TY - JOUR
T1 - Exploring the role of blockchain technology, warehouse automation, smart routing, and cloud computing in logistics performance
AU - Rahman, Md Habibur
AU - Menezes, Brenno Castrillon
AU - Baldacci, Roberto
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024/8/21
Y1 - 2024/8/21
N2 - Recently, there has been a heightened emphasis on employing smart technologies for evaluating logistics performance, and hence we have considered four key technologies, namely blockchain technology (BT), warehouse automation (WA), smart routing (SR), and cloud computing (CC), and measured their aggregate impacts on logistics performance. We have considered these four technologies as exogenous constructs, and the logistics performance factors as endogenous constructs. First, we generate 23 items or indicators under those technologies and measure their loadings to determine how strongly they are linked to each technology. Next, we determine how strongly technologies are linked to logistics performance factors. Finally, we test our theoretical model using partial least squares structured equation modeling (PLS-SEM). Our findings confirm that the constructs and indicators in our theoretical framework meet the criteria, supported by PLS-SEM results and fit indices. This study advances logistics theory by highlighting smart technology adoption in practice and supporting institutional theory.
AB - Recently, there has been a heightened emphasis on employing smart technologies for evaluating logistics performance, and hence we have considered four key technologies, namely blockchain technology (BT), warehouse automation (WA), smart routing (SR), and cloud computing (CC), and measured their aggregate impacts on logistics performance. We have considered these four technologies as exogenous constructs, and the logistics performance factors as endogenous constructs. First, we generate 23 items or indicators under those technologies and measure their loadings to determine how strongly they are linked to each technology. Next, we determine how strongly technologies are linked to logistics performance factors. Finally, we test our theoretical model using partial least squares structured equation modeling (PLS-SEM). Our findings confirm that the constructs and indicators in our theoretical framework meet the criteria, supported by PLS-SEM results and fit indices. This study advances logistics theory by highlighting smart technology adoption in practice and supporting institutional theory.
KW - Blockchain technology
KW - cloud computing
KW - logistics performance
KW - smart routing
KW - warehouse automation
UR - http://www.scopus.com/inward/record.url?scp=85201668101&partnerID=8YFLogxK
U2 - 10.1080/21693277.2024.2393614
DO - 10.1080/21693277.2024.2393614
M3 - Article
AN - SCOPUS:85201668101
SN - 2169-3277
VL - 12
JO - Production and Manufacturing Research
JF - Production and Manufacturing Research
IS - 1
M1 - 2393614
ER -