The Development of Adopting Innovation on Entrepreneurship Status of Madura Cattle Farmers

Pambudy, Rachmat

doi:10.5398/tasj.2018.41.2.147

Cited by 4 publications

(5 citation statements)

References 16 publications

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“…The significant influence of the price volatility of imported feeder cattle to the slaughter rate is reasonable considering the behavior of local farmers and the large scale farmers or feedlotters. Local farmers are usually small farmers who have small scale production, live in the rural areas, and have difficulty in developing the production of beef due to their resource limitation (Kalangi et al, 2014;Pambudy, 2018). Meanwhile, feddlotters are medium to large scale farmers who commercially raise their cattle to produce beef in high scale and could have the ability to produce beef in day to day basis.…”

Section: Discussionmentioning

confidence: 99%

Modeling Price Volatility and Supply Response of Beef in Indonesia

Komalawati

Asmarantaka

Nurmalina

et al. 2019

Trop. Anim. Sci. J.

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Beef is one of the strategic livestock commodities in Indonesia. As demand increases, the price of beef increases and tends to be volatile. The increased volatility in beef prices could influence production decision and the supply of beef. This study aimed to investigate the price volatility and the impact of price volatility on the supply response of beef in Indonesia. This study used secondary data obtained from various related institutions. Volatility was estimated using the GARCH (p,q) model and the supply response model using OLS model. The empirical results indicated that among the estimated GARCH models, the GARCH (2,3) seemed to be particularly appropriate to describe the beef price supply response. Beef price volatility in Indonesia was found to be low and persistent in the long run. Price uncertainty appeared to have a substantial negative effect on Indonesian beef production. The slow adjustment of farmers to demand and supply shocks indicate the importance of import as a temporary policy to fulfill the demand of beef in the short and medium-run.

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Section: Discussionmentioning

confidence: 99%

Modeling Price Volatility and Supply Response of Beef in Indonesia

Komalawati

Asmarantaka

Nurmalina

et al. 2019

Trop. Anim. Sci. J.

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“…Disseminating information to a large audience or individuals can be achieved through the adoption of communication channels. According to research by Pambudy (2018) and Arjune and Kumar (2022) [42,63], the implementation of digital technologies can be facilitated by the use of extension contact tools and exposure to mass media.…”

Section: Institutional Factorsmentioning

confidence: 99%

“…Internet usage is suggested to aid adoption [61]. Limited capital and a lack of expertise in using digital communication devices result in low utilisation among farmers [42].…”

Section: Technological Factorsmentioning

confidence: 99%

Promoting the Transition towards Agriculture 4.0: A Systematic Literature Review on Drivers and Barriers

Fragomeli,

Annunziata,

Punzo

2024

Sustainability

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In the modern era, the imperative of digitalisation to enhance competitiveness spans various sectors, with agriculture being no exception. Agriculture 4.0, strategically positioned to address challenges like climate change, food security, and resource preservation, holds the potential to increase productivity, profitability, and sustainability in agriculture. Despite the global accessibility to digital technologies, their adoption within the agriculture sector, especially among small and medium-sized farms, encounters obstacles. Realising the full potential of Agriculture 4.0 requires understanding the factors influencing technology adoption. To address this, the study conducts a systematic literature review using the PRISMA method, focusing on identifying the primary drivers and barriers associated with the implementation of Agriculture 4.0 technologies. The study is complemented by a network analysis of the identified drivers and barriers. A total of 42 articles from 2011 to 2023, sourced from the Scopus database, are examined. Individual and farm-related factors play a crucial role in driving the adoption of smart farming technologies, along with social trust and influence. Economic constraints and lack of infrastructure, such as internet access, emerge as significant barriers. The identified drivers and barriers can inform the development of strategies to promote the transition to Agriculture 4.0. Farmers stand to benefit from insights into potential advantages, required skills, and challenges, aiding informed decision-making in the adoption of Agriculture 4.0 technologies.

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“…Farmers require entrepreneurship skills in responding to technology development. They have to adopt innovation in their businesses to scale up their welfare (Pambudy, 2018). They have the freedom to access technical information, capital, market, and other information as needed, to increase productivity, business efficiency, and income.…”

Section: Meaning Of Life Dimensionmentioning

confidence: 99%

The happiness of small-scale dairy farmers: A case at Malang Regency of East Java, Indonesia

Sutawi

Prihartini

Khotimah

et al. 2021

J. Indonesian Trop. Anim. Agric.

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This study was conducted to assess the happiness of small-scale dairy cattle farmers based on subjective well-being conditions. The research was conducted in July-October 2020 using a survey method in the Malang Regency of East Java Province. Analysis units were 145 small-scale dairy cattle farmer households purposively selected with less than 30 heads of dairy cattle ownership and have managed their livestock farming for more than five years. Data collection was conducted through interviews about three dimensions of happiness including life satisfaction, affection, and the meaning of life. The three dimensions were divided into 19 indicators to calculate the Happiness Index. The ten Life Satisfaction indicators produced a Life Satisfaction Index of 7.43 (Happy), consisting of a Personal Life Satisfaction Index of 7.26 (Happy) and a Social Life Satisfaction Index of 7.85 (Happy). The three Affection indicators produced the Affection Index of 7.29 (Happy). The six Meaning of Life indicators produced the Meaning of Life Index of 7.44 (Happy). The Happiness Index of small-scale dairy cattle farmers in East Java was 7.43 and classified as "Happy".

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The Development of Adopting Innovation on Entrepreneurship Status of Madura Cattle Farmers

Cited by 4 publications

References 16 publications

Modeling Price Volatility and Supply Response of Beef in Indonesia

Modeling Price Volatility and Supply Response of Beef in Indonesia

Promoting the Transition towards Agriculture 4.0: A Systematic Literature Review on Drivers and Barriers

The happiness of small-scale dairy farmers: A case at Malang Regency of East Java, Indonesia

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