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 economic globalisation has opened new pathways for commerce and triggered a logistical revolution, which in turn has produced enormous technological innovations. In this context, the role of startups is becoming increasingly crucial since they are positioning themselves as innovation enablers among large and small companies. Between these innovations, IoT, Big Data Analytics and Blockchain can be used in various domains, among which the logistics of the whole wine supply chain.
This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, https://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products.
According to transition science, system innovation requires experimentation and social learning to explore the potential of innovations for sustainable development. However, the transition science literature does not elaborate much on the learning processes involved. Senge's Field of Change provides a more detailed approach to the role of learning and action in innovation. We linked the Field of Change to transition management literature in order to explore social learning in an agricultural innovation experiment in the Netherlands called the ‘New Mixed Farm’.
Innovations are considered as a key driver for economic growth and increased competitiveness. Investments in agricultural research and development could generate not only economic and social effects but also environmental benefits. The study aims to analyse of agricultural innovation system in Bulgaria and the linkages with agricultural R&D to formulate conclusions and recommendation for future development. The paper presents some of the theoretical concepts of innovation systems and the role of R&D in the process.
In this paper the authors used a network perspective to study the micro level of agricultural innovation systems and investigate the different roles and functions that collaborating actors have to perform to spread their innovation both horizontally and vertically. Based on a literature review, we distinguish between three separate network functions: (1) learning and knowledge co-creation, (2) upscaling and institutional entrepreneurship and (3) outscaling and innovation brokerage.
The transition to a market for agricultural research and knowledge-intensive services presents various challenges for actors in the agricultural knowledge infrastructure, on both the demand side (end users of innovations such as farmers, and the government) and the supply side (providers of research and knowledge-intensive services). New organizational arrangements try to bring together supply and demand in the agricultural knowledge infrastructure. This thesis is about such new organizational arrangements
Companies’ environmental responsibility has significantly increased in the last decade. However, the question about the benefits that this responsible decision has on the company’s performance in the market remains. In this scenario, the main goal of this study is to analyze the conditions that improve the performance of companies in the agri-food industry, paying specific attention to technological eco-innovation and different types of cooperation (in the use and in the development of eco-innovations). The initial sample contains data of agri-food companies operating in Spain.
Understanding eco-innovation is an essential endeavor to achieve global sustainable development. In this sense, further research on implementation is needed to expand knowledge beyond current boundaries. The aim of this paper is to contribute to this debate by conducting an original multidimensional analysis using Spanish agri-food sector data. The empirical methodology applies a combination of descriptive statistics, cluster analysis and the chi-squared test.
Proven that the adoption rate of a new product is influenced by the network characteristics of the early adopters, the aim of this paper is to find the network features of the early adopters associated with high adoption rates of a specific new practice: the use of biodegradable mulching films containing soluble bio-based substances derived from municipal solid wastes. The study simulated the diffusion process by means of an agent-based model calibrated on real-world data.