Managing changes initiated by industrial big data technologies: A technochange management model

Fei Xing; Guochao Peng; Tian Liang; Simin Zuo; Shuyang Li

doi:10.1007/978-3-030-21935-2_7

Managing changes initiated by industrial big data technologies: A technochange management model

Fei Xing^*, Guochao Peng, Tian Liang, Simin Zuo, Shuyang Li

^*Corresponding author for this work

Accounting

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

Abstract

With the adoption of Internet of Things and advanced data analytical technologies in manufacturing firms, the industrial sector has launched an evolutionary journey toward the 4th industrial revolution, or so called Industry 4.0. Industrial big data is a core component to realize the vision of Industry 4.0. However, the implementation and usage of industrial big data tools in manufacturing firms will not merely be a technical endeavor, but can also lead to a thorough management reform. By means of a comprehensive review of literature related to Industry 4.0, smart manufacturing, industrial big data, information systems (IS) and technochange management, this paper aims to analyze potential changes triggered by the application of industrial big data in manufacturing firms, from technological, individual and organizational perspectives. Furthermore, in order to drive these changes more effectively and eliminate potential resistance, a conceptual technochange management model was developed and proposed. Drawn upon theories reported in literature of IS technochange management, this model proposed four types of interventions that can be used to copy with changes initiated by industrial big data technologies, including human process intervention, techno-structural intervention, human resources management intervention and strategic intervention. This model will be of interests and value to practitioners and researchers concerned with business reforms triggered by Industry 4.0 in general and by industrial big data technologies in particular.

Original language	English
Title of host publication	Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
Editors	Norbert Streitz, Shin’ichi Konomi
Publisher	Springer Verlag
Pages	75-87
Number of pages	13
ISBN (Print)	9783030219345
DOIs	https://doi.org/10.1007/978-3-030-21935-2_7
Publication status	Published - 2019
Event	7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States Duration: 26 Jul 2019 → 31 Jul 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11587 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
Country/Territory	United States
City	Orlando
Period	26/07/19 → 31/07/19

Bibliographical note

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

Keywords

Conceptual model
Industrial big data
Industry 4.0
Interventions
Technochange management

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-21935-2_7

Cite this

Xing, F., Peng, G., Liang, T., Zuo, S., & Li, S. (2019). Managing changes initiated by industrial big data technologies: A technochange management model. In N. Streitz, & S. Konomi (Eds.), Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings (pp. 75-87). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11587 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-21935-2_7

Xing, Fei ; Peng, Guochao ; Liang, Tian et al. / Managing changes initiated by industrial big data technologies : A technochange management model. Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. editor / Norbert Streitz ; Shin’ichi Konomi. Springer Verlag, 2019. pp. 75-87 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{906ad417fd35491d986a200684026352,

title = "Managing changes initiated by industrial big data technologies: A technochange management model",

abstract = "With the adoption of Internet of Things and advanced data analytical technologies in manufacturing firms, the industrial sector has launched an evolutionary journey toward the 4th industrial revolution, or so called Industry 4.0. Industrial big data is a core component to realize the vision of Industry 4.0. However, the implementation and usage of industrial big data tools in manufacturing firms will not merely be a technical endeavor, but can also lead to a thorough management reform. By means of a comprehensive review of literature related to Industry 4.0, smart manufacturing, industrial big data, information systems (IS) and technochange management, this paper aims to analyze potential changes triggered by the application of industrial big data in manufacturing firms, from technological, individual and organizational perspectives. Furthermore, in order to drive these changes more effectively and eliminate potential resistance, a conceptual technochange management model was developed and proposed. Drawn upon theories reported in literature of IS technochange management, this model proposed four types of interventions that can be used to copy with changes initiated by industrial big data technologies, including human process intervention, techno-structural intervention, human resources management intervention and strategic intervention. This model will be of interests and value to practitioners and researchers concerned with business reforms triggered by Industry 4.0 in general and by industrial big data technologies in particular.",

keywords = "Conceptual model, Industrial big data, Industry 4.0, Interventions, Technochange management",

author = "Fei Xing and Guochao Peng and Tian Liang and Simin Zuo and Shuyang Li",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 ; Conference date: 26-07-2019 Through 31-07-2019",

year = "2019",

doi = "10.1007/978-3-030-21935-2_7",

language = "English",

isbn = "9783030219345",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "75--87",

editor = "Norbert Streitz and Shin{\textquoteright}ichi Konomi",

booktitle = "Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings",

}

Xing, F, Peng, G, Liang, T, Zuo, S & Li, S 2019, Managing changes initiated by industrial big data technologies: A technochange management model. in N Streitz & S Konomi (eds), Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11587 LNCS, Springer Verlag, pp. 75-87, 7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019, Orlando, United States, 26/07/19. https://doi.org/10.1007/978-3-030-21935-2_7

Managing changes initiated by industrial big data technologies: A technochange management model. / Xing, Fei; Peng, Guochao; Liang, Tian et al.
Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. ed. / Norbert Streitz; Shin’ichi Konomi. Springer Verlag, 2019. p. 75-87 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11587 LNCS).

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

TY - GEN

T1 - Managing changes initiated by industrial big data technologies

T2 - 7th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019

AU - Xing, Fei

AU - Peng, Guochao

AU - Liang, Tian

AU - Zuo, Simin

AU - Li, Shuyang

PY - 2019

Y1 - 2019

N2 - With the adoption of Internet of Things and advanced data analytical technologies in manufacturing firms, the industrial sector has launched an evolutionary journey toward the 4th industrial revolution, or so called Industry 4.0. Industrial big data is a core component to realize the vision of Industry 4.0. However, the implementation and usage of industrial big data tools in manufacturing firms will not merely be a technical endeavor, but can also lead to a thorough management reform. By means of a comprehensive review of literature related to Industry 4.0, smart manufacturing, industrial big data, information systems (IS) and technochange management, this paper aims to analyze potential changes triggered by the application of industrial big data in manufacturing firms, from technological, individual and organizational perspectives. Furthermore, in order to drive these changes more effectively and eliminate potential resistance, a conceptual technochange management model was developed and proposed. Drawn upon theories reported in literature of IS technochange management, this model proposed four types of interventions that can be used to copy with changes initiated by industrial big data technologies, including human process intervention, techno-structural intervention, human resources management intervention and strategic intervention. This model will be of interests and value to practitioners and researchers concerned with business reforms triggered by Industry 4.0 in general and by industrial big data technologies in particular.

AB - With the adoption of Internet of Things and advanced data analytical technologies in manufacturing firms, the industrial sector has launched an evolutionary journey toward the 4th industrial revolution, or so called Industry 4.0. Industrial big data is a core component to realize the vision of Industry 4.0. However, the implementation and usage of industrial big data tools in manufacturing firms will not merely be a technical endeavor, but can also lead to a thorough management reform. By means of a comprehensive review of literature related to Industry 4.0, smart manufacturing, industrial big data, information systems (IS) and technochange management, this paper aims to analyze potential changes triggered by the application of industrial big data in manufacturing firms, from technological, individual and organizational perspectives. Furthermore, in order to drive these changes more effectively and eliminate potential resistance, a conceptual technochange management model was developed and proposed. Drawn upon theories reported in literature of IS technochange management, this model proposed four types of interventions that can be used to copy with changes initiated by industrial big data technologies, including human process intervention, techno-structural intervention, human resources management intervention and strategic intervention. This model will be of interests and value to practitioners and researchers concerned with business reforms triggered by Industry 4.0 in general and by industrial big data technologies in particular.

KW - Conceptual model

KW - Industrial big data

KW - Industry 4.0

KW - Interventions

KW - Technochange management

UR - http://www.scopus.com/inward/record.url?scp=85069699926&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-21935-2_7

DO - 10.1007/978-3-030-21935-2_7

M3 - Conference contribution

AN - SCOPUS:85069699926

SN - 9783030219345

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 75

EP - 87

BT - Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings

A2 - Streitz, Norbert

A2 - Konomi, Shin’ichi

PB - Springer Verlag

Y2 - 26 July 2019 through 31 July 2019

ER -

Xing F, Peng G, Liang T, Zuo S, Li S. Managing changes initiated by industrial big data technologies: A technochange management model. In Streitz N, Konomi S, editors, Distributed, Ambient and Pervasive Interactions - 7th International Conference, DAPI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. Springer Verlag. 2019. p. 75-87. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-21935-2_7

Managing changes initiated by industrial big data technologies: A technochange management model

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this