Precision agriculture adoption and technical efficiency: An analysis of sugarcane farms in Brazil

Carrer, Marcelo José; Filho, Hildo Meirelles de Souza; Vinholis, Marcela de Mello Brandão; Mozambani, Carlos Ivan

doi:10.1016/j.techfore.2022.121510

Cited by 47 publications

(35 citation statements)

References 41 publications

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“…The barriers to adopting digital technologies include high initial investment costs and a lack of skilled labor (Pivoto et al, 2019;Bolfe et al, 2020). Compared to small-scale farmers, larger farmers are better able to adopt digital technologies (Lambert et al, 2015;Kolady et al, 2021) due to larger farmers needing more tools to manage their more complex production systems (Carrer et al, 2022) and economies of scale (Zhang et al, 2019;Mao et al, 2021). In China, digital technologies have gained popularity in dairy production systems incorporating TMR feeding (Cox, 2007).…”

Section: Introductionmentioning

confidence: 99%

Can the use of digital technology improve the cow milk productivity in large dairy herds? Evidence from China's Shandong Province

Han

Shadbolt

et al. 2022

Front. Sustain. Food Syst.

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IntroductionImproving milk productivity is essential for ensuring sustainable food production. However, the increasing difficulty of supervision and management, which is associated with farm size, is one of the major factors causing the inverse relationship between size and productivity. Digital technology, which has grown in popularity in recent years, can effectively substitute for manual labor and significantly improve farmers' monitoring and management capacities, potentially addressing the inverse relationship.MethodsBased on data from a survey of farms in Shandong Province in 2020, this paper employs a two-stage least squares regression model to estimate the impact of herd size on dairy cow productivity and investigate how the adoption of digital technology has altered the impact of herd size on dairy cow productivity.ResultsAccording to the findings, there is a significant and negative impact of herd size on milk productivity for China's dairy farms. By accurately monitoring and identifying the time of estrus, coupled with timely insemination, digital technology can mitigate the negative impact of herd size on milk productivity per cow.DiscussionTo increase dairy cow productivity in China, the government should promote both small-scale dairy farming and focus on enhancing management capacities of farm operators, as well as large-scale dairy farms and increase the adoption of digital technologies.

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Section: Introductionmentioning

confidence: 99%

Can the use of digital technology improve the cow milk productivity in large dairy herds? Evidence from China's Shandong Province

Han

Shadbolt

et al. 2022

Front. Sustain. Food Syst.

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“…The adoption of technology, which is characterized by its use by a company or individual at a given moment in time, is understood as a separated moment from the innovation process. Adoption results from an individual decision influenced by a set of factors that affect an individual's perception of the expected usefulness of the technology (Sunding & Zilberman, 2001;Vinholis et al, 2015;Carrer et al, 2022). The adoption of an innovation by a group of individuals or companies over time represents the diffusion of the technological innovation.…”

Section: Theories Of Adoption and Diffusion Of Innovationsmentioning

confidence: 99%

Adoption of Industry 4.0 technologies: an analysis of small and medium-sized companies in the state of São Paulo, Brazil

Baio

Carrer

2022

Gest. Prod.

Self Cite

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This paper analyzed the level of adoption and compared characteristics of adopters and non-adopters of Industry 4.0 technologies. Primary data for the year 2021 were collected by means of a structured questionnaire applied to 30 small and medium-sized companies of the metallurgical sector, who operate with machining processes, in the state of São Paulo. Data were analyzed using descriptive statistical measures and correlation estimates. The technologies adopted by the companies in the sample were: Cloud Computing (10 companies), Horizontal and Vertical Integration Systems (5 companies), Big Data (4 companies) and Industrial Internet of Things (4 companies). The comparative analysis between the characteristics of adopters and non-adopters showed that: (I) adopters have, much more frequently, employees with ICT capabilities and also more frequently hire ICT consulting services; (II) the use of ERP and MRP systems is much higher among companies that adopt Industry 4.0 technologies; (III) adopters participate more frequently in cooperation programs with Universities, Science and Technology Institutes or Research and Technological Development Promotion Agencies; (IV) companies that adopt 4.0 technologies have a greater perception of relative advantage and compatibility of these technologies.

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“…Previous research by Francis, Samuel, and Samuel (2020) found that sugarcane farming in developing countries had not yet reached optimum efficiency, presumably due to the ratoon farming system practised by most farmers and the use of local seeds. Carrer, de Souza Filho, Vinholis, and Mozambani (2022) argued that sugarcane farming could still be optimised to achieve full efficiency, especially in countries with high agricultural potential. In Indonesia, research on sugarcane farming has also found technical inefficiencies.…”

Section: Introductionmentioning

confidence: 99%

Technology gap ratio decomposition in sugarcane farming in Indonesia

AR¹,

Asmara

Fahriyah

2023

5005

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Indonesia's population and income growth have led to a higher demand for raw sugar and its derivative products; for this reason, sugarcane production must be improved, especially in central production areas. However, efforts are constrained by the disparity in resource endowment and technology. This study aimed to analyse technical, technological, and managerial gaps in sugarcane farming in different areas of East Java. The study used primary data collected through a survey during the 2019/2020 sugarcane planting season in Malang, Kediri, and Mojokerto Regencies. A structured questionnaire was used to collect data on inputs and outputs. A meta-frontier data envelopment analysis (meta-DEA) approach was used to measure the technical efficiency of sugarcane farming in each research area. The decomposition using meta-DEA showed that, on average, the meta-technical inefficiency of sugarcane farmers was caused mainly by managerial gaps, as the average managerial gap inefficiency (MGI) was more significant than the technological gap inefficiency (TGI). Malang regency showed the largest TGI and MGI, indicating that sugarcane farmers in Malang regency have lower managerial skills for decision-making and a lower level of production technology compared to the other two regions. Based on the findings of this study, the government should improve technological innovation to mitigate the technology gap that was found in our research location.

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Precision agriculture adoption and technical efficiency: An analysis of sugarcane farms in Brazil

Cited by 47 publications

References 41 publications

Can the use of digital technology improve the cow milk productivity in large dairy herds? Evidence from China's Shandong Province

Can the use of digital technology improve the cow milk productivity in large dairy herds? Evidence from China's Shandong Province

Adoption of Industry 4.0 technologies: an analysis of small and medium-sized companies in the state of São Paulo, Brazil

Technology gap ratio decomposition in sugarcane farming in Indonesia

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