Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management

Ohiomah Ifije; Clinton Aigbavboa; Nita Sukdeo

doi:10.1007/978-3-030-80462-6_30

Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management

Ohiomah Ifije
, Clinton Aigbavboa
, Nita Sukdeo

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	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
Editors	Stefan Trzcielinski, Beata Mrugalska, Waldemar Karwowski, Emilio Rossi, Massimo Di Nicolantonio
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	237-244
Number of pages	8
ISBN (Print)	9783030804619
DOIs	https://doi.org/10.1007/978-3-030-80462-6_30
Publication status	Published - 2021
Event	AHFE Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021 - Virtual, Online Duration: 25 Jul 2021 → 29 Jul 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	274
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	AHFE Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021
City	Virtual, Online
Period	25/07/21 → 29/07/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Manufacturing
Resource commitment
Reverse supply chain
South Africa

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-3-030-80462-6_30

Cite this

Ifije, O., Aigbavboa, C., & Sukdeo, N. (2021). Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management. In S. Trzcielinski, B. Mrugalska, W. Karwowski, E. Rossi, & M. Di Nicolantonio (Eds.), 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 (pp. 237-244). (Lecture Notes in Networks and Systems; Vol. 274). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-80462-6_30

Ifije, Ohiomah ; Aigbavboa, Clinton ; Sukdeo, Nita. / Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management. 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. editor / Stefan Trzcielinski ; Beata Mrugalska ; Waldemar Karwowski ; Emilio Rossi ; Massimo Di Nicolantonio. Springer Science and Business Media Deutschland GmbH, 2021. pp. 237-244 (Lecture Notes in Networks and Systems).

@inproceedings{28e6efe4b534499c9c86f3a018b4a0f7,

title = "Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management",

abstract = "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{\textquoteright}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.",

keywords = "Manufacturing, Resource commitment, Reverse supply chain, South Africa",

author = "Ohiomah Ifije and Clinton Aigbavboa and Nita Sukdeo",

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booktitle = "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",

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Ifije, O, Aigbavboa, C & Sukdeo, N 2021, Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management. in S Trzcielinski, B Mrugalska, W Karwowski, E Rossi & M Di Nicolantonio (eds), 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. Lecture Notes in Networks and Systems, vol. 274, Springer Science and Business Media Deutschland GmbH, pp. 237-244, AHFE Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, 2021, Virtual, Online, 25/07/21. https://doi.org/10.1007/978-3-030-80462-6_30

Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management. / Ifije, Ohiomah; Aigbavboa, Clinton ; Sukdeo, Nita.
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. ed. / Stefan Trzcielinski; Beata Mrugalska; Waldemar Karwowski; Emilio Rossi; Massimo Di Nicolantonio. Springer Science and Business Media Deutschland GmbH, 2021. p. 237-244 (Lecture Notes in Networks and Systems; Vol. 274).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 - https://www.scopus.com/pages/publications/85142222062

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 -

Ifije O, Aigbavboa C , Sukdeo N. Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management. In Trzcielinski S, Mrugalska B, Karwowski W, Rossi E, Di Nicolantonio M, editors, 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. Springer Science and Business Media Deutschland GmbH. 2021. p. 237-244. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-80462-6_30

Structural Equation Modelling of Resource Commitment Constructs as a Predictor of Implementation of Reverse Supply Chain Management

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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