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A Systematic Selection Process of Machine Learning Cloud Services for Manufacturing SMEs

Title data

Kaymakci, Can ; Wenninger, Simon ; Pelger, Philipp ; Sauer, Alexander:
A Systematic Selection Process of Machine Learning Cloud Services for Manufacturing SMEs.
In: Computers. Vol. 11 (17 January 2022) Issue 1 . - No. 14.
ISSN 2073-431X
DOI: https://doi.org/10.3390/computers11010014

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI Künstliche IntelligenzNo information
Projektgruppe WI Strategisches IT-ManagementNo information

Abstract in another language

Small and medium-sized enterprises (SMEs) in manufacturing are increasingly facing
challenges of digital transformation and a shift towards cloud-based solutions to leveraging artificial
intelligence (AI) or, more specifically, machine learning (ML) services. Although literature covers
a variety of frameworks related to the adaptation of cloud solutions, cloud-based ML solutions in
SMEs are not yet widespread, and an end-to-end process for ML cloud service selection is lacking.
The purpose of this paper is to present a systematic selection process of ML cloud services for
manufacturing SMEs. Following a design science research approach, including a literature review
and qualitative expert interviews, as well as a case study of a German manufacturing SME, this paper
presents a four-step process to select ML cloud services for SMEs based on an analytic hierarchy
process. We identified 24 evaluation criteria for ML cloud services relevant for SMEs by merging
knowledge from manufacturing, cloud computing, and ML with practical aspects. The paper provides
an interdisciplinary, hands-on, and easy-to-understand decision support system that lowers the
barriers to the adoption of ML cloud services and supports digital transformation in manufacturing
SMEs. The application in other practical use cases to support SMEs and simultaneously further
development is advocated.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: SME; cloud computing; machine learning; service selection problem; manufacturing; decision support system (DSS); analytic hierarchy process (AHP)
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professor Information Systems Management and Strategic IT Management
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 27 Jan 2022 10:53
Last Modified: 27 Jan 2022 10:53
URI: https://eref.uni-bayreuth.de/id/eprint/68527