Analysing the Influence of Logistics, Corruption, FDI and GDP on Global Competitiveness: a Cross-Sectional Study

Naduni Kalansuriya (), Shara Silva (), Nishen Perera (), Banuli Wanigarathna (), Ruwan Jayathilaka (), Parami Paranavitana () and Saliya C. Arachchige ()
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Naduni Kalansuriya: SLIIT Business School, Sri Lanka Institute of Information Technology
Shara Silva: SLIIT Business School, Sri Lanka Institute of Information Technology
Nishen Perera: SLIIT Business School, Sri Lanka Institute of Information Technology
Banuli Wanigarathna: SLIIT Business School, Sri Lanka Institute of Information Technology
Ruwan Jayathilaka: Department of Information Management, SLIIT Business School, Sri Lanka Institute of Information Technology
Parami Paranavitana: MAS Capital (Pvt) Ltd
Saliya C. Arachchige: SLIIT Business School, Sri Lanka Institute of Information Technology

Journal of the Knowledge Economy, 2024, vol. 15, issue 3, No 128, 13532-13551

Abstract: Abstract This ground-breaking research investigates the impact of the logistics performance index (LPI), corruption perception index (CPI), foreign direct investment (FDI), and per capita gross domestic product (PGDP) on the global competitiveness index (GCI). This research is motivated by the willingness to uncover the collective impact of the considered independent variables that strengthen the global competitiveness of countries in the world region. Using cross-sectional data from 110 countries in 2018, the study employed the forward stepwise technique of Ordered Probit Regression Model to analyse the impact of aforementioned variables towards the categorised levels of GCI unveiling varying impacts on high, moderate and low-ranked nations. The research findings revealed that logistic performance, FDI and PGDP significantly contribute to global competitiveness, while the impact of CPI deemed insignificant. This research will contribute to the existing literature by providing theoretical and empirical insights into decision-making processes related to global competitiveness. Furthermore, the results will offer valuable information to policymakers and regulatory authorities seeking to enhance competitiveness on a global scale.

Keywords: Logistics performance index; Corruption perception index; Global competitive index; Foreign direct investment; Per capita gross domestic product; Ordered probit regression; Stepwise method (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13132-023-01615-z

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