TY - JOUR
T1 - The diffusion and the international context of logistics performance
AU - Lin, Pei Chun
AU - Cheng, T. C.E.
N1 - Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/3/4
Y1 - 2019/3/4
N2 - We spatially analyze 2016 data on logistics performance and country wealth using a linear regression framework to determine the relationships between a country’s logistics performance index (LPI) and its domestic product (GDP) per capita, and between its LPI and those of its neighbours. We find that richer countries score better on logistics and GDP per capita appears to have limited ability in accounting for variations in logistics performance, but a country’s LPI is closely related to those of its neighbours. We also find that very large differences in one country’s GDP per capita do not significantly change the world’s expected logistics performance level. We obtain the key insights that LPIs, each of which measures the performance along the logistics supply chain within a country, cannot in general be assumed to be mutually independent and that observations that are spatially close to one another are likely to be similar.
AB - We spatially analyze 2016 data on logistics performance and country wealth using a linear regression framework to determine the relationships between a country’s logistics performance index (LPI) and its domestic product (GDP) per capita, and between its LPI and those of its neighbours. We find that richer countries score better on logistics and GDP per capita appears to have limited ability in accounting for variations in logistics performance, but a country’s LPI is closely related to those of its neighbours. We also find that very large differences in one country’s GDP per capita do not significantly change the world’s expected logistics performance level. We obtain the key insights that LPIs, each of which measures the performance along the logistics supply chain within a country, cannot in general be assumed to be mutually independent and that observations that are spatially close to one another are likely to be similar.
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U2 - 10.1080/13675567.2018.1510907
DO - 10.1080/13675567.2018.1510907
M3 - Article
AN - SCOPUS:85052107748
SN - 1367-5567
VL - 22
SP - 188
EP - 203
JO - International Journal of Logistics Research and Applications
JF - International Journal of Logistics Research and Applications
IS - 2
ER -