Publication type: Conference paper
Type of review: Peer review (publication)
Title: Improving service value creation for manufacturing SMEs by overcoming data sharing hurdles in ecosystems
Authors: Meierhofer, Jürg
Kugler, Petra
Vogt, Helen
Dobler, Martin
Benedech, Rodolfo Andres
Strittmatter, Marc
Treiterer, Manuel
et. al: No
Proceedings: Achieving Net-Zero through Servitization
Editors of the parent work: Bigdeli, Ali
Rapaccini, Mario
Saccani, Nicola
Adrodegari, Federico
Baines, Tim
Pages: 86
Pages to: 94
Conference details: Spring Servitization Conference (SSC), Florence, Italy, 9-10 May 2022
Issue Date: May-2022
Publisher / Ed. Institution: Aston University
Publisher / Ed. Institution: Birmingham
ISBN: 978-1-85449-805-2
Language: English
Subjects: Smart service ecosystem; Data-driven value creation; Data sharing; Data-driven organization and culture; Data governance
Subject (DDC): 658.403: Decision making, information management
Abstract: Purpose: Although there is an apparent potential in using data for advanced services in manufacturing environments, SMEs are reluctant to share data with their ecosystem partners, which prevents them from leveraging this potential. Therefore, the purpose of this paper is to analyse the reasons behind these resistances. The argumentation paves the way for elaborating countermeasures that are adequate for the specific situation and the typical capabilities of SMEs. Design/Methodology/Approach: The analysis is based on literature research and in-depth interviews with management representatives of 15 companies in manufacturing service ecosystems. Half of these are manufacturers and the other half technology or service providers for manufacturers. They are SMEs or partly larger companies operating in structures that are typical for SMEs. Findings: Data sharing hurdles are investigated in the five dimensions, 1. quantifying the value of data, 2. willingness to share data and trust, 3. organizational culture and mindset, 4. legal aspects, and 5. security and privacy. The ability to quantify the value of data is a necessary but not sufficient precondition for data sharing, which must be enabled by adequate measures in the other four dimensions. Originality/Value: The findings of this empirical study and the solution approach provide an SME-specific framework to analyze hurdles that must be overcome for sharing data in an ecosystem. Manufacturing SMEs can apply the framework to overcome the hurdles by specific insights and solution approaches. Furthermore, the analysis illustrates the future research direction of the project towards a comprehensive solution approach for data sharing in a manufacturing ecosystem.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Institute of Marketing Management (IMM)
Published as part of the ZHAW project: Data Sharing Framework
Appears in collections:Publikationen School of Engineering

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