Factors influencing farmer intentions to scale up organic rice farming: preliminary findings from the context of agricultural production in Central Vietnam

Abstract

The Vietnamese government encourages organic farming (OF) as a move toward safer and more eco-friendly agricultural practices. To achieve the goal of popularizing OF, besides encouraging the participation of newcomers, the government should also focus on farmers already involved because their production decisions are the most effective means for communication. By blending quantitative and qualitative approaches, this study investigated smallholder farmer intentions to scale up organic rice farming (ORF). Data were obtained through direct interviews with 325 farmers in the Phu Vang, Phong Dien and Huong Thuy Districts of Thua Thien Hue Province, Central Vietnam. The results revealed the ineffectiveness in demographic characteristics, including gender, age, education, number of laborers, OF experience, percentage of organic rice area, non-farm jobs and involvement in community-based organizations to predict farmer intentions to expand ORF. The findings highlighted the more significant influence of factors related to economic outcomes, farmer awareness of OF, and their confidence in the market outlook. We recommend policies and interventions associated with promoting the advantages of organic agriculture, intensifying technical training, linking production with the market following the value chain model, equipping the market with information, diversifying support and timely undertaking of issued policies.

Introduction

Sustainable farming practices are being promoted to counter the threats posed by the overuse of chemicals on the environment and human health. Among these, organic agriculture represents one of the most reasonable choices targeted by most countries (Lee et al. 2015; Mishra et al. 2019). Organic agriculture is defined as a production system that responds to site-specific conditions by integrating cultural, biological, and mechanical practices that foster resource cycling, promote ecological balance, and conserve biodiversity (SARE 2003).

Sustainable farming is currently being practiced by 3.1 million farmers in 187 countries. The total area of organic farmland increased considerably within a decade, from 36.3 million ha in 2009 to 72.3 million in 2019. Australia, Argentina, Spain, the USA, and India are the top five countries in terms of organic farmland area worldwide. By share of total agricultural land, Liechtenstein is the leading country (41%), followed by Austria (26.1%) (Willer et al. 2021). Consumers are increasingly turning to organic products because they believe they are healthier and more eco-friendly (Smith and Paladino 2010; Nguyen et al. 2019). The global organic food market was worth 201.77 billion USD in 2020 and is expected to be worth 380.84 billion USD in 2025 at a compound annual growth rateof 14.5% (Research and Markets 2021).

Despite the rapid industrialization and modernization in recent years, agriculture remains an essential component of the Vietnamese economy. In 2020, agriculture, forestry, and fisheries accounted for 14.85% of the economy (GSO 2020). This sector creates stable earnings for approximately 13.8 million laborers, equivalent to 27.01% of the national labor force (GSO 2021a). Vietnamese agricultural products were exported to 190 countries and territories, with a turnover of USD 41.2 billion in 2020 and USD 22.83 billion in the first 5 months of 2021 (GSO 2021b). Rice, coffee, rubber, pepper, cashews, and vegetables are the main agricultural products exported by Vietnam. Although it is one of the leading producers and exporters of agricultural products, the targeted economic value of Vietnamese agricultural products has not been achieved. Vietnam currently ranks 2nd in Southeast Asia and 15th globally in agricultural exports but accounts for only 1.95% of the world’s agricultural import value. Low quality should be considered the primary cause of this issue, which is the main obstacle for Vietnamese agricultural products to overcome in order to penetrate deeper into strictly regulated markets, such as the UK, the USA, Japan, Australia, and the EU. Therefore, improving the quality of agricultural products is essential to boost the export value to 50 billion USD by 2025 and 60 billion USD by 2030, as targeted in the scheme to enhance the competitiveness of Vietnam’s exports by 2020, with a vision to 2030 (Vietnamese Government 2017).

In addition to exports, the Vietnamese government has also moved toward cleaner, safer, and more eco-friendly agriculture for domestic consumption. In recent decades, the pressure to increase crop yields has raised many concerns. Notably, agricultural input pollution has increased considerably in Vietnam over the past 2 decades with the expansion and intensification of crops. It is estimated that the use of pesticides in Vietnam has increased by approximately 3- to 5-fold in almost 25 years, with imports of active pesticide ingredients ranging from 20,000 to 30,000 tons per year in the 1990s to nearly 100,000 tons in 2015. Likewise, the levels of the active ingredient per hectare tripled during this period (World Bank 2017). According to an overview of toxic pesticides in Vietnam (Phong and Tran 2020), several highly toxic active ingredients are still licensed for use despite being banned by the Asia–Pacific Pesticide Use Reduction Action Network. In the long run, this should be considered a substantial threat to consumer health, the reputation of Vietnamese agricultural products, and environmental sustainability (Nguyen 2017; Huyen et al. 2020). Developing organic agriculture appears to be a critical measure taken by the Vietnamese government to steer agriculture toward sustainability. According to the Ministry of Agriculture and Rural Development, the organic agricultural area in Vietnam increased from 53,350 ha in 2016 to approximately 237,693 ha in 2019. Moreover, 46 out of 63 provinces were implementing organic cultivation, and the number of farmers involved in OF was roughly 17,168 (MARD 2020). Vietnam currently ranks 32nd globally and 2nd in Southeast Asia regarding organic farmland area. However, OF accounts for only approximately 1.1% of the total agricultural land area (equivalent to 237,000 ha), which is unimpressive compared to its agricultural potential.

The Vietnamese government has established the goal of developing organic agriculture through decision 885/QD-TTg, approving the organic agriculture development scheme for 2020–2030. Accordingly, the organic agricultural land area is scheduled to increase to approximately 2% by 2025 and 3% by 2030. Its efficiency was also targeted to be 1.3–1.5 times higher than conventional models by 2025 and 1.5–1.8 times higher by 2030 (Vietnamese Government 2020). In addition to government efforts, farmers' roles should be emphasized to achieve these goals. Farmers still make the ultimate decisions regarding farming; therefore, the consensus of farmers is a prerequisite to popularizing this sustainable farming model.

In addition to encouraging newcomers’ participation, intensifying organic agriculture can be achieved by encouraging those considering expanding their area. The farmers’ decision to extend, limit, or withdraw from this model directly changes the current scale of OF and affects the psychology of those intending to participate, as their production decisions are the most effective means of communication. Recent studies (Sterrett et al. 2005; Karki et al. 2011; Peterson et al. 2012; Azam and Banumathi 2015; Pinthukas 2015; Xie et al. 2015; Ma et al. 2017; Métouolé Méda et al. 2018) have focused on investigating the factors driving the decision to engage in OF while neglecting the production decisions afterward (e.g., extending, limiting, or withdrawing from the model). Understanding the factors driving farmers’ intentions toward OF expansion is crucial for proposing timely and effective policies and interventions.

To fill this knowledge gap, we aimed to examine the factors driving the intention to expand the OF area of smallholder farmers in Thua Thien Hue province, central Vietnam. The results of this study are expected to provide deeper insights into the drivers promoting ORF in Vietnam, which are crucial for proposing effective policies and interventions.

Literature review on factors promoting organic farming

Owing to the scarcity of studies investigating farmers’ intentions toward expanding OF, we reviewed the published literature regarding factors driving farmers’ decisions to engage in organic agriculture and employed them as a basis for the discussions. These studies are also helpful in identifying the differences between farmers’ expectations of participating in this model (e.g., economic and market conditions, government support, health, and environment) and the performance achieved in practice.

Adoption of OF requires favorable conditions to improve the likelihood of the conversion process. Besides lacking motivation, farmers may encounter several barriers and obstacles in this process, decreasing the likelihood of adoption. Scholars have employed various factors to investigate households' decisions to engage in OF models. In general, these are diverse and vary by country and region. The following is a brief and systematic summary of these factors.

As baseline factors, demographic variables were most commonly employed by previous scholars to examine farmers’ decisions toward adopting OF (Genius et al. 2006; Isin et al. 2007; Mwiathi 2008; Karki et al. 2011; Läpple and Rensburg 2011; Azam and Banumathi 2015; Pinthukas 2015; Xie et al. 2015; Métouolé Méda et al. 2018). Isin et al. (2007) employed social, structural, and intellectual group factors to examine dried fig production in Turkey. Their findings revealed that producers’ educational status, age, and fig-growing experience were influential parameters in adopting organic dried fig agriculture. Using Nepalese tea producers in the Ilam and Panchthar districts of Nepal as a case study, Karki et al. (2011) found that farmers who are older, located further from regional markets, better trained, affiliated with institutions, and have larger farms are more likely to adopt organic cultivation. Läpple and Rensburg (2011) investigated the temporal aspects of organic agriculture implementation in the Republic of Ireland. They concluded that the factors influencing adoption played different roles for early, medium, and late adopters, particularly regarding farming intensity, age, information collection, and farmers’ attitudes. More specifically, early adopters of OF were the youngest, and their decisions were less profit-related than those of other groups. A study of potato farming in the Nalanda district of Bihar by Azam and Banumathi (2015) showed that educational attainment, age, and gender had an influence; however, family size and land ownership were less influential. It was found that the economic situation of organic farmers had improved considerably, and training provided by the government had led farmers to become more confident and self-reliant. Meda et al. (2018) highlighted the role of education in selecting conventional, organic, and genetically modified cotton-planting models in Burkina Faso. Pinthukas’s (2015) research on organic vegetables in Chiang Mai, Thailand, emphasized the crucial role of age, education level, household labor, farm income, and extension visits on farmers' awareness of organic cultivation. Moreover, education level, experience, availability of natural water, and farmers’ networks or membership markedly contributed to their adopting organic vegetable production. However, Cukur (2015) found a negative association between farmers’ educational levels and their intention to produce organic milk in the future. Meanwhile, the study by Xie et al. (2015) explored the willingness of small farmers to engage in OF in Jiangsu, China. Five factors were discovered: the farmer’s age, risk preferences, labor costs, expected benefits, and the environment. The effects of farm size and farming year were further noted by Liu et al. (2019) and Pradhan et al. (2017) for small farms in the US and India, respectively.

Financial reasons were demonstrated as critical factors in making decisions regarding OF (Sholubi et al. 1997; Entz and Guilford 1998; Lohr 2000; Pietola 2001; Sterrett et al. 2005; Ács 2006; Läpple and Kelley 2010; Nguyen et al. 2020). Entz and Guilford (1998) noted that organic wheat and alfalfa farms in Canada were more profitable than conventional models despite not setting higher prices. Similarly, Sholubi et al. (1997) found that organic dairy farms were more profitable than conventional farms. According to Pietola (2001), low output prices and the escalation of direct government subsidies spurred farmers in Finland to become organic producers. Lohr (2000) demonstrated the role of subsidy requirements as determinants that encouraged Swedish farmers to convert to OF. Accordingly, services had a more substantial impact than subsidies in promoting farmer participation in organic practices. By examining the Netherlands’ transition to OF systems, Ács (2006) concluded that OF remained economically attractive to producers, despite the difficulties in the conversion phase. Meanwhile, Sterrett et al. (2005) scrutinized organic conversion in Virginia and concluded that high costs and uncertain certification processes were the main obstacles. Marketing shortages and the high cost of labor and information were additional obstacles. By considering farmers’ decisions to abandon OF, Läpple and Kelley (2010) suggested that structural and economic factors primarily drove abandonment decisions. Farmers engaged in non-farm jobs were likelier to abandon OF, whereas more intensive farm systems tended to maintain their organic practices. Based on a dataset of factors influencing intentions to engage in OF in Vietnam, Nguyen et al. (2020) emphasized the positive impact of farmers’ attitudes toward productivity and profit on their application. Similarly, the investigation of Kaufmann et al. (2011) in Lithuania stressed that the main drivers of future in-conversions were related to economic and farm management reasons. These depended primarily on the type of farm, whether farmers believed it was possible to manage an organic farm effectively, subsidies, and, in this regard, farmers’ expectations about the impact on land prices and land rents.

Farmers’ awareness and attitude toward the advantages of organic production have also been thoroughly investigated in previous studies (Anderson 1995; Marshall 1999; Duram 2000; Burton et al. 2003; De Cock 2005; Parra López and Calatrava Requena 2005; Läpple and Kelley 2010; Läpple and Rensburg 2011; Pornpratansombat et al. 2011; Peterson et al. 2012; Yanakittkul and Aungvaravong 2020). Environmental and health issues that emerge in common practices have contributed markedly in developing the sustainable agriculture movement (Anderson 1995). Organic farming is closely related to an eco-friendly lifestyle that addresses environmental and health issues. Duram (2000) revealed that farmers who are more concerned about the environment and have a better attitude toward challenges were more likely to choose OF. Meanwhile, Marshall (1999) showed that the value brought about by OF was the primary motivation for farmers to convert to the organic model in France. Burton et al. (2003) proposed a model to test the adoption of organic horticultural technology in the UK. They proved that attitudes toward the environment and information systems were essential drivers of adoption decisions. Similarly, Peterson et al. (2012) discovered that younger farmers were more likely to be motivated by environmental and lifestyle goals than older farmers. This asserts that environmental judgments were the main reason for switching from conventional to OF. Through a case study of Spanish olive orchards, Parra López and Calatrava Requena (2005) indicated that farmers with more negative opinions regarding chemical usage tended to engage in organic agriculture, even though it requires more time and effort. Compared with Belgian farmers’ attitudes toward conventional and organic models, De Cock (2005) revealed that conventional farmers were more concerned with yield, risk, and cost reduction. Achieving higher economic efficiency than colleague farmers was often considered important. Meanwhile, organic farmers valued business goals such as flexibility, production quality, and reduced environmental impact. Through a case study in Ireland, Läpple and Kelley (2010) stated that conversion to OF was strongly affected by farmers’ attitudes toward the environment, perceived social pressure, and ability to convert. In the agricultural context of Ireland, Läpple and Rensburg (2011) also found that later adoption of OF was constrained by risk considerations, while environmental attitudes and social learning were identified as important determinants for all adopters. Research by Pornpratansombat et al. (2011) in northeastern Thailand concluded that water accessibility, on-farm prices, and farmers’ attitudes toward conventional production problems promoted their engagement in OF models. In addition, Yanakittkul and Aungvaravong (2020) accentuated the positive influences of farmers’ attitudes toward farming behavior and perception of risk on their organic cultivation decisions in Thailand. Mohamed Haris et al. (2018), through a case study in four regions of Peninsular Malaysia, underscored that positive environmental attitude was the most influential factor, followed by information-sharing attitudes and land ownership.

Other valuable factors, such as technical aspects (Fairweather 1999; Schneeberger et al. 2002), information acquisition (Wynen 2004; Genius et al. 2006; Isin et al. 2007; Läpple and Rensburg 2011), social relationships (Lobley et al. 2005), institutional support (Lynggaard 2001; Michelsen et al. 2001; Koesling et al. 2008; Pradhan et al. 2017; Yanakittkul and Aungvaravong 2020), production contracts (Ma et al. 2017), and training (Métouolé Méda et al. 2018), were also investigated by previous researchers.

In general, the above literature sketched a vivid picture of the factors driving farmers to switch to OF. However, the factors influencing the intention of farmers with experience with this model to scale up OF have not been adequately considered. Therefore, by examining farmers’ intentions toward expanding the organic rice area in central Vietnam, this study aims to expand this area of knowledge.

Study design

Study sites

This study was conducted in Thua Thien Hue Province in Central Vietnam. The province’s total agricultural land area is almost 70,000 ha, accounting for approximately 14.12% of the total natural land area. Rice is one of the key crops in Thua Thien Hue Province, with a total area of almost 31,000 ha (the annual rice cultivation area is about 54,000 ha). The province’s high-quality rice area exceeded 17,125 ha in 2020, 6,780 ha higher than that in 2015, and accounted for approximately 31.5% of the province’s rice area. Currently, the province is implementing agricultural restructuring toward increasing added value and sustainable development. The People’s Committee of Thua Thien Hue Province has issued Decision No. 67/2021/QD-UBND (November 12, 2021), encouraging the development of key goods and products in 2021–2025. Accordingly, expanding the scale of high-quality rice production following sustainable cultivation models, such as OF, is highly prioritized. The province’s target is to reach roughly 25,000 ha of high-quality rice by 2025, with half of the area used based on commitments or contracts with enterprises (see Table 1). The profit from high-quality rice production is also expected to increase by 10–15% compared to conventional production. Organic rice development, which started in 2014 with a five-ha pilot area, is considered a key direction in the province’s scheme toward improving the quality and efficiency of agricultural products. Currently, the province is implementing many measures to attract more farmers to this sustainable model and encourage those already involved in expanding their scale of ORF. However, this province’s scale of organic rice production is currently inadequate. As of 2021, the province’s organic rice production area is approximately 370 ha, accounting for roughly 1% of the total land under rice. Therefore, determining the underlying cause of this situation is crucial.

Table 1.

Planned area (hectare) for high-quality rice production in the period 2020–2025

City/district	Year
	2020	2021	2022	2023	2024	2025
Phong Dien	3000	3000	3100	3250	3350	3500
Quang Dien	2033	2190	2420	2590	2800	3050
Huong Tra	2480	2850	3080	3220	3280	3300
Huong Thuy	2890	2955	2955	3025	3025	3025
Phu Loc	1540	1540	1540	1540	1540	1540
Hue City	668	655	654	654	654	654
Nam Dong	16	17	17	17	17	17
A Luoi	923	956	1008	1058	1097	1158
Phu Vang	5246	6066	6566	7202	7919	8624
Total	18,796	20,229	21,340	22,556	23,682	24,868

Source: People’s Committee of Thua Thien Hue Province (2020)

The Phu Vang, Phong Dien, and Huong Thuy districts were selected as the key organic and high-quality rice production areas of Thua Thien Hue Province (see Fig. 1). In recent years, the scale of organic rice cultivation in these locations has increased more impressively than elsewhere. For example, the organic rice field area in Huong Thuy District reached 75 ha in 2020, which is 30 ha greater than that in 2019. However, this organic rice area is still small, accounting for only approximately 1.25% of the district’s total rice cultivation area. In the Phong Dien district, the An Lo cooperative deployed the organic rice production model in the Phong Hien commune in 2016, over approximately 8 ha. Although it was expanded to 22 ha in 2020, the district’s organic rice scale is now facing many obstacles due to difficulties related to product consumption. Phu Vang is one of the districts with the most extensive rice farming areas in Thua Thien Hue Province, with approximately 12,000 ha. The Phu Luong commune is a typical rice-producing commune with an annual rice production area of nearly 2300 ha. The organic rice scale in this area has considerably extended from just 10–130 ha in 2020.

Fig. 1.

Map of study sites

Methods

Data collection

The data for analysis were collected in the Phu Vang, Phong Dien, and Huong Thuy districts from June to July 2021 and October to December 2021. In the first step, the unstructured in-depth interview method was employed to obtain secondary socio-economic and agricultural production data from local government agencies at the provincial, district, and commune levels (Department of Agriculture and Rural Development; People’s Committees of districts; People’s Committees of communes). This step aided us in identifying key organic rice-growing areas in selected districts for the survey. The same method was used to interview individuals responsible for producing rice in agricultural cooperatives. The farmers at the selected sites were interviewed using a semi-structured questionnaire. The study population included households that concurrently produce organic and conventional rice in Thua Thien Hue province. As most of these households are managed by local cooperatives, the survey was conducted following cooperatives’ guides. The questionnaires were distributed equally among the six selected agricultural cooperatives in three districts: Phu Vang, Phong Dien, and Huong Thuy, where the organic rice production of Thua Thien Hue province is concentrated (60 per cooperative). The number of surveyed households was decided based on consultation with local authorities and cooperatives’ representatives. Accordingly, surveying around 60 households per cooperative was appropriate to capture the general situation of organic rice production. Regarding the survey method, we applied simple random sampling to eliminate discrimination in household selection. Accordingly, households were randomly selected by interviewers based on lists provided by representatives of agricultural cooperatives, regardless of their production scale and socio-economic conditions. Our target interviewees were household heads (husband or wife) who understood production activities and often held the highest decision-making power in the family. A household would be ignored or visited later if the head was absent. Regarding the interview content, the interviewees were first asked to provide basic information on their demographic characteristics and livelihood activities. We then explored the results and effectiveness of recent crops that were organically farmed, the advantages and disadvantages encountered, and their views on this sustainable production model. Finally, farmers were asked to share their intentions regarding scaling up ORF over the next five years and their explanations. Out of 360 questionnaires distributed, only 325 contained complete information and were used for analysis (90.28%), while the others with missing data were excluded. The number of questionnaires obtained from agricultural cooperatives was relatively uniform (53–57).

Data analysis

Both qualitative and quantitative approaches were used to perform this study. While the interactions of output variables and predictors were tested using a quantitative approach, the meanings behind the predicted numerical data were interpreted using a qualitative approach. The study used a binary logistic regression model to investigate the factors driving farmers’ intention to scale up ORF. The dependent variable is farmers’ intention to scale up organic rice farming (expanding cultivated land area). It was split into either “intended” or “not intended,” corresponding to 1 and 0 in the regression model. Data were processed using IBM SPSS Statistics 22 software.

Through reviewing relevant literature in Sect. 2, this study considered 17 explanatory variables related to household demographics, economic outcomes of ORF, farmers’ awareness of OF, and their confidence in this model’s prospects. These variables are briefly described in Table 2. We expected to discover some statistically significant effects on households’ production intention from these variables. Based on the results of published documents (see Sect. 2), we hypothesize that households characterized by one or several of the following attributes intend to scale up ORF: male-headed households, younger and better-educated householders, having more laborers, having more experience in organic cultivation, engaging in off-farm occupations, active involvement in community-based organizations, satisfaction with organic rice outcomes, awareness of OF’s positive effects, and positive beliefs in OF prospects. These characteristics are often seen as advantages for households to access/implement advanced agricultural production models. Their positive influence on farmers’ decisions to engage in OF has also been demonstrated (see Sect. 2). But how they affect farmers’ intention to scale up OF remains unknown and thus needs to be explored.

Table 2.

Brief description of the key variables

Variable	Type	Description	Min	Max	Mean	SD	Expected signs
Dependent variable
Intention to scale up organic rice farming	Binary	1 = intended; 0 = not intended	0	1	0.46	0.499	N/A
Explanatory variables
Household demographics
Householder’s sex	Binary	1 = male; 0 = female	0	1	0.81	0.391	+
Householder’s age	Nominal	1 = under 40 years old; 2 = 40–60 years old 3 = over 60 years old	1	3	2.11	0.653	–
Householder’s highest educational attainment	Nominal	1 = elementary school; 2 = Secondary school; 3 = high school	1	3	1.60	0.571	+
Number of agricultural laborers	Continuous	Number of self-employed agricultural laborers	1	5	2.57	0.968	+
Experience in organic agriculture	Continuous	Number of years in OF	2	9	4.00	1.633	+
Percentage of ORF land	Continuous	Percentage of ORF land to rice land	15	70	31.32	8.435	±
Engaging in non-farm job	Binary	1 = yes; 0 = no	0	1	0.56	0.497	±
Actively involved in community-based organizations	Binary	1 = yes; 0 = no	0	1	0.11	0.318	+
Economic outcomes of organic rice farming
Organic rice yield achieved as expected	5-level Likert	1 = strongly disagree–5 = strongly agree	1	5	2.50	0.922	+
Organic rice price achieved as expected	5-level Likert	1 = strongly disagree–5 = strongly agree	1	4	2.18	0.699	+
Consumption of organic rice is guaranteed	5-level Likert	1 = strongly disagree–5 = strongly agree	1	5	2.96	0.890	+
Income from ORF plays an important role	5-level Likert	1 = strongly disagree–5 = strongly agree	1	5	1.59	0.678	+
Farmers’ awareness of organic farming
OF contributed to improving the environment	5-level Likert	1 = strongly disagree–5 = strongly agree	2	5	3.47	1.020	+
OF enhanced my family members’ health	5-level Likert	1 = strongly disagree–5 = strongly agree	1	5	3.67	1.344	+
My OF fostered awareness and adoption of others	5-level Likert	1 = strongly disagree–5 = strongly agree	1	5	3.46	1.023	+
Farmers’ belief in market prospects
I believe in the market prospects of organic agriculture	5-level Likert	1 = strongly disbelieve–5 = strongly believe	1	5	3.12	1.016	+
I believe in government support for organic agriculture	5-level Likert	1 = strongly disbelieve–5 = strongly believe	1	5	3.43	1.361	+

Source: household interviews

Results and discussion

Demographic profile of respondents

The main characteristics of the study population are shown in Table 3. Most respondents were male (81.2%) and middle-aged (56.3%). More than half of the households (51.7%) had only attended secondary school, while only 4% claimed high school. The average number of laborers per household was 2.57; however, less than half (47.7%) of the households had more than two laborers. By income level, most households (59.7%) were classified as middle-class, with a monthly average income in the range of 1.5–4.5 million VND. In comparison, approximately, one-fifth (19.1%) of households were poor. Approximately 60% of the interviewees had used OF for approximately 3–5 years. Meanwhile, the number of respondents with less than two or more than 5 years of experience was approximately 20%. Most households (78.7%) used 20–40% of the rice land for organic cultivation. More than half (56%) of the farmers engaged in non-farm work to improve their household earnings. Most families resided in semi-permanent houses (67.1%), whereas only 13.2% were still using temporary dwellings.

Table 3.

Demographic profile of respondents

Characteristic	Frequency	Percentage
Householder’s sex
Male	264	81.2
Female	61	18.8
Householder’s age
< 40 years old	53	16.3
40–60 years old	183	56.3
> 60 years old	89	27.4
Householder’s highest educational attainment
Elementary school	143	44.0
Secondary school	168	51.7
High school	14	4.3
Number of agricultural laborers
≤ 2	170	52.3
> 2	155	47.7
Monthly per capita income
< 1.5 million VND	62	19.1
1.5–4.5 million VND	194	59.7
> 4.5 million VND	69	21.2
Experience in organic agriculture
≤ 2 years	73	22.5
3–5 years	190	58.4
> 5 years	62	19.1
Percentage of ORF land
< 20%	34	10.5
20–40%	256	78.7
> 40%	35	10.8
Engaging in non-farm job
No	143	44.0
Yes	182	56.0
Household classification
Poor	62	19.1
Non-poor	263	80.9
Housing type
Permanent	64	19.7
Semi-permanent	218	67.1
Temporary	43	13.2

Source: household interviews

Factors influencing household intention to scale up organic rice farming

This study used the binary logistic regression model to explore the factors driving smallholder farmers’ intention to scale up ORF. Based on the model design, the dependent variable (intention to expand the scale of ORF) is treated as a discrete variable that can only take values of zero or one. One (1) refers to households that intend to scale up organic rice cultivation, whereas zero (0) refers to those that do not. As predictors, the model comprised 17 variables related to household demographics, ORF outputs, awareness of ORF impacts, and their confidence in the prospects of this sustainable farming method in the coming years.

Table 4 summarizes the accuracy of the model in making predictions. The model correctly anticipated 157 of 176 cases (89.2%) with no intention of expanding ORF. Similarly, the model misjudged only 28 out of 149 households intending to expand ORF, equivalent to an accuracy rate of 81.2%. As a result, the model’s average success rate reached 85.5%, indicating its robust dependability.

Table 4.

Percentage accuracy in classification (PAC)

Observed	Predicted
	Expanding ORF		Percentage correct
	No	Yes
Expanding ORF
No	157	19	89.2
Yes	28	121	81.2
Overall percentage			85.5

Source: data calculated by authors

Since this study’s outcome variable is designed in binary form, the Hosmer–Lemeshow goodness of fit test was used to assess the model’s fit. Although this test has certain limitations, for instance, its results can be different when the Hosmer–Lemeshow goodness of fit test is performed with a lower number of covariate samples than the number of objects (Hosmer et al. 1997; Bertolini et al. 2000; Kramer and Zimmerman 2007), it is still widely accepted and used by previous scholars (Kwadzo and Quayson 2021; Abdillah Tiffany et al. 2022; Ha et al. 2022).

Table 5 lists the calculated parameters for the binary logistic regression. The p-value of the Hosmer–Lemeshow goodness of fit test (0.786 > α = 0.05) demonstrates that the model adequately fits the data. Otherwise stated, the overall link between explanatory factors and household intention probability is plausible (χ² = 4.729; p = 0.786 > 0.05). The value of Nagelkerke’s R² (0.706) further indicates that the predictive variables included in the model explained 70.6% of households’ intention to expand ORF. The factors driving household intention to scale up ORF are discussed in the following sub-sections.

Table 5.

Binary logistic regression results on factors driving farmers’ intention to scale up organic rice farming

Indicators	B	S.E.	Wald	df	Sig.	Exp(B)	95% CI for EXP(B)
							Lower	Upper
Householder’s sex	0.372	0.466	0.636	1	0.425	1.450	0.582	3.615
Householder’s age	0.278	0.281	0.983	1	0.322	1.321	0.762	2.291
Householder’s highest educational attainment	− 0.354	0.327	1.170	1	0.279	0.702	0.369	1.333
Number of agricultural laborers	− 0.263	0.235	1.253	1	0.263	0.769	0.485	1.218
Experience in organic agriculture	0.179	0.124	2.081	1	0.149	1.196	0.938	1.524
Percentage of ORF land	− 0.021	0.024	0.732	1	0.392	0.979	0.934	1.027
Engaging in non-farm job	− 0.169	0.397	0.181	1	0.670	0.844	0.388	1.839
Actively involved in community-based organizations	0.257	0.647	0.157	1	0.692	1.292	0.364	4.591
Organic rice yield achieved as expected**	2.042	0.314	42.335	1	0.000	7.702	4.164	14.246
Organic rice price achieved as expected*	0.675	0.301	5.045	1	0.025	1.964	1.090	3.540
Consumption of organic rice is guaranteed**	1.329	0.251	27.975	1	0.000	3.778	2.309	6.182
Income from ORF plays an important role	0.351	0.291	1.453	1	0.228	1.420	0.803	2.511
OF contributed to improving the environment	0.318	0.198	2.594	1	0.107	1.375	0.933	2.025
OF enhanced my family members’ health*	0.428	0.190	5.070	1	0.024	1.534	1.057	2.227
My OF fostered awareness and adoption of others	0.064	0.206	0.095	1	0.758	1.066	0.711	1.597
I believe in the market prospects of organic agriculture*	0.444	0.217	4.195	1	0.041	1.559	1.019	2.385
I believe in government support for organic agriculture	0.016	0.113	0.021	1	0.885	1.016	0.815	1.268
Constant	− 15.221	2.195	48.087	1	0.000	0.000
Model summary	− 2 log-likelihood			204.293
	Cox and Snell R2			0.528
	Nagelkerke R2			0.706
	Chi-square			4.729
	Sig.			0.786

Source: Data calculated by the authors

*^,**Significant at 5% and 1%, respectively

Effects of demographic characteristics

We found no statistically significant relationship between farmers’ intentions and the eight demographic predictors. Although the intention to expand ORF was higher in male-headed households, this linkage was statistically insignificant (p = 0.425). Similarly, the effects of age and education level were insignificant (p = 0.322; p = 0.279). Male, younger, and better-educated household heads are often considered more advantageous and active in exploring new information and advanced production approaches, including OF (Vo et al. 2021). Most farmers in the study sites mastered ORF techniques regardless of gender, age, or education level. This may explain why the above characteristics did not make any difference to farmers’ intentions to scale up ORF. Our results were distinct from those of previous studies. On the contrary, Azam and Banumathi (2015) revealed a positive relationship between farmers’ ages and OF practices, and Singh et al. (2015) showed a negative relationship. Most previous studies concluded that males were more likely to engage in OF (Pinthukas 2015; Ma et al. 2017; Pradhan et al. 2017). Shaban (2015) found that farmers with higher educational qualifications were more likely to convert to organic cultivation models, contradicting the findings of Cukur (2015).

Contrary to our hypothesis, the role of agricultural laborer numbers in anticipating farmers’ intentions toward expanding ORF was negligible (p = 0.263). Households with more laborers were even less willing to broaden their ORF. Several studies have demonstrated that the labor required for ORF is almost twice that of conventional rice farming (Thanh et al. 2020). However, the fieldwork suggested that most households did not face much difficulty in OF despite having a couple of regular agricultural laborers. Some households reported that labor shortage did not affect their decisions, as the labor requirement was concentrated in several stages of the rice growth cycle. In addition, this issue could be easily solved through labor exchange, which is quite common in rural Vietnam. This could be a plausible explanation for the poor correlation between farmers’ decisions and their workforce. This result would negate the findings of Wollni and Andersson (2014) and Ullah et al. (2015) that family laborers were able to join farming activities, even if they worked elsewhere. Thus, households reduce the cost of hiring other workers. Meanwhile, it was consistent with the result of Läpple and Rensburg (2011) that an increase in household members was an obstacle deterring households’ intentions. This indicated that the number of laborers determined a households’ decision to enter OF but was less significant for their scaling-up intention.

Farmers’ intentions were also unaffected by their experience (p = 0.149). Most households stated that their organic rice production strictly followed the instructions of the extension staff, cooperatives, and local authorities. In general, knowledge of organic agriculture among households was relatively similar. Therefore, longer organic rice production time may not offer any advantage in increasing crop yields. More experience in ORF might slightly improve production efficiency by reducing labor input. Since households were equipped with similar and adequate knowledge, fewer years of experience was not a significant obstacle and, therefore, had no effect on a households’ intention to increase farming scale. Most previous studies showed a negative relationship between conventional agricultural experience and intention to adopt OF practices. Farmers with vast experience in conventional farming were usually older and less educated; therefore, it was difficult to shift them to the relatively new concept of OF (Parra López and Calatrava Requena 2005; Adesope et al. 2012; Pinthukas 2015; Ullah et al. 2015; Ma et al. 2017; Liu et al. 2019). Only a few studies have reported the opposite result that farmers with more agricultural experience were more likely to practice OF, possibly because they had a deeper understanding of the environment and the potential adverse effects of conventional farming on human health. On the other hand, with regard to OF experience, most scholars showed a positive correlation between OF experience and farmers’ intentions to scale up. It is likely that farmers with more experience with organic cultivation had more accurate perceptions of the advantages of this model for health, productivity, markets, and the environment (Parra López and Calatrava Requena 2005; Saoke 2011; Pradhan et al. 2017).

Likewise, the percentage of area under organic rice cultivation was separate from the farmer’s plan to scale up ORF (p = 0.392). In the context that household intentions are separated by experience, technique, and human resources, as discussed above, the reluctance of households to scale up OF implies that they may face certain obstacles or potential risks (e.g., selling price and output market). Concerning farm size, some studies found a negative association (Khaledi et al. 2010; Läpple and Kelley 2010; Läpple and Rensburg 2011; Malá and Malý 2013; Métouolé Méda et al. 2018; Liu et al. 2019), whereas others found a positive association with farmers’ decisions (Genius et al. 2006; Mwiathi 2008; Kafle 2011; Karki et al. 2011). For instance, Liu et al. (2019) and Pradhan et al. (2017) argued that large farms were more difficult to manage in terms of crops, inputs, and other support, resulting in fewer incentives for farmers to deal with these problems. Meanwhile, Läpple and Kelley (2010) and Läpple and Rensburg (2011) clarified that OF was more labor-intensive when dealing with pests, diseases, and marketing. Therefore, organic agriculture was more likely to be adopted in small farms managed by family laborers. Other researchers explained that it was often more challenging for small-scale farms to access credit, which led to a drop in adoption rates. However, the available evidence on farm size was inconclusive.

The results were similar for the non-farm job variables (p = 0.670). Due to the relatively low income from agricultural activities, many farmers engage in non-farm work during their leisure time. Several studies in Vietnam have demonstrated the importance of non-farm income in rural household income structures (Nguyen et al. 2021; Dinh et al. 2021; Phuong et al. 2022). Their findings also revealed that prioritizing off-farm jobs causes farmers to pay less attention to agricultural activities, such as implementing climate change adaptation measures (Ha et al. 2022). The results of this study also showed a similar trend: household heads with non-agricultural work tended to be less interested in expanding the area of ORF (B = − 0.169). However, this relationship was weak and statistically insignificant (p = 0.670). This result contradicts the findings of Sriwichailamphan and Sucharidtham (2014) and Liu et al. (2019) that extra income earned from non-agricultural sources increased the probability of farmers participating in OF. They further argued that income from non-agricultural sources was the basis for applying new technology.

Households’ intentions were not promoted by actively evolving in community-based organizations (p = 0.692). Actively participating in community-based organizations such as farmers’ unions and cooperatives was regarded as a factor driving farmers to adopt more advanced and sustainable agricultural production models because they had more opportunities to access scientific, technical, and market information, as well as gain more experience and skills from other active members (Vo et al. 2021). These organizations’ key members occasionally act as pioneers in implementing new production models and farming techniques. This is often regarded as a guarantee of the participation of other members and may be crucial for the initial stage when deciding to enter OF, but it was ineffectual in promoting scale-up in this study context. Previous studies found a positive association (Parra López and Calatrava Requena 2005; Mwiathi 2008; Karki et al. 2011; Sriwichailamphan and Sucharidtham 2014; Wollni and Andersson 2014; Singh et al. 2015; Lu and Cheng 2019), while only one study suggested a negative linkage (Mohamed Haris et al. 2018). Almost all articles implied that farmers from community-based organizations, such as agricultural associations, were more likely to adopt organic agriculture. They explained that group activities and knowledge shared by other organic farmers simplified information access, marketing, and achievement of product certifications. Additionally, membership in an agricultural association could increase bargaining power with commission merchants.

Effects of results and economic efficiency

Contrary to the above results, the model demonstrated the significant influence of variables related to results and economic efficiency. First, households’ intentions were influenced by the achievement of expected yield in previous crops (B = 2.042, p = 0.000). This was the most influential factor among the variables in the regression model. The farmers’ intention odds to expand ORF will increase 7.7 times with each additional level of satisfaction (OR = 7.702). Otherwise stated, the below-expectation yield of organic rice reduces farmers’ motivation to expand ORF. Some respondents stated that their family’s organic rice yield in the last year was approximately 260 kg/Sao (equivalent to 5.35 tons/hectare), close to 70% of the conventional cultivation model. This yield did not meet their expectations. Other households’ yields were even lower due to poor disease regulation. Similarly, farmers who had achieved the expected price for organic rice tended to have positive intentions for expanding organic farm areas, while the rest showed the opposite intentions. This result is statistically significant at p = 0.005 (B = 0.675, p = 0.025). With each higher satisfaction level, the farmers’ intention odds to expand ORF will increase approximately double (OR = 1.964). The below-expectation selling price dampened farmers’ motivation. The descriptive statistics results showed that up to 71.7% of the respondents were dissatisfied with the selling price (5-level Likert). The price varied among the study sites depending on the type of sale (free sale, agreement, or under contract) and contractors. Therefore, farmers’ satisfaction levels varied. For instance, the organic rice price in Phu Luong 1 Cooperative (Phu Luong Commune, Phu Vang District) for the winter-spring crop of 2021 was approximately 8000 VND/kg, only 500 VND/kg more than that of normal rice. Occasionally, the difference was only approximately 200 VND/kg. Meanwhile, organic rice in An Lo was sold by the cooperative (Phong Hien commune, Phong Dien district) at 10,000 VND/kg, approximately 2500 VND more than normal rice. Some farmers in Phu Luong complained that the organic rice price, which was already low in normal conditions, was even lower due to the difficulties experienced during the COVID-19 outbreak. It was not worth the effort their family put in. By underscoring the importance of economic output to farmers’ scaling intentions, this study reinforced the conclusions from the Netherlands, i.e., Ács (2006) and Kaufmann et al. (2011). Through a case study in the Netherlands, Ács (2006) concluded that OF remained economically attractive to producers despite difficulties in the conversion phase. Similarly, the investigation of Kaufmann et al. (2011) in Lithuania stressed that the main drivers of future in-conversions were related to economic and farm management reasons. However, some studies found that farmers still devoted more time to OF, despite their relatively low yields. The organic growers differed from their conventional counterparts in that their orchards were less productive and in the part-time nature of their dedication to agriculture (Parra López and Calatrava Requena 2005). Some studies concluded that profit and productivity were not the driving factors for adopting OF (Mohamed Haris et al. 2018).

Guaranteeing the output market for organic rice was also an important factor boosting the farmers’ intentions (B = 1.329, p = 0.000). With each higher level of satisfaction in guaranteeing the output market, the farmers’ intention odds to expand ORF will increase 3.778 times (OR = 3.778). The descriptive statistics showed that the average value of farmers’ assessment for the statement "consumption of organic rice is guaranteed" was relatively low (2.96). Accordingly, 41.2% of the informants expressed that the market guarantee was acceptable, whereas 31.7% were disappointed. This implies that the output market for organic rice in the study sites was uncertain, and this may be a barrier preventing households from expanding production. Consumption of organic agricultural products in Vietnam, in general, is facing many difficulties due to factors related to the distribution system and consumer habits and acceptance. Several enterprises and organizations at the study sites secured organic rice output through commitments with cooperatives or local authorities. However, most of these commitments were not highly binding and covered only a small part of the organic rice area. The low purchase price from these enterprises and organizations further discouraged farmers from expanding their production. Some offering acceptable prices, such as the An Lo cooperative (Phong Hien commune, Phong Dien district), faced many consumption hardships due to the COVID-19 pandemic’s impact, which narrowed the market. This delayed the retrieval of capital for re-investment. Since organic rice is not preserved, the quality will deteriorate over time; therefore, some households had to sell at a low price to reduce risks, while others waited for interventions from local authorities.

Effects of farmers’ awareness of organic farming

This study also examined the association between farmers’ awareness of ORF and their intention to scale up. Although farmers who appreciated the positive impacts of OF on the environment were more likely to expand farming, this connection was statistically insignificant (B = 0.318, p = 0.107). This result also implies that underestimating the effects of organic agriculture on improving the environment diminishes the incentive to expand farming to some extent. Organic agriculture has been shown to improve soil, water, air, and ecosystem quality through strict regulations regarding chemical usage. Previous studies have also shown that enhancing environmental quality encourages farmers to engage in OF. However, since OF improves the environment gradually, it is difficult for farmers to notice this change. This may reduce farmers’ confidence in this model and, thus, discourage their intention to scale up OF. Most previous studies unveiled a statistically significant affinity between farmers’ perceptions/awareness/attitudes of the environmental advantages of OF and their adoption (Genius et al. 2006; Koesling et al. 2008; Läpple and Kelley 2010; Kaufmann et al. 2011; Läpple and Rensburg 2011; Mohamed Haris et al. 2018). For instance, Kaufmann et al. (2011) suggested that OF is more environmentally friendly. Similarly, Koesling et al. (2008) noted that sustainable and environmentally friendly farming is the ultimate goal for organic farmers. However, this linkage was ambiguous in the context of this study.

In contrast to the above results, there is a statistically significant association between the perception of OF’s positive effects on family members’ health and the intention to expand the scale. Accordingly, the perception of the significance of organic agriculture for health increased the farmers’ intentions (B = 0.428, p = 0.024). With each higher level of satisfaction, the farmers’ intention odds to expand OF will increase about 1.5 times (OR = 1.534). As discussed, organic agricultural production must ensure the long-term management of resources (including soil, water, and air) according to systematic and ecological principles. Synthetic chemical materials are prohibited at all stages to avoid exposing people and the environment to hazardous chemicals, thereby minimizing pollution in the field and the surrounding environment. By limiting exposure to harmful chemicals, the health of workers directly involved in production can gradually improve. Regarding this, some farmers asserted that their family member’s health issues related to respiratory and skin diseases had been reversed since the restriction on the use of chemicals. They intend to expand the organic rice model to minimize these toxic chemicals. Our results are in agreement with the findings of Wollni and Andersson (2014), Ullah et al. (2015), Ma et al. (2017), and Nguyen et al. (2020). For instance, Wollni and Andersson (2014) revealed that farmers who associate sustainable practices with positive health effects are more likely to adopt organic practices. Nguyen et al. (2020) analyzed a dataset of factors influencing intentions for OF expansion in Vietnam and obtained similar results.

Another hypothesis of this study is that perception of the positive effects of OF on other farmers’ consciousness and adoption would encourage farmers to scale up. However, the results of the regression model contradict our hypothesis (B = 0.064, p = 0.758). About 45% of the respondents agreed with the following statement: “My OF promoted other farmers’ adoption.” A farmer in An Lo said that his sharing information about ORF had inspired other farmers to engage in this model. He believes that expanding production would increase other farmers’ awareness and belief in ORF. Although he acknowledges it is meaningful, this is not a reason for him to expand the farming area at present.

Influence of farmers’ belief in market prospects

Farmers’ beliefs about OF prospects were also considered predictors. The results show that anticipated market opportunities positively impact farmers’ intentions to scale up OF (B = 0.444, p = 0.041). With each higher belief level, the farmers’ intention odds to expand OF will increase roughly 1.5 times (OR = 1.559). Some farmers believe that consumers will extensively accept organic products as a future consumption trend. Scaling up OF at present is a way to seize this opportunity. Even in the event of market hardships, businesses may prioritize the output of organic rice products by farmers who have been associated with them for an extended period. This perspective is reasonable because Vietnamese consumers are increasingly turning to clean and safe agricultural products to mitigate health issues induced by insecure foods (Thang 2021). This is consistent with the Vietnamese government’s current green and sustainable agricultural development orientation (Vietnamese Government 2020). Contrary to the above result, farmers’ intentions were not influenced by their belief in government support (p = 0.885). The average value of farmers’ assessment for the statement “I believe in government support for organic agriculture” was only 3.43 on a 5-level Likert scale (see Table 2). This may imply that the government’s efforts to encourage the development of organic agriculture are currently less impressive and thus insufficient to motivate households to expand scale decisions. Although the government issued approval to the Organic Agriculture Development Scheme for 2020–2030 in June 2020, its support has been sparse as it mainly focuses on training in farming techniques and ensuring the supply of organic production inputs. Similarly, although the government of Thua Thien Hue Province has enforced several activities to connect farmers and enterprises under the value chain model, the scale of these linkages remains small and fragile.

Conclusion and policy implications

Organic farming is one of the Vietnamese government’s foremost priorities regarding sustainable agricultural development. However, the popularization of organic agriculture in Vietnam still faces many challenges, despite the implementation of many incentive policies. Understanding the factors driving farmers’ cultivation intentions could solve this issue. Therefore, this study investigated farmers’ intentions toward expanding ORF in connection with their demographics, expected farm and market performance, awareness of OF, and confidence in market prospects in Thua Thien Hue Province, Central Vietnam.

The binary logistic regression model results showed the underperformance of demographic characteristics (e.g., gender, age, education, number of laborers, OF experience, percentage of organic rice area, engagement in non-farm jobs, and active involvement in community-based organizations) in anticipating farmers’ intentions toward scaling up organic rice production. In other words, these characteristics are separate from the farmers’ intentions. Therefore, local authorities should not differentiate according to these characteristics when implementing incentives and interventions.

In contrast, the model indicates a greater influence of factors related to economic outcomes, farmers’ awareness of OF, and belief in the prospects of organic agriculture. Economic outputs, such as productivity, price, and the market, were decisive factors for farmers’ intentions to expand OF. Low yields and selling prices associated with an uncertain output market reduce farmers’ intentions to expand ORF. The lower yield of OF compared to conventional farming is inevitable because it resists chemical usage during farming. However, yields that are too low may also show limitations regarding farming techniques, such as pest and weed control. Therefore, local authorities should further strengthen technical training for farmers in combination with developing measures to strictly control the application of these cultivation techniques in organic rice fields. This result may also imply that the local government’s efforts and interventions to link organic rice products to the market are less effective. Although the local government has cooperated with several enterprises/organizations to sell products, the scale is still limited, and the price difference compared to conventional rice products is relatively low. This was one of the reasons for reducing the farmers’ motivation to expand the farming area. Therefore, boosting organic rice production linkages following the value chain model, which ensures the output market for the product at an appropriate price, may solve this problem. This is especially meaningful in the era of COVID-19, which challenges the consumption of agricultural products. In addition to enterprises in the province, local governments should actively seek and contract with those in other provinces and countries to expand and diversify consumers. To realize this task, more emphasis should be placed on product quality assurance, manufacturing process certification, and brand building and promotion. It is a fact that there is a demand for organic products but a lack of product information and sales spots. Although often shopping in small volumes, the number of individual customers is vast. Therefore, in addition to focusing on corporate customers, local authorities should also introduce and promote exhibitions, build appropriate distribution channels, and create online sales systems to reach individual customers in the domestic market.

The study also revealed that the positive effects of OF on farmers’ health motivated their intention to expand ORF. In other words, farmers appreciate the health benefits of reducing chemical use in organic agriculture. This is an essential point that policymakers should focus on to achieve the goal of scaling up ORF. Propaganda might be effective in this case; however, propaganda should be associated with sharing experiences with farmers to increase persuasion instead of solely conveying confusing scientific information. Besides, despite the statistically insignificant relationship in the model, propaganda can also integrate the significance of OF to improve environmental quality, such as soil, water, and air, in the long term, which also positively impacts public health.

The findings of this study also demonstrated the positive influence of belief in OF prospects on farmers’ intentions to scale up farming. Farmers who positively view the future of OF are more likely to expand their farming scale. Farmers’ views on organic markets may vary depending on the variety and accuracy of their acquired information. Therefore, to further develop this sustainable farming model, local authorities should focus on equipping farmers with market information to understand the trend of switching to this farming model globally and the increasing use of clean and safe agricultural products by consumers. In addition to reports from experts, local authorities can launch contests on market trends and organic agricultural product consumption among farming communities to increase communication effectiveness. Moreover, related to farmers’ beliefs, this study did not find a statistically significant relationship between government support and the farmers’ intentions. This finding implies that government support is insufficient to encourage people to expand farming. Therefore, the government and local authorities should consider diversifying and actualizing policies, support, and interventions to incentivize farmers to scale up organic rice production.

The above suggestions are proposed based on the specific contextualization of organic agricultural production, the market, and the characteristics of farmers in Thua Thien Hue province, Central Vietnam. Thus, applying these suggestions in other geographical areas (e.g., other provinces or regions) requires flexibility based on thorough consideration of differences in, for instance, cultural peculiarities, market characteristics, farmers’ awareness, level of access to market information, and current incentives of local authorities, etc. to achieve the target.

Limitations of the study

This study was conducted during the COVID-19 outbreak in many countries, including Vietnam. Although this context contributed to identifying gaps in the implementation of product offtake contracts between farmers/cooperatives and enterprises, the context also led to limitations in the study. During the COVID-19 pandemic, economic activities, including the production and consumption of organic agricultural products, were severely affected due to the disruption of supply chains in the domestic and international markets. Government support for OF was also limited as the government had to share financial and human resources to restore other economic sectors. Although this study considered farmers’ intentions toward scaling up organic rice areas after they had experienced the organic model for several years, it was difficult to avoid the adverse effects of the COVID-19 pandemic at the time of the interviews. Some consequences of the COVID-19 pandemic on farmers’ psychology included the purchasing power of both individual and corporate customers decreasing, prices of high-quality agricultural products falling, agricultural offtake contracts being canceled, and government support policies/activities for organic agriculture being disrupted. We acknowledge the limitations of this study caused in the context of the COVID-19 pandemic and recommend that further studies integrate external factors that potentially affected informants’ psychology at the time of the survey. In addition, since this study was conducted in a limited geographical area in Thua Thien Hue province, applying this study’s results to other geographical regions requires flexibility and thorough consideration of differences in agricultural production contexts, market characteristics, farmers’ characteristics, and other relevant factors.

Funding

This work was partially supported by Hue University under the Core Research Program, Grant no. NCM.DHH.2022.11.

Data availability

The datasets analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All procedures performed in participatory human studies were obtained with the informed consent of the participants and were in accordance with ethical research standards. This article does not contain any studies involving animals performed by any authors.