Next Article in Journal
Cradle-to-Grave LCA of In-Person Conferences: Hotspots, Trade-Offs and Mitigation Pathways
Previous Article in Journal
Application of Deep Learning Technology in Monitoring Plant Attribute Changes
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Factors Influencing Consumers’ Direct Sale Purchase Intention in the Context of Climate Change

1
Department of Economics and Agricultural Development, Institute of Agriculture and Tourism, 52440 Poreč, Croatia
2
Department of Management and Rural Entrepreneurship, Faculty of Agriculture, University of Zagreb, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(17), 7603; https://doi.org/10.3390/su17177603
Submission received: 14 July 2025 / Revised: 20 August 2025 / Accepted: 21 August 2025 / Published: 22 August 2025

Abstract

Direct purchasing offers consumers the advantage of fresher, higher-quality food, often at lower prices, with greater transparency in terms of origin and production methods, which creates trust and enables more environmentally conscious choices. On the other hand, direct selling empowers farmers by cutting out middlemen and improving their income. As a climate-friendly option, direct selling reduces transport emissions, supports environmentally friendly agricultural practises and strengthens the resilience of the food system. This paper examines the factors that influence consumer purchase intentions for direct sales in the context of climate change. The study was conducted with a sample of 313 direct sales consumers at on- and off-farm locations in Croatia (Istria and Primorsko-goranska County). The sample consists mainly of women with higher education and over 45 years of age. The exploratory factor analysis revealed three factors: (1) attitude towards climate change, (2) influence of direct sales on climate change, and (3) intention to buy in direct sales. A hierarchical regression analysis revealed a positive and significant influence of the factors’ attitude towards climate change and the influence of direct selling on climate change on the purchase intention in direct selling. The results suggest that direct selling consumers are aware of climate change and are inclined to choose sustainable behaviours, such as direct selling, to mitigate climate change.

1. Introduction

The direct sale of agricultural products is a distribution method in which the products reach the consumer without intermediaries, meaning that a direct relationship is established between producer and consumer [1]. Corsi et al. [2] define direct sales approaches as on-farm and off-farm channels. On-farm channels mean that consumers come to the farm and buy agricultural products directly from the farm. Off-farm channels, on the other hand, mean that farmers come to urban areas and sell their agricultural products at farmers’ markets, for example [2]. According to Kretter and Kádeková [1], direct sales are mostly on-farm sales, sales from the field, from the garden, mobile stores, market stalls, own stores, the possibility for consumers to pick up products grown directly on the farm, or customized orders delivered to consumers. Similarly, D’Amico et al. [3] distinguish direct sales channels such as farm stores, farmers’ markets, roadside sales, self-collection, fair trade groups, box schemes, home delivery, and e-commerce. Direct sales channels are referred to as the short food supply chain (SFSC), as Majewski et al. [4] and Malak-Rawlikowska et al. [5] have defined that there are several different forms of SFSC. One of the simplest is direct on-farm sales, known as self-pickers, and sales to individual consumers, as well as direct off-farm sales, known as internet deliveries, delivery to consumers, and at farmers’ markets. Selling to retail shops is one of the simplest forms of SFSC with one middleman.
The main objective of SFSC is to assess potential environmental and social impacts that promote direct interaction between farmers and consumers, the exchange of information about products, trust between the parties involved, and sustainability [6]. Studies show that food transport is responsible for around 19% of total emissions within the food system worldwide [7]. Therefore, increasing the consumption of locally produced food can have a positive impact on reducing these transport-related emissions [8]. Other benefits include the reduction of packaging, food waste, and energy consumption [5]. The positive effects of direct sales create an interesting link with climate change, providing new insights for a better understanding of consumer behaviour. Climate change affects almost all aspects of human life today, including consumer concerns about climate change [9]. Consumers favour food produced using sustainable methods, such as organic products, because they perceive them as fresher and healthier, as well as more environmentally friendly production methods that can contribute to environmental protection and the sustainability of the food system in the long term [10].
On the other hand, some papers [4] argue that SFSC also has a negative aspect, meaning that longer supply chains cause a lower carbon footprint per unit of food due to efficient logistics and economies of scale in transport and distribution, but do not contribute to climate change mitigation and increase the carbon footprint. In this paper, we use the term direct selling so that readers know that it is a direct seller–buyer relationship in a limited geographic area and focus on analysing the factors that influence consumers’ intention to buy food through direct sales channels in the context of climate change.

1.1. Brief Description of the National Context

In Croatia, small family farms are increasingly focusing on direct sales, especially in tourist-oriented regions [11]. More than 50% of consumers in Croatia buy fruit, vegetables, meat, and meat products directly from the farmer [12]. The direct sale of agricultural products is regulated by various directives (e.g., Agricultural Act (152/24) [13], Regulation on the implementation of the programme to support the direct sale of agricultural products via self-service devices in the process of fiscalisation (Official Gazette 9/21) [14], Regulation on the sale of own agricultural products produced on family farms (Official Gazette 76/2014) [15]). The literature repeatedly emphasizes the importance of tourism in promoting local agricultural development [16]. Therefore, tourism in Croatia also plays an important role in the demand for locally produced food, which makes the rural part of Croatia [17] an ideal location to study how direct selling can contribute to climate change mitigation. Furthermore, as part of the Mediterranean region, Croatia is already confronted with the effects of climate change, which influence both agricultural production and public awareness.

1.2. Consumer Attitudes Towards Climate Change and Purchase Intention

Predieri et al. [18], who investigated consumer attitudes towards climate change, concluded that most consumers agreed that climate change will have a greater impact in the future and has been present for a long time, and that consumers cite reducing CO2 emissions and saving water and energy as the best measures to combat climate change. The IFIC study [19] found that consumers are concerned about the impact of food production on climate change and that those with higher incomes and higher education are very concerned about climate change. Faber et al. [9] found that consumers can influence the reduction of greenhouse gas emissions by eating more local food, buying less imported food, reducing food waste, eating a healthy diet, or switching to a vegetarian diet. Deconinck et al. [20] found that, in addition to mitigating climate change, consumers prefer products produced using sustainable practices, but that high price, unclear labelling, lack of understanding, poor availability, and lack of trust in labelling are also barriers to purchasing sustainable products. Hatibovic et al. [21] emphasize that a stronger concern and emotional engagement with climate change leads to a greater willingness to change personal habits and support sustainable practices. This can be indirectly linked to the research question that a more positive attitude towards climate change increases consumer purchase intent in direct sales channels.

1.3. Consumer Perception of Direct Selling and Direct Purchase Intentions

Consumers increasingly want to know where their food comes from and how it is produced. This transparency makes buying directly from the farmer more attractive. From an economic perspective, this can mean better value or better quality. Socially, consumers often value personal relationships with producers, and many are willing to pay more for food that has been produced using traditional or organic methods. Avoiding industrial farming and supporting sustainable practices are also important factors for consumers [22]. Farmers in direct sales must offer a value or quality that supermarkets cannot in order to be attractive to consumers. To summarize, direct sales channels offer several advantages: revenues go directly to producers, value-added products can increase local incomes and employment, and when produced sustainably, these products support environmental goals. From the consumer’s perspective, the benefits are freshness, quality, lower prices (10–20% cheaper than retail), and greater food safety [1,22]. These factors encourage sustainable consumption and the willingness to pay more for supposedly higher-quality, environmentally friendly products. In addition, Li and Kallas [23] show that consumers are willing to pay more, e.g., generally a 29.5% premium for sustainable food products. Consumer attitudes, environmental concerns, sensory characteristics of products, as well as subjective norms, price, health consciousness, perceived convenience of purchase, and education level, for example, affect the intention to buy organic food [24].
Hansika and Wijerathna [25] found that the direct sale of organic products is a climate-friendly solution. Previous studies have shown that consumer demand for direct selling can provide a clear link to environmentally friendly agriculture, as it promotes a direct relationship between consumers and producers and encourages more sustainable agricultural practises [22], thus reducing the negative impacts of climate change. Recent research highlights direct selling as a resilient food system model that offers benefits to both consumers and farmers [26]. Peña Rodríguez et al.; Neumann and Mehlkop; Wardle et al. [27,28,29] also found that farmers’ markets as direct distribution channels contribute to environmental sustainability by reducing energy consumption for consumer transport and building infrastructure compared to traditional (shopping) malls. Allegra et al. [30] emphasised that direct selling at markets helps farmers make money faster and build closer relationships with consumers, while consumers receive fresh, seasonal food with lower CO2 emissions. Ma and Chang [31] found that consumers who choose sustainably produced agricultural products (“green products”) directly support practises that protect the environment and support the local economy. The economic aspect of sustainable products is a fair price for farmers and an affordable price for consumers, the environmental aspect focuses on preserving the environment and sustainable management of natural resources, while the social aspect emphasises aligning agriculture with societal needs and supporting the agri-food sector [32].

1.4. The Socio-Demographic Characteristics of Consumers Influence the Purchase Intention

Consumer purchasing behaviour is influenced by socio-demographic characteristics, and this relationship is discussed in the scientific literature [33]. Some studies have confirmed a significant relationship between these characteristics and purchasing habits [34,35,36], but a weak influence of socio-demographic characteristics on purchasing behaviour has also been reported [37,38]. Studies on consumers and the factors that influence their purchase intention and willingness to buy through direct channels are mainly influenced by demographic factors (e.g., age, gender, education) and socioeconomic factors (e.g., region, number of children/family members, income) [39,40]. While some older studies [41] found that freshness, quality, variety, price and atmosphere are the reasons why consumers favour the direct form of farmers’ markets, more recent studies [42,43] point to environmental awareness, support for the local economy, and freshness and especially quality of products as factors that drive consumers to buy through direct channels. Lee and Kim [44] concluded in their 2020 study that demographic factors, socio-economic factors, and personal preferences influence consumers’ intention to buy products via direct channels. Ammann et al. [45] concluded that socio-demographic characteristics (gender and education level) also play an important role in the choice of sustainable food. In addition, product quality also influences consumer behaviour. Information about the production of the product also has an influence on purchasing behaviour. Sufficient product information increases consumer confidence and has a positive effect on their purchasing behaviour. Consumers with better product knowledge make more informed decisions, while consumers with less information tend to rely more on external recommendations [31,46]. The above section summarises which factors, with a focus on socio-demographic factors, influence consumers’ purchase intentions in direct selling.
Despite the proposed literature review, the authors concluded that there is little research linking consumer attitudes towards climate change and direct sales in the Croatian context. These factors make Croatia a valuable case study for this research. The main objective of this paper is to examine the factors that influence consumer purchase intention in direct selling in the context of climate change. Through empirical research, this paper addresses the following research questions:
  • What are consumers’ attitudes towards climate change?
  • What is consumer opinion on the impact of direct sales on climate change?
  • Do consumers’ socio-demographic characteristics influence their intention to buy direct sales?
  • Do consumers’ attitudes towards climate change influence their purchase intention in direct selling?
  • Does consumers’ perceived impact of direct selling on climate change influence their purchase intention for direct selling?

2. Materials and Methods

The field research was conducted in the counties of Istria and Primorsko-goranska (Republic of Croatia) from June to September 2024, as there was a greater supply of available products, especially fruit and vegetables, during this period. The target population consisted of consumers who visited direct sales points for agricultural products in both counties, and not all consumers who buy agricultural products. Direct sales locations included on-farm direct sales and off-farm direct sales. For on-farm direct sales, consumers visited the farm and purchased through direct sales methods, such as on-site or pick-your-own products. Off-farm direct sales referred to urban direct sales methods, including farmers’ markets, buying groups, community supported agriculture, etc. [2]. Specifically, the respondents in this study were consumers who purchase agricultural products either directly on farms (on-farm) or at farmers’ markets (off-farm). The farms (on-farm locations) where the survey was conducted sold milk and dairy products (5 farms), vegetables and fruit (4 farms), olive oil (4 farms), honey and bee products (4 farms), and alcoholic beverages (3 farms). The questionnaires were collected at farmers’ markets (outside the farms) in the five largest cities in the region (Rijeka, Pula, Opatija, Poreč, and Rovinj).
During the purchase process, the researchers approached the consumers, explained the purpose of the study, emphasised that participation was anonymous, asked them to take part in the survey, and, after obtaining their consent, gave them a printed version of a QR code containing a link to the online questionnaire. The data was collected through a questionnaire containing 16 questions, divided into six sections: Consumer purchasing habits related to direct sales, motives for purchasing direct selling products, opinions on the characteristics of direct selling products, attitudes towards the impact of direct sales on climate change, future purchase intentions related to direct sales and socio-demographic characteristics of participants (including: Gender, age, education, number of household members, annual income). The aim was to collect a total of 300 completed questionnaires based on the planned data analysis [47].
The data were analysed using descriptive and multivariate statistics. The descriptive statistics included frequencies and percentages to describe the socio-demographic characteristics of the participants. Exploratory factor analysis (EFA) and varimax rotation, with eigenvalues of 1.00 or higher, were used to identify potential factors. Varimax rotation was chosen to maximise the dispersion of loadings by maximising the number of large and small coefficients and to identify homogeneous groups of variables [48]. Internal reliability was determined by computing Cronbach’s alpha [49], and the factors were calculated as mean values for each respondent. Cronbach’s alpha values ranged from a minimum value of 0.70 (0.60 in exploratory research) to a recommended 0.80–0.90 [50]. The exploratory factor analysis was conducted using three items to measure attitudes towards climate change, five items to measure direct sales purchase intention, and three items to measure consumer purchase intention. This scale was modified for the research purpose and adopted from previous studies (Table 1). All scales were measured using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
The application of EFA is a frequently conducted research analysis for the purpose of scale reliability in marketing research [53].
To test the influence of climate change attitude and direct sale on climate change, a hierarchical regression was performed. When conducting regression analyses, the values are often presented as dichotomous variables for easier interpretation [47]. In line with this approach, the socio-demographic characteristics of the respondents are presented in this way. The correlation between the independent variables was calculated before performing the hierarchical regression. As the socio-demographic characteristics were identified as an influencing factor on consumers’ purchase intention, they are used as a control variable [45]. In the second stage of the hierarchical regression, the attitude towards climate change and the direct influence of sales on climate change were introduced to test their influence on consumers’ purchase intention. The multicollinearity of the variables was analysed through the variance inflation factors (VIF). Hierarchical regression is commonly used in marketing research to test the influence of variables on the prediction of an outcome [54]. The data were analysed using the Statistical Software Package for Social Sciences (SPSS) version 21 (IBM Corporation, Armonk, NY, USA).

3. Results and Discussion

A total of 313 questionnaires were completed, achieving the required sample size for the planned data analyses [47].
In the sample collected, most of the respondents were women (70.3%), and over 45 years old (61%). Most had a university degree (65.2%), lived in households with three or more members (63.3%), and had an annual household income of up to €40,000 (69.6%), as shown in Table 2.
The sample obtained may appear slightly unbalanced. The explanations for such results could be: Higher percentage of women—women are usually responsible for grocery shopping and perform this activity for a longer period of time than men [31,55]. A slightly higher percentage of middle-aged and older respondents and a slightly higher number of 3 or more household members—people with families are more likely to buy products at the farmers’ market. This habit may be associated with age older than 45 and the number of household members [31].
Slightly higher percentage of college and university graduates—more educated customers can better understand and appreciate the value of fresh products, such as products from direct sale. Higher percentage with an annual income of more than €40,000—This data may be related to monthly salaries in Croatia, and there is also a percentage of older respondents (retirees) with lower monthly incomes in this group.
Exploratory factor analysis was used to identify constructs related to attitudes towards climate change, the influence of direct sales on factors related to climate change, and consumers’ purchase intentions in relation to direct sales. Three factors were identified: (1) attitude towards climate change, (2) influence of direct selling on climate change, (3) consumer purchase intention (Table 3, explanation of abbreviations in the Section 2 and in Appendix A).
All three factors account for 60.19% of the cumulative variance, with the factor loadings for all items exceeding 0.6. Cronbach’s α values for the measurement scales ranged from 0.785 to 0.915. The KMO measure of sampling adequacy was 0.869, and Bartlett’s test for sphericity was significant (p = 0.000), indicating that the data were suitable for exploratory factor analysis (EFA). Most factor loadings were above 0.7, indicating that all scales had high convergent validity.
Participants’ attitudes towards climate change ranged from agreement to neutral. Most participants agree with the statements that direct sales contribute to climate change mitigation. In addition, respondents generally agree that they intend to buy from direct sales in the future.
It is also interesting to note that the statement CCA2_Climate change is a consequence of human action (M = 4.01) was rated highest by respondents. This means that consumers believe that climate change is caused by human activity and that they can therefore contribute to mitigating climate change through sustainable behaviour, such as choosing direct sales as a purchasing method.
This is also confirmed by the statement DSICC5_Direct selling contributes to climate change mitigation (M = 4.14), which was also rated highly by respondents. Previous studies have also confirmed that consumers who are more aware of climate change are more likely to engage in sustainable behaviour [56,57].
Climate change is now an issue in almost all areas of business, including supply chains. Consumers increasingly feel part of a community whose actions can contribute to reducing climate change [58].
Table 4 shows the results of the hierarchical regression analysis. This analysis was applied to examine the relationship between respondents’ socio-demographic characteristics and consumers’ purchase intention in Model 1, and the relationship between respondents’ socio-demographic characteristics, attitudes towards climate change, the direct impact of sales on climate change, and consumers’ purchase intention in Model 2.
Model 1 did not show a significant F-test, while Model 2 showed a significant F-test, indicating that attitudes towards climate change and the impact of direct selling on climate change have a greater influence on consumers’ purchase intention than the socio-demographic characteristics of respondents. Variance inflation factors varied between models, but ranged from 1.007 to 1.014, which is below 3.00 and, thus, below the threshold of 10 [47].
The influence of socio-demographic characteristics on consumer purchasing behaviour is contested in the literature [33]. Some previous studies have confirmed the influence of socio-demographic characteristics on purchasing habits [34,35,36]. While some other studies report a weak influence of sociodemographic characteristics on purchasing behaviour [37,38], this is consistent with the results of the present study. The lack of influence of socio-demographic characteristics on purchase intention can be partly explained by the inconsistent results found in previous studies [59] regarding the influence of socio-demographic characteristics of consumers in the context of sustainable consumption.
The relatively low R-squared and adjusted R-squared values in Model 2 indicate a somewhat limited representativeness of the independent variables. This means that the proportion of variance in consumers’ purchase intention explained by attitudes towards climate change and the direct influence of sales on climate change is 40%. The attitude factor has positively influenced purchase intention for agricultural products in a significant number of studies [60,61,62]. Attitude has also proven to be an important predictor in studies dealing with sustainable purchasing [63,64]. Environmental attitude has also been shown to be a significant predictor of green purchasing behaviour in previous studies [65]. In line with the findings of the above studies, this research confirms that attitude is a significant predictor of behaviour.
Another factor that was found to be significant is the impact of direct sales on climate change. Nowadays, consumers favor locally produced food, which directly contributes to reducing CO2 emissions, especially compared to transport over long distances [8]. Consumers are therefore increasingly focusing on sustainable food consumption. This is consistent with the findings of this study, which confirm that concerns about climate change significantly influence purchase intentions related to direct sales, emphasizing its role as a sustainable supply chain model [9].

4. Conclusions

This study analysed the factors that influence the intention to buy agricultural products through direct sales. A total of 313 consumers took part in the study, who were asked about their attitudes, the effects of direct selling, their intention to buy products from direct selling, and their socio-demographic characteristics using a questionnaire.
The majority of respondents were female, had a university education, and were over 45 years old.
An exploratory factor analysis was conducted to determine the underlying factors. A total of three factors were identified: (1) attitude towards climate change, (2) influence of direct sale on climate change, (3) purchase intention of direct sale.
Consumer attitudes towards climate change were measured using a three-part scale. The results show that customers have different attitudes towards climate change. The degree of agreement varies from neutral to in favor. In this study, the highest level of agreement was found for the item stating that climate change is a result of human activity. This indicates that consumers see humans as the main cause of climate change. Furthermore, this result could encourage customers to adopt sustainable behaviours, such as choosing direct sales locations when purchasing products. Consumer opinion on climate change was measured using a five-point scale. The results show that customers mostly agree with the statements about the impact of direct sales on climate change. It is important to emphasize that the items stating that direct sales reduce waste and contribute to climate change mitigation were rated highest by respondents. This result provides a good basis for the further development and expansion of various direct sales points, as customers perceive them as a sustainable action against climate change.
Model 1 of the hierarchical regression analysis investigated the impact of socio-demographic characteristics on purchase intention in relation to climate change; however, no significant results were found. In Model 2, in addition to the socio-demographic variables, the factors attitude towards climate change and the influence of direct sales on climate change were added. Here, too, the results confirmed that the socio-demographic characteristics had no influence. Generally, past research shows that socio-demographic characteristics have varying impacts on purchase intention, creating a gap and an unclear relationship between these characteristics and the degree of behavioral influence. While the factors’ attitude towards climate change and the influence of direct sales on climate change significantly influenced the intention to buy in direct sales. Consumer attitudes, therefore, have a significant influence on sustainable purchase intentions. The results indicate that consumers perceive the increase in climate change as a consequence of human activity. They are also aware that choosing direct selling as part of the supply chain can have a direct impact on reducing climate change due to the benefits that direct selling offers. Consumers, therefore, perceive the positive impact of direct sales on climate change and are inclined to choose this form of purchase in order to contribute to climate change mitigation.
This study makes several contributions to the scientific literature. First, the proposed measurement scales attitude towards climate change, impact of direct selling on climate change, and purchase intention for direct selling were tested, and the items measuring them were identified as unidimensional constructs. Furthermore, it was found that the independent variables’ attitude towards climate change and the impact of direct selling on climate change have a significant influence on the dependent variable purchase intention in direct selling.
The practical implications of the results can help agricultural producers to better communicate to consumers the importance of buying local produce directly from the producer, as this contributes directly to reducing climate change. These results can also be an important message for policy makers to further promote direct sales through financial or legislative measures.
Future research should focus on producers and their willingness to adopt and expand direct sales in the context of climate change mitigation. The results of this study may serve as a valuable starting point for future research examining the factors influencing consumers’ purchase intentions at direct sales locations as a measure for climate change mitigation behavior.
The main limitations of this study relate to the specific group of consumerswho buy in direct sales, which means that the conclusions cannot be generalised to the whole population. In addition, the study analysed a model that included attitudes towards climate change and the impact of direct sales on climate change. However, future research could include other variables such as environmental/product knowledge, environmental awareness, subjective norm, perceived behavioural control, and past behaviour to identify new variables that significantly influence the prediction of purchase intention.

Author Contributions

Conceptualization, A.Č.M. and T.Č.; methodology, A.Č.M.; software, A.Č.M.; validation, A.T.D., A.Č.M. and M.O.; formal analysis, A.Č.M.; investigation, A.T.D., A.Č.M. and M.O.; resources, M.O.; data curation, A.Č.M.; writing—original draft preparation, T.Č., M.N., A.T.D., A.Č.M. and M.O.; writing—review and editing, T.Č., M.N., A.T.D., A.Č.M. and M.O.; visualization, A.Č.M.; supervision, A.T.D., M.N. and M.O.; project administration, M.O.; funding acquisition, M.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research and publication of this work were funded by the Farmers Web Market project, which is financially supported by the Istrian County, the City of Pula-Pola, the City of Poreč-Parenzo, the City of Buje-Buie, the Municipality of Vrsar-Orsera, and the Municipality of Tar-Vabriga-Torre Abrega (Klasa: 402-08/24-01/157, Ur.broj: 2163-03/1-24-04).

Institutional Review Board Statement

This study is waived for ethical review as the study was based solely on the collection of anonymous data through a structured questionnaire by Institution Committee.

Informed Consent Statement

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

Data Availability Statement

The data presented in this study are available upon request from the first author due to contractual obligations.

Acknowledgments

The authors would like to thank the farmers for participating in the survey.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

Appendix A

Items for Climate change attitude (CCA), Direct sales impact on climate change (DSICC), Consumers’ Purchase intention (CPI).
All items are answered using a 5-point Likert scale (ranging from 1 (totally not agree) to 5 (totally agree).
Climate change attitude (CCA)
CCA1_Climate change is a normal natural phenomenon.
CCA2_Climate change is a consequence of human activity.
CCA3_Climate change is a consequence of agricultural activities.
Direct sales impact on climate change (DSICC)
DSICC1_The direct sale of agricultural products helps to reduce CO2 emissions from transportation.
DSICC2_Direct sales of agricultural products result in lower energy consumption for cooling and storage.
DSICC3_Direct sales reduce waste.
DSICC4_Through direct communication with consumers, farmers are encouraged to produce sustainably or ecologically.
DSICC5_Direct sales contribute to mitigating climate change.
Consumers’ Purchase Intention (CPI)
CPI1_I want to buy products directly from farmers because I contribute to mitigating climate change.
CPI2_I want to buy products directly from farmers because I encourage climate-sustainable practices in agriculture.
CPI3_Because of the contribution to mitigating climate change, I would recommend direct purchase to relatives and friends.

References

  1. Kretter, A.; Kádeková, Z. Marketing of direct selling of agricultural products. Zesz. Nauk. SGGW Polityki Eur. Finans. I Mark. 2012, 7, 38–44. [Google Scholar]
  2. Corsi, A.; Novelli, S.; Pettenati, G. Producer and farm characteristics, type of product, location: Determinants of on-farm and off-farm direct sales by farmers. Agribusiness 2018, 34, 631–649. [Google Scholar] [CrossRef]
  3. D’Amico, M.; Di Vita, G.; Bracco, S. Direct sale of agro-food product: The case of wine in Italy. Calitatea 2014, 15 (Suppl. S1), 247. [Google Scholar]
  4. Majewski, E.; Komerska, A.; Kwiatkowski, J.; Malak-Rawlikowska, A.; Wąs, A.; Sulewski, P.; Gołaś, M.; Pogodzińska, K.; Lecoeur, J.L.; Tocco, B.; et al. Are short food supply chains more environmentally sustainable than long chains? A life cycle assessment (LCA) of the eco-efficiency of food chains in selected EU countries. Energies 2020, 13, 4853. [Google Scholar] [CrossRef]
  5. Malak-Rawlikowska, A.; Majewski, E.; Wąs, A.; Gołaś, M.; Kłoczko-Gajewska, A.; Borge, S.O.; Coppola, E.; Csillag, P.; de Labarre, M.D.; Freeman, R.; et al. Quantitative Assessment of Economic, Social and Environmental Sustainability of Short Food Supply Chains and Impact on Rural Territories; Deliverable 7.2., Strength2Food Project no.678024; Strength2Food: Krakow, Poland, 2019; Available online: https://www.strength2food.eu/wp-content/uploads/2019/02/D7.2-Quantitative-assessment-of-economic-social-and-environmental-sustainability-of-short-food-supply-chains-and-impact-on-rural-territories_final_protected.pdf (accessed on 16 June 2025).
  6. Galli, F.; Brunori, G. (Eds.) Short Food Supply Chains as Drivers of Sustainable Development. Evidence Document; Document Developed in the Framework of the FP7 Project FOODLINKS (GA No. 265287); Laboratorio Di Studi Rurali Sismondi: Pisa, Italy, 2013; ISBN 978-88-90896-01-9. Available online: https://orgprints.org/id/eprint/28858/1/evidence-document-sfsc-cop.pdf (accessed on 16 June 2025).
  7. Li, M.; Jia, N.; Lenzen, M.; Malik, A.; Wei, L.; Jin, Y.; Raubenheimer, D. Global food-miles account for nearly 20% of total food-systems emissions. Nat. Food 2022, 3, 445–453. [Google Scholar] [CrossRef]
  8. Emberger-Klein, A.; Schöps, J.; Menrad, K. The influence of climate attitudes and subjective and social norms on supermarket consumers’ intention toward climate-friendly food consumption. Front. Sustain. Food Syst. 2021, 5, 764517. [Google Scholar] [CrossRef]
  9. Faber, J.; Schroten, A.; Bles, M.; Sevenster, M.; Markowska, A.; Smit, M.; Rohde, C.; Duetschke, E.; Köhler, J.; Gigli, M.J.D.C.D.; et al. Behavioural Climate Change Mitigation. Options and Their Appropriate Inclusion in Quantitative Longer Term Policy Scenarios; Main Report; CE Delft: Delft, The Netherlands, 2012. [Google Scholar]
  10. Annunziata, A.; Vecchio, R. Organic farming and sustainability in food choices: An analysis of consumer preference in Southern Italy. Agric. Agric. Sci. Procedia 2016, 8, 193–200. [Google Scholar] [CrossRef]
  11. Kovačić, D.; Kolega, A.; Radman, M. Izravna prodaja poljoprivrednih proizvoda u Hrvatskoj—Mogućnosti i ograničenja. In Prilagodba Europskoj Zajednici, Hrvatske Poljoprivrede, Šumarstva i Ribarstva; Hrvatska akademija znanosti i umjetnosti, Znanstveno vijeće za poljoprivredu i šumarstvo i Sekcija za gospodarstvo; Hrvatsko Agroekonomsko Dru$štvo: Zagreb, Croatia, 2002; pp. 110–123. [Google Scholar]
  12. Kovačić, D. Izravna Prodaja Seljačkih Proizvoda; Agrarno Savjetovanje: Zagreb, Croatia, 2005. [Google Scholar]
  13. Act on Amendments to the Agricultural Act, Official Gazette of the Republic of Croatia, No. 152/2024, Ministry of Agriculture, Croatia. Available online: https://narodne-novine.nn.hr/clanci/sluzbeni/2024_12_152_2517.html (accessed on 12 June 2025).
  14. Regulation on the Implementation of the Programme of Assistance in the Direct Sale of Agricultural Products Through Self-Service Devices in the Process of Fiscalization, Official Gazette of the Republic of Croatia, No. 9/2021, Ministry of Agriculture, Croatia. Available online: https://www.ecolex.org/details/legislation/regulation-on-the-implementation-of-the-programme-of-assistance-in-the-direct-sale-of-agricultural-products-through-self-service-devices-in-the-process-of-fiscalization-lex-faoc200629/?xpage=2&None= (accessed on 12 June 2025).
  15. Regulation on the Sale of Own Agricultural Products Produced on Family Farms, Official Gazette of the Republic of Croatia, No. 76/2014, Ministry of Agriculture, Croatia. Available online: https://www.ecolex.org/details/legislation/regulation-on-the-sale-of-own-agricultural-products-produced-on-family-farms-lex-faoc171005/ (accessed on 12 June 2025).
  16. Puljiz, J.; Biondić, I.; Jelinčić, D.A. Production basis for food tourism in Croatia: Market position of small agricultural producers. J. Foodserv. Bus. Res. 2022, 25, 725–744. [Google Scholar] [CrossRef]
  17. Jurdana, D.S.; Frleta, D.S.; Ðedović, L. Tourism characteristics in rural area. In Proceedings of the 4. Međunarodni Kongres o Ruralnom Turizmu, Zbornik Radova, Supetar, Hrvatska, 9–13 May 2018; pp. 220–229. [Google Scholar]
  18. Predieri, S.; Cianciabella, M.; Daniele, G.M.; Gatti, E.; Lippi, N.; Magli, M.; Medoro, C.; Rossi, F.; Chieco, C. Italian consumers’ awareness of climate change and willingness to pay for climate-smart food products. Sustainability 2023, 15, 4507. [Google Scholar] [CrossRef]
  19. IFIC. Consumer Survey: Climate Change Perceptions and Purchase Impacts. 2023. Available online: https://foodinsight.org/consumer-survey-climate-change-perceptions-and-purchase-impacts/ (accessed on 18 June 2025).
  20. Deconinck, K.; Giner, C.; Hobeika, M.; Nauges, C. How Do Consumers Interact with Environmental Sustainability Claims on Food? Evidence from 40 Countries (No. 218); OECD Publishing: Paris, France, 2025. [Google Scholar]
  21. Hatibovic, F.; Gaete, J.M.; Sandoval, J.; Faúndez, X.; Godoy, M.P.; Ilabaca, P. What Do Believers Believe in? Beliefs, Emotions, and Willingness to Engage in Collective Action on Climate Change Among Residents of a Chilean Region Affected. Sustainability 2025, 17, 6694. [Google Scholar] [CrossRef]
  22. Gilg, A.W.; Battershill, M. To what extent can direct selling of farm produce offer a more environmentally friendly type of farming? Some evidence from France. J. Environ. Manag. 2000, 60, 195–214. [Google Scholar] [CrossRef]
  23. Li, S.; Kallas, Z. Meta-analysis of consumers’ willingness to pay for sustainable food products. Appetite 2021, 163, 105239. [Google Scholar] [CrossRef] [PubMed]
  24. Bazhan, M.; Shafiei Sabet, F.; Borumandnia, N. Factors affecting purchase intention of organic food products: Evidence from a developing nation context. Food Sci. Nutr. 2024, 12, 3469–3482. [Google Scholar] [CrossRef]
  25. Hansika, S.; Wijerathna, M. Evaluation of short organic food supply chains with special reference to climate smartness-the case of direct farmers’ market, Kurunegala, Sri Lanka. J. Agric. Sci.-Sri Lanka 2021, 16, 352–368. Available online: https://jas.sljol.info/articles/9340/files/submission/proof/9340-1-33225-1-10-20210502.pdf (accessed on 10 June 2025). [CrossRef]
  26. Advani, S.; O’Hara, J.K.; Shoffler, S.M.; da Silva, P.P.; Agar, J.; Arnett, J.; Brislen, L.; Cutler, M.; Harley, A.; Hospital, J.; et al. Estimating the scope, scale, and contribution of direct seafood marketing to the United States seafood sector. Mar. Policy 2024, 165, 106188. [Google Scholar] [CrossRef]
  27. Peña Rodríguez, F.J.; Matarán Ruiz, A.; Torres Rodríguez, A.J.; de la Cruz Abarca, C.E.; Sánchez Contreras, J.; Ruiz Díez, A.; Visquert Bruguera, S.; Morilla Moreno, J.C. Long-Time Assessment of the Organic Farmer’s Market in Granada (Spain). Sustainability 2024, 16, 4050. [Google Scholar] [CrossRef]
  28. Neumann, R.; Mehlkop, G. Revisiting Farmers Markets—Disentangling Preferences and Conditions of Food Purchases on Countrywide Data from Germany. Food Qual. Prefer. 2023, 106, 104815. [Google Scholar] [CrossRef]
  29. Wardle, J.; Sorathia, A.; Smith, P.; Feliciano, D. Environmental, Social and Economic Perceptions of Local Food Production: A Case Study of Aberdeenshire Farmers’ Markets. Scott. Geogr. J. 2024, 140, 233–247. [Google Scholar] [CrossRef] [PubMed]
  30. Allegra, V.; Bellia, C.; Zarbà, A.S. The logistics of direct sales: New approaches of the EU. Ital. J. Food Sci. Riv. Ital. Sci. Degli Aliment. 2014, 26, 443–450. [Google Scholar]
  31. Ma, C.C.; Chang, H.P. Consumers’ perception of food and agriculture education in farmers’ markets in Taiwan. Foods 2022, 11, 630. [Google Scholar] [CrossRef]
  32. Vermeir, I.; Verbeke, W. Sustainable food consumption: Exploring the consumer “attitude–behavioral intention” gap. J. Agric. Environ. Ethics 2006, 19, 169–194. [Google Scholar] [CrossRef]
  33. Islam, T.; Meade, N.; Carson, R.T.; Louviere, J.J.; Wang, J. The usefulness of socio-demographic variables in predicting purchase decisions: Evidence from machine learning procedures. J. Bus. Res. 2022, 151, 324–338. [Google Scholar] [CrossRef]
  34. Hood, N.; Urquhart, R.; Newing, A.; Heppenstall, A. Sociodemographic and spatial disaggregation of e-commerce channel use in the grocery market in Great Britain. J. Retail. Consum. Serv. 2020, 55, 102076. [Google Scholar] [CrossRef]
  35. Massey, M.; O’Cass, A.; Otahal, P. A meta-analytic study of the factors driving the purchase of organic food. Appetite 2018, 125, 418–427. [Google Scholar] [CrossRef]
  36. Vaughan, C.A.; Collins, R.; Ghosh-Dastidar, M.; Beckman, R.; Dubowitz, T. Does where you shop or who you are predict what you eat?: The role of stores and individual characteristics in dietary intake. Prev. Med. 2017, 100, 10–16. [Google Scholar] [CrossRef]
  37. Laukkanen, T. Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking. J. Bus. Res. 2016, 69, 2432–2439. [Google Scholar] [CrossRef]
  38. Diamantopoulos, A.; Schlegelmilch, B.B.; Sinkovics, R.R.; Bohlen, G.M. Can socio-demographics still play a role in profiling green consumers? A review of the evidence and an empirical investigation. J. Bus. Res. 2003, 56, 465–480. [Google Scholar] [CrossRef]
  39. Onianwa, O.; Mojica, M.; Wheelock, G. Consumer characteristics and views regarding farmers markets: An examination of on-site survey data of Alabama consumers. J. Food Distrib. Res. 2006, 37, 119–125. [Google Scholar]
  40. Govindasamy, R.; Nayga, R.M., Jr. Determinants of farmer-to-consumer direct market visits by type of facility: A logit analysis. Agric. Resour. Econ. Rev. 1997, 26, 31–38. [Google Scholar] [CrossRef]
  41. Connell, C.M.; Beierlein, J.G.; Vroomen, H. Consumer Preferences and Attitudes Regarding Fruit and Vegetable Purchases from Direct Market Outlets; Paper No.185; Department of Agricultural Economics and Rural Sociology, Pennsylvania State University: University Park, TX, USA, 1986. [Google Scholar]
  42. Hébert, M. Examining Current Research on Local Food: A Review. Stud. Undergrad. Res. Guelph 2011, 4, 88–92. [Google Scholar] [CrossRef]
  43. Skulskis, V.; Girgžiene, V. Direct marketing and consumer trust in organic food products: Vilnius (Lithuania) Case. J. Agric. Sci. Technol. 2013, 3, 272–283. [Google Scholar]
  44. Lee, J.W.; Kim, J.J. Study on the Selection Determinants on Consumers Purchasing Agricultural Products via Direct Market. East Asian J. Bus. Econ. (EAJBE) 2020, 8, 43–56. [Google Scholar] [CrossRef]
  45. Ammann, J.; Arbenz, A.; Mack, G.; Nemecek, T.; El Benni, N. A review on policy instruments for sustainable food consumption. Sustain. Prod. Consum. 2023, 36, 338–353. [Google Scholar] [CrossRef]
  46. Huang, S.H. The Effect of Consumer Knowledge, Attitude and Behavior on Organic Agricultural Production-Researching on Farmers’ Markets of Kaohsiung Area. Master’s Thesis, National Sun Yat-sen University, Kaohsiung, Taiwan, 2012. Available online: https://hdl.handle.net/11296/g6j5kp (accessed on 12 June 2025).
  47. Hair, J.F.; Black, W.C.; Babin, B.J. Multivariate Data Analysis. A Global Perspective, 7th ed.; Pearson Education Inc.: Hoboken, NJ, USA, 2009. [Google Scholar]
  48. Richman, M.B. Rotation of principal components. J. Clim. 1986, 6, 293–335. [Google Scholar] [CrossRef]
  49. Ursachi, G.; Horodnic, I.A.; Zait, A. How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Econ. Financ. 2015, 20, 679–686. [Google Scholar] [CrossRef]
  50. Hair, J.F., Jr.; Matthews, L.M.; Matthews, R.L.; Sarstedt, M. PLS-SEM or CB-SEM: Updated guidelines on which method to use. Int. J. Multivar. Data Anal. 2017, 1, 107–123. [Google Scholar] [CrossRef]
  51. Arbuckle, J.G.; Morton, L.W.; Hobbs, J. Understanding Farmer Perspectives on Climate Change Adaptation and Mitigation: The Roles of Trust in Sources of Climate Information, Climate Change Beliefs, and Perceived Risk. Environ. Behavior. 2015, 47, 205–234. [Google Scholar] [CrossRef]
  52. Giampietri, E.; Koemle, D.B.A.; Yu, X.; Finco, A. Consumers’ Sense of Farmers’ Markets: Tasting Sustainability or Just Purchasing Food? Sustainability 2016, 8, 1157. [Google Scholar] [CrossRef]
  53. Curvelo, I.C.G.; Watanabe, E.A.D.M.; Alfinito, S. Purchase intention of organic food under the influence of attributes, consumer trust and perceived value. Rev. Gestão 2019, 26, 198–211. [Google Scholar] [CrossRef]
  54. Bringula, R.P.; Moraga, S.D.; Catacutan, A.E.; Jamis, M.N.; Mangao, D.F. Factors influencing online purchase intention of smartphones: A hierarchical regression analysis. Cogent Bus. Manag. 2018, 5, 1496612. [Google Scholar] [CrossRef]
  55. Astbury, C.C.; Foley, L.; Penney, T.L.; Adams, J. How does time use differ between individuals who do more versus less foodwork? A compositional data analysis of time use in the United Kingdom time use survey 2014–2015. Nutrients 2020, 12, 2280. [Google Scholar] [CrossRef]
  56. Zhuang, W.; Luo, X.; Riaz, M.U. On the factors influencing green purchase intention: A meta-analysis approach. Front. Psychol. 2021, 12, 644020. [Google Scholar] [CrossRef]
  57. Taufique, K.M.R.; Nielsen, K.S.; Dietz, T.; Shwom, R.; Stern, P.C.; Vandenbergh, M.P. Revisiting the promise of carbon labelling. Nat. Clim. Change 2022, 12, 132–140. [Google Scholar] [CrossRef]
  58. Winterich, K.P.; Reczek, R.W.; Makov, T. How lack of knowledge on emissions and psychological biases deter consumers from taking effective action to mitigate climate change. J. Acad. Mark. Sci. 2024, 52, 1475–1494. [Google Scholar] [CrossRef]
  59. Peattie, K. Green consumption: Behavior and norms. Annu. Rev. Environ. Resour. 2010, 35, 195–228. [Google Scholar] [CrossRef]
  60. Fahlevi, M.; Hasan, F.; Islam, M.R. Exploring consumer attitudes and purchase intentions: Unraveling key influencers in China’s green agricultural products market. Corp. Bus. Strategy Rev. 2023, 4, 74–87. [Google Scholar] [CrossRef]
  61. Li, R.; Lee, H.-Y.; Lin, Y.-T.; Liu, C.-W.; Tsai, P.F. Consumers‘ willingness to pay for organic foods in China: Bibliometric review for an emerging literature. Int. J. Environ. Res. Public Health 2019, 16, 1713. [Google Scholar] [CrossRef]
  62. Xu, P.; Su, H.; Lone, T. Chinese consumers‘ willingness to pay for rice. J. Agribus. Dev. Emerg. Econ. 2018, 8, 256–269. [Google Scholar] [CrossRef]
  63. Chanda, R.C.; Vafaei-Zadeh, A.; Hanifah, H.; Thurasamy, R. Modeling eco-friendly house purchasing intention: A combined study of PLS-SEM and fsQCA approaches. Int. J. Hous. Mark. Anal. 2025, 18, 123–157. [Google Scholar] [CrossRef]
  64. Sharma, L.; Trivedi, M.; Bagdi, H.; Bulsara, H.P. The influence of product availability and social media on green food product purchase intention. Asia-Pac. J. Bus. Adm. 2025, 17, 814–839. [Google Scholar] [CrossRef]
  65. Ogiemwonyi, O.; Alam, M.N.; Alshareef, R.; Alsolamy, M.; Azizan, N.A.; Mat, N. Environmental factors affecting green purchase behaviors of the consumers: Mediating role of environmental attitude. Clean. Environ. Syst. 2023, 10, 100130. [Google Scholar] [CrossRef]
Table 1. Items used for measuring factors.
Table 1. Items used for measuring factors.
FactorItemSource
Climate change attitude (CCA)Climate change is a normal natural phenomenon. (CCA1)[51]
Climate change is a consequence of human activity. (CCA2)
Climate change is a consequence of agricultural activities. (CCA3)
Direct sale impact on
climate change (DSICC)
The direct sale of agricultural products helps reduce CO2 emissions from transportation. (DSICC1)[31,52]
Direct sales of agricultural products result in lower energy consumption for cooling and storage. (DSICC2)
Direct sales reduce waste. (DSICC3)
Through direct communication with consumers, farmers are encouraged to produce sustainably or ecologically. (DSICC4)
Direct sales contribute to mitigating climate change. (DSICC5)
Consumers’ purchase intention (CPI)I want to buy products directly from farmers because I contribute to mitigating climate change. (CPI1)[30,31]
I want to buy products directly from farmers because I encourage climate-sustainable practices in agriculture. (CPI2)
Because of the contribution to mitigating climate change, I would recommend direct purchase to relatives and friends. (CPI3)
Table 2. Sample characteristics.
Table 2. Sample characteristics.
CharacteristicsPercent (%)
GenderMale29.1
Female70.3
AgeUntil 4539.0
More than 4561.0
EducationHigh school and lower 34.8
College and higher65.2
No of household membersUntil 236.7
3 and more63.3
Yearly incomeUntil 40,000 euro69.6
More than 40,000 euro30.4
Source: Data processed by authors.
Table 3. Results of explanatory factor analysis.
Table 3. Results of explanatory factor analysis.
VariablesMeanSD123
Climate change attitude (CCA)
CCA24.010.8990.866
CCA13.121.2110.802
CCA32.961.0830.776
Direct sale impact on climate change (DSICC)
DSICC24.080.794 0.855
DSICC34.140.791 0.827
DSICC13.790.948 0.815
DSICC54.140.781 0.786
DSICC43.730.942 0.719
Consumers’ purchase intention (CPI)
CPI13.871.034 0.922
CPI23.950.969 0.888
CPI33.911.070 0.808
Eigenvalues 2.7782.7161.127
% variance 25.25424.68710.249
% cumulative variance 25.25449.94160.191
Cronbach’s α 0.7850.9150.840
Source: Data processed by authors.
Table 4. Results of hierarchical regression analysis.
Table 4. Results of hierarchical regression analysis.
VariablesDirect Sale Purchase Intention
Model 1Model 2
Constant0.1651.256 ***
Gender0.1180.048
Age0.0260.035
Year income0.0190.005
Education0.017−0.038
No of household members−0.065−0.056
Climate change attitude-0.238 ***
Direct sale impact on climate change-0.560 ***
R20.0190.454
Adjusted R20.0150.435
F statistic1.08032.967 ***
R2 Change0.0190.435 ***
F Change1.080110.563
Note: *** significant at α = 0.001. Source: Data processed by authors.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Čehić Marić, A.; Težak Damijanić, A.; Čop, T.; Njavro, M.; Oplanić, M. Factors Influencing Consumers’ Direct Sale Purchase Intention in the Context of Climate Change. Sustainability 2025, 17, 7603. https://doi.org/10.3390/su17177603

AMA Style

Čehić Marić A, Težak Damijanić A, Čop T, Njavro M, Oplanić M. Factors Influencing Consumers’ Direct Sale Purchase Intention in the Context of Climate Change. Sustainability. 2025; 17(17):7603. https://doi.org/10.3390/su17177603

Chicago/Turabian Style

Čehić Marić, Ana, Ana Težak Damijanić, Tajana Čop, Mario Njavro, and Milan Oplanić. 2025. "Factors Influencing Consumers’ Direct Sale Purchase Intention in the Context of Climate Change" Sustainability 17, no. 17: 7603. https://doi.org/10.3390/su17177603

APA Style

Čehić Marić, A., Težak Damijanić, A., Čop, T., Njavro, M., & Oplanić, M. (2025). Factors Influencing Consumers’ Direct Sale Purchase Intention in the Context of Climate Change. Sustainability, 17(17), 7603. https://doi.org/10.3390/su17177603

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

Article Metrics

Back to TopTop