Management approaches for Industry 4.0: A human resource management perspective

Saqib Shamim, Shuang Cang, Hongnian Yu, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

28 Citations (Scopus)

Abstract

Industry 4.0 is characterized by smart manufacturing, implementation of Cyber Physical Systems (CPS) for production, i.e., embedded actuators and sensors, networks of microcomputers, and linking the machines to the value chain. It further considers the digital enhancement and reengineering of products. It is also characterized by highly differentiated customized products, and well-coordinated combination of products and services, and also the value added services with the actual product or service, and efficient supply chain. All these challenges require continuous innovation and learning, which is dependent on people and enterprise's capabilities. Appropriate management approaches can play a vital role in the development of dynamic capabilities, and effective learning and innovation climate. This paper aims at offering a viewpoint on best suitable management practices which can promote the climate of innovation and learning in the organization, and hence facilitate the business to match the pace of industry 4.0. This paper is one of the initial attempts to draw the attention towards the important role of management practices in industry 4.0, as most of the recent studies are discussing the technological aspect. This paper also suggests empirical and quantitative investigation on these management approaches in the context of industry 4.0.

LanguageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5309-5316
Number of pages8
DOIs
Publication statusPublished - 14 Nov 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Conference

Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016
CountryCanada
CityVancouver
Period24/07/1629/07/16

Fingerprint

Human Resource Management
Human resource management
Industry
Climate
Innovation
Reengineering
Microcomputer
Supply Chain
Linking
Sensor Networks
Actuator
Enhancement
Manufacturing
Microcomputers
Supply chains
Sensor networks
Dependent
Actuators
Learning

Keywords

  • HR practices
  • industry 4.0
  • leadership style
  • management practices
  • organizational structure

Cite this

Shamim, S., Cang, S., Yu, H., & Li, Y. (2016). Management approaches for Industry 4.0: A human resource management perspective. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 5309-5316). [7748365] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2016.7748365
Shamim, Saqib ; Cang, Shuang ; Yu, Hongnian ; Li, Yun. / Management approaches for Industry 4.0 : A human resource management perspective. 2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 5309-5316
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Shamim, S, Cang, S, Yu, H & Li, Y 2016, Management approaches for Industry 4.0: A human resource management perspective. in 2016 IEEE Congress on Evolutionary Computation, CEC 2016., 7748365, Institute of Electrical and Electronics Engineers Inc., pp. 5309-5316, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/CEC.2016.7748365

Management approaches for Industry 4.0 : A human resource management perspective. / Shamim, Saqib; Cang, Shuang; Yu, Hongnian; Li, Yun.

2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 5309-5316 7748365.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Shamim S, Cang S, Yu H, Li Y. Management approaches for Industry 4.0: A human resource management perspective. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 5309-5316. 7748365 https://doi.org/10.1109/CEC.2016.7748365