TY - GEN
T1 - Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management
AU - Ifije, Ohiomah
AU - Aigbavboa, Clinton
AU - Sukdeo, Nita
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
PY - 2021
Y1 - 2021
N2 - This paper reports the use of Structural Equation Modelling technique to test the influence of resource commitment as a predictor of reverse supply chain management implementation. The study was conducted among professionals involved in supply chain and reverse supply chain using a survey method for data collection. At total of 314 questionnaires were filled completely and retuned back. The data gathered was analysed using structural equation modelling, which was used to assess the factorial structure of the constructs, the structural equation modelling software used was the Amos 26.0. the factorial structure, reliability and validity of resource commitment indicator variables were investigated. The finding revealed a positive influence on the outcome of the implementation of RSC. Further SEM analysis revealed that the Rho and the Cronbach’s alpha coefficients of internal consistency were over 0.70 criterions for acceptability, and the constructs shows a good mode fit to the sample data.
AB - This paper reports the use of Structural Equation Modelling technique to test the influence of resource commitment as a predictor of reverse supply chain management implementation. The study was conducted among professionals involved in supply chain and reverse supply chain using a survey method for data collection. At total of 314 questionnaires were filled completely and retuned back. The data gathered was analysed using structural equation modelling, which was used to assess the factorial structure of the constructs, the structural equation modelling software used was the Amos 26.0. the factorial structure, reliability and validity of resource commitment indicator variables were investigated. The finding revealed a positive influence on the outcome of the implementation of RSC. Further SEM analysis revealed that the Rho and the Cronbach’s alpha coefficients of internal consistency were over 0.70 criterions for acceptability, and the constructs shows a good mode fit to the sample data.
KW - Manufacturing
KW - Resource commitment
KW - Reverse supply chain
KW - South Africa
UR - http://www.scopus.com/inward/record.url?scp=85142222062&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-80462-6_30
DO - 10.1007/978-3-030-80462-6_30
M3 - Conference contribution
AN - SCOPUS:85142222062
SN - 9783030804619
T3 - Lecture Notes in Networks and Systems
SP - 237
EP - 244
BT - Advances in Manufacturing, Production Management and Process Control - Proceedings of the AHFE 2021 Virtual Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021
A2 - Trzcielinski, Stefan
A2 - Mrugalska, Beata
A2 - Karwowski, Waldemar
A2 - Rossi, Emilio
A2 - Di Nicolantonio, Massimo
PB - Springer Science and Business Media Deutschland GmbH
T2 - AHFE Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021
Y2 - 25 July 2021 through 29 July 2021
ER -