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Relationships between Logistics Performance and Aspects of Sustainability: A Cross-Country Analysis

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  • Paul D. Larson

    (Department of SCM, University of Manitoba, 632 Drake Centre, Winnipeg, MB R3T 5V4, Canada)

Abstract

The purpose of this study is to investigate relationships between national logistics performance and dimensions of sustainability. A series of hypotheses are developed and tested using regression analysis of secondary data. The sources of data are the Sustainable Society Index (SSI) and the World Bank’s Logistics Performance Index (LPI). Fundamental aspects of social sustainability and well-being—a healthy, educated population, equality, good governance, and reasonable income distribution—are related to higher levels of logistics performance. In addition, while logistics performance is a driver of economic activity and success, it is also a contributor to environmental degradation in the form of harmful emissions. If economic growth is among a nation’s goals, its leaders are advised to support social well-being, along with technologies and practices for greater energy efficiency (and lower emissions) in transportation.

Suggested Citation

  • Paul D. Larson, 2021. "Relationships between Logistics Performance and Aspects of Sustainability: A Cross-Country Analysis," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:623-:d:478213
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    References listed on IDEAS

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    1. Piera Centobelli & Roberto Cerchione & Emilio Esposito & Shashi, 2020. "Evaluating environmental sustainability strategies in freight transport and logistics industry," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1563-1574, March.
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    6. Mingxuan Lu & Ruhe Xie & Peirong Chen & Yifeng Zou & Jie Tang, 2019. "Green Transportation and Logistics Performance: An Improved Composite Index," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
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    Cited by:

    1. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    2. Gürler, Hasan Emin & Özçalıcı, Mehmet & Pamucar, Dragan, 2024. "Determining criteria weights with genetic algorithms for multi-criteria decision making methods: The case of logistics performance index rankings of European Union countries," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    3. Elisabete Nogueira & Sofia Gomes & João M. Lopes, 2022. "The Key to Sustainable Economic Development: A Triple Bottom Line Approach," Resources, MDPI, vol. 11(5), pages 1-18, May.
    4. Magazzino, Cosimo & Alola, Andrew Adewale & Schneider, Nicolas, 2021. "The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: a quantile regression evidence," LSE Research Online Documents on Economics 117654, London School of Economics and Political Science, LSE Library.
    5. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2022. "A new artificial neural networks algorithm to analyze the nexus among logistics performance, energy demand, and environmental degradation," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 315-328.

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