An ANP-based network to measure the impact of Lean production on organisational performance
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | An ANP-based network to measure the impact of Lean production on organisational performance |
| 2. | Creator | Author's name, affiliation, country | José Luis Ruano Pérez; Universitat Politècnica de València; Spain |
| 2. | Creator | Author's name, affiliation, country | Raúl Rodríguez-Rodríguez; Universitat Politècnica de València; Spain |
| 2. | Creator | Author's name, affiliation, country | Juan-José Alfaro Saiz; Universitat Politècnica de València; Spain |
| 2. | Creator | Author's name, affiliation, country | María-José Verdecho; Universitat Politècnica de València; Spain |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Lean Production, Organisational Performance, Analytic Network Process |
| 4. | Description | Abstract | Purpose: The main objective of this research is to design a decision-making network, based on the Analytic Network Process (ANP) technique (Saaty, 1996), which will include the main elements to take into account when stating the effect that the application of LP techniques has got on the performance of an organisation, measured this through a Performance Measurement System (PMS). Design/methodology/approach: The authors have carried out a scientific literature search to state what the main LP techniques are –and how to group them into different clusters- and have then applied the ANP, its first phase, in order to design the decisional network. Findings: There is a gap in the literature when trying to identify and quantify to what extent the implementation of LP techniques affects to organisational performance. The ANP is an appropriate technique to do so due to the need of gathering and quantifying experts’ opinions. Originality/value: The designed ANP-based network to measure the impact of LP over organisational performance is a novel approach. This paper justifies its usage and paves the way to implement the rest of the ANP phases in future research work. |
| 5. | Publisher | Organizing agency, location | OmniaScience (Omnia Publisher SL) |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2018-04-06 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://www.jiem.org/index.php/jiem/article/view/2536 |
| 10. | Identifier | Digital Object Identifier (DOI) | https://doi.org/10.3926/jiem.2536 |
| 11. | Source | Title; vol., no. (year) | Journal of Industrial Engineering and Management; Vol 11, No 2 (2018): Special Issue: Engineering Digital Transformation |
| 12. | Language | English=en | en |
| 13. | Relation | Supp. Files | |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2018 José Luis Ruano Pérez, Raúl Rodríguez-Rodríguez, Juan-José Alfaro Saiz, María-José Verdecho https://creativecommons.org/licenses/by-nc/4.0 |