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A ctors in an agricultural innovation system (AIS) innovate not in isolation, but through interacting with other actors-farmers, firms, farmer organizations, researchers, financial institutions, and public organizations-and the socioeconomic environment. In other words, agricultural innovation is an organizational phenomenon influenced by individual and collective behaviors, capabilities for innovation, and enabling conditions. Interaction, coordination, and collective action are based above all on the actors' capacity to identify opportunities for innovation, assess the challenges involved, and access the social, human, and capital resources required for innovating, learning, and sharing information. Better coordination can improve the design and implementation of innovation policies by allowing more actors to voice their needs and concerns, resulting in more inclusive policies and faster diffusion of innovations. Stronger interaction and coordination can also induce all actors in an innovation system, particularly public research and extension organizations, to be more aware of and responsive to the needs and concerns of other actors, especially resourcepoor households. Despite such advantages, interaction and coordination have been difficult to achieve for the same reasons that hinder collective action: opportunistic behavior; lack of trust, incentives, and capacity; and difficulties in setting and enforcing rules. Interaction and coordination in the innovation systems of developing countries are hampered as well by segmented markets, different technological regimes, lack of collaboration cultures, inappropriate incentives, weak channels of communication, and insufficient innovation capabilities. Effective interaction, coordination, and collective action are based on existing capabilities, appropriate incentives, and the empowerment of individuals; thus they rely on voluntary action. Coordination and interaction can emerge spontaneously or be induced by specific public or private programs. Effective coordination requires (1) a committed and capable leadership; (2) appropriate incentives; (3) an enabling environment, in which important stakeholders that coordinate their activities have the mandate, culture, and freedom to participate; (4) stable support programs; (5) efforts to strengthen the capabilities for innovation and collective action; and (6) adaptation of public organizations to participate more effectively in innovation processes. The organizational innovations (committees or councils, platforms or networks, and diverse associations) reviewed in this module show that many innovations are not planned in detail beforehand; instead, they result from the adaptation of organizational structures in response to emerging problems or opportunities. They also show that creative and committed individuals guide the adaptation and that an enabling environment allows the organizations to change.
A ctors in an agricultural innovation system (AIS) innovate not in isolation, but through interacting with other actors-farmers, firms, farmer organizations, researchers, financial institutions, and public organizations-and the socioeconomic environment. In other words, agricultural innovation is an organizational phenomenon influenced by individual and collective behaviors, capabilities for innovation, and enabling conditions. Interaction, coordination, and collective action are based above all on the actors' capacity to identify opportunities for innovation, assess the challenges involved, and access the social, human, and capital resources required for innovating, learning, and sharing information. Better coordination can improve the design and implementation of innovation policies by allowing more actors to voice their needs and concerns, resulting in more inclusive policies and faster diffusion of innovations. Stronger interaction and coordination can also induce all actors in an innovation system, particularly public research and extension organizations, to be more aware of and responsive to the needs and concerns of other actors, especially resourcepoor households. Despite such advantages, interaction and coordination have been difficult to achieve for the same reasons that hinder collective action: opportunistic behavior; lack of trust, incentives, and capacity; and difficulties in setting and enforcing rules. Interaction and coordination in the innovation systems of developing countries are hampered as well by segmented markets, different technological regimes, lack of collaboration cultures, inappropriate incentives, weak channels of communication, and insufficient innovation capabilities. Effective interaction, coordination, and collective action are based on existing capabilities, appropriate incentives, and the empowerment of individuals; thus they rely on voluntary action. Coordination and interaction can emerge spontaneously or be induced by specific public or private programs. Effective coordination requires (1) a committed and capable leadership; (2) appropriate incentives; (3) an enabling environment, in which important stakeholders that coordinate their activities have the mandate, culture, and freedom to participate; (4) stable support programs; (5) efforts to strengthen the capabilities for innovation and collective action; and (6) adaptation of public organizations to participate more effectively in innovation processes. The organizational innovations (committees or councils, platforms or networks, and diverse associations) reviewed in this module show that many innovations are not planned in detail beforehand; instead, they result from the adaptation of organizational structures in response to emerging problems or opportunities. They also show that creative and committed individuals guide the adaptation and that an enabling environment allows the organizations to change.
This chapter presents results of a randomised evaluation that assesses the effects of different incentives for diffusion of agricultural knowledge by smallholders in northern Uganda. Randomly selected disseminating farmers (DFs) from a large sample of villages are assigned to one of three treatment arms: (i) training about climate smart agriculture, (ii) training plus a material reward for knowledge diffusion, and (iii) training plus a reputational gain for knowledge diffusion. The chapter documents fairly robust evidence that leveraging somebody's reputation (or social recognition) has large effects on experimentation with new technologies and diffusion effort by DFs. The impact of providing private material gains is less robust.
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