Stakeholder interactions and capacity development for innovation and adoption of agricultural technologies: the case of banana value chain in Uganda

Abstract

The low level of adopting improved technologies has been a major challenge towards increasing agricultural productivity and ensuring food security in developing countries. Although multiple studies have been conducted with regard to how the adoption of improved technologies could be enhanced, less attention has been focused on understanding the role of interactions among stakeholders in an agricultural system such as the value chain and their capacities to influence innovation and adoption of improved technologies. This study examined interactions and capacity development needs for innovation and adoption of technologies among stakeholders in the Ugandan banana value chain. The study employed a mixed methods design, involving the use of qualitative and quantitative methods as complements in collecting and analyzing primary data. Primary data were collected by conducting focus group discussions with banana farmers and traders; the key informant interviews (KIIs) with the banana traders (retailers, wholesalers, bicycle/motorbike banana traders), the processors for various banana products, export farmers, researchers and extension agents as key influential stakeholders in the banana value chain. A household survey was also conducted among banana farming households. The study took place in low-land, highland, and mid-highland agroecological zones in Uganda; specifically, in Nakaseke, Bunyangabu, and Isingiro districts respectively, representing the historical banana growing areas in Uganda. The data collected through FGDs and KIIs were analyzed qualitatively using the Social Network Analysis (SNA) methodology to establish the stakeholder interactions for innovation and technology adoption. Thematic analysis was also conducted to establish Capacity Development (CD) gaps for innovation and adoption of technologies. Data from the household survey was analyzed using the Multivariate probit and Ordered probit models in order to establish factors that influence multiple adoption decisions of improved technologies among banana farming households. According to the study findings, there are various stakeholders in the banana value chain with the potential to contribute to innovation and adoption of technologies. Social Network Analysis (SNA) results indicate the densities of 28.0%, 25.6%, and 26.8% from Bunyangabu, Isingiro, and Nakaseke value chains, respectively, implying the existence of weak linkages among stakeholders in such areas which indicates that most of them are working in isolation. This limits the possibility of innovating together. Particularly, research and extension had weak or missing connections with the key stakeholders such as the processors, traders, and farmer groups. This depicts the existing limited discussions, cooperation and feedback among them, with the likely outcome of generating and promoting technologies that are not acceptable among end users. Betweenness results indicate that in Bunyangabu, regulatory bodies were the most influential stakeholders for facilitating information exchange and service delivery as indicated by the relative betweenness of 1. The position of regulatory bodies in this area depicts the importance of an enabling environment in facilitating information exchange and service delivery for innovation and adoption of technologies. In Isingiro and Nakaseke, farmer groups were the most influential stakeholders. The results show that the potential of various stakeholders to engage in innovation activities could be unlocked by engaging in capacity development at individual, organizational and enabling environment dimensions. Capacity development needs at all the dimensions were similar and are; banana value addition, marketing and financial access options, and management in order to improve adoption. Results from the econometric analysis show that a number of banana technologies can be adopted as complements or substitutes. The results further show that household size, total area under banana production, ecological location, household membership to a farmer group, access to formal sources of credit, and, input and output markets in major towns of Uganda produced significant results with the MVP model and ordered probit model. This indicates that the type and the number of technologies that can be adopted at a time are determined by similar factors which should be taken into account when designing adoption interventions for multiple agricultural technologies. The study results provide evidence that there were missing linkages among essential stakeholders (such as research, extension, processors, financial service providers, and traders) which further limits their involvement in the innovation activities in banana value chain. The need for improved access to and management of finance and marketing services to facilitate innovation and adoption of technologies is reflected in the capacity development needs and was identified as a key limiting factor for the adoption of technologies among banana farming households. Therefore, the banana farming environment should be improved such that there are favorable marketing systems and availability of funding at low-interest rates affordable by the value chain stakeholders. By answering the three research questions, this study provides a guiding framework for identification of appropriate technological packages, intervention zones and training topics as capacity development requirements to be fulfilled in order to facilitate innovation and adoption of technologies in the Ugandan banana value chain.