Abstract
Humanitarian and development workers often various challenges in developing and applying logic models in their interventions. Faced with a wide array of logic models that are often confusing, time and resource constraints further compound the decision to use a particular logic model or models, especially in emergencies. The decision of whether or not to use a single logic model such as the LFA or the ToC is not an easy one. Factors prevalent in the sector do not make this task an easy one. The question of whether the use of a single logic model independently should suffice to deliver the desired outcomes of the intervention remains paramount. Some humanitarian professionals and scholars argue that the use of a single logic model cannot sufficiently deliver the results of the intervention while others hold an opposing view. We sought to understand how time and resource constraints affect the choice of logic modes, the possibilities of using each logic model (ToC or LFA) independently to achieve projects/programme objectives as well as to make recommendations on the possibilities of uniting the key features of the ToC and the LFA into the Unified Logic Model Approach (ULMA) for better planning, implementation, monitoring and evaluation of humanitarian and development interventions. Primary data was collected as the main method of study between June and July 2024 with humanitarian and development professionals focused on the development of these tools and their use. Some of the categories of professionals interviewed included humanitarian and organisational CEOs, directors, coordinators, business development professionals, grant management professionals, programme and project managers, project officers, monitoring and evaluation specialists and assistants, sector leads and officers. These professionals from around the world were reached both online in their professional WhatsApp Groups and offline in their respective organisations (both local and international organisations). The survey questionnaire was structured to contain closed and open-ended questions and was informed by the core problems and the research hypothesis. The sample size included 284 participants and the data was analysed using the Chi-square (X 2 ) test of independence and descriptive statistics to determine the level of association and significance of the findings. The open-ended questions were analysed thematically to find relevant themes to further support the statistical analysis.
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More From: International Journal of Innovative Science and Research Technology (IJISRT)
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