Relationships of Selected Key Logistics Factors and Logistics Performance Index of Sub-Saharan African Countries

Logistics and supply chain bottlenecks are magnified with inefficient business processes and can result in increases of trade costs. Logistics Performance Index is a measure of how well different countries perform in their logistics activities to increase trade efficiencies. This study tries to explore the relationship of critical logistics factors with logistics performance index (LPI) developed by the World Bank. By taking Rwanda as a case study, the paper also explores the performance differences in logistics between landlocked and coastal countries, among countries within the same region, and income group. It shades light how a landlocked and low-income country was able in a decade to improve its logistics performance. The findings of two-stage least square provides a single estimated logistics index. It can explain the multiple logistic indicators which can be used to improve the ability to compete and improve logistics performance. Moreover, countries in the study, as well as other countries can utilize this estimated index to target policy actions to improve logistics operations

Basic efficiency measurement of Hungarian logistics centres using data envelopment analysis

Data envelopment analysis (DEA) is a non-parametric linear programming method capable of evaluating the efficiency of decision making units (DMUs) of various kinds. It is widely utilised for the ranking of companies operating in the transport sector. It is, however, not very often applied for the analysis of logistics centres, although its characteristics make it perfectly suitable for this purpose. The present article investigates how DEA can be used for the evaluation of Hungarian logistics centres. The statistic data of 26 DMUs have been collected and the sample has been corrected so as to include only the firms with sufficient data available for an extensive efficiency rating, leaving 12 logistics centres in the pool. Their efficiency was examined as based on the following inputs: surface size of offices, number of employees, surface of available storage space (excluding external storage facilities). The output considered was the volume of total sales revenue and in a second test, the tons of freight hand led. Aggregate, pure technical and scale efficiencies have also been determined

Assessing the logistics efficiency of European countries by using the DEA-PC methodology

Data envelopment analysis is a non-parametric linear programming method widely used for the efficiency evaluation of decision making units active in the transport sector. However, it is seldom applied for the efficiency assessment of logistics efficiency at a macro level. The article presents such an example which is at the same time the very first application of a lately developed methodology where data envelopment analysis is combined with analytic hierarchy process to yield an appropriate tool for efficiency evaluation with full ranking. The logistics efficiency of 29 European countries is tested with the new DEA-PC (pairwise comparison) methodology while it is also compared with the results gained with the original DEA method. Furthermore, the outcomes are also evaluated in light of the ‘Logistics quality and competence’ index of the Logistics Performance Indicator (LPI), a major international survey into the logistics competence of countries. Thus, the results of traditional DEA and DEA-PC are both weighted against survey data which is also a novelty in the logistics sector

Research on Logistics Network Infrastructure Based on HCA and DEA-PCA Approach

Abstract—Logistics Network Infrastructure (LNI) is an important area of Logistics Infrastructure Capability (LIC). The connotation of LNI is analyzed in this paper. Compared with the extensive research on LNI in developed world, empirical work is still rare in China. In this paper the theory of LNI is firstly overviewed. Then a new evaluation index system for LNI evaluation is set up which contains factors that reflect economic development level, transportation accessibility and turnover volume of freight traffic. Thirdly, an empirical study is carried out by usin