Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments

Carlos Montenegro; Marco Segura; Edison Loza-Aguirre

doi:10.1007/978-3-030-01171-0_11

Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments

Carlos Montenegro^*
, Marco Segura
, Edison Loza-Aguirre

^*Corresponding author for this work

Escuela Politecnica Nacional
CERAG

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

1 Scopus citations

Abstract

To be effective, sustainable development must maintain an equilibrium between its social, environmental and economic efforts. Several studies have suggested that an unbalance exists about the attention given to those three dimensions; however, few contributions have demonstrated such unbalance. This research describes a synthesis of two manual and semiautomatic methods published in the technical literature and includes additional developments, conceived to speed up and increase the accuracy of the analysis of the sustainable orientation of a corpus. The results are compared with the previous studies on about ten years of literature from top-tier journals dealing with Sustainable Supply Chain issues. The results confirm unbalance on research in this field. They show that most of the studies have been focussed on environmental and economic aspects, leaving aside social issues.

Original language	English
Title of host publication	Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018
Editors	Jezreel Mejia, Mirna Munoz, Alvaro Rocha, Adriana Pena, Marco Perez-Cisneros
Publisher	Springer Verlag
Pages	121-131
Number of pages	11
ISBN (Print)	9783030011703
DOIs	https://doi.org/10.1007/978-3-030-01171-0_11
State	Published - 2019
Externally published	Yes
Event	7th International Conference on Software Process Improvement, CIMPS 2018 - Guadalajara, Mexico Duration: 17 Oct 2018 → 19 Oct 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	865
ISSN (Print)	2194-5357

Conference

Conference	7th International Conference on Software Process Improvement, CIMPS 2018
Country/Territory	Mexico
City	Guadalajara
Period	17/10/18 → 19/10/18

UN SDGs

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

SDG 12 Responsible Consumption and Production

Keywords

Content analysis
Feature selection
LDA topic model
Sustainable Development
Sustainable Supply Chain

Access to Document

10.1007/978-3-030-01171-0_11

Cite this

Montenegro, C., Segura, M., & Loza-Aguirre, E. (2019). Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments. In J. Mejia, M. Munoz, A. Rocha, A. Pena, & M. Perez-Cisneros (Eds.), Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018 (pp. 121-131). (Advances in Intelligent Systems and Computing; Vol. 865). Springer Verlag. https://doi.org/10.1007/978-3-030-01171-0_11

Montenegro, Carlos ; Segura, Marco ; Loza-Aguirre, Edison. / Identifying the orientations of sustainable supply chain research using data mining techniques : Contributions and new developments. Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018. editor / Jezreel Mejia ; Mirna Munoz ; Alvaro Rocha ; Adriana Pena ; Marco Perez-Cisneros. Springer Verlag, 2019. pp. 121-131 (Advances in Intelligent Systems and Computing).

@inproceedings{64003f1aa3f24515bea13167c9294c77,

title = "Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments",

abstract = "To be effective, sustainable development must maintain an equilibrium between its social, environmental and economic efforts. Several studies have suggested that an unbalance exists about the attention given to those three dimensions; however, few contributions have demonstrated such unbalance. This research describes a synthesis of two manual and semiautomatic methods published in the technical literature and includes additional developments, conceived to speed up and increase the accuracy of the analysis of the sustainable orientation of a corpus. The results are compared with the previous studies on about ten years of literature from top-tier journals dealing with Sustainable Supply Chain issues. The results confirm unbalance on research in this field. They show that most of the studies have been focussed on environmental and economic aspects, leaving aside social issues.",

keywords = "Content analysis, Feature selection, LDA topic model, Sustainable Development, Sustainable Supply Chain",

author = "Carlos Montenegro and Marco Segura and Edison Loza-Aguirre",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 7th International Conference on Software Process Improvement, CIMPS 2018 ; Conference date: 17-10-2018 Through 19-10-2018",

year = "2019",

doi = "10.1007/978-3-030-01171-0\_11",

language = "Ingl{\'e}s",

isbn = "9783030011703",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "121--131",

editor = "Jezreel Mejia and Mirna Munoz and Alvaro Rocha and Adriana Pena and Marco Perez-Cisneros",

booktitle = "Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018",

}

Montenegro, C, Segura, M & Loza-Aguirre, E 2019, Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments. in J Mejia, M Munoz, A Rocha, A Pena & M Perez-Cisneros (eds), Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018. Advances in Intelligent Systems and Computing, vol. 865, Springer Verlag, pp. 121-131, 7th International Conference on Software Process Improvement, CIMPS 2018, Guadalajara, Mexico, 17/10/18. https://doi.org/10.1007/978-3-030-01171-0_11

Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments. / Montenegro, Carlos; Segura, Marco; Loza-Aguirre, Edison.
Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018. ed. / Jezreel Mejia; Mirna Munoz; Alvaro Rocha; Adriana Pena; Marco Perez-Cisneros. Springer Verlag, 2019. p. 121-131 (Advances in Intelligent Systems and Computing; Vol. 865).

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

TY - GEN

T1 - Identifying the orientations of sustainable supply chain research using data mining techniques

T2 - 7th International Conference on Software Process Improvement, CIMPS 2018

AU - Montenegro, Carlos

AU - Segura, Marco

AU - Loza-Aguirre, Edison

PY - 2019

Y1 - 2019

N2 - To be effective, sustainable development must maintain an equilibrium between its social, environmental and economic efforts. Several studies have suggested that an unbalance exists about the attention given to those three dimensions; however, few contributions have demonstrated such unbalance. This research describes a synthesis of two manual and semiautomatic methods published in the technical literature and includes additional developments, conceived to speed up and increase the accuracy of the analysis of the sustainable orientation of a corpus. The results are compared with the previous studies on about ten years of literature from top-tier journals dealing with Sustainable Supply Chain issues. The results confirm unbalance on research in this field. They show that most of the studies have been focussed on environmental and economic aspects, leaving aside social issues.

AB - To be effective, sustainable development must maintain an equilibrium between its social, environmental and economic efforts. Several studies have suggested that an unbalance exists about the attention given to those three dimensions; however, few contributions have demonstrated such unbalance. This research describes a synthesis of two manual and semiautomatic methods published in the technical literature and includes additional developments, conceived to speed up and increase the accuracy of the analysis of the sustainable orientation of a corpus. The results are compared with the previous studies on about ten years of literature from top-tier journals dealing with Sustainable Supply Chain issues. The results confirm unbalance on research in this field. They show that most of the studies have been focussed on environmental and economic aspects, leaving aside social issues.

KW - Content analysis

KW - Feature selection

KW - LDA topic model

KW - Sustainable Development

KW - Sustainable Supply Chain

UR - https://www.scopus.com/pages/publications/85054782295

U2 - 10.1007/978-3-030-01171-0_11

DO - 10.1007/978-3-030-01171-0_11

M3 - Contribución a la conferencia

AN - SCOPUS:85054782295

SN - 9783030011703

T3 - Advances in Intelligent Systems and Computing

SP - 121

EP - 131

BT - Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018

A2 - Mejia, Jezreel

A2 - Munoz, Mirna

A2 - Rocha, Alvaro

A2 - Pena, Adriana

A2 - Perez-Cisneros, Marco

PB - Springer Verlag

Y2 - 17 October 2018 through 19 October 2018

ER -

Montenegro C, Segura M, Loza-Aguirre E. Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments. In Mejia J, Munoz M, Rocha A, Pena A, Perez-Cisneros M, editors, Trends and Applications in Software Engineering - Proceedings of the 7th International Conference on Software Process Improvement CIMPS 2018. Springer Verlag. 2019. p. 121-131. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-01171-0_11

Identifying the orientations of sustainable supply chain research using data mining techniques: Contributions and new developments

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this