— grouping projects with similar purposes into clusters and evaluating overall performance by cluster — will enable comparative evaluation of different project sectors and provide meaningful insights in devising strategic plans for development assistance. With the establishment of the Country Partnership Strategy (CPS), the demand for comprehensive evaluation of aid performance at the industry level or the overall national development level, rather than at the level of each individual project, has been increasing. The research pursues evaluation in line with this policy demand.
   Recently, there has been a growing consensus in the domestic and international aid community that sporadic project aid should be avoided, while achieving CPS-level performance goals, and seeking state-level development assistance that meets the national development strategies of recipient countries.
   Chapter 2 examines the current state of Rwanda’s agricultural ODA as well as its main characteristics. Based on the cluster classification criteria of this study, it was observed that Korea dispersed aid funds in a more decentralized manner compared to other developed countries. In addition, various aid projects of different characteristics were observed within a single cluster, making fragmentation in aid practice more evident. For example, in the case of the “agricultural development” cluster, three aid agencies have each carried out assistance projects with different characteristics. Aid projects have been executed independently without any link among different clusters. Considering Korea's relatively small aid scale and insufficient aid capacity, a decentralized resource allocation structure and sporadic aid delivery are not desirable.
   In Chapter 3, a comprehensive evaluation was conducted on Korea’s ODA projects in Rwanda’s agricultural sector between 2013 and 2017, using three frameworks: planning, operation and performance. The evaluation criteria consists of four indicators (relevance, efficiency, effectiveness and sustainability) widely used in the evaluation of international development projects. This study devised Cluster Performance Index (CPI) by numerically calculating each cluster’s performance by each indicator. In addition, the Resource Allocation Index (RAI) was formulated to assess Korea’s presence in the Rwandan agriculture ODA sector, where a number of international actors competitively provide aid. The RAI and CPI were then mapped in quandrants to visualize each cluster’s performance compared to the amount of funds injected. The results of the comprehensive evaluation are summarized as follows.
   First, in terms of planning or strategic management, it appears that projects are mostly planned appropriately, but in some clusters, large amounts of the budget have been invested in poorly planned projects. Project sites being dispersed across multiple provinces was also a problem. Although Rwanda’s small land area reduces inconveniences caused by such dispersion of sites, it would still be advisable to carry out similar or related projects in neighboring areas and to strategically conduct projects in the same cluster within the same district or cell through aid harmonization. Such strategic planning would promote efficiency in project management and lead to synergy between projects.
   Secondly, in terms of operational management, there was considerable room for improvement in all clusters. Particularly, all clusters scored below average in the Monitoring and Evaluation (M&E) category. The number of monitoring sessions should be increased, and there is much to be improved in terms of monitoring quality. While it is important to build partnerships with aid agencies in the recipient countries in order to implement projects efficiently, all clusters scored moderately in this category. In terms of the rate of budget execution versus budget commitment, most clusters implemented their budgets efficiently as planned. While there were few cases of project periods being extended, there were several cases of modifications being made to the project contents. Considering that project planning cannot be perfect due to the shortage of professional ODA consulting agencies in Korea’s ODA sector, this study avoided lowering CPI scores entirely based on the number of changes made. Instead, the background and gravity of each change were considered in the evaluation. Nevertheless, some projects had made significant changes that could undermine project efficiency, indicating some improvements would be necessary in terms of the efficiency of project operations.
   Third, in terms of performance evaluation, all clusters scored relatively high in effectiveness. On average, scores were also high in sustainability, but relatively lower in effectiveness. Within the effectiveness category, scores were particularly high in goal achievement with many projects exceeding the planned goals. On the other hand, some inadequacies were revealed in ex-ante evaluations of the project implementation environment. While it is important to achieve planned goals, it is also crucial to improve effectiveness by considering the characteristics of the project site during project implementation. Rwanda’s distinct project environment characterized by a high percentage of unschooled farmers and multiple official languages also necessitates improvement in communication through strengthening the capacities of local coordinators and interpreters, or having dispatched Korean workers learn the local languages. In terms of sustainability, no case was observed where Rwandan government’s policy changes hampered the sustainability of projects. On the contrary, risk management was found to be relatively inadequate in all clusters. Stakeholders tended to perceive potential risks as relatively less important than other factors. Feasibility study reports also had very little content related to risk analysis, and in-depth analyses were scarce. In some cases, project sustainability was jeopardized due to poor response to risks. Further efforts should be made to analyze risks at the planning stage, and risk management capacities should be strengthened by sharing cases of risk occurrence and successful risk management. In terms of follow-up management, all clusters scored average. While post-completion project maintenance largely depends on the coordination system with the recipient country as well as the administration capacity of the local government in the project site, as projects are mainly carried out in areas with high poverty rates, the local governments tend to lack capacity. Korean ODA agencies can do little about the local governments’ capacity, while they can make efforts to strengthen cooperation with the recipient country to ensure project sustainability. The better the partnership is, the more willing the recipient government will be to maintain completed projects. Overall, in terms of cluster average scores, projects have done best in the area of effectiveness, followed by relevance and sustainability, and scored lowest in efficiency.
   Chapter 4 comprehensively analyzes Korea’s ODA to Rwanda’s agriculture sector through network analysis and contribution analysis. Firstly, the “consistency” of Korea’s ODA with regard to the goals presented in the Rwandan national development strategy and the CPS of the Korean government was measured through network analysis. While in the previous chapter the degree of consistency was simply measured by indexing, in this chapter, the degree was measured quantitatively. Considering that Korea’s CPS is based on the development needs of the recipient country, it could be said that the CPS and Rwanda’s national development strategy share common goals, but this study assumes that in reality they could have different priorities and examines both sides independently when measuring the degree of relevance of Korea’s agricultural ODA with regard to them. Secondly, using System Dynamics Simulation, this study estimated the contribution of Korea’s agricultural ODA to Rwanda’s GDP and its employment inducement effect. The contribution of Korean ODA to Rwanda’s GDP was analyzed by industry, and the contribution of the agricultural sector relative to that of other sectors was subsequently calculated in proportion.
   Quantitative measurement of the consistency of Korean project- type ODA with respect to Rwanda’s national development needs showed the highest consistency with the goal of expanding agricultural productivity, while there was little consistency with other objectives such as good governance, economic integration, etc. Combined analysis of project-type ODA and training-type ODA showed links, albeit weak, to development goals in fields other than agriculture. Moreover, contribution analysis showed that Korea’s agricultural ODA to Rwanda has contributed approximately $100 million to Rwanda’s GDP in 2016. Agricultural ODA contributed more to Rwanda’s GDP than ODA in any other field. This implies that Korea should continue to prioritize the agricultural sector in its ODA to Rwanda. Furthermore, it was estimated that Korea’s agricultural ODA has led to an average of about 4,000 jobs being created per year over the analysis period.
   Chapter 5 draws suggestions and lessons from the aforementioned observations and analysis results and presents several measures to improve aid quality, summarized as follows. First, budget allocation optimization was presented as a means of better strategic planning and management. Strategic allocation of ODA resources is directly related to efficiency in goal achievement and is an important issue to be addressed at the planning stage. Rwanda is one of Korea’s 24 priority partner countries, and ODA budget allocation is becoming more complex as aid sectors and means in agriculture grow diverse and participating entities expand. In turn, strategically deciding how much resources, within a given budget, are to be invested in which sector through systematic analysis has emerged as an important issue. This study seeks ways to optimize budget allocation by applying cluster performance index (CPI) and resource allocation index (RAI) values to Fiedler’s Contingency Theory Model. According to the analysis, resource allocation efficiency would be improved if ODA is expanded significantly in the Agricultural Training and Education cluster (C3), gradually expanded in the Agricultural Policy and Administration cluster (C1) and Rural Development cluster (C5), and gradually reduced in the Agricultural Development (C2) and Agricultural Cooperatives (C4) clusters.
   Secondly, this chapter presents measures to improve monitoring efficiency in terms of strategic operational management. Project evaluation results showed low overall efficiency scores across all clusters, and among efficiency assessment categories, scores were particularly low in M&E. Based on stakeholder interviews, this study proposes that considering the distinct features of agricultural ODA projects, agencies could dispatch Korean or local employees in the vicinity of the project site to frequently monitor projects in order to enhance efficiency. Moreover, with projects conducted by multiple agencies, monitoring quality could be improved by enabling monitoring experts to obtain necessary information through direct communication with the recipient government and project beneficiaries, rather than by relying on project implementation agencies. In addition, this chapter points out that project efficiency and performance can only be assessed properly with a thorough baseline survey to refer to in evaluating progress and performance with regard to the project plan. Furthermore, this chapter emphasizes the necessity to supplement inaccurate data through qualitative assessment when considering the risk of data collected from surveying farmers lacking accuracy. Lastly, this chapter suggests that establishing feedback measures for monitoring results warrants more attention and effort.
   Third, this study proposes enhancing synergy in ODA through cluster integration. Among its five East African priority partner countries, Korea provides the largest amount of agricultural ODA to Rwanda. Compared to other advanced donor countries, Korea’s agricultural aid to Rwanda is characterized by decentralized investment of aid funds. Differences in the allocation of funds could be due to each donor country’s unique aid policies or comparative advantages, so it is not an issue to be simply judged right or wrong. However, such dispersed allocation is not desirable considering Korea’s limited aid capacity and the “selection and concentration” ODA strategy. This study proposes intracluster, intercluster linkage or convergence as a strategy to enhance ODA effectiveness. We must seek measures to combine individual projects currently implemented and build a meaningful program. Combining multiple projects and forming a program targeting a single purpose can reduce the administrative burden caused by fragmentation and enhance aid effectiveness. However, since it would be difficult to create a “convergence program” simply by tying existing projects without a framework established at the planning stage, we would need an approach where a core cluster is selected as the backbone and other clusters are linked around it or reinforced with future projects.
   Lastly, this study presents the agricultural value chain program approach. Rwanda’s agricultural development strategy aims to shift away from its subsistence-level agriculture and transform into a market-led structure, while Korea’s CPS is aimed at increasing agricultural productivity and increasing farmers’ income by strengthening self-help capacity in rural communities. Considering Rwanda’s development goals and Korea’s aid objectives, Korea’s ODA approach needs to expand beyond the current individual project level to a higher program level supporting the value chain. Given Korea’s limited aid capacity and experience, it is likely that Korea would only be able to plan “narrow-range” value chain projects in the initial stage, and it would first need to seek connection and convergence between the agricultural sector and other key areas such as education and ICT. This is also presented as an important strategy in Korea’s CPS. Rwanda is a country with underdeveloped agriculture and has been pushing for transformation in its agricultural structure through value-added agricultural products, and demand is expected to surge in the agricultural industry; in turn, Korea should include areas such as processing, packaging, and quality control technologies in vocational education and training projects to seek synergy in ODA. Projects that connect agriculture with ICT should also be actively promoted. As ICT has cross-cutting characteristics, it should be used as a solution for improving access to technical information (cultivation techniques), spreading market information on agricultural products (trading volume and price), and increasing financial accessibility (mobile microfinance and payments). In Rwanda, the proportion of people who own mobile phones has surged from 6% in 2006 to 71% in 2017.
   To successfully lead Rwanda’s agricultural ODA, efficient operation (implementation) management must be emphasized along with systematic planning (strategic) management. Many of the improvement measures presented in this study regard planning and management. As most agricultural ODA projects are carried out in rural areas with poor conditions, problems such as additional expenses due to unexpected logistical costs, weak monitoring, and delays in project schedules are inevitable. Considering such realities, the stance of this study is that strengthening the planning stage through, for instance, feasibility studies and basic design studies (BDS) based on sufficient information is more important than repeatedly pointing out similar problems that recur in operational management. Budget allocation at the planning stage is important in terms of strategic management because funds should be allocated appropriately to each cluster early on for ODA predictability and effectiveness to be enhanced. Enhanced aid predictability helps improve the stability of project operations, which can lead to higher aid quality. Rational allocation of aid funds is also in line with the policy demand calling for a top-down approach. Without proper planning and adequate resource allocation corresponding to each cluster’s respective potential aid effectiveness, there will be limits to achieving goals no matter how much effort and time is spent on operation and management. While it is important to increase the overall quantity of aid, in terms of achieving objectives, it is essential that given budgets are strategically allocated and efficiently executed.