Climate-smart agriculture (CSA) is increasingly seen as a promising approach to feed the growing world population under climate change. The review explored how institutional perspectives are reflected in the CSA literature. In total, 137 publications were analyzed using institutional analysis framework, of which 55.5% make specific reference to institutional dimensions. While the CSA concept encompasses three pillars (productivity, adaptation, and mitigation), the literature has hardly addressed them in an integrated way.
This paper seeks to contribute to a better understanding of the complex dynamics that shape the contribution of research to policy and innovation processes that address ‘competing claims’ on natural resources and their management.
This article proposes a novel conceptualization of knowledge-intensive innovative entrepreneurship, which can capture the main characteristics of a vital phenomenon in the modern economy. Our conceptualization is based upon the integration of Schumpeterian entrepreneurship, evolutionary economics, and innovation systems approach. It consists of a theoretical definition and a stylized process model.
In organizations, mandated adoption contexts are the rule rather than the exception. Individuals, who are denied the choice between adopting and rejecting an innovation, are more likely to engage in opposition behavior, particularly if the innovation conflicts with their held beliefs. Interestingly, neither the construct of forced adoption nor its consequences have received much research attention. To address this gap, was conducted a systematic literature review and provide theoretical rationales for the emergence of innovation resistance and opposition behaviors in organizations.
The integration of ethics into the day-to-day work of research and innovation (R&I) is an important but difficult challenge. However, with the Aachen method for identification, classification and risk analysis of innovation-based problems (AMICAI) an approach from an engineering perspective is presented that enables the integration of ethical, legal and social implications into the day-to-day work of R&I practitioners.
Since global issues (i.e. disruption technology and sustainability) attracted the attention of agricultural system researchers and company, innovation system plays a significant role in the development of agricultural downstream supply chain, in order to make agriculture business sustain. Hence, researches in innovation system for agricultural downstream supply chain are very important in dealing with these challenges.
In this perspective paper the authors consider the implications of a digital transformation for agricultural knowledge, a subject which hitherto has received limited attention. They raise critical questions about how digital agriculture will intersect with established modes of knowing and decision-making.
Agriculture 4.0 is comprised of different already operational or developing technologies such as robotics, nanotechnology, synthetic protein, cellular agriculture, gene editing technology, artificial intelligence, blockchain, and machine learning, which may have pervasive effects on future agriculture and food systems and major transformative potential. These technologies underpin concepts such as vertical farming and food systems, digital agriculture, bioeconomy, circular agriculture, and aquaponics.
Technological influence was a great support for judgment-making in various fields, especially in agriculture. Agriculture production has been on the rise over recent years due to a lack of knowledge of agriculture and ecological shifts. The main goal of this system is to accomplish farmers in e-Agriculture of their wakefulness, usage, and observation. The study used a technique of numerical study design to collect data from farmers for their e-commerce awareness The data gathered indicate there is less understanding that there is a need for help for e-agriculture.
Facing the challenges of the 21st century, into the agricultural sector have been designing strategies focused on the management of ecosystem resources, risk management associated with crops and the promotion of sustainable growth of agricultural communities. These strategies have been configured considering functional and competitive levels for open agricultural production systems, and usually based on low-cost technologies such that Wireless Sensor Networks (WSN), Internet of Things (IoT), Unmanned Aerial Vehicles (UAV), Cloud Computing, and Computational Algorithms.