Fail no more in industrial automation investment!: A novel technology success indicator model

Janne Leinonen; Jurgen Poesche; Ilkka Kauranen

Fail no more in industrial automation investment! A novel technology success indicator model

Janne Leinonen
, Jurgen Poesche
, Ilkka Kauranen

Department of Industrial Engineering and Management

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

3 Citations (Scopus)

Abstract

The research question of this study is how company management can make better decisions when deciding on industrial automation investments. The objective of the study is to create a general, global and structured technology success indicator model for companies that evaluate investments in industrial automation. The model takes a comprehensive approach by analysing the company, the technology, and the social environment in question. The model entails a technology readiness index and combinations of success factors that decision makers can utilize. The emphasis is on discrete manufacturing operations. Only the very newest technologies are analysed, with the anticipation that the results will be applicable into the 2020s.

This study describes the needs for a novel technology success indicator model. The current rapidly changing production environment is analysed from the technological perspective in order to build a conceptual foundation for the technology success indicator model. The technology success indicator model is developed and hypotheses to be tested in the empirical stage of the research project are presented.

Original language	English
Title of host publication	Towards Sustainable Technologies and Innovation
Subtitle of host publication	27th Annual Conference of the International Association for Management of Technology
Editors	Breno Nunes, Ali Emrouznejad, David Bennett, Leon Pretorius
Publisher	University of Aston
Pages	1-13
ISBN (Electronic)	978-1-85449-453-5
Publication status	Published - 25 Apr 2018
MoE publication type	A4 Conference publication
Event	International Conference on Management of Technology - Birmingham, United Kingdom Duration: 22 Apr 2018 → 26 Apr 2018 Conference number: 27

Conference

Conference	International Conference on Management of Technology
Abbreviated title	IAMOT
Country/Territory	United Kingdom
City	Birmingham
Period	22/04/2018 → 26/04/2018

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure
SDG 17 Partnerships for the Goals

Keywords

Technology success indicator mode
technology investment
success factor
robotics
5G wireless technology
discrete manufacturing

Access to Document

https://www2.aston.ac.uk/migrated-assets/applicationpdf/aston-business-school/388090-IAMOT2018_paper_77.pdf

Cite this

Leinonen, J., Poesche, J., & Kauranen, I. (2018). Fail no more in industrial automation investment! A novel technology success indicator model. In B. Nunes, A. Emrouznejad, D. Bennett, & L. Pretorius (Eds.), Towards Sustainable Technologies and Innovation: 27th Annual Conference of the International Association for Management of Technology (pp. 1-13). University of Aston. https://www2.aston.ac.uk/migrated-assets/applicationpdf/aston-business-school/388090-IAMOT2018_paper_77.pdf

Leinonen, Janne ; Poesche, Jurgen ; Kauranen, Ilkka. / Fail no more in industrial automation investment! A novel technology success indicator model. Towards Sustainable Technologies and Innovation: 27th Annual Conference of the International Association for Management of Technology. editor / Breno Nunes ; Ali Emrouznejad ; David Bennett ; Leon Pretorius. University of Aston, 2018. pp. 1-13

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title = "Fail no more in industrial automation investment!: A novel technology success indicator model",

abstract = "The research question of this study is how company management can make better decisions when deciding on industrial automation investments. The objective of the study is to create a general, global and structured technology success indicator model for companies that evaluate investments in industrial automation. The model takes a comprehensive approach by analysing the company, the technology, and the social environment in question. The model entails a technology readiness index and combinations of success factors that decision makers can utilize. The emphasis is on discrete manufacturing operations. Only the very newest technologies are analysed, with the anticipation that the results will be applicable into the 2020s. This study describes the needs for a novel technology success indicator model. The current rapidly changing production environment is analysed from the technological perspective in order to build a conceptual foundation for the technology success indicator model. The technology success indicator model is developed and hypotheses to be tested in the empirical stage of the research project are presented. ",

keywords = "Technology success indicator mode, technology investment, success factor, robotics, 5G wireless technology, discrete manufacturing",

author = "Janne Leinonen and Jurgen Poesche and Ilkka Kauranen",

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Leinonen, J, Poesche, J & Kauranen, I 2018, Fail no more in industrial automation investment! A novel technology success indicator model. in B Nunes, A Emrouznejad, D Bennett & L Pretorius (eds), Towards Sustainable Technologies and Innovation: 27th Annual Conference of the International Association for Management of Technology. University of Aston, pp. 1-13, International Conference on Management of Technology, Birmingham, United Kingdom, 22/04/2018. <https://www2.aston.ac.uk/migrated-assets/applicationpdf/aston-business-school/388090-IAMOT2018_paper_77.pdf>

Fail no more in industrial automation investment! A novel technology success indicator model. / Leinonen, Janne; Poesche, Jurgen; Kauranen, Ilkka.
Towards Sustainable Technologies and Innovation: 27th Annual Conference of the International Association for Management of Technology. ed. / Breno Nunes; Ali Emrouznejad; David Bennett; Leon Pretorius. University of Aston, 2018. p. 1-13.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Fail no more in industrial automation investment!

T2 - International Conference on Management of Technology

AU - Leinonen, Janne

AU - Poesche, Jurgen

AU - Kauranen, Ilkka

N1 - Conference code: 27

PY - 2018/4/25

Y1 - 2018/4/25

N2 - The research question of this study is how company management can make better decisions when deciding on industrial automation investments. The objective of the study is to create a general, global and structured technology success indicator model for companies that evaluate investments in industrial automation. The model takes a comprehensive approach by analysing the company, the technology, and the social environment in question. The model entails a technology readiness index and combinations of success factors that decision makers can utilize. The emphasis is on discrete manufacturing operations. Only the very newest technologies are analysed, with the anticipation that the results will be applicable into the 2020s. This study describes the needs for a novel technology success indicator model. The current rapidly changing production environment is analysed from the technological perspective in order to build a conceptual foundation for the technology success indicator model. The technology success indicator model is developed and hypotheses to be tested in the empirical stage of the research project are presented.

AB - The research question of this study is how company management can make better decisions when deciding on industrial automation investments. The objective of the study is to create a general, global and structured technology success indicator model for companies that evaluate investments in industrial automation. The model takes a comprehensive approach by analysing the company, the technology, and the social environment in question. The model entails a technology readiness index and combinations of success factors that decision makers can utilize. The emphasis is on discrete manufacturing operations. Only the very newest technologies are analysed, with the anticipation that the results will be applicable into the 2020s. This study describes the needs for a novel technology success indicator model. The current rapidly changing production environment is analysed from the technological perspective in order to build a conceptual foundation for the technology success indicator model. The technology success indicator model is developed and hypotheses to be tested in the empirical stage of the research project are presented.

KW - Technology success indicator mode

KW - technology investment

KW - success factor

KW - robotics

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KW - discrete manufacturing

UR - https://www.scopus.com/pages/publications/85085666014

M3 - Conference article in proceedings

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EP - 13

BT - Towards Sustainable Technologies and Innovation

A2 - Nunes, Breno

A2 - Emrouznejad, Ali

A2 - Bennett, David

A2 - Pretorius, Leon

PB - University of Aston

Y2 - 22 April 2018 through 26 April 2018

ER -