Analysis of Risk and Risk Management Strategies: The Case of Vegetable Producer Farmers in North Eastern Ethiopia (Published)
In Ethiopia, smallholders’ farmers and agricultural cooperatives produce vegetable crops in various agro-ecological zones across the country through the commercial initiative. Vegetable productions take place in a highly biophysical and economic environment, which poses various types of risks. As follows, this study identifies measures and analyses the key sources of risks in vegetable production, based on vegetable farmers’ perceptions. A simple random sampling technique was used in the selection of 394 smallholder vegetable farmers in North Eastern Ethiopia. Primary data collected through structured questionnaires and secondary data were preferentially used. Data collected were analysed using frequency distribution, arithmetic mean, and likert scales. This study recommends the training for vegetable farmers on risk management mechanisms, price supports mechanisms, providing the required infrastructure and the use of vegetable varieties that tolerates for natural disasters and pests/disease resistance.
A Novel Risk-Based Sampling Calculator (Published)
In addition to conventional sample size tables, few formulae were developed according to risk-based approaches and used for calculating the size of food commodity samples for inspection purposes. The current paper hypothesized the dependency of the sample size on both the risk level of the commodity or establishment and the confidence level of sampling. Accordingly, a sampling formula was developed using the commonly used 95% confidence level as fixed attribute. Application of the developed formula on populations and lots selected from three different sources, sample size tables, official authorities’ information, and calculated number of units for a fixed lot of hay (2,400 tonnes), revealed no significant difference between the sample sizes at the two selected risk probabilities 0.99 and 0.75. The findings of the current paper strongly support the use of lot units as basis for calculating the sample size rather than the lot weight, further the use of individual lot sizes to calculate sample sizes is more realistic than the common use of groups of lot and populations. The developed formula could confidently be used for calculating sample sizes for commodities of known risk probabilities.
Environmental and Social Impact Assessment for a Modular Power Plants Project in Menengai, Nakuru County, Kenya: Impact Identification, Evaluation and Risk Analysis (Published)
This paper is an extract from the Environmental and Social Impact Assessment report for the Menengai modular geothermal power plants projects for Geothermal Development Company Limited. Geothermal Development entails exploration drilling, steam collection, construction of power generation units and power transmission lines. Preliminary phase of land acquisition, vegetation clearing, construction and power generation is likely to cause environmental disturbance. Integrated resource utilization and environmental conservation needs an effective and efficient environmental and social management plan in order to facilitate sustainable implementation of the proposed project. Impact identification and risk analysis for any proposed project, are key for they provide useful information to decision- makers. This paper aims to provide a valuation’s perspective on how to best design and execute the impact identification and risk analysis to achieve results that align mitigation with identified potential impacts of the proposed project activities. The process involved identifying where the interactions were likely to occur between the proposed project activities and the receiving environments. A modified Leopold Matrix (LM) integrated with Lohani & Thanh methods were used to identify and estimate the magnitudes and importance of the potential impacts. Cumulative impacts were estimated using consequence and probability ranking model adapted from the South African Department of Environmental Affairs’ guideline document on EIA regulations of 1998. The model predicts the significance of impacts by considering magnitude, duration, spatial scale and factoring in probability of the impact to occur. Based on results of analysis, the cumulative impacts ranged from minor to moderate and can be mitigated.
Sensitivity analysis allows to evaluate how the resulting performance of the project at different values of given variables required for calculation. This type of analysis to determine the most critical variables that have the greatest affect on the feasibility and effectiveness of the project. In this paper we reviewed the concept and essence of the sensitivity analysis and it stages in addition to the study of one of the projects ability to continue using the net present value index NPV. the ranking of the major indices performed in order of importance to the outcome of the project. In other words, the size of the NPV according to the obtained values of the critical point and sensitive edge