This work has largely focused on the developed world, yet the majority of people and future economic growth lies in the developing world. Further, most research examines micro data on consumers or firms, limiting what is known regarding the role of macro factors on diffusion, such as social systems. Addressing these limitations, this research provides the first high-level insights into how green building adoption is occurring in developing countries.
This paper used systematic literature network analysis to review the state-of-the-art blockchain technology including its recent advances, main applications in agri-food value chain and challenges from a holistic perspective. The findings suggest that blockchain technology together with advanced information and communication technology and internet of things have been adopted for the improvement of agri-food value chain management in four main aspects: traceability, information security, manufacturing and sustainable water management.
In this paper is presented insights from a co-design process with private farm advisers and ask: What enables farm advisers to engage with digital innovation? And, how can digital innovation be supported and practiced in smart farming contexts? Digital innovation presents challenges for farmers and advisers due to the new relationships, skills, arrangements, techniques and devices required to realise value for farm production and profitability from digital tools and services.
In this paper, the authors describe the adaptation and validation of a project-level WEAI (or pro-WEAI) that agricultural development projects can use to identify key areas of women’s (and men’s) disempowerment, design appropriate strategies to address identified deficiencies, and monitor project outcomes related to women’s empowerment. The 12 pro-WEAI indicators are mapped to three domains: intrinsic agency (power within), instrumental agency (power to), and collective agency (power with). A gender parity index compares the empowerment scores of men and women in the same household.
Digitalisation is widely regarded as having the potential to provide productivity and sustainability gains for the agricultural sector. However, there are likely to be broader implications arising from the digitalisation of agricultural innovation systems. Agricultural knowledge and advice networks are important components of agricultural innovation systems that have the potential to be digitally disrupted.
The main objective of this study was to investigate and analyse the farmers’ perceptions on criteria and indicators for sustainable management of indigenous agroforestry systems in Uttarakhand state of India. The present study was conducted to document the traditional knowledge and considered five broad categories including agriculture management, livestock management, forest sustainability, social benefits, and policy inputs along with 16 criteria and 34 indicators were identified.
Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper, we reviewed crowdsourcing initiatives in agricultural science and farming activities and further discussed the particular characteristics of this approach in the field of agriculture. On-going crowdsourcing initiatives in agriculture were analysed and categorised according to their crowdsourcing component.
The impulse towards a larger introduction of Information and Communication Technology (ICT) in the agricultural field is currently experiencing its momentum, as digitisation has large potentialities to provide benefits for both producers and consumers; on the other hand, pushing technological solutions into a rural context encounters several challenges.
The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.
This special issue contains contributions from 42 authors representing 21 organizations and institutes around the world. Overall, the publication presents a number of innovations related to the key elements of climate risk management and resilience building in agriculture. The approaches, tools and methods are illustrated with case studies and examples from different parts of the world. While the innovations presented are not without certain limitations, any such limitations are identified and discussed, and recommendations are made for future research.