysis we were conducting meant that including 59 items directly into the structural model would complicate the model and limit our ability to control for multicollinearity. To contain these limitations and avoid producing misleading or unstable estimates, we were guided to convert this higher-order construct into first-order construct. In other words, we aggregated (or computed) items from the same subdimension into single indicators measuring the subdimensions. We used the computed or aggregated indicators to represent the main construct as direct measures. Overall, this approach minimized the number of indicators, improved parsimony of the model, and maintained the logical flow of the construct145.
Table 6 shows the discriminant validity based on the Fornell-Larcker criterion. If the diagonal elements of the matrix are greater than the corresponding off-diagonal elements, discriminant validity based on this criterion is confirmed. As shown in this Table 6, the diagonal elements of the matrix are greater than the corresponding off-diagonal elements, confirming discriminant validity based on this criterion. HTMT is another criterion for assessing discriminant validity. According to this criterion, the values in each column of the table must be less than 0.90. According to Table 6, the values in the columns are less than the suggested threshold. Therefore, the discriminant validity of the constructs is also confirmed based on this criterion. In summary, the implementation of the measurement model in this study confirms that the reliability and validity of the research tools and the data used for analysis are confirmed.
To assess collinearity of the items, the Outer Variance Inflation Factor (Outer VIF) was used, and for evaluating collinearity of the variables (latent constructs), the Inner Variance Inflation Factor (Inner VIF) was applied. If there is high correlation between an item or variable, the VIF value increases, which indicates high multicollinearity between some items or variables. In fact, a high VIF value indicates collinearity, which can lead to bias in the test results. It is important to note that the acceptable range for the VIF index is between one and five, and the closer the value is to one, the better the result (Hair et al. 2010). As shown in Table 5, the VIF values for each of the items fall within the acceptable range (1.17 to 2.91). Additionally, Table 7 shows that the VIF values for the variables (latent constructs) are also within the acceptable range (1.14 to 1.88). Therefore, the correlation between items and variables is reasonable and logical, and thus does not cause any disturbance in the test results.
Structural model
To examine the relationships between the variables and test the hypotheses, the structural model of the research was used. Table 8 and Fig. 3 summarize the results of hypothesis testing and related information. According to Table 8, the variables of attitude (Beta = 0.43; P = 0.0001, T = 6.68), perceived behavioral control (Beta = 0.31; P = 0.0001, T = 7.27), and subjective norm (Beta = 0.11; P = 0.01, T = 2.47) have a significant positive impact on pro-animal behavior, while the variable of awareness of behavioral consequences (Beta = 0.04; P = 0.41, T = 0.71) does not have a significant impact on pro-animal behavior. Therefore, hypotheses 1, 6, and 8 are confirmed, and hypothesis 3 is rejected. It is important to note that the perceived behavioral control variable has the most significant impact on behavior.
Path model with standardized factor loadings.
Furthermore, awareness of behavioral consequences (Beta = 0.54; P = 0.0001, T = 10.56), perceived behavioral control (Beta = 0.12; P = 0.001, T = 2.75), and subjective norm (Beta = 0.17; P = 0.0001, T = 3.98) had a significant positive impact on attitude. Therefore, hypotheses 2, 5, and 7 are confirmed. Among the variables within the framework, awareness of behavioral consequences has the greatest power in predicting attitude. Additionally, the results indicated that awareness of behavioral consequences has a significant positive effect on perceived behavioral control (Beta = 0.30; P = 0.0001, T = 6.10), while subjective norm (Beta = 0.10; P = 0.09, T = 1.66) does not have a significant effect on perceived behavioral control. Therefore, hypothesis 4 is confirmed, and hypothesis 9 is rejected. To evaluate the predictive power of the model, the coefficient of determination (R2) was applied. This coefficient indicates to what extent the independent variables are capable of predicting the changes in the dependent variable. Overall, the presented model explains 13% (R2 = 0.130) of the variance in perceived behavioral control, 46% (R2 = 0.468) of the variance in attitude, and 48% (R2 = 0.485) of the variance in pro-animal behavior.
Discussions and implications
Discussion from the comparison of traditional and factory dairy farms in terms of psychometric variables
The study found that stockmen working in factory dairy farms exhibited significantly greater awareness of the consequences of their behavior compared to those in traditional farms. This heightened awareness is attributed to more frequent and effective communication with veterinarians and nutrition experts. Both farming systems showed high and similar levels of subjective norms, indicating that stockmen across both systems feel pressure from various social and professional networks to maintain expected standards. However, factory farm stockmen demonstrated a significantly higher sense of perceived behavioral control, mainly due to greater financial resources and better access to equipment and infrastructure. Additionally, their attitudes toward pro-animal behavior were more positive, as they viewed animal welfare as a vital factor in improving productivity and profitability, whereas traditional stockmen recognized animal welfare but did not prioritize certain aspects due to resource constraints.
Factory stockmen were also found to practice more pro-animal behavior, largely influenced by their scientific approach to animal husbandry and better access to resources. These stockmen often invest in advanced feeding systems, clean water supplies, and comfortable housing to support animal health and increase production efficiency. They also prioritize regular veterinary care, timely vaccinations, and disease prevention due to the larger scale of their operations. In contrast, traditional stockmen often lack the financial means or technical knowledge to adopt such practices. While both groups showed some commitment to animal interaction and care, factory stockmen’s access to better infrastructure, expert guidance, and higher awareness enables them to provide more comprehensive and consistent animal welfare.
The reported differences between traditional and factory farms (stockmen) practically and theoretically are of great importance. They are theoretically significant; since these differences can contribute to the extension of the TPB employed in this study theoretically. The hypothetical model helps explain how contextual variables including “access to infrastructure”, “expert consultation”, and “financial resources” mediate main psychological constructs like PBC and attitudes toward animal welfare. For instance, the stronger PBC observed in factory farms aligns with stockmen better access to tools and systems required to adopt pro-animal measures, thus reinforcing the TPB’s emphasis on control beliefs. Likewise, the more favorable attitudes among factory stockmen demonstrate a cognitive association between animal welfare and economic performance, a point of view formed through their direct exposure to industrial management frameworks. From a practical point of view, these results make salient the significance of tailoring in-action and field-oriented interventions and educational programs to the realities of each farming system. Although factory stockmen might take the advantage of reinforcing existing knowledge and values, traditional stockmen may be in need of more foundational supporting packages in infrastructure and training to bridge gaps in PBC and actual behavior. Future research should explore the interplay of these dynamics in more depth. More specifically, future researchers can examine how interventions can be tailored to distinct farming contexts in ways that enhance the practical utility of behavioral models like TPB.
Discussions from analyzing factors affecting pro-animal behavior
This study, by incorporating the awareness of behavioral consequences to the TPB and outlining new relationships and interactions between the constructs of the theory, aims to examine pro-animal behavior among stockmen. In other words, it tests the direct and indirect effects of four variables—attitude, perceived behavioral control, subjective norms, and awareness of behavioral consequences—on pro-animal behavior. The results indicate that attitude toward pro-animal behavior strongly predicts pro-animal behavior. In other words, stockmen who consider the welfare of animals across various dimensions important exhibit better pro-animal behavior. Studies111,112 also show that attitude has a positive and significant effect on sustainability-supporting behaviors. Furthermore, Munoz et al.67 claim that, Farmer behaviors are influenced by attitude among sheep farmers. In this research, attitude is an important mediating variable, as it mediates the effects of awareness of behavioral consequences, subjective norms, and perceived behavioral control on pro-animal behavior. Given the significant effect of attitude on pro-animal behavior, it is recommended to strengthen stockmen’ attitude toward animal welfare with more seriousness. Since ensuring animal welfare often increases stockmen’s profits, emphasizing profitability can be a great strategy to enhance stockmen’ attitudes toward animal welfare. However, application of this strategy as tool to improve the attitude required a deep investigation and quantification of the impacts of considering animal welfare on the profitability of stockmen. Additionally, many stockmen have shown sensitivity toward environmental protection. Therefore, the positive role of ensuring animal welfare in maintaining environmental sustainability can be highlighted for stockmen, and through this make significant improvement in the attitude of stockmen towards animal welfare. Besides, ensuring animal welfare plays a significant role in the health of both animals and humans. A large portion of citizens’ food comes from animal sources, and if the animals used are not sufficiently healthy, consumers’ health can be compromised. Alongside these points, the ethical aspect is also of considerable importance that can be used as a tool to improve the attitude towards pro-animal behaviors. It must be kept in mind that animals, like humans, are sensitive beings, and respecting ethics when dealing with them is very important.
The results also showed that awareness of behavioral consequences has a positive and significant effect on stockmen attitudes and perceived behavioral control. This means that as stockmen’s awareness of the positive consequences of pro-animal behavior increases, their positive attitude toward animal welfare and their perception of the possibility of achieving animal welfare will also increase. Studies120,121,122 also support the results that awareness of behavioral consequences has a positive and significant effect on individuals’ attitudes. In this regard, stockmen believed that they must treat the animals well because mistreatment causes stress and decreases milk production. Based on the results, increasing awareness of the consequences of pro-animal behavior among stockmen can strengthen their attitudes and perceived behavioral control as well. Therefore, it is necessary to provide strategies to enhance awareness of behavioral consequences. Increasing the communication between stockmen and livestock specialists can be an effective strategy for raising awareness. There are solutions to strengthen the relationship between stockmen and specialists/experts. For example, experts can increase their communication with stockmen through common messaging software or platforms created for stockmen. Experts can send positive outcomes of management practices in different areas (nutrition, health, housing and behavior) to stockmen under their supervision through these messengers at a particular time interval (daily, weekly, monthly, etc.). These messages can be in the form of videos, images and text. On the other hand, stockmen can share their problems with them by sending messages to experts and become aware of the results of their management behaviors. This communication can also be established in person. More particularly, experts can be assigned to a specific number of stockmen in the fields of nutrition, health, housing, and behavior. In this process, experts can visit livestock farms at a specific time and inform farmers about the consequences of their farming practices. Farmers will also be able to share their problems with the experts. On the other hand, by showcasing successful livestock farms, awareness of the consequences of behavior can be improved among livestock farmers. In charge organizations can plan visits to successful livestock farms for stockmen. In this regard, experts and livestock owners can explain appropriate management methods such as feeding and treatment methods to visitors and present the positive consequences resulting from them with accurate statistics.
The results also showed that awareness of behavioral consequences does not have a significant impact on pro-animal behavior, directly. Some stockmen claimed that while they were aware of the benefits of pro-animal behavior, certain constraints prevented them from ensuring animal welfare. Factors including financial constraints, limited farm space, and lack of access to necessary inputs made it difficult for stockmen to implement certain practices, even if they were aware of their benefits and willing to adopt them. Furthermore, the study found that perceived behavioral control has a statistically significant positive impact on both stockmen’s behavior and attitudes. Essentially, the more feasible stockmen perceive animal welfare to be, the more favorable their attitude toward ensuring it becomes, leading to greater adherence to animal welfare practices. Studies130,131,132 also confirm this result. In addition, Kauppinen et al.64 shows that perceived behavioral control builds up animal welfare in the dairy farms. When stockmen believe that ensuring animal welfare is not difficult and is within their capacity, they exhibit more supportive behavior. The perceived ease of implementing welfare measures fosters a more positive attitude toward animal welfare among stockmen. Given the crucial role of this factor in promoting pro-animal behavior, it is essential to develop strategies to strengthen it among stockmen. External factors play a significant role in reinforcing this variable, and therefore, policy-makers and governmental entities should facilitate necessary support. For example, reduction the cost of livestock inputs, appropriate pricing of animal products, establishment of supportive regulations, removing bureaucratic constraints, simplifying the licensing process, and providing stockmen with free or low-cost services under climate change can significantly contribute to strengthening perceived behavioral control.
The results also indicate that subjective norms of pro-animal behavior can predict stockmen’s attitudes and behavior, but they do not have a significant impact on perceived behavioral control. In other words, the social pressure perceived by stockmen can reinforce their attitudes and behaviors toward animal welfare. Ogiemwonyi et al.138 suggest that subjective norms have a significant positive influence on individual behavior. Similarly140, found that subjective norms have a significant positive effect on both behavior and attitudes. Moreover, Lind et al.139 claim that subjective norm affects positively acceptance of mastitis prevention methods. Overall, livestock farming operates as a network interconnected with various individuals and organizations. Just as stockmen have expectations from these entities, the entities also have expectations from them. For instance, veterinary networks vaccinate stockmen’s cattle for free and expect them to maintain proper hygiene for their animals. Additionally, some stockmen are members of livestock cooperatives that supply essential inputs, and in return, they deliver their milk to cooperative collection centers. These interactions create expectations for stockmen to uphold proper hygiene and feed their cattle well to ensure high-quality milk production. Beyond external organizational interactions, livestock farms are often located close to one another, leading to expectations among stockmen themselves. Stockmen expect each other to vaccinate and treat their cattle on time, as well as to maintain clean farm environments by properly managing manure disposal. These factors contribute to overall animal welfare. Given this dynamic, providing stockmen with feedback from organizations and peers can strengthen subjective norms. Observations indicate that stockmen who are cooperative members exhibit stronger subjective norms. Therefore, establishing livestock cooperatives in areas where they do not yet exist would be an effective step toward strengthening subjective norms. Encouraging membership in cooperatives can further reinforce this variable. Strengthening the subjective norm through responsible organizations is one of the strategies for improving the subjective norm. In this regard, the relevant organizations can remind the livestock farmers of their organization’s goals along with their expectations. In fact, these organizations can set standards for each management method (such as appropriate space, water and food quality, ventilation) and share them to the livestock farmers. In this regard, the organizations can remind these standards continuously and through various communication methods. Also, Organizations can produce content on public media, such as television, to highlight the poor welfare situation of livestock in their country and the problems it causes. On the other hand, they can present the public with suitable conditions for raising livestock, so that by comparing these two situations, people’s expectations of livestock farmers can be increased.
Conclusions, limitations, and future research pathways
Due to their close relationship with livestock, stockmen can play a significant role in ensuring the welfare of animals. Therefore, the present study aimed to assess the factors that influence the occurrence of pro-animal behavior among dairy cattle farmers. Accordingly, the study utilizes an extended version of the TPB to examine the role of psychological constructs in the manifestation of pro-animal behavior. The results from testing the hypotheses indicate that enhancing attitudes, perceived behavioral control, and subjective norms can positively reinforce pro-animal behavior of stockmen. Furthermore, it can be concluded that while awareness of behavioral consequences does not directly influence the pro-animal behavior of stockbreeders, this variable can indirectly explain behavior due to its significant direct effect on perceived behavioral control and attitude variables. Additionally, the results of evaluating the effect of subjective norms on stockmen’s attitudes suggest that the development of social pressure factors is key to enhancing positive attitudes toward animal welfare. This, in turn, can lead to actual behaviors that promote animal welfare. This study aims to provide insightful results by measuring stockmen’s actual behaviors rather than their intentions. Furthermore, by drawing on fundamental projects in the field of animal welfare, such as Welfare Quality (WQ) assessments, the Farm Animal Welfare Council (FAWC), and the Bramble Report, this research seeks to take steps forward in realizing animal welfare. The results of this study emphasize that policymakers and relevant organizations, in addition to focusing on external and technical components, should pay special attention to social and psychological constructs, as stockmen are the ultimate factor in realizing animal welfare.
This research provides invaluable results; however, like other studies, it faces certain limitations. Based on the existing literature, it can be claimed that few social-psychological studies have been conducted in the field of animal welfare. Therefore, the present study had limited references to such studies and background. Additionally, the assessment of pro-animal behavior among stockmen was based on their self-reports. As a result, it is likely that some stockmen responded conservatively to the questions. It is also worth noting that due to the large size, high costs, and scattered nature of livestock farms in Fars Province, it was not possible to collect data from all the counties. Therefore, efforts were made to gather data from five counties in Fars Province that have the highest concentration of cattle farms. Furthermore, due to health protocols, the interviewers were unable to enter certain farms and had to rely solely on the stockmen’s statements in some situations. It should also be mentioned that this research is the first to measure animal welfare dimensions using questionnaires and self-reporting. Therefore, it is possible that some shortcomings exist in the questionnaire design. Additionally, the study areas had a similar climate, which was generally suitable. As a result, there is a possibility that the findings could differ in colder or hotter regions of the province.
Given the importance of various areas in animal husbandry, researchers can conduct similar studies on farmers involved in the breeding of calves, sheep, goats, and poultry. They could likewise expand the TPB by examining other variables, such as knowledge, moral norms, connectedness to nature, cultural background, individual values, and other similar variables. Alternatively, they could use other theories, such as Schwartz’s Norm Activation Theory or the Value-Belief-Norm Theory, in animal welfare research. Animal welfare has multiple dimensions; further research can be conducted to confirm existing indicators and develop new ones for animal welfare dimensions. Considering the broad range of animal welfare indicators, researchers may choose to focus on specific aspects of animal welfare in their studies. Conducting qualitative research to extract concepts related to animal welfare and the factors influencing it is another viable option for future studies. In the same vein, comparing structural models in industrial and traditional farming systems could provide valuable insights. Exploring ethical and rational models to explain pro-animal behavior is another potential area for future research. Researchers might also combine the use of animal welfare assessment forms with questionnaires and ultimately compare the results of both to help design a more robust questionnaire. In addition, researchers can examine and compare the effects of various communication methods (face-to-face and social media) on increasing awareness of behavioral consequences and pro-animal behavior. An interventional study could be conducted to examine the effect of visiting successful livestock farms on increasing awareness of behavioral consequences and developing pro-animal behavior. Lastly, future research can investigate the impact of feedback from animal-related organizations as well as mass media content on livestock farmers’ subjective norms and animal welfare.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Food and Agriculture Organization. Food and Agriculture Organization Statistics on Crops and livestock products. https://www.fao.org/faostat/en/#data/QCL (2023).
Food and Agriculture Organization. World Livestock: Transforming the livestock sector through the Sustainable Development Goals Rome (2018).
MacDonald, J. M. & Barrett, D. Companion animals and well-being in palliative care nursing: A literature review. J. Clin. Nurs. 25, 300–310 (2016).
Echeverri, A., Karp, D. S., Naidoo, R., Zhao, J. & Chan, K. M. Approaching human-animal relationships from multiple angles: A synthetic perspective. Biol. Conserv. 224, 50–62 (2018).
Plannthin, D. K. Animal ethics and welfare in the fashion and lifestyle industries. Green Fash. 2, 49–122 (2016).
Boyd, B. Archaeology and human–animal relations: Thinking through anthropocentrism. Annu. Rev. Anthropol. 46, 299–316 (2017).
Alonso, M. E., González-Montaña, J. R. & Lomillos, J. M. Consumers’ concerns and perceptions of farm animal welfare. Animals 10, 385 (2020).
Prato-Previde, E., Basso Ricci, E. & Colombo, E. S. The complexity of the human–animal bond: Empathy, attachment and anthropomorphism in human–animal relationships and animal hoarding. Animals 12, 2835 (2022).
Boogaard, B. K., Bock, B. B., Oosting, S. J., Wiskerke, J. S. & van der Zijpp, A. J. Social acceptance of dairy farming: The ambivalence between the two faces of modernity. J. Agric. Environ. Ethics 24, 259–282 (2010).
Wagner, K., Brinkmann, J., Bergschmidt, A., Renziehausen, C. & March, S. The effects of farming systems (organic vs. conventional) on dairy cow welfare, based on the Welfare Quality® protocol. Animal 15, 100301 (2021).
de Graaf, S., Ampe, B. & Tuyttens, F. A. M. Assessing dairy cow welfare at the beginning and end of the indoor period using the Welfare Quality® protocol. Animal 26, 213–221 (2017).
Zuliani, A., Esbjerg, L., Grunert, K. G. & Bovolenta, S. Animal welfare and mountain products from traditional dairy farms: How do consumers perceive complexity?. Animals 8, 207 (2018).
Cojkic, A. & Morrell, J. M. Animal welfare assessment protocols for bulls in artificial insemination centers: requirements, principles, and criteria. Animals 13, 942 (2023).
Farm Animal Welfare Council. Farm Animal Welfare in Great Britain: Past, Present and Future (Farm Animal Welfare Council, 2009).
Beaver, A., Meagher, R. K., von Keyserlingk, M. A. & Weary, D. M. Invited review: A systematic review of the effects of early separation on dairy cow and calf health. J. Dairy Sci. 102, 5784–5810 (2019).
Sirovica, L. V. et al. public attitude toward and perceptions of dairy cattle welfare in cow-calf management systems differing in type of social and maternal contact. J. Dairy Sci. 105, 3248–3268 (2021).
Nicolao, A. D. et al. Animal performance and stress at weaning when dairy cows suckle their calves for short versus long daily durations. Animal 16, 100536 (2022).
De Vries, M. et al. Housing and management factors associated with indicators of dairy cattle welfare. Prev. Vet. Med. 118, 80–92 (2014).
Beaver, A., Weary, D. M. & Von Keyserlingk, M. A. Invited review: The welfare of dairy cattle housed in tiestalls compared to less-restrictive housing types: A systematic review. J. Dairy Sci. 104, 9383–9417 (2020).
Gieseke, D., Lambertz, C. & Gauly, M. Effects of housing and management factors on selected indicators of the welfare quality® protocol in loose-housed dairy cows. Vet. Sci. 9, 353 (2022).
Coleman, G. J., Hemsworth, P. H., Hemsworth, L. M., Munoz, C. A. & Rice, M. Differences in public and producer attitudes toward animal welfare in the red meat industries. Front. Psychol. 13, 875221 (2022).
Tucker, C. B., Jensen, M. B., de Passillé, A. M., Hänninen, L. & Rushen, J. Invited review: Lying time and the welfare of dairy cows. J. Dairy Sci. 104, 20–46 (2021).
Bochniarz, M. et al. Cytokine inflammatory response in dairy cows with mastitis caused by Streptococcus agalactiae. J. Vet. Res. 68, 115 (2024).
Chinmayee, S., Kumar, M. A., Kumar, M. T. & Deepak, C. Strategies for preventing environmental mastitis in dairy farming: A review. Asian J. Adv. Agric. Res. 24, 7–15 (2024).
Jensen, M. B. & Vestergaard, M. Invited review: Freedom from thirst—Do dairy cows and calves have sufficient access to drinking water?. J. Dairy Sci. 104, 11368–11385 (2021).
Burkhardt, F. K., Hayer, J. J., Heinemann, C. & Steinhoff-Wagner, J. Drinking behavior of dairy cows under commercial farm conditions differs depending on water trough design and cleanliness. Appl. Anim. Behav. Sci. 256, 105752 (2022).
Sacramento, J. P. et al. Energy requirement for primiparous Holstein× Gyr crossbred dairy cows. J. Dairy Sci. 107, 6686–6695 (2024).
Leerdam, M. V. et al. A predictive model for hypocalcaemia in dairy cows utilizing behavioural sensor data combined with deep learning. Comput. Electron. Agric. 220, 108877 (2024).
Almiron, N. Beyond anthropocentrism: Critical animal studies and the political economy of communication. Polit. Econ. Commun. 4 (2017).
Fleming, P. J. & Ballard, G. Homo sapiens is the apex animal: Anthropocentrism as a Dionysian sword. Aust. Zool. 38, 464–476 (2017).
Lund, T. B., Denver, S., Nordström, J., Christensen, T. & Sandøe, P. Moral convictions and meat consumption—a comparative study of the animal ethics orientations of consumers of pork in Denmark, Germany, and Sweden. Animals 11, 329 (2021).
Jörgensen, S., Lindsjö, J., Weber, E. M. & Röcklinsberg, H. Reviewing the review: A pilot study of the ethical review process of animal research in Sweden. Animals 11, 708 (2021).
Baltaci, F., Yirik, Ş, Sargi, S. A. & Yumusak, A. From the ecocentric and anthropocentric perspectives, a survey of future tourism entrepreneurs’ attitudes toward environmental issues: Sample of Akdeniz University. Int. J. Humanit. Soc. Sci. 5, 139–143 (2015).
Van Uhm, D. P. A green criminological perspective on environmental crime: The anthropocentric, ecocentric and biocentric impact of defaunation. Rev. Int. Droit Pénal 87, 323–340 (2017).
Aigner, A., Pieper, K. & Grimm, H. Post-anthropocentrism” in animal philosophy and ethics: The disparity of the prefix “post. Humanimalia 7, 56–83 (2016).
Droz, L. Anthropocentrism as the scapegoat of the environmental crisis: A review. Ethics Sci. Environ. Polit. 22, 25–49 (2022).
Sueur, C., Forin-Wiart, M. A. & Pelé, M. Are they really trying to save their buddy? The anthropomorphism of animal epimeletic behaviours. Animals 10, 2323 (2020).
Stucki, S. Towards a theory of legal animal rights: Simple and fundamental rights. Oxf. J. Leg. Stud. 40, 533–560 (2020).
Callahan, M. M., Satterfield, T. & Zhao, J. Into the animal mind: Perceptions of emotive and cognitive traits in animals. Anthrozoös 34, 597–614 (2021).
Beck, B. V. D., Wissmann, A., Tolba, R. H., Dammann, P. & Hilken, G. What can laboratory animal facility managers do to improve the welfare of laboratory animals and laboratory animal facility staff? A German perspective. Animals 14, 1136 (2024).
Bassey, S. ‘anthropoholism’as an authentic tool for environmental management. Int. J. Environ. Pollut. Environ. Model. 2, 160–168 (2019).
de Graaf, S. D. et al. Determinants of consumer intention to purchase animal-friendly milk. J. Dairy Sci. 99, 8304–8313 (2016).
Grunert, K. G., Sonntag, W. I., Glanz-Chanos, V. & Forum, S. Consumer interest in environmental impact, safety, health and animal welfare aspects of modern pig production: Results of a cross-national choice experiment. Meat Sci. 137, 123–129 (2017).
Derstappen, R., & Christoph-Schulz, I. The Importance of Animal Welfare and Country of Origin in Consumer Preferences: A Cross-National Study. J. Int. Food Agribus. Market. 1–25 (2024).
Blokhuis, H. J., Keeling, L. J., Gavinelli, A. & Serratosa, J. Animal welfare’s impact on the food chain. Trends Food Sci. Technol. 19, 79–87 (2008).
Grimard, B. et al. Relationships between welfare and reproductive performance in French dairy herds. Vet. J. 248, 1–7 (2019).
Cornish, A. R. et al. The price of good welfare: Does informing consumers about what on-package labels mean for animal welfare influence their purchase intentions?. Appetite 148, 104577 (2020).
World Organisation for Animal Health. Terrestrial Animal Health Code 28th ed, Vol. 1 (OIE, 2019).
Food and Agriculture Organization. Livestock transportation and slaughter practices—Practical guidelines for Asia and the Pacific region (2023).
Keeling, L. et al. Animal welfare and the United Nations sustainable development goals. Front. Vet. Sci. 6, 336 (2019).
Visseren-Hamakers, I. J. The 18th sustainable development goal. Earth Syst. Gov. 3, 100047 (2020).
Torpman, O. & Röcklinsberg, H. Reinterpreting the SDGs: Taking animals into direct consideration. Sustainability 13, 843 (2021).
Kauppinen, T., Vesala, K. M. & Valros, A. Farmer attitude toward improvement of animal welfare is correlated with piglet production parameters. Livest. Sci. 143, 142–150 (2012).
Hansen, B. G. Animal welfare and farm economy-exploring the relationship between dairy animal welfare indicators and economic efficiency. Prev. Vet. Med. 221, 106058 (2023).
Ruthrakumar, R., Sathriyan, G., Mukesh, S., & Nithishkumar, C. Livestock production: Recent trends and economic importance (2023).
Donat, K., Einax, E., Rath, D. & Klassen, A. Successful control of Mycobacterium avium subspecies paratuberculosis infection in a dairy herd within a decade—a case study. Animals 14, 984 (2024).
Aminzare, M. et al. Residual antibiotics as an alarming health threat for human; A systematic study and meta-analysis in Iranian animal food products. J. Agric. Food Res. 18, 101435 (2024).
Leone, F. & Ferrante, V. Effects of prebiotics and precision biotics on performance, animal welfare and environmental impact. A review. Sci. Total Environ. 901, 165951 (2023).
Silva, W. C. D. et al. Animal welfare and effects of per-female stress on male and cattle reproduction A review. Front. Vet. Sci. 10, 1083469 (2023).
Kotsampasi, B., Karatzia, M. A., Tsiokos, D. & Chadio, S. Nutritional strategies to alleviate stress and improve welfare in dairy ruminants. Animals 14, 2573 (2024).
Phillips, C. J. Farm animal welfare—from the farmers’ perspective. Animals 14, 671 (2024).
Borges, J. A. R. et al. Identifying the factors impacting on farmers’ intention to adopt animal friendly practices. Prev. Vet. Med. 170, 104718 (2019).
Jafari-Gh, A. et al. An investigation of dairy cattle welfare in commercial Iranian farms: Results from animal-and stockperson-based measures. Animals 15, 359 (2025).
Kauppinen, T., Valros, A. & Vesala, K. M. Attitudes of dairy farmers toward cow welfare in relation to housing, management and productivity. Anthrozoös 26, 405–420 (2013).
Matore, Z. Knowledge, Attitudes and Practices of Zimbabwean large scale dairy stockpeople towards animal welfare. https://doi.org/10.21203/rs.3.rs-1776965/v1 (2022).
Albernaz-Gonçalves, R., Olmos, G. & Hötzel, M. J. My pigs are ok, why change? Animal welfare accounts of pig farmers. Animal 15, 100154 (2020).
Munoz, C. A., Coleman, G. J., Hemsworth, P. H., Campbell, A. J. & Doyle, R. E. Positive attitudes, positive outcomes: The relationship between farmer attitudes, management behaviour and sheep welfare. PLoS ONE 14, e0220455 (2019).
Clay, N., Garnett, T. & Lorimer, J. Dairy intensification: Drivers, impacts and alternatives. Ambio 49, 35–48 (2019).
Brodziak, A. et al. Organic versus conventional raw cow milk as material for processing. Animals 11, 2760 (2021).
Lorenzi, V. et al. Using Expert Elicitation for ranking hazards, promoters and animal-based measures for on-farm welfare assessment of indoor reared beef cattle: An Italian experience. Vet. Res. Commun. 47, 141–158 (2022).
Tallo-Parra, O., Salas, M. & Manteca, X. Zoo animal welfare assessment: where do we stand?. Animals 13, 1966 (2023).
Browning, H. Improving welfare assessment in aquaculture. Front. Vet. Sci. 10, 1060720 (2023).
Brambell, F. W. R. Report of the technical committee to enquire into the welfare of animals kept under intensive livestock husbandry systems (1965).
Quality, W. Consortium: Welfare Quality® Assessment Protocol for Cattle (Lelystad, 2009).
Dawkins, M. S. The science of animal suffering. Ethology 114, 937–945 (2008).
Gilbert, M. S., Cai, Y., Folkerts, G., Braber, S. & Gerrits, W. J. J. Effects of nondigestible oligosaccharides on inflammation, lung health, and performance of calves. J. Dairy Sci. 107, 2900–2915 (2024).
Orzuna-Orzuna, J. F., Godina-Rodríguez, J. E., Garay-Martínez, J. R. & Lara-Bueno, A. Capsaicin as a dietary additive for dairy cows: A meta-analysis on performance, milk composition, digestibility, rumen fermentation, and serum metabolites. Animals 14, 1075 (2024).
Li, C. Y., Lin, W. C., Moonmanee, T., Chan, J. P. W. & Wang, C. K. The protective role of vitamin e against oxidative stress and immunosuppression induced by non-esterified fatty acids in bovine peripheral blood leukocytes. Animals 14, 1079 (2024).
Chen, L., Thorup, V. M., Kudahl, A. B. & Østergaard, S. Effects of heat stress on feed intake, milk yield, milk composition, and feed efficiency in dairy cows: A meta-analysis. J. Dairy Sci. 107, 3207–3218 (2024).
Turk, R., Rošić, N., Beer Ljubić, B. & Vince, S. Effects of summer heat on adipose tissue activity in periparturient simmental cows. Metabolites 14, 207 (2024).
Shin, H. et al. Applicability evaluation of a temperature humidity index-controlled ventilation system in livestock using a building energy simulation model. Case Stud. Therm. Eng. 57, 104335 (2024).
Roche, S. M., Renaud, D. L., Saraceni, J., Kelton, D. F. & DeVries, T. J. Invited review: Prevalence, risk factors, treatment, and barriers to best practice adoption for lameness and injuries in dairy cattle—A narrative review. J. Dairy Sci. 107, 3347–3366 (2024).
Hagner, K. A., Nordgren, H. S., Sarjokari, K., Sukura, A. & Rajala-Schultz, P. J. Role of mastitis in on-farm deaths of Finnish dairy cows. J. Dairy Sci. 107, 5962–5973 (2024).
Kaura, R. et al. Association of clinical respiratory disease signs and lower respiratory tract bacterial pathogens with systemic inflammatory response in preweaning dairy calves. J. Dairy Sci. 107, 5988–5999 (2024).
Ullah, A., Rehman, S., Noor, N. & Arshad, N. Role of strategic human resource management practices in managing dairy farms of Australia. NICE Res. J. 16, 87–118 (2023).
de Oliveira, J., Grajales-Cedeño, J. K., Cerezo, M. P., Valente, T. S. & Paranhos da Costa, M. J. Hot iron branding of beef cattle: Process characterization, implications for animal welfare, and its efficiency for cattle individual identification. Ruminants 4, 192–200 (2024).
Ulker-Demirel, E. & Ciftci, G. A systematic literature review of the theory of planned behavior in tourism, leisure and hospitality management research. J. Hosp. Tour. Manag. 43, 209–219 (2020).
Rozenkowska, K. Theory of planned behavior in consumer behavior research: A systematic literature review. Int. J. Consum. Stud. 47, 2670–2700 (2023).
Lu, S., Sun, Z. & Huang, M. The impact of digital literacy on farmers’ pro-environmental behavior: An analysis with the Theory of Planned Behavior. Front. Sustain. Food Syst. 8, 1432184 (2024).
Ho, V. C. et al. Assessing immediate emotions in the theory of planned behavior can substantially contribute to increases in pro-environmental behavior. Front. Clim. 6, 1344899 (2024).
Albayati, H., Alistarbadi, N. & Rho, J. J. Assessing engagement decisions in NFT Metaverse based on the Theory of Planned Behavior (TPB). Telemat. Inform. Rep. 10, 100045 (2023).
Gumasing, M. J. J., Bayola, A., Bugayong, S. L. & Cantona, K. R. Determining the factors affecting Filipinos’ acceptance of the use of renewable energies: A pro-environmental planned behavior model. Sustainability 15, 7702 (2023).
Dada, O., Perrigot, R. & Watson, A. Influential factors of pro-environmental behaviors among franchisees in the fast-food sector. Bus. Strategy Environ. 33, 2301–2313 (2023).
Oludoye, O. O. et al. Pro-environmental behavior regarding single-use plastics reduction in urban–rural communities of Thailand: Implication for public policy. Sci. Rep. 14, 4713 (2024).
Carfora, V., Cavallo, C., Catellani, P., Del Giudice, T. & Cicia, G. Why do consumers intend to purchase natural food? Integrating theory of planned behavior, value-belief-norm theory, and trust. Nutrients 13, 1904 (2021).
Pang, S. M., Tan, B. C. & Lau, T. C. Antecedents of consumers’ purchase intention towards organic food: Integration of theory of planned behavior and protection motivation theory. Sustainability 13, 5218 (2021).
Omarova, L. & Jo, S. J. Employee pro-environmental behavior: The impact of environmental transformational leadership and GHRM. Sustainability 14, 2046 (2022).
Wang, Q. C., Ren, Y. T., Liu, X., Chang, R. D. & Zuo, J. Exploring the heterogeneity in drivers of energy-saving behaviours among hotel guests: Insights from the theory of planned behaviour and personality profiles. Environ. Impact Assess. Rev. 99, 107012 (2022).
Wach, D., Kruse, P., Costa, S. & Antonio Moriano, J. Exploring social and commercial entrepreneurial intentions from theory of planned behaviour perspective: A cross-country study among Namibian and German students. J. Soc. Entrep. 14, 226–247 (2021).
Si, H. et al. Application of the theory of planned behavior in environmental science: A comprehensive bibliometric analysis. Int. J. Environ. Res. Public Health 16, 2788 (2019).
Yuriev, A., Dahmen, M., Paillé, P., Boiral, O. & Guillaumie, L. Pro-environmental behaviors through the lens of the theory of planned behavior: A scoping review. Resour. Conserv. Recycl. 155, 104660 (2020).
Suntornsan, S., Chudech, S. & Janmaimool, P. The role of the theory of planned behavior in explaining the energy-saving behaviors of high school students with physical impairments. Behav. Sci. 12, 334 (2022).
Maichum, K., Parichatnon, S. & Peng, K. C. Application of the extended theory of planned behavior model to investigate purchase intention of green products among Thai consumers. Sustainability 8, 1077 (2016).
Ahmed, N. et al. Purchase intention toward organic food among young consumers using theory of planned behavior: Role of environmental concerns and environmental awareness. J. Environ. Plan. Manag. 64, 796–822 (2020).
Li, J., Jiang, R. & Tang, X. Assessing psychological factors on farmers’ intention to apply organic manure: An application of extended theory of planned behavior. Environ. Dev. Sustain. 26, 2467–2491 (2024).
Hwang, S., Lee, J. & Jang, D. Climate change awareness and pro-environmental intentions in sports fans: Applying the extended theory of planned behavior model for sustainable spectating. Sustainability 16, 3246 (2024).
Ajzen, I. The Theory of planned behavior. Org. Behav. Hum. Decis. Process. 50, 179–211 (1991).
Lee, S. S., Kim, Y. & Roh, T. Pro-environmental behavior on electric vehicle use intention: Integrating value-belief-norm theory and theory of planned behavior. Jo. Clean. Prod. 418, 138211 (2023).
Mufidah, I. et al. Understanding the consumers’ behavior intention in using green ecolabel product through pro-environmental planned behavior model in developing and developed regions: Lessons learned from Taiwan and Indonesia. Sustainability 10, 1423 (2018).
Qiu, H., Wang, X., Morrison, A. M., Kelly, C. & Wei, W. From ownership to responsibility: Extending the theory of planned behavior to predict tourist environmentally responsible behavioral intentions. J. Sustain. Tour. 331–24 (2022).
Tian, H., Zhang, J. & Li, J. The relationship between pro-environmental attitude and employee green behavior: The role of motivational states and green work climate perceptions. Environ. Sci. Pollut. Res. 27, 7341–7352 (2019).
Dhir, A., Sadiq, M., Talwar, S., Sakashita, M. & Kaur, P. Why do retail consumers buy green apparel? A knowledge-attitude-behaviour-context perspective. J. Retail. Consum. Serv. 59, 102398 (2020).
Platto, S. et al. Chinese farmers’ attitude towards the improvement of animal welfare in their facilities. Anim. Welf. 29, 99–112 (2020).
Schwartz, S. H. Normative influences on altruism. In Advances in Experimental Social Psychology Vol. 10 221–279 (Academic Press, 1977).
Stern, P. C. New environmental theories: Toward a coherent theory of environmentally significant behavior. J. Soc. Issues 56, 407–424 (2000).
Manosuthi, N., Lee, J. S. & Han, H. Predicting the revisit intention of volunteer tourists using the merged model between the theory of planned behavior and norm activation model. J. Travel Tour. Mark. 37, 510–532 (2020).
Wang, T., Shen, B., Springer, C. H. & Hou, J. What prevents us from taking low-carbon actions? A comprehensive review of influencing factors affecting low-carbon behaviors. Energy Res. Soc. Sci. 71, 101844 (2020).
Liobikienė, G. & Poškus, M. S. The importance of environmental knowledge for private and public sphere pro-environmental behavior: Modifying the value-belief-norm theory. Sustainability 11, 3324 (2019).
Fang, W. T., Chiang, Y. T., Ng, E. & Lo, J. C. Using the norm activation model to predict the pro-environmental behaviors of public servants at the central and local governments in Taiwan. Sustainability 11, 3712 (2019).
Han, H. Theory of green purchase behavior (TGPB): A new theory for sustainable consumption of green hotel and green restaurant products. Bus. Strategy Environ. 29, 2815–2828 (2020).
Rastegari Kopaei, H. et al. Drivers of residents’ home composting intention: Integrating the theory of planned behavior, the norm activation model, and the moderating role of composting knowledge. Sustainability 13, 6826 (2021).
Savari, M., Damaneh, H. E., Damaneh, H. E. & Cotton, M. Integrating the norm activation model and theory of planned behaviour to investigate farmer pro-environmental behavioural intention. Sci. Rep. 13, 5584 (2023).
Zhao, L., Yin, J. & Song, Y. An exploration of rumor combating behavior on social media in the context of social crises. Comput. Hum. Behav. 58, 25–36 (2015).
Zhang, X., Geng, G. & Sun, P. Determinants and implications of citizens’ environmental complaint in China: Integrating theory of planned behavior and norm activation model. J. Clean. Prod. 166, 148–156 (2017).
Gkargkavouzi, A., Halkos, G. & Matsiori, S. Environmental behavior in a private-sphere context: Integrating theories of planned behavior and value belief norm, self-identity and habit. Resour. Conserv. Recycl. 148, 145–156 (2019).
Karimi, S. & Saghaleini, A. Factors influencing ranchers’ intentions to conserve rangelands through an extended theory of planned behavior. Glob. Ecol. Conserv. 26, e01513 (2021).
Du, J. & Pan, W. Examining energy saving behaviors in student dormitories using an expanded theory of planned behavior. Habitat Int. 107, 102308 (2021).
Esfandiar, K., Pearce, J., Dowling, R. & Goh, E. The extended theory of planned behaviour model and national parks visitors’ pro-environmental binning behaviour: A cross-cultural perspective. J. Outdoor Recreat. Tour. 42, 100602 (2023).
Erfanian, S., Maleknia, R. & Halalisan, A. F. Application of social cognitive theory to determine shaping factors of environmental intention and behaviors of ecotourist in forest areas. Front. For. Glob. Change 7, 1489170 (2024).
Sultan, P., Tarafder, T., Pearson, D. & Henryks, J. Intention-behaviour gap and perceived behavioural control-behaviour gap in theory of planned behaviour: Moderating roles of communication, satisfaction and trust in organic food consumption. Food Qual. Prefer. 81, 103838 (2019).
Sabbir, M. M. & Taufique, K. M. R. Sustainable employee green behavior in the workplace: Integrating cognitive and non-cognitive factors in corporate environmental policy. Bus. Strategy Environ. 31, 110–128 (2021).
Kumar, G. A. Framing a model for green buying behavior of Indian consumers: From the lenses of the theory of planned behavior. J. Clean. Prod. 295, 126487 (2021).
Moon, M. A., Mohel, S. H. & Farooq, A. I green, you green, we all green: Testing the extended environmental theory of planned behavior among the university students of Pakistan. Soc. Sci. J. 58, 316–332 (2021).
Hossain, I., Fekete-Farkas, M. & Nekmahmud, M. Purchase behavior of energy-efficient appliances contribute to sustainable energy consumption in developing country: Moral norms extension of the theory of planned behavior. Energies 15, 4600 (2022).
Cao, J., Qiu, H., Morrison, A. M. & Wei, W. The role of social capital in predicting tourists’ waste sorting intentions in rural destinations: Extending the theory of planned behavior. Int. J. Environ. Res. Public Health 19, 12789 (2022).
Hamari, J. & Koivisto, J. “Working out for likes”: An empirical study on social influence in exercise gamification. Comput. Hum. Behav. 50, 333–347 (2015).
He, J., Yu, Z. & Fukuda, H. Extended theory of planned behavior for predicting the willingness to pay for municipal solid waste management in Beijing. Sustainability 13, 13902 (2021).
Ogiemwonyi, O. et al. Environmental factors affecting green purchase behaviors of the consumers: Mediating role of environmental attitude. Clean. Environ. Syst. 10, 100130 (2023).
Lind, N., Hansson, H., Emanuelson, U. & Lagerkvist, C. J. Explaining farmers’ adoption of mastitis control practices using psychological constructs from the theory of planned behavior. Livest. Sci. 277, 105341 (2023).
Van Tonder, E., Fullerton, S., De Beer, L. T. & Saunders, S. G. Social and personal factors influencing green customer citizenship behaviours: The role of subjective norm, internal values and attitudes. J. Retail. Consum. Serv. 71, 103190 (2023).
López-Mosquera, N., García, T. & Barrena, R. An extension of the Theory of Planned Behavior to predict willingness to pay for the conservation of an urban park. J. Environ. Manag. 135, 91–99 (2014).
Park, J. & Ha, S. Understanding consumer recycling behavior: Combining the theory of planned behavior and the norm activation model. Fam. Consum. Sci. Res. J. 42, 278–291 (2014).
Ponto, J. Understanding and evaluating survey research. J. Adv. Pract. Oncol. 6, 168 (2015).
Ansari-Lari, M., Rezagholi, M. & Reiszadeh, M. Trends in calving ages and calving intervals for Iranian Holsteins in Fars province, southern Iran. Trop. Anim. Health Prod. 41, 1283–1288 (2009).
Hair, J., Hollingsworth, C. L., Randolph, A. B. & Chong, A. Y. L. An updated and expanded assessment of PLS-SEM in information systems research. Ind. Manag. Data Syst. 117, 442–458 (2017).
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The authors express their gratitude to all the pastoralists who dedicated their time to participate in the interviews and respond to the questions of this study. Also, we have used Chat GPT 3 for paraphrasing and improving the language of the manuscript and we hereby would like to extend our thanks to this bot. It should also be mentioned that we have not used Chat GPT for generation of content of present research work.
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All authors contributed to the study conception and design. Material preparation, data collection, analysis, first drafting, revising draft, visualization, tabulation, and discussing results were performed by M.M., D.H., & N.V.
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Mohammadzadeh, M., Hayati, D. & Valizadeh, N. Behavioral factors linking sustainability and animal welfare in dairy farming. Sci Rep 15, 26042 (2025). https://doi.org/10.1038/s41598-025-10260-2
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DOI: https://doi.org/10.1038/s41598-025-10260-2
