User acceptance of AI advice in the context of collaborative supply chains formation

Sonia Cisneros Cabrera; Nikolay Mehandjiev; Alexander Felfernig; Pedro Sampaio; Sophia Kununka

User acceptance of AI advice in the context of collaborative supply chains formation

Sonia Cisneros Cabrera, Nikolay Mehandjiev, Alexander Felfernig, Pedro Sampaio, Sophia Kununka

Technische Universitaet Graz

Research output: Contribution to conference › Poster › peer-review

Abstract

The future manufacturing vision behindIndustry 4.0 identifies businesscollaboration as one of the core enablersof the new industrial paradigm [1]. Ourteam at the University of Manchester worksclosely with automotive and aerospacemanufacturers to develop an advancedknowledge-driven configurator system [2]that advises its users with whichbusinesses to partner to “catch” a specificbusiness opportunity. The users of oursystem are of course the key to its uptakeand impact. We therefore need tounderstand the key factors which makethem accept recommendations from such asystem, and their relationships, creating afactor model of advice acceptance.We aim to answer this research question:What are the important factors influencingusers’ acceptance of advice coming out ofa knowledge-based system in the contextof business collaboration?

Original language	English
Number of pages	1
Publication status	Published - 2019
Event	Network Plus: Industrial Systems in the Digital Age Conference 2019: Designing a Connected Future - The University of Nottingham, Nottingham, United Kingdom Duration: 25 Jun 2019 → 26 Jun 2019 https://connectedeverything.ac.uk/conference-2019-2/

Conference

Conference	Network Plus: Industrial Systems in the Digital Age Conference 2019
Country/Territory	United Kingdom
City	Nottingham
Period	25/06/19 → 26/06/19
Internet address	https://connectedeverything.ac.uk/conference-2019-2/

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Cisneros Cabrera, S., Mehandjiev, N., Felfernig, A., Sampaio, P., & Kununka, S. (2019). User acceptance of AI advice in the context of collaborative supply chains formation. Poster session presented at Network Plus: Industrial Systems in the Digital Age Conference 2019, Nottingham, United Kingdom. https://connectedeverythingmedia.files.wordpress.com/2019/07/ce2019_paper_16.pdf

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title = "User acceptance of AI advice in the context of collaborative supply chains formation",

abstract = "The future manufacturing vision behindIndustry 4.0 identifies businesscollaboration as one of the core enablersof the new industrial paradigm [1]. Ourteam at the University of Manchester worksclosely with automotive and aerospacemanufacturers to develop an advancedknowledge-driven configurator system [2]that advises its users with whichbusinesses to partner to “catch” a specificbusiness opportunity. The users of oursystem are of course the key to its uptakeand impact. We therefore need tounderstand the key factors which makethem accept recommendations from such asystem, and their relationships, creating afactor model of advice acceptance.We aim to answer this research question:What are the important factors influencingusers{\textquoteright} acceptance of advice coming out ofa knowledge-based system in the contextof business collaboration? ",

author = "{Cisneros Cabrera}, Sonia and Nikolay Mehandjiev and Alexander Felfernig and Pedro Sampaio and Sophia Kununka",

year = "2019",

language = "English",

note = "Network Plus: Industrial Systems in the Digital Age Conference 2019 : Designing a Connected Future ; Conference date: 25-06-2019 Through 26-06-2019",

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TY - CONF

T1 - User acceptance of AI advice in the context of collaborative supply chains formation

AU - Cisneros Cabrera, Sonia

AU - Mehandjiev, Nikolay

AU - Felfernig, Alexander

AU - Sampaio, Pedro

AU - Kununka, Sophia

PY - 2019

Y1 - 2019

N2 - The future manufacturing vision behindIndustry 4.0 identifies businesscollaboration as one of the core enablersof the new industrial paradigm [1]. Ourteam at the University of Manchester worksclosely with automotive and aerospacemanufacturers to develop an advancedknowledge-driven configurator system [2]that advises its users with whichbusinesses to partner to “catch” a specificbusiness opportunity. The users of oursystem are of course the key to its uptakeand impact. We therefore need tounderstand the key factors which makethem accept recommendations from such asystem, and their relationships, creating afactor model of advice acceptance.We aim to answer this research question:What are the important factors influencingusers’ acceptance of advice coming out ofa knowledge-based system in the contextof business collaboration?

AB - The future manufacturing vision behindIndustry 4.0 identifies businesscollaboration as one of the core enablersof the new industrial paradigm [1]. Ourteam at the University of Manchester worksclosely with automotive and aerospacemanufacturers to develop an advancedknowledge-driven configurator system [2]that advises its users with whichbusinesses to partner to “catch” a specificbusiness opportunity. The users of oursystem are of course the key to its uptakeand impact. We therefore need tounderstand the key factors which makethem accept recommendations from such asystem, and their relationships, creating afactor model of advice acceptance.We aim to answer this research question:What are the important factors influencingusers’ acceptance of advice coming out ofa knowledge-based system in the contextof business collaboration?

M3 - Poster

T2 - Network Plus: Industrial Systems in the Digital Age Conference 2019

Y2 - 25 June 2019 through 26 June 2019

ER -

User acceptance of AI advice in the context of collaborative supply chains formation

Abstract

Conference

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