Measuring the importance of the Global Supply Chain for economic development based on diachronic data of the Logistics Performance Index (LPI)

Research Hypotheses
Our research focuses on understanding the relationship between the Logistics Performance Index (LPI) and GDP per capita across 169 countries over a span of 16 years, from 2007 to 2023. The hypothesis driving this study is twofold:
1. Primary Hypothesis: There is a statistically significant and positive correlation between a country’s LPI and its GDP per capita. This hypothesis is grounded in the understanding that higher logistics performance, as measured by the LPI, reflects more efficient trade and economic activities, which in turn should contribute to higher economic outputs and, therefore, higher GDP per capita.
2. Secondary Hypothesis: Among various indicators related to supply chain efficiency, the LPI is the most accurate predictor of GDP per capita.
To test these hypotheses, we compiled a dataset that includes annual LPI scores, other supply chain performance variables and GDP per capita values for 169 countries from 2007 to 2023
Data Analysis
The data was analyzed using SPSS, a statistical software package widely used in academic research. The analysis involved several key steps:
• Correlation Analysis: Pearson correlation coefficients were calculated to assess the strength and direction of the relationship between LPI and GDP per capita across different countries and years.
• Multivariate Linear Regression: A series of regression models were developed to determine the extent to which LPI and other logistics-related variables predict GDP per capita.
• Proximity to Mean Analysis: This analysis was conducted to evaluate the consistency of the relationship between LPI and GDP per capita across different contexts, identifying variables that showed a stable and significant impact on economic outcomes.
How to Interpret the Data
The dataset provides a comprehensive view of the relationship between logistics performance and economic output. When analyzing the data, the following points should be considered:
1. Correlation Between LPI and GDP per Capita:
o The data reveals a strong positive correlation between the LPI and GDP per capita, indicating that countries with higher logistics performance tend to have higher economic output per person. This suggests that improvements in logistics efficiency, such as better customs procedures and infrastructure, can significantly contribute to economic growth.
2. Significance of LPI Components:
o Each component of the LPI plays a role in the overall score, and understanding these components can provide deeper insights into specific areas of strength or weakness in a country’s logistics performance.
3. Impact of External Factors:
o The data spans a period that includes significant global events, such as the 2008 financial crisis and the COVID-19 pandemic. These events may cause noticeable fluctuations in both LPI scores and GDP per capita.