Logistics-related determinants of regional gross domestic product - an exploratory investigation

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

Abstract

Many indices (e.g., Logistics Performance Index) provide a framework for evaluating the relative standing of countries in terms of infrastructure quality and performance. However, universal investment in infrastructure is not an efficient way to influence economic growth. It is critical to identify and assess all indicators of infrastructure for regions within a country and focus on improving infrastructure that underlies weak indictors. Research investigating the factors for regional wealth and regional economic growth is limited. With this backdrop, the purpose of this research is to investigate the relationship between regional logistics infrastructure and the regional GDP. In this comprehensive research, we evaluate the relationship between logistics-related infrastructure and regional GDP for all regions of Austria. This will help to better understand the relative importance of diverse logistics indicators in influencing economic development and provide insights for policy decision-making. The paper contributes to the ongoing discussion by analyzing the relationships between different components of infrastructure, the attractiveness of a region for business investment and the regional GDP. A theoretical model was developed and tested using partial least squares – structural equation modeling, with comprehensive data from all 34 regions in Austria. The findings show that business knowledge infrastructure has a positive effect on regional GDP via logistics infrastructure and business attractiveness.
OriginalspracheEnglisch
Seiten (von - bis)73-93
Seitenumfang21
FachzeitschriftEuropean Journal of Transport and Infrastructure Research
Jahrgang22
Ausgabenummer4
DOIs
PublikationsstatusVeröffentlicht - 5 Dez. 2022

Schlagwörter

  • Regional Logistics
  • Gross Domestic Product
  • Logistics Infrastructure
  • Partial Least Squares
  • Structural Equation Modeling

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