Agricultural Mechanization Services Research Articles

PURCHASE CHANNEL SELECTION OF AGRICULTURAL MACHINERY BY WHEAT AND BARLEY FARMERS IN IRAQ: A TRANSACTIONS COST ATTITUDE

This study was aimed to identify the role of transaction costs and their attributes in the selection of markets for the purchase of agricultural mechanization services in Baghdad province. To achieve this goal, a random sample of 150 wheat and barley farmers in the province was selected, and the data was collected through a questionnaire form prepared for this purpose. The research was based on the transaction cost theory as a modified theoretical framework to explain the farmer's behavior towards choosing installment market channels to buy agricultural machinery and through the analysis of the binary logistic regression model. The results of the regression analysis showed that some elements of transaction cost, such as a privacy and uncertainty, have an important role in determining and choosing the installment market for the purchase of tractors, while the element of the number of repeat transactions proved its important role in choosing the installment market for seeders, and the time saving element showed its important role in choosing the installment market for combine harvesters. The results also showed the existence of significant differences in some demographic and economic characteristics related to farmer, such as farmer experience, farm area and net farm income, in influencing the respondents' decision towards choosing the markets for agricultural machinery transactions referred to above.

Being a happy farmer: Technology adoption and subjective well-being

This paper empirically investigates the impact of technology adoption on farmers’ subjective well-being, as measured by happiness and life satisfaction. A theoretical framework is constructed to link farmers’ subjective well-being to technology adoption, with a particular emphasis on mechanization services in agricultural production. By fitting a nationally representative panel dataset – China Family Panel Studies – into an endogenous switching regression model that addresses potential selection bias, we find that technology adoption leads to a 0.194 standard deviation increase in happiness and a 0.065 standard deviation increase in life satisfaction. Further analysis reveals that the effect is more pronounced for individuals engaged in off-farm employment and varies across farm sizes. To underpin the causal effect, we test three plausible mechanisms – absolute income, relative income, and leisure – which are well-documented in the literature for their correlations with happiness and life satisfaction. Our empirical analysis indicates that the adoption of agricultural mechanization services indeed increases the absolute income of farmers and allows them to allocate more time to leisure activities.

Financial Support for Agriculture, Agricultural Mechanization Service and Agricultural Economic Development -- An Empirical Study Based on Provincial Panel Data

Financial Support for Agriculture, Agricultural Mechanization Service and Agricultural Economic Development -- An Empirical Study Based on Provincial Panel Data

The Scaling-up of Agricultural Mechanization Services and the Re-shaping of Small-Scale Household Farming in China

Abstract Taking the case of the agricultural mechanization service industry as an example, this study discusses the dynamics of the transformation of China’s agricultural contracting service industry in the context of the scaling-up of agricultural production, and how the transformation is reshaping small-scale household farming in grain production. With the accelerated growth of farmland transfer, large-scale agricultural producers have been emerging rapidly in different parts of China in the past years. Since their demand for agricultural contracting services is different from that of small-scale household producers, the scaling-up of agricultural production has promoted the scaling-up of agricultural contracting services. Meanwhile, the capital surplus in the agricultural machinery manufacturing industry has created three consequences simultaneously: the excess supply of agricultural mechanization services, the acceleration of agricultural machinery renewal, and the rising cost of machinery purchases. The interactions of these three factors not only raised the threshold of the agricultural machinery service industry, which makes it difficult for part-time service providers to survive market competition, but also shortened the time window for machinery service provision, which makes it difficult for large-scale agricultural producers to balance land operation and machinery service provision. Consequently, large-scale agricultural machinery service organizations are continuously replacing those small-scale part-time service providers. During this process, small-scale household producers engaged in grain production are faced with increasing risks of being excluded from farming, both directly and indirectly, as it is difficult for small producers to deal with large service organizations, and the small-scale part-time service providers that used to serve them are continually being replaced.

Adoption mode of agricultural machinery and food productivity: evidence from China

Many researchers argue that the adoption of agricultural mechanization services (AMSs) is an important way for smallholder farmers in China to engage in modern agricultural production. However, the impact of the adoption mode of agricultural machinery on food productivity remains under-analyzed. We investigate the links between the adoption mode of agricultural machinery and food productivity using data on 795 grain farmers collected from the North China Plain. The results indicate that, compared with service outsourcing (SO), self-purchase (SP) improves the technical efficiency of farms; however, it reduces the input efficiency of agricultural machinery. The channel of the effect is that, although SO can reduce the redundancy of agricultural machinery's input, the opportunistic behavior of AMS suppliers and labor supervision problems lead to a decline in agricultural machinery's operation quality. The impact of the adoption mode of agricultural machinery on food productivity is asymmetrical among different types of farmers. Large-scale and professional farmers benefit more from SP, whereas small-scale and part-time farmers benefit more from SO. The AMS is not perfect, and the Chinese government should pay close attention to the loss of technical efficiency in agricultural production caused by the opportunistic behavior of AMS suppliers. Therefore, it is necessary to adjust the agricultural machinery subsidy policy and reduce the transaction cost of AMS.

The role of agricultural mechanization services in reducing pesticide input: promoting sustainable agriculture and public health.

An increasing amount of pesticide input is posing a serious threat to the environment and public health. However, the quantitative analysis of the impact of agricultural mechanization services (AMS) on reducing pesticide input is not yet clear. In this study, the impact of AMS on pesticide input was estimated by using the Chinese Family Database and the endogenous switching regression model. Subsequently, testing the robustness of the model using the substitution variable method. The impact of AMS on different types of pesticides and the influence of farmers' choices of AMS on pesticide input under different terrain conditions and farm sizes were analyzed as well. The results demonstrate that AMS has a significant and negative impact on pesticide input, reducing pesticide expenditures by 56.08% for farmers who adopt AMS. For farmers who do not adopt AMS, adopting such services is assumed to reduce pesticide input by 14.97%. AMS can also reduce the use of insecticides and herbicides by over 54%. Compared to mountainous and hilly areas, AMS in plain areas increase the effectiveness of pesticide input reduction by 30.40%. Furthermore, small-scale farmers who adopt AMS can increase pesticide input reduction by 90 yuan/mu compared with large-scale farmers. Therefore, promoting the development of socialized AMS, strengthening AMS in mountainous and hilly areas, and expanding the scale of operation for small-scale farmers can help improve the effectiveness of pesticide input reduction. The results of this study can inform the development of strategies to reduce chemical pesticide use in agricultural soil.

Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi

AbstractOne of the main barriers to adopting smallholder agricultural mechanization in developing countries is the mismatch between the economies of scale of machines and farm size. Private sector‐led mechanization services hold a promise to address this challenge, but there is a lack of evidence on demand for smallholder mechanization services. This study estimates the farmers' willingness to pay for mechanization services using the double‐bounded contingent valuation method and data from 1512 households. Results show that, on average, farmers are willing to pay 11%, 33%, and 5% more than prevailing market rates for land preparation, maize shelling, and transportation services, respectively. The amounts farmers are willing to pay for the mechanization services vary by sex, age group, size of cultivated land, the value of farmer assets, market access, and agroecology. Men are willing to pay 26%, 25%, and 11% more than women for land preparation, maize shelling, and transportation services. Moreover, 40% of female and 90% of male farmers are willing to pay more than or equal to the prevailing market rate for land preparation services. The high demand for mechanization services among smallholder farmers points to the need for making the machinery available to rural communities through mechanization service providers or machinery hiring centers run by the private sector. The paper concludes by discussing the contextual factors and policy options for promoting smallholder mechanization in Malawi. [EconLit Citations: O33, Q11, Q13, Q16].

Factors affecting farmers’ hiring decisions on agricultural mechanization services: A case study in Ethiopia

Factors affecting farmers’ hiring decisions on agricultural mechanization services: A case study in Ethiopia

Field-road classification for GNSS recordings of agricultural machinery using pixel-level visual features

The understanding of agricultural machinery, whether it is used “in field” or “on road”, plays an essential role in optimizing the efficiency of cross-regional agricultural mechanization services that have been available in China for decades. With the widespread availability of Global Navigation Satellite System(GNSS)-enabled devices, developing a method for automatically identifying the activity associated with each point in GNSS recorded trajectories can significantly enhance the optimization of these services. In this paper, we propose a novel field-road classification method that utilizes two feature vectors to represent each point in a GNSS trajectory. The first feature vector is a statistical feature vector extracted with existing methods, while the second feature vector is a visual feature vector obtained through an image segmentation model. To extract visual features, we first convert each GNSS trajectory into a trajectory image that encodes the motion information (e.g., speed, direction) of each point and the spatiotemporal relationship between points. Then, an image segmentation model specifically for field-road classification was developed, which can effectively extract a visual feature vector for each pixel in a trajectory image, corresponding to each point in the GNSS trajectory. The image segmentation model used in our approach has a robust feature extraction capability that enhances the statistical feature representation of each point by adding pixel-level visual features. We evaluated the effectiveness of our multi-view field-road classification method using trajectories of corn, wheat, and paddy harvesters. The results demonstrated that our method achieved accuracy scores of 94.17%, 90.93%, and 83.43% for respective datasets. Our method outperformed state-of-the-art field-road classification methods, especially for trajectories with high-frequency GNSS acquisition.

The Influence of Agricultural Production Mechanization on Grain Production Capacity and Efficiency

As an important production factor of grain production, agricultural machinery can effectively provide a theoretical basis for agricultural modernization development strategies by exploring its impact on grain production capacity and efficiency. This research starts from the two aspects of grain production capacity and grain production efficiency, takes rice, wheat, and corn as the research objects, and uses the C–D production function and Tobit model as the basis, respectively, to establish two impact models of production capacity and production efficiency. At the same time, according to the different emphases of the two models, this research designs different variable systems and finally uses the data from 2017 to 2021 for empirical analysis. The research results show that the influence coefficients of machinery service income and machinery power resource input on the total grain production capacity are 0.0976 and 0.0437, respectively, with a significant positive impact. At the same time, for rice crops, wheat crops, and corn crops, the amount of mechanization cost per mu has a significant positive impact on the yield capacity of crops, with impact coefficients of 0.0311, 0.0827, and 0.0233, respectively. The supply level of agricultural machinery services and the utilization rate of agricultural machinery services per mu have a significant positive impact on grain production efficiency. The impact coefficients of the supply level of agricultural machinery services per mu are 0.0192, 0.0587, and 0.0241, respectively. The impact coefficients of the agricultural machinery service utilization rate are 0.0059, 0.0148, and 0.0607, respectively, with a significant positive impact. It can be seen that agricultural production mechanization can effectively promote the improvement in grain production capacity and efficiency and promote the process of agricultural modernization. At present, most of the research on industrial mechanization services is biased toward the choice of agricultural mechanization services by farmers. However, this research has carried out the impact mechanism analysis from the perspective of time and space and the perspective of crops, rationalizing the impact mechanism of agricultural production capacity and agricultural production efficiency under agricultural mechanization.

Can agricultural mechanization services narrow the income gap in rural China?

This paper examines the impact of agricultural mechanization services (AMS) on rural household income and income gap, utilizing the recentered influence function regression method and publicly available data collected through the China Labor-force Dynamics Survey. The results of this study shed light on various impacts of AMS. First, agricultural mechanization services can significantly increase rural household income, but there is heterogeneity in the impact on rural household income in different quantiles. The effect of income growth on medium-income and low-income groups is greater. Second, agricultural mechanization services help to narrow the income gap between rural households and alleviate income inequality in rural areas. Third, the effect of agricultural mechanization services on reducing the income gap between rural households in the eastern and western regions is significantly stronger than that in the central region. Finally, further analysis based on income source structure reveals that agricultural mechanization services can significantly reduce the non-agricultural income gap of rural households, but the impact on the agricultural income gap is negligible. Our findings highlight the importance of government's efforts in promoting the development of agricultural mechanization service market in order to improve the income inequality in rural areas.

How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?

Agricultural mechanization service (AMS) is a critical path to achieving agricultural green transformation with smallholders as the mainstay of agricultural production. Based on the panel data of 30 Chinese provinces from 2011 to 2020, this paper measures the AGTFP using the Super-SBM model and examines the effects of different AMS supply agents on AGTFP and spatial spillover effects through the spatial Durbin model. The main conclusions are as follows: First, China's AGTFP showed a stable growth trend, with the mean value increasing from 0.1990 in 2011 to 0.5590 in 2020. Second, the specialization (SPO) and large-scale (LSO) of AMS supply organizations have significantly positive effect on the AGTFP of the local province. However, SPO has a significantly positive effect on the AGTFP of the neighboring provinces, while LSO has the opposite effect. Third, the specialization of AMS supply individuals (SPI) has significantly negative effect on the AGTFP of the local province. In contrast, the large-scale AMS supply individuals (LSI) has the opposite effect. Furthermore, the spatial spillover effects of both are insignificant. Fourth, the spatial spillover effect of AGTFP shows asymmetry among different regions and indicates that AMS resources flow from non-main grain production and economically developed regions to main grain production and less developed regions. These findings provide helpful policy references for constructing and improving the agricultural mechanization service system and realizing the agricultural green transformation in economies as the mainstay of agricultural production.

Impact of New Rural Pension Insurance on Farmers’ Agricultural Mechanization Service Inputs

The rural social security system is a crucial guarantee for the purpose of transforming agricultural production methods. This research assesses how the new rural pension insurance (NRPI) alters the farmers’ agricultural mechanization service (AMS) inputs. Using the 2016 and 2018 waves of the China Family Panel Studies (CFPS), the study observed that NRPI significantly increased farmers’ AMS inputs. Participation in the NRPI could increase AMS inputs by 18.6% and 13.2% for households with and without elderly farmers, respectively. Both grandchild care and labor off-farm transfer were significant in mediating the relationship between NRPI and AMS inputs with elderly farmers, accounting for 13.72% and 9.13% of inputs, respectively. Furthermore, for families without elderly farmers, the mechanism tests suggest that the crowding-out effect of labor off-farm transfer was a fundamental transmission mechanism for the NRPI to contribute to the increase in AMS inputs, with a proportion value of 15.41%. Additionally, the heterogeneity analysis demonstrated that for households with elderly farmers, the NRPI had a more evident effect on the AMS inputs of the farmers with grandchild care, as well as a low proportion of non-agricultural labor transfer and a high level of agricultural income. For households without elderly farmers, the NRPI’s promotion effect on the investment in AMS inputs was more significant when there was a low proportion of non-agricultural labor transfer and for farmers with low levels of agricultural income. The conclusion provides references for improving NRPI and promoting the promotion of AMS and sustainable agricultural development.

Adoption patterns and productivity impacts of agricultural mechanization services

AbstractAgricultural mechanization services (AMS) have emerged as a viable and effective solution for helping farmers gain access to machinery equipment in developing countries. This study investigates the simultaneous decision‐making regarding multiple mechanization services and the causal impacts of the AMS on land productivity among Chinese smallholders. We find that: (i) The ratio of off‐farm wage to AMS price, or the wage‐rent ratio, has a significant positive effect on AMS adoption; the sequential adoption of AMS starts with power‐intensive followed by control‐intensive production tasks, (ii) Switching to AMS in plowing, transplanting, and harvesting increases rice yield by 48.0 kg, 23.7 kg, and 7.9 kg, respectively, and (iii) The AMS of pesticide spraying significantly decreases yield but the negative effect can be mitigated with professional service providers and effective labor monitoring, highlighting potential moral hazards associated with AMS when monitoring is costly. Simulation illustrates that increased AMS adoption can significantly enhance food security in China.

The Provision of Agricultural Mechanization Service and the Financial Performance of Rice Farms in Vietnam

The aim of this study was to analyze the financial performance of agricultural mechanization service delivery for rice farms in Vietnam. From the Vietnam Household Living Standard Survey 2014 data set, data of 164 farmers who provided agricultural mechanization services for rice production were extracted to evaluate the financial performance. Results showed that the duration of farmers’ operation to provide services for rice production was about 2.8 months/year on average. The profit of mechanization service delivery for rice production was about 17 million VND/year. The average return on sales ratio was about 56.4%. Regression results indicated that Kinh households had lower financial efficiency than other ethnic groups. If the main person in charge was the household's head, it was less effective than other family members. Variables of asset depreciation, labor outsourced, agricultural credit, and rice land area reduced the financial efficiency of agricultural service providers. Meanwhile, farmers who were men with primary income from rice production had higher financial efficiency in providing agricultural services.

The paradox of developing agricultural mechanization services in China: Supporting or kicking out smallholder farmers?

Developing agricultural mechanization services (AMS) is commonly regarded as an important step in the modernization of smallholder farmers in China. However, given the increase in the opportunity costs of agriculture and the high cost of AMS, further study is needed to determine the relationship between AMS and smallholder farmers' exit from agricultural production. In this paper, data from the China Family Panel Survey collected in 2017 and 2019 are used to investigate this issue. Our findings show that the development of AMS reduces the probability that smallholder farmers exit from agricultural production though land abandonment, but increases the probability through land renting-out. Further analysis shows that with the emergence of large farm operators and the increase in land size rented by large farm operators, the development of AMS induces smallholder farmers' exit from agricultural production through both land abandonment and land renting-out. We also find that AMS can increase the market demand for land transfers and the marketization of land rentals, and as land markets develop, AMS induce smallholder farmers' exit through the abandonment of fragmented and distant land plots.

Is small beautiful? Links between agricultural mechanization services and the productivity of different-sized farms

ABSTRACT Developing agricultural mechanization services is commonly regarded as an important approach to pushing smallholder farmers engaging in modern agricultural production in China. However, whether smallholder farmers can benefit more from agricultural mechanization services is ambiguous. Using household-level data collected from Henan province in China, this study investigates the effect of agricultural mechanization services on the productivity of different-sized farms. The results indicate that the productivity of medium farms benefits more from agricultural mechanization services rather than small and large farms. Further analysis shows that medium farms are more likely to adopt agricultural mechanization services and reveals a positive relationship between the adoption of agricultural mechanization services and farm productivity. The higher rate of adoption of agricultural mechanization services and the related higher productivity of medium farms can be explained by the tendency of large farms to invest in self-owned agricultural machinery and the likelihood that small farms will input more labourers in wheat production. Although Chinese governments aim to develop the social service in agriculture for smallholder farmers, it seems that they do not get positive responses.

Farmers' Exit from Land Operation in Rural China: Does the Price of Agricultural Mechanization Services Matter?

AbstractThis study uses data covering 3,914 farm households, collected from Henan province in China, to investigate the links between the price of agricultural mechanization services and farmers' exit from land operation. The results indicate that the increasing price of agricultural mechanization services leads to farmers leaving land operation, especially when the high sunk costs and the long‐term breakeven period of self‐owned machinery are considered. This effect is intensified by the rapid rural–urban migration in China. Further analysis reveals that the surge in service prices reduced land renting‐in and encouraged non‐grain production. Our analysis suggests that the agricultural mechanization service market in China tends to work against the survival of smallholder farmers. However, the price of agricultural mechanization services is conducive to eliminating less‐productive farmers and cultivating new agricultural operators.

Do small farms prefer agricultural mechanization services? Evidence from wheat production in China

ABSTRACT Developing agricultural mechanization services has been an important approach to pushing smallholder farmers engaging modern agricultural production in China. However, whether smallholder farmers prefer adopting agricultural mechanization services is still under-analysed. In this paper, we use data covering 3,440 wheat farmers collected from Henan province in China to investigate the links between farm size and the adoption of agricultural mechanization services. The results indicate that an inverted U-shaped relationship between farm size and the adoption of agricultural mechanization services exists. We also find that small farms can input more family labour, and large farms tend to invest in self-owned machinery assets. Our analysis implies that the development of agricultural mechanization services is not inevitable to attract farmers with alternative elements, and smallholder farmers may not be the major groups involved in the market of social services in agriculture in the future.

EFFECTS OF AGRICULTURAL TRACTOR LEASING PROGRAMMES ON FARMERS IN NIGERIA: 2015 - 2017

The study analysed effects of agricultural tractor leasing programmes on farmers in Nigeria for the period 2015 - 2017. The study was carried out in Kaduna, Katsina, Osun and Ogun States, respectively. A random sampling technique was used in selecting 200 beneficiaries who registered with their State tractor owners and operators association of Nigeria (TOOAN). The sampling frame comprised all the registered TOOAN farmers’ beneficiaries in the surveyed States who took bank loan. Data collected were analysed using simple statistical tools like frequencies, percentages, means, and inferential statistics (multiple linear regression analysis). The results showed that within the study periods, a total of 987 farmers applied for bank loan through State chapters of TOOAN in Nigeria totalling N137,049,650 leaving a credit supply gap of N65,163,900.00.00. The total amount of loan repaid by the beneficiaries during the period was N35,230,180.00 which gave a repayment rate of 69% and a default rate of 31%. The loan granted to the beneficiaries increased national output by 23.3% and affected positively on the beneficiaries’ income. It was recommended that government should continue to encourage increased funding in collaboration with private sectors agricultural mechanization service providers to the agricultural sector for increased accelerated food production in Nigeria by small and medium scale farmers.