However, there is still limited information regarding the factors influencing the adoption of modern rice varieties by farmers and the economic impact of this adoption across different l
Introduction
Rice is a crucial cereal crop that supports over half of the global population, playing a vital role in economic stability and poverty reduction in developing countries However, environmental challenges such as pollution, deforestation, and urbanization are adversely affecting agricultural yields To combat these issues, adopting innovative agricultural technologies is essential for enhancing sustainable farming practices, boosting rural household welfare, and improving productivity while minimizing resource use Modern rice varieties can increase land efficiency, improve ecological landscapes, and address food insecurity Nonetheless, effective implementation of these technologies requires significant time and education efforts to raise awareness among farmers Understanding farmers' preferences and behaviors is key to the successful adoption of improved rice varieties.
Numerous studies have demonstrated that household factors influence the adoption of modern rice varieties (Bannor Ct al., 2020; Bello et al., 2021; Wang et al.,
Research indicates that household-level factors, such as education, machinery ownership, cultivated land area, access to credit, and labor experience, significantly influence the adoption of modern rice varieties (Akinnagbc & Akinbobola, 2022; Qi et al., 2021; Tiongco & Hossain, 2019) Additionally, local factors like the availability of agricultural services, supportive policies, and effective marketing systems positively affect this adoption (Mariano et al., 2012; Rahman, 2003; Wang et al., 2020) However, findings regarding the impact of farm size on the adoption of new rice varieties are inconsistent; while some studies report a positive correlation (ỌÍ et al., 2021), others suggest a negative relationship (Zakaria et al., 2020).
Recent studies have significantly advanced agricultural production by providing insights into household factors, agricultural management, and the roles of government and NGOs This comprehensive approach facilitates the development of effective support policies for sustainable agriculture across various regions However, gaps remain in the research, including challenges related to data accuracy and incomplete analyses of factors influencing technology adoption in agriculture To address these issues, our focus is on the "Determinants of Adoption of Modern Rice Varieties," exploring the economic and social factors that influence farmers' decisions to adopt these innovative rice varieties in their agricultural practices.
Vietnam serves as a significant example for examining the household factors that influence the adoption of modern rice varieties Transitioning from a poor nation, Vietnam has achieved national food security and emerged as one of the world’s largest rice exporters, with production increasing more than threefold Approximately two-thirds of its 96 million population is engaged in agriculture, utilizing around 4 million hectares of land Despite this progress, many farmers cultivate rice on a small scale and struggle to generate sufficient income for their daily needs Furthermore, numerous rice varieties are susceptible to weather fluctuations and environmental challenges, leading to decreased yields and crop failures.
2012) This serious problem requires rice breeders to develop a strategy for creating modern rice varieties, combined with flexible responses to new conditions and practices (Sebcsvari et al., 2011; Wassmann et al., 2004).
This study utilizes commune-level data from the Vietnam Household Living Standards Survey (VARHS) to analyze the impact of household factors on the adoption of modern rice varieties It significantly contributes to agricultural production literature by offering insights into the determinants influencing household decisions regarding modern rice adoption Employing various experimental models, the research addresses inconsistencies and biases, enhancing the accuracy of findings and reinforcing the authors' conclusions Additionally, to mitigate the limitations of cross-sectional data, the study incorporates panel data from VARHS collected in 2014 and 2016, allowing for the detection and measurement of statistical effects that cross-sectional analyses may overlook.
This paper is structured to first explore the analytical framework surrounding the factors that affect the adoption of modern rice varieties, highlighting existing research gaps It then details the regression models utilized and describes the data in Section 3 Following this, Section 4 analyzes the results and presents key findings Finally, the conclusion offers policy implications based on the research outcomes.
Literature review
Concepts
Rice is a vital agricultural crop in developing countries, covering about 19% of harvested land and contributing 20% of energy intake from major food sources It represents up to 50% of food expenditure for low-income individuals, underscoring its essential role in their diets Additionally, rice is one of the most nutritionally valuable cereal crops globally and serves as a staple food in many African nations, significantly shaping the dietary habits of their populations.
Modern rice varieties have been developed through extensive research by scientists and breeders at prominent institutions like the Bangladesh Rice Research Institute and the International Rice Research Institute These varieties exhibit genetic diversity and are engineered for high yields, featuring short growth durations and enhanced productivity, which can greatly improve operational efficiency in rice cultivation.
The Green Revolution led to remarkable advancements in agricultural productivity and income through the use of high-yielding rice varieties and modern agricultural inputs, significantly aiding in the fight against hunger and enhancing global food security However, the increasing severity of climate change, characterized by extreme weather events like droughts, floods, and salinity intrusion, presents serious challenges to traditional rice cultivation Therefore, it is essential to research and assess the effectiveness of drought-tolerant, flood-resistant, and salt-tolerant rice varieties to ensure sustainable rice production in the face of these climatic adversities.
Disseminating information about improved rice varieties from experienced farmers to their peers is vital for encouraging adoption, as highlighted by Ashoori et al (2019) Financial support for low-income farmers significantly enhances the uptake of these varieties, ultimately boosting their productivity and income Additionally, understanding and addressing farmers' preferences and needs is crucial for the successful implementation of improved rice varieties in real-world settings.
Findings
A study by Dariush Ashoori and colleagues (2019) in Northern Iran examines the link between economic profit and the adoption of improved rice varieties The findings emphasize that factors such as technology tailored to farmers' needs, farming experience, livestock quantity, and farm income significantly encourage the adoption of these enhanced rice varieties.
A study conducted in 2012 explored the factors affecting the adoption of modern rice technologies in the Philippines, highlighting the importance of education level, ownership of machinery, size of cultivated land, irrigation capacity, access to credit, and activities that boost profitability The findings emphasize the crucial role of support mechanisms and knowledge transfer in facilitating the adoption of these technologies Furthermore, the research identifies agricultural extension services as vital for increasing acceptance rates among farmers.
Research on the adoption of New Rice for Africa (NERICA) varieties in West Africa highlights the significance of social networks and connections with agricultural agencies in raising awareness, while structural factors such as farm organization, asset ownership, and technical support play a crucial role in actual adoption (Diagne et al., 2012) A study by Wang et al (2012) utilized a probit model to analyze adoption rates and revealed that demographic characteristics, land size, access to markets and seeds, crop models, and planting locations influence the differences in adoption among households Additionally, a Tobit model was used to assess the intensity of adoption, indicating that factors like farm scale, land size, irrigation, and location are vital in determining both the rate and extent of adoption of modern rice varieties.
Research by Tiongco and Hossain (2019) indicates that adopting improved rice varieties leads to a decrease in varietal diversity on farms This supports the idea that the cultivation of these varieties reduces crop diversity, as their superior agronomic traits, such as higher yields and better pest and disease resistance, lower production risks Furthermore, farmers' education plays a vital role in rice varietal diversity, as it affects their access to information about modern rice varieties Educated farmers are better equipped to make informed choices among various improved rice options, highlighting the importance of developing effective information campaigns to enhance the adoption rates of new varieties.
In summary, the adoption of modern rice varieties in rural Vietnam is influenced by multiple factors at the farm, household, community, and policy levels Research also reveals an inverse relationship between the adoption of improved rice varieties and varietal diversity Gaining insight into these factors is essential for developing effective intervention policies and strategies to promote the widespread use of modern rice varieties.
Methods
Numerous studies have investigated the factors influencing the adoption of modern rice varieties, utilizing various datasets from rural household surveys For instance, Duong et al (2021) employed panel data from the Vietnam Access to Resources Household Survey (VARHS) conducted in 2012 and 2014, ensuring that all sampled households were re-surveyed to create a comprehensive dataset Similarly, Ashoori et al (2019) analyzed data from the Rice Farming Household Survey (RBFHS), which has been conducted every five years since 1996, covering 30 provinces that account for 70% of Iran's rice production In Cambodia, Wang et al (2012) focused on household-level data that included economic and social aspects of rice cultivation, while Tiongco & Hossain (2019) utilized a dataset from the International Rice Research Institute and the Department of Agricultural Extension in Bangladesh, comprising 14,095 farmer households Ghimire et al (2015) gathered data from a survey in central Nepal, employing a multi-stage random sampling procedure to select districts and households, with respondents being those who directly managed the farms.
Previous studies on the adoption of modern rice varieties utilized various statistical methods, including random sampling and regression models, to analyze the relationship between independent variables and adoption rates Binary models enable a focused examination of farmers' decisions regarding specific technologies, offering insights into the characteristics of adopters (Burton et al., 1999; Zhou et al., 2008) Probit and Tobit regression models were employed to assess the impact of adopting modern varieties, as demonstrated in research conducted in Bangladesh (Tiongco & Hossain, 2019) In Yunnan, China, a stratified random sampling method and Tobit models were used to analyze adoption levels, while the Propensity Score Matching (PSM) technique helped mitigate self-selection biases (Wang et al., 2020) Descriptive statistics and the Mann-Whitney test were applied in a study of small-scale producers in northern Iran to compare adopters and non-adopters, complemented by logistic regression to explore the relationship between variables (Ashoori et al., 2019) Furthermore, a two-hurdle approach was utilized in Vietnam to investigate the decision-making process of farmers, distinguishing between adopters and non-adopters, and measuring the intensity of adoption through various metrics, including expenditure on agricultural inputs and area planted with modern varieties (Duong et al., 2021; Phimister & Roberts, 2006; Asfaw et al., 2012; Mason & Smale, 2013; Shiferaw et al., 2008).
In analyzing the factors influencing the adoption of modern rice varieties, both fixed effects models (FEM) and random effects models (REM) have been utilized, as demonstrated in a study on agricultural technology adoption in Ethiopia (Asfaw et al., 2012) The key distinction between these models lies in their assumptions: FEM posits that unobserved characteristics of subjects remain constant over time, while REM assumes these characteristics are random and can vary FEM is appropriate when subjects are believed to share similar functional traits, whereas REM is favored when there are significant differences among subjects (Borenstein et al., 2021) Importantly, when data is drawn from independently conducted studies, the assumptions of FEM may not hold, making REM a more suitable choice Previous research has underscored the significance of REM in accurately estimating average effects across different studies on specific topics (Brockwell & Gordon, 2001).
Research gaps
Despite numerous empirical studies on factors influencing the adoption of modern rice varieties globally, there is a notable lack of research focused on Vietnam (Ashoori et al., 2019; Bannor et al., 2020; Bello et al., 2021; Wang et al., 2020) Most existing studies in Vietnam tend to be theoretical or qualitative, often employing ordinary least squares models to evaluate household decisions regarding improved rice varieties This approach may yield biased and inconsistent estimates due to the influence of endogenous factors within the model Additionally, many studies rely on cross-sectional data, which introduces limitations such as selection bias, recall bias, and an inability to establish temporal relationships between outcomes and exposure levels, as both are assessed simultaneously (Dag s Thelle and Petter Laake, 2015).
This research offers valuable insights into the factors that influence households' decisions to adopt modern rice varieties To enhance the reliability of our findings, we utilize various econometric models, including the least squares and probit models, addressing inconsistencies and biases in previous research This comparative analysis strengthens the implications and conclusions drawn Additionally, by employing panel data from the Vietnam Access to Resources Household Survey (VARHS) for the years 2014 and 2016, we overcome the limitations of cross-sectional data The use of panel data provides richer information and allows for the detection of statistical effects that traditional cross-sectional analysis may overlook.
Research models and Hypothesis development
Research on the adoption of modern rice varieties in agriculture identifies several influencing factors, primarily categorized into three groups: household characteristics, production management, and soil characteristics (Khandker et al., 2009).
Household characteristics significantly influence the adoption of modern rice varieties The education level of the household head plays a crucial role, as it reflects their understanding of the advantages associated with these varieties Additionally, factors such as age, gender, and household size are relevant, as they affect the household's capacity to manage and effectively implement the use of modern rice varieties.
Poverty, self-employment, and geographic location significantly influence households' ability to adopt modern rice varieties Economically disadvantaged households often lack the financial resources necessary for this transition, whereas those engaged in non-agricultural self-employment typically possess better financial stability and management skills, enabling them to select modern rice varieties more effectively Additionally, geographic factors can pose challenges in accessing and transporting these varieties, further impacting adoption decisions.
Production management factors significantly influence the adoption of modern rice varieties Access to formal loans enhances financial conditions, enabling farmers to select these improved varieties (Kassic et al., 2011; Langyintuo & Mungoma, 2008) Additionally, ownership of production tools, such as plows and rice harvesters, plays a vital role; households with plows can achieve greater labor efficiency and reduced labor demands, facilitating the choice of modern rice varieties Likewise, owning rice harvesters boosts productivity and lowers production costs, creating a favorable environment for adopting these advanced agricultural options.
The characteristics of cultivated and irrigated land significantly influence the choice of modern rice varieties Studies indicate that households with larger cultivated areas are more likely to select modern rice varieties to maximize production potential Additionally, the presence of local irrigation programs plays a crucial role, as access to irrigation water is vital for cultivating these varieties Furthermore, the distance from home to the main road can affect decisions, with longer distances potentially increasing transportation costs for modern rice varieties.
In summary, the adoption of modern rice varieties by farmers is significantly influenced by household characteristics, production management, and soil conditions To evaluate the impact of these factors, we utilize three regression analysis methods—Probit and Ordinary Least Squares (OLS)—analyzing the VARHS dataset along with the dependent variables outlined in Table 1.
Figure Ì The theoretical framework offactors affecting the adoption of modern rice varieties
Variable used for empirical analyses
Because this study uses a probit model to determine the factors influencing the adoption of modern rice varieties by households, the research is divided into two sets of variables.
Households that cultivate at least one type of modern rice variety, including those developed in China and Vietnam, as well as local and regional improved varieties, are considered adopters of modern rice varieties.
Households that do not adopt modern rice varieties typically cultivate only traditional or local varieties, or may not cultivate rice at all This analysis relies on data collected from the 2014 survey to understand the characteristics of these households.
The adoption decision of improved agricultural varieties is influenced by various explanatory variables, including the characteristics of the household head—such as education, gender, and age—demographic factors like ethnicity, labor force participation, non-agricultural employment, cultivated area, and irrigation practices, as well as village, commune, and regional characteristics, including location, infrastructure, and proximity to main roads Additionally, weather conditions play a significant role in this decision-making process (Bannor et al., 2020; Bello et al., 2021; Duong & Thanh, 2019; Mariano et al., 2012) After reviewing relevant literature and available data, we identified specific explanatory variables for inclusion in our model, as detailed in Table 1, which outlines definitions, measurements, and statistical descriptions of these research variables.
Table I Variables used to construct the model
Source: Own calculations based on survey data.
Variables Definition and measurement Mean S.D.
1 if household adopts any modern rice varieties in the previous survey, 0 otherwise
Education Education of household head (Grade completed) 4.130 1.733
Age Age of household head (Years) 2.849 1.739
Gender 1 if male-headed household, 0 otherwise 0.396 0.489
Household size Number of household members 0.579 0.494
Adults Number of working-age members (15-60 years old) 0.465 0.499
Ethnicity 1 if Kinh (majority) ethnicity, 0 otherwise 0.216 0.412 Poverty status 1 if poor household, 0 otherwise 0.277 0.447
Self-employment 1 if household is involved in off-farm sclf-cmploymcnt activities, 0 otherwise 0.084 0.277
Red River Delta 1 if household is located in Red River
1 if household is located in Northern Midlands and Mountains, 0 otherwise 0.138 0.345
North Central 1 if household is located in North Central,
South Central Coast 1 if household is located in South Central
.1 1 if household is located in Central „
Total area of cultivated land (ha) Total area of irrigated cultivated land (ha)
1 if commune where household resides has any irrigation program, 0 otherwise
Distance from home to All weather road (km)
1 if household has any formal Ioans used for production, 0 otherwise
1 if household owns a tractor, 0 otherwise
1 if household owns a grain harvest machine, 0 otherwise
Methodology
Probit regression
The research aims to assess the factors influencing the adoption of modern rice varieties among rural households Utilizing a probit regression model, the study will estimate the likelihood of adopting improved rice varieties, drawing on insights from previous empirical studies (Bello et al., 2021; Duong & Thanh, 2019; Ghimire et al., 2015; Mariano et al., 2012).
1997) and (Verbeek, 2008), the probit model takes the following form:
The function G(z) ranges from 0 to 1, where 0 represents the standard normal probability density function In this context, z is a vector of variables, and f denotes the standard normal cumulative distribution function (Bello et al., 2021).
The estimated probit model is presented below:
The decision to adopt modern rice varieties is represented by the latent variable y*, while Y' denotes the observed adoption outcome for each household The matrix of explanatory variables, X, encompasses household, land, and management characteristics The estimated parameters are indicated by p, and ci represents the error term in the model.
With the aim of the research, the model is developed as follows: p{xlm,) = ^KoJ = “ + I^ZOM ®
In our study, Di indicates the adoption of modern rice varieties by household i, focusing on the factors that influence this adoption among rural households based on surveys conducted in 2014 and 2016 The binary variable is coded as 1 if a household utilized any modern rice varieties during these years A detailed discussion of all variables used in the analysis will follow in the next section.
Ordinary Least Squares
The study employs both the Probit model and Ordinary Least Squares (OLS) model to assess the influence of various factors on rural households' decisions to adopt rice varieties in Vietnam The OLS model is specifically designed to quantify these impacts effectively.
The adoption status of modern rice varieties by household i is indicated by Previous_adoption, while X represents a set of independent variables that influence this dependent variable Our research aims to identify the factors affecting the adoption of modern rice varieties among rural households based on surveys conducted in 2014 and 2016 A binary variable will be assigned a value of 1 if households utilized any modern rice varieties during these years A detailed discussion of all variables used in the analysis will follow in the next section.
This study conducts empirical analysis using data from the Vietnam Access to Resources Household Survey (VARHS) for 2014 and 2016 Developed collaboratively by the University of Copenhagen and Vietnamese institutions, VARHS is a comprehensive household survey that offers in-depth information on key demographic and socio-economic characteristics of rural households The survey covers various aspects, including household characteristics, agricultural inputs and outputs, non-agricultural activities, resource endowments, economic activities, and social welfare.
Table 2 Distribution of samples by adoption status and year
Source: Own calculations based on survey data.
Base-line (2014 survey) survey) Total
To effectively evaluate the factors influencing the adoption of modern rice varieties, the research focuses exclusively on households engaged in rice cultivation A balanced panel dataset was achieved by excluding households with incomplete data from both years, resulting in a final sample of 5,332 farming households This sample comprises 3,959 households that have adopted modern rice varieties and 1,373 that have not, allowing for a comprehensive analysis of adoption trends over the years.
2014 and 2016 is presented in Table 2.
Table 3 The descriptive statistics of the sample data
Source: Own calculations based on survey data.
Full sample Adopters Non-adopters
In the binary data model, explanatory variables are categorized into three main groups: household characteristics, plot characteristics, and management characteristics Summary statistics of the sampled households involved in the study are detailed in Table 3.
The analysis indicates that there are minimal differences in household characteristics between adopting and non-adopting households, with a slightly higher proportion of male household heads among adopters The average age of household heads is 61 years for adopters and 62 years for non-adopters, suggesting that most surveyed farming households are not in their productive working age Education levels are generally average, with most farmers having 8 to 9 years of formal education, which corresponds to lower secondary school Notably, the adopting group exhibits a higher education level compared to the non-adopting group Additionally, the average household size is around four members, with three working-age members in the adopting households.
2 members in the non-adopting group.
Cultivated land area significantly influences the adoption of improved agricultural varieties, with adopting households averaging 51.37 acres compared to just 14.01 acres for non-adopting households Larger land holdings enable farmers to manage the risks associated with technology failure by dedicating only a portion of their land to new varieties, a strategy less feasible for those with smaller plots (Mariano et al., 2012) Additionally, access to irrigation is crucial; adopting households typically have greater irrigated land and better access to irrigation programs Modern varieties often require well-irrigated conditions, prompting adopting households to prioritize irrigation (Duong & Thanh, 2019) Effective irrigation systems enhance water retention and soil fertility, while also reducing the negative effects of climate shocks, thereby fostering an environment conducive to the adoption of innovative agricultural technologies (Duong & Thanh, 2019).
Results and Discussion
Variable Probit regression OLS regression
Table 4, Ordinary Least Squares and Probit estimation
Source: Own calculations based on survey data.
Househ old ch ar act eristics
Age of household head (years) -0.0009 -0.45 -0.0002 -0.60
Gender of household head (1 Male, 0 otherwise) 0.191*** 3.65 0.045*** 3.54
Ethnicity (1= Kinh majority ethnicity, 0 otherwise) -1.016*** -13.25 -0.288 -11.95 Poverty status (1 = Poor, 0 otherwise) 0.854*** 10.82 0.215*** 8.96
Red River Delta (1 = Yes, 0 otherwise) 0.587*** 7.94 0.130*** 7.37
South Central Coast (1 = Yes, 0 otherwise) 0.252*** 3.26 0.062*** 3.29
Distance to All weather roads (km) -0.002 0.596 -0.0004**
Tractor (1 = Yes, 0 otherwise) 0.273* 1.73 0.050 1.30 Grain harvest machine (1 = Yes, 0
Note: * **, and *** are significance levels at 10%, 5%, and 1%), respectively.
Table 4 highlights the estimated effects of various factors influencing the adoption of modern rice varieties, utilizing Probit regression and Least Squares Variance methods The Probit model demonstrated a predictive accuracy of 80.93%, while the OLS model achieved 79.48%, showcasing their effectiveness in predicting the adoption of improved rice varieties among households Researchers opted to base their conclusions on the Probit model due to its superior accuracy and alignment with the research objectives The findings reveal that numerous variables significantly affect the adoption of modern rice varieties, with diverse and varied impacts.
Table 4 displays the estimates from the Ordinary Least Square (OLS) model and the Probit model, highlighting that factors such as educational level, gender of the household head, distance, non-agricultural activities, cultivated land, irrigated land, rice harvesters, and regional variables significantly influence the adoption of modern rice varieties among rural households in Vietnam.
Educational level significantly influences the adoption of modern rice varieties in rural households, with OLS and Probit models showing positive coefficients of 0.0042 and 0.0162, respectively, at a 10% significance level Households with higher education are more likely to research and utilize imported or hybrid rice varieties compared to those with lower education levels This finding aligns with Mariano et al (2012), which identified formal education as a crucial factor in adopting agricultural technologies in the Philippines, and Bello et al (2021), who noted that more educated farmers are more inclined to embrace new rice varieties The ability of educated farmers to access, process, and interpret information effectively contributes to this trend.
At a significance level of 10%, the coefficients for the Gender variable in both OLS and Probit models were 0.0448 and 0.01914, respectively, demonstrating a positive influence on the adoption of modern rice varieties among rural households in Vietnam This indicates that male-headed households are more likely to utilize modern rice varieties compared to others These findings align with previous research by Bello et al (2021) and Duong & Thanh (2019) In contrast, Feyisa (2020) reported a negative average impact of Gender on the adoption of modern rice varieties, though this effect was deemed insignificant.
The poverty status of rural households significantly hinders the adoption of modern rice varieties, with a notable coefficient of -0.854 indicating an 85.4% decrease in adoption likelihood for households classified as poor by local authorities Limited income restricts access to essential resources, such as tractors, harvesters, and quality seeds, necessary for implementing improved rice cultivation Furthermore, poverty hampers access to education and information, preventing these households from recognizing the advantages and productivity potential of modern rice varieties over traditional ones Additionally, the financial vulnerability of poor households makes them reluctant to invest in modern rice varieties, which often involve higher initial costs and increased risks.
Therefore, it is not encouraged for farmers who are struggling with poverty to adopt modern rice varieties.
Self-employment significantly influences the adoption of modern rice varieties in rural households, as evidenced by OLS and Probit model coefficients of 0.037 and 0.016 at a 1% significance level This indicates that increased engagement in non-agricultural activities enhances the likelihood of adopting these varieties Supporting this finding, Akinnagbe & Akinbobola (2022) highlighted similar results, while Wang et al (2020) demonstrated that adopting modern rice varieties positively impacts total income, with non-agricultural income facilitating the use of hybrid rice.
Cultivated land significantly influences rice production, with a positive coefficient of 0.00035 at a 10% significance level in both OLS and Probit models Larger landowners can mitigate technology failure risks by selectively adopting improved rice varieties, a strategy less viable for smaller landholders (Mariano et al., 2012) Additionally, modern rice variety adoption necessitates well-irrigated land; our findings show that a 1-hectare increase in irrigated land boosts the likelihood of rural households using improved varieties by 3.5% (Duong & Thanh, 2019) This aligns with Mendola (2007), who emphasized that better soil quality and a higher proportion of irrigated land facilitate adoption Amid escalating climate change challenges, including floods and droughts, greater access to irrigated land can help Vietnamese households minimize crop failure risks while promoting the use of modern rice varieties.
The analysis revealed that distance negatively affects the adoption of modern rice varieties among rural households Specifically, the OLS regression model showed a coefficient of -0.002 at a 10% significance level, while the Probit model indicated a coefficient of -0.004 at a 1% significance level This suggests that greater distance from the main road, particularly a well-constructed highway, reduces the likelihood of adopting these varieties This finding aligns with Feyisa (2020) but contrasts with earlier studies by Admassic & Ayclc (2010) and Hagos & Zcmcdu (2015), which reported a significant impact of distance on agricultural technology adoption One possible explanation for this discrepancy is that households located farther from the main road may operate larger farms, enabling them to utilize diverse technologies.
The ownership of tractors significantly influences rural households' decision to adopt improved rice varieties, with a coefficient of 0.273 indicating a 27.3% increase in the likelihood of adoption at a 10% significance level This finding aligns with previous research by Mariano et al (2012) and Rahman (2003) In Vietnam, farmers who possess rice production machinery, such as tractors, typically have larger land holdings and enhanced production capabilities, making them more inclined to embrace modern agricultural technologies, including advanced rice varieties.
Conclusions
Vietnam has shifted from a centrally planned economy to a market-oriented one, leading to increased access to modern rice varieties that enhance productivity and resilience to environmental changes The adoption of these varieties not only benefits farming households economically but also boosts overall agricultural productivity and ensures food security However, challenges such as limited information access, financial constraints, and inadequate policies and infrastructure hinder this adoption It is essential to understand the factors influencing the adoption of modern rice varieties in rural Vietnam to foster a sustainable agricultural sector and meet the country's growing food demands Current research lacks a comprehensive analysis of these factors, necessitating further evaluation to better understand the benefits and challenges faced by farmers.
This study analyzes the factors influencing the adoption of modern rice varieties in rural Vietnam through detailed household surveys The research aims to enhance understanding of the adoption process and its economic impacts on farming households Utilizing a probit or logit model, the study estimates the likelihood of adopting improved rice varieties by examining the relationship between this adoption (dependent variable) and various influencing factors (independent variables) within the rural Vietnamese context Key determinants include income, education, access to information, and policy support, which collectively inform the probability of a farming household adopting modern rice varieties.
Research findings reveal that various factors significantly influence the adoption of modern rice varieties, with notable differences in their effects Male household heads, individuals from non-Kinh ethnic groups, and those with higher education levels are more likely to adopt improved rice varieties Additionally, larger cultivated land areas and access to irrigation and agricultural machinery, like tractors, enhance adoption decisions Conversely, poverty emerges as a major barrier to adopting these improved varieties Other factors, including the gender, age of the household head, and household size, show minimal or no significant impact on the adoption process.
The findings of this article highlight several key policy implications essential for sustainable agricultural development in Vietnam Firstly, enhancing education and training for rural residents is vital, as it empowers farmers to adopt modern rice varieties and advanced agricultural techniques through organized training courses and knowledge-sharing networks Secondly, effective land differentiation and management policies are necessary to protect agricultural land and facilitate the adoption of modern practices Thirdly, financial support, including favorable loan programs, is crucial for enabling farmers to invest in high-yield, drought-resistant rice varieties Additionally, robust land management strategies are needed to minimize risks associated with water shortages and nutrient-deficient soils, requiring investments in irrigation and fertilization technologies Finally, implementing environmental and climate management policies will help farmers adapt to climate change and promote sustainable farming methods Collectively, these policies can foster the adoption of modern rice varieties and ensure the sustainability of agricultural practices.