Marketing outlets choice is one of the most important farm household decisions to sell their produce and has a great impact on household income. Though the study area has great potential of honey production, the farmers in the study area faced the marketing problem in choice of appropriate honey market outlets. This study was therefore carried out to analyze determinants of honey producers' market outlet choice decisions in Chena district. A total of 154 honey-producing households were surveyed, and the data obtained were analyzed by using multivariate probit model. The results show that most sampled households in the study area sell their honey to cooperative outlet as compare to other outlets. The results of the econometric model show the dependency of household level marketing decisions as a strategy to maximize their incomes in the long term. The model results also reveal that the quantity of honey sold, frequency extension contact, beekeeping experience, distance to nearest market, market information about each outlet, cooperative membership, and trust in buyers determine market outlet choice decision of honey producers in the study area. Expanding equal accessibility of infrastructures, establishing honey collection centers in potential production areas, increasing the frequency of extension contact, and organizing additional beekeepers into honey cooperatives is suggested.

In a country like Ethiopia where the vast majority of the populations are employed in agriculture, land is an important economic resource for the development of rural livelihoods. Agricultural land in peri-urban areas is, however, transformed into built-up regions through horizontal urban expansion that has an effect on land use value. In recent years Ethiopia has been experiencing rapid urbanization, which has led to an ever-increasing demand for land in peri-urban areas for housing and other nonagricultural activities that pervades agricultural land. There is a high demand for informal and illegal peri-urban land which has been held by peri-urban farmers, and this plays a vital role in the unauthorized and sub-standard house construction on agricultural land. This urbanization has not been extensively reviewed and documented. In this review an attempt has been made to assess the impacts of rapid urbanization on agricultural activities. Urban expansion has reduced the areas available for agriculture, which has seriously impacted upon peri-urban farmers that are often left with little or no land to cultivate and which has increased their vulnerability. Housing encroachments have been observed to be uncontrolled due to a weak government response to the trend of unplanned city expansion. This has left peri-urban farmers exposed to the negative shocks of urbanization because significant urbanization-related agricultural land loss has a positive correlation with grain production decrease. Appropriate governing bodies should control urban development in order to control the illegal and informal spread of urbanization on agricultural land that threatens food production.

Banana is produced by the highest number of farmers in Bench Maji and Sheka zones of the Southern region of Ethiopia. Even though the zones have high banana production potential, several constraints hamper the development of the banana sector along with the value chain. Therefore, this study was intended to analyze banana value chain in these zones of Ethiopia. Data from 180 banana producers were collected and analyzed by using descriptive statistics, marketing margin and econometric Heckman two-stage model. The result showed there is a weak relationship between banana value chain actors. The marketing margin result showed that collectors from the traders' side received the highest profit share in the banana value chain. The econometric regression result showed that extension contact, type of varieties utilized, the area allocated for banana production, distance to the nearest market, total income and education level are significantly determining factors of banana market participation. In addition, lack of an organized market, low demand during the production season, expensiveness of improved varieties and disease were top identified problems by banana producers. Thus, the concerned stakeholders and government need to give attention to increasing improved banana varieties access and improving the technical knowledge of banana producers on using best practices by arranging cross visits and field trips to areas with best banana production practice. In addition, the promotion of value addition practices and the establishment of banana cooperatives to overcome the marketing problem are also suggested.

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.

Background Kaffa, Sheka and Bench Maji zones of Southern Ethiopia are high honey production areas with dense forest coverage. However, due to the traditional production system, the productivity per hive is low. To exploit this production potential in these zones by increasing productivity per hive, different governmental and non-governmental organizations disseminate improved beehives technologies. Yet, the impact of these disseminated and adopted technologies on honey production has not been determined. Thus, this study aimed to estimate the impact of improved beehive adoption on honey production efficiency. Methodology A multistage sampling technique was used to select 360 sampled households. This study applied a stochastic frontier model to assess the technical efficiency (TE) of honey producers and propensity score matching (PSM) with probit model to analyze adoption decision of improved beehive and its impact on honey production efficiency. Results The finding of this study shows that the number hives, type of beehive used, and proximity to the available forest had a significant and positive effect on honey production. The mean TE was 77% that shows the deviation of actual from optimal production amounts. Beekeeping experience, education, level, cooperative membership, participation in improved beehive technology demonstration and extension contact had significant effects on TE. The result of PSM indicates that the adoption of improved beehive technology has a positive and significant effect on production efficiency, as measured by TE. Farmers who adopted improved beehive technology were less technically inefficient than those who did not adopt. Conclusion Overall, the estimated 19.5% difference in TE among the two groups shows there is considerable room for the improvement of beekeeping by efficient utilization of inputs and also provides strong evidence for the diffusion of improved beehives in Kaffa Sheka and Bench Maji zones.