This study aims to identify value-chain actors, estimating the profit share of each actor in the chain and identifying constraints and opportunities along the fish value chain. Data from 120 sampled respondents were collected through extensive personal interviews; field observation and the collected data were processed in a (SPSS) statistical package for social science. The study identified six main value-chain actors (fishermen, fishermen cooperatives, wholesalers, processors, retailers, and end-users/consumers) who were involved in value-adding, supplying, collecting and marketing, and consuming, but still there were slightly strong market linkage among actors. They lack a win-win strategy in the overall share of cost and profit. For instance, of the value-chain actors in districts, fishermen share high costs but as evident, they earn little profit. The sector faces many production constraints (lack of modern knowledge and poor harvesting and storage facilities, illegal fishing materials, weak governance, and many harvesting sites) and marketing constraints (price fluctuation, poor quality supply-insufficient value-added and seasonality of market). However, to ensure the benefit of the actors and profitability of the sector there should be a need for building good governance for better proper management of monitoring and evaluation and thereby strengthen the chain. Creating an enabling environment of postharvest handling and optimal value addition. Further, there is still a need for studying standard mesh size, weight and maturity stage of each fish species in each lake.

Even though agriculture has ample potential to absorb a large number of people, youths tend to stand away from the subsector. As a result, rural job creation works were started in southern Ethiopia by participating youth in different agricultural enterprises in the form of groups and cooperatives. However, as compared to sector potential, youths are not participating in agricultural job creation works in Ethiopia. Therefore, this study was intended to assess factors affecting youth participation in agricultural enterprises in selected districts of Southern Ethiopia. A multistage sampling procedure was followed to select 160 sample youths. The collected data from sampled youths were analyzed by both descriptive statistics and a probit econometric model. Among the agricultural enterprises, the majority of the youths (63.3%) preferred livestock enterprises indicating livestock sector job creation capacity in Ethiopia. The seasonal nature of agricultural income, fear of agricultural risk, and lack of initial capital were the top three factors hindering youth participation in the agricultural enterprise as rural job creation works. The probit model result shows that, among the hypothesized variables, education level, credit getting bureaucracy, lack of initial capital, fear of the group, risk and uncertainty, and lack of working place determine significantly youth participation in agriculture enterprises. Hence, respective bodies must group youths based on their preferred interest and evaluate their business plan critical before credit disbursement, while solving credit providing terms problems on the microfinance side and the introduction of agricultural insurance through these youth agricultural enterprises for agricultural risk fear needs stakeholders’ interventions. Overall, initial savings, interest rate, and payback period of credit need special policy adjustments to increase youth participation in an agricultural enterprise.

The majority of farmers are producing maize in the Gamo and Gofa zones and they are not benefiting from it due to the marketing problem. Thus, this study was intended to analyze the maize market chain and determinants of market participation in the selected maize-producing districts of the Gamo and Gofa zones. To achieve this objective, multistage sampling techniques were followed to randomly select 151 sample respondents. The data were analyzed by using descriptive statistics, marketing margins, and the double hurdle model. The survey results revealed that approximately 35.88% of the maize from the total maize produced by the sampled farmers was marketed in the study area. The result indicates that among the five identified maize marketing channels, the largest volume of maize passed through channel V (producers, urban collectors, and consumers). In the marketing of maize, traders set the price due to poor market linkage and the low bargaining power of producers. The model regression result indicates that among the hypothesized factors, family size, allocated land size for maize, and market information have a significant effect on the quantity of maize market supply. Based on this finding, strengthening extension services through training and accessing inputs are recommended. Furthermore, market linkage through the cooperative establishment and the availability of market information by respective bodies is suggested.