Humanitarian Logistics and Service Delivery in Turkana County, Kenya

Significant funds are spent globally on humanitarian logistics (HL).This is due to the highly logistically dependent activities that are key in humanitarian aid projects and program delivery, as well as the unpredictability of disasters in terms of time (when they occur) and location (where they occur).The study sought to assess the effect of Humanitarian Logistics on Service Delivery in Turkana County.The following specific objectives informed the study: to determine the extent of implementation of Humanitarian Logistics in Turkana County, to assess the influence of Humanitarian Logistics on Service Delivery in Turkana County, and to investigate challenges encountered in the implementation of Humanitarian Logistics in Turkana County.The study adopted Descriptive approaches to explain and analyze the results of open-ended, qualitative questions.The population of the study comprised 18 Humanitarian Organizations domiciled in Turkana County with the highest level of involvement in humanitarian logistics.A census was adopted for this study because the study population was relatively small.The respondents were humanitarian logisticians, supply chain officers, procurement officers, or their equivalents, resulting in a total of 54 respondents.Descriptive analysis was used for open-ended questions, and inferential statistics was used for regression analysis.Results reveal that more than 50% of the respondents agree that humanitarian services in Turkana County are objective.The results further indicated a need for humanitarian logistics organizations to involve the local communities they serve, noting that most respondents were neutral on understanding the benefits of humanitarian logistics and its ability to meet local needs.The multiple regression analysis results of previously mentioned explanatory variables significantly influence humanitarian logistic service delivery; the coefficient of determination (R-squared) is 0.604.This implies that approximately 60.4%> 50% of the variability within the response variable can be explained by the four explanatory variables (inventory management, planning, transportation, and distribution).Still, in the ANOVA table, the regression sum of squares (6.241) was higher than the residual sum of squares (4.209).This difference indicates that the regression model accounts for a significant portion of the total variability in service delivery of humanitarian logistics.A close examination of the coefficients table reveals critical insight into the relationship between service delivery and other factors.For instance, only the distribution variable has a significant impact on service delivery.This is justified by the fact that the distribution variable has a P-value of 0.000 < 0.01.All other P-values (0.958, 0.612, and 0.106) are greater than 0.01, implying that there is no significant relationship with service delivery.This finding implies that the impact of planning, transportation, and inventory management might not be as pronounced as that of distribution.However, while planning, transportation, and inventory management may not exhibit strong individual impacts, their collective influence should not be dismissed.