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Gama, F. & Holmén, M. (2024). Ideation and Machine Learning: Problem Finding in Disruptive Innovation. In: : . Paper presented at R&D 2022 Management Conference, June 9-13, 2022, Trento, Italy. Trento: RADMA, Research and Development Management
Open this publication in new window or tab >>Ideation and Machine Learning: Problem Finding in Disruptive Innovation
2024 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Disruptive innovation is widely recognised as a bold enterprise. Risks and uncertainties drive incumbent firms to seek alternative solutions to find disruptive ideas. Machine learning emerges as a powerful tool to reduce uncertainties while processing vast amounts and types of information. However, incumbents encounter immense difficulty in codifying tacit knowledge into effective algorithms and often end up with incremental or tactical outcomes despite bold aspirations. Using the literature on problem finding, we explore the development process of machine learning for ideation. Our action research conducted on a healthcare firm provides theoretical and managerial contributions. First, this study suggests that ideation for disruptive innovation benefits from machine learning by facilitating a heuristic search in which a group of actors evaluate plausible hypotheses rather than seek logically accurate conclusions. Previous studies on ideation stress directional search. Second, we propose an ideation process centred on problem formulation to identify disruptive innovation based on its inherent characteristics (e.g., radical functionality and discontinuous technical standard). Third, we discuss the challenges of adopting algorithm-based systems in the ideation — a process well known for being fuzzy.

Place, publisher, year, edition, pages
Trento: RADMA, Research and Development Management, 2024
Keywords
disruptive innovation, ideation, machine learning, artificial intelligence, problem finding
National Category
Information Systems, Social aspects
Research subject
Health Innovation
Identifiers
urn:nbn:se:hh:diva-47176 (URN)
Conference
R&D 2022 Management Conference, June 9-13, 2022, Trento, Italy
Funder
Knowledge Foundation, 220023
Available from: 2022-06-17 Created: 2022-06-17 Last updated: 2023-04-19
Irgang dos Santos, L. F., Barth, H. & Holmén, M. (2023). Data-Driven Technologies as Enablers for Value Creation in the Prevention of Surgical Site Infections: a Systematic Review. Journal of Healthcare Informatics Research, 7, 1-41
Open this publication in new window or tab >>Data-Driven Technologies as Enablers for Value Creation in the Prevention of Surgical Site Infections: a Systematic Review
2023 (English)In: Journal of Healthcare Informatics Research, ISSN 2509-4971, E-ISSN 2509-498X, Vol. 7, p. 1-41Article, review/survey (Other academic) Published
Abstract [en]

Despite the advances in modern medicine, the use of data-driven technologies (DDTs) to prevent surgical site infections (SSIs) remains a major challenge. Scholars recognise that data management is the next frontier in infection prevention, but many aspects related to the benefits and advantages of using DDTs to mitigate SSI risk factors remain unclear and underexplored in the literature. This study explores how DDTs enable value creation in the prevention of SSIs. This study follows a systematic literature review approach and the PRISMA statement to analyse peer-reviewed articles from seven databases. Fifty-nine articles were included in the review and were analysed through a descriptive and a thematic analysis. The findings suggest a growing interest in DDTs in SSI prevention in the last 5 years, and that machine learning and smartphone applications are widely used in SSI prevention. DDTs are mainly applied to prevent SSIs in clean and clean-contaminated surgeries and often used to manage patient-related data in the postoperative stage. DDTs enable the creation of nine categories of value that are classified in four dimensions: cost/sacrifice, functional/instrumental, experiential/hedonic, and symbolic/expressive. This study offers a unique and systematic overview of the value creation aspects enabled by DDT applications in SSI prevention and suggests that additional research is needed in four areas: value co-creation and product-service systems, DDTs in contaminated and dirty surgeries, data legitimation and explainability, and data-driven interventions. © 2023, The Author(s).

Place, publisher, year, edition, pages
Cham: Springer, 2023
Keywords
Healthcare technology, Surgical site infections, Infection prevention and control, Value-based Care, Technology implementation, Systematic review
National Category
Nursing Engineering and Technology
Research subject
Health Innovation, Information driven care
Identifiers
urn:nbn:se:hh:diva-50052 (URN)10.1007/s41666-023-00129-2 (DOI)000939789800001 ()2-s2.0-85149042899 (Scopus ID)
Funder
Halmstad University, 220021Knowledge Foundation
Note

Funding: Open access funding provided by Halmstad University.

Available from: 2023-03-02 Created: 2023-03-02 Last updated: 2023-11-24Bibliographically approved
Żukowicka-Surma, A., Holmén, M., Johansson, J. & Andersson, S. (2023). Healthcare ecosystems and business models reconfiguration: Decoupling and resilience in the context of data-driven technologies: A Systematic Literature Review (1ed.). In: Svetla T. Marinova; Marin A. Marinov (Ed.), Reconfiguration of Business Models and Ecosystems: Decoupling and Resilience (pp. 204-235). New York: Routledge
Open this publication in new window or tab >>Healthcare ecosystems and business models reconfiguration: Decoupling and resilience in the context of data-driven technologies: A Systematic Literature Review
2023 (English)In: Reconfiguration of Business Models and Ecosystems: Decoupling and Resilience / [ed] Svetla T. Marinova; Marin A. Marinov, New York: Routledge, 2023, 1, p. 204-235Chapter in book (Refereed)
Abstract [en]

This chapter researches the reconfiguration of business models and ecosystems in relation to decoupling and resilience in the context of data-driven technologies via conducting a systematic literature review (SLR). New data-driven technologies have been largely introduced to different sectors. Digitalisation may lead to disruptive changes in any industry, including creating or entering new business models, lowering or changing entry barriers into markets and enabling the breakup of sectorial silos. Although the COVID-19 pandemic accelerated significantly the digitalisation of the healthcare sector, innovation adoption in the sector proceeds slower than in most other industries. This chapter reviews systematically the existing literature on this area and develops a research agenda aiming at answering the pre-set research question: To address the research question, an SLR methodology has been applied to provide insights, critical reflections, managerial implications and research road maps for future research. The chapter identifies the potential benefits of the use of data-driven technology in healthcare at organisational, institutional, ethical and macro-level dimensions. It discusses the adoption of digitalisation and healthcare management practices to enhance data-driven outcomes. Based on the conducted literature review and the bibliometric analysis of articles included in the chapter, an integrative conceptual framework for digital healthcare is suggested. © 2023 selection and editorial matter, Svetla T. Marinova and Marin A. Marinov; individual chapters, the contributors

Place, publisher, year, edition, pages
New York: Routledge, 2023 Edition: 1
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:hh:diva-50020 (URN)2-s2.0-85147936678 (Scopus ID)978-1-032-35402-6 (ISBN)978-1-003-32673-1 (ISBN)
Available from: 2023-02-24 Created: 2023-02-24 Last updated: 2023-02-24Bibliographically approved
Hoveskog, M., Holmén, M., Ernest, A. & Bergquist, M. (2023). Mobilizing Service Ecosystems for Sustainability – the Case of Polestar. In: Abel Diaz Gonzalez; Juliette Koning; Nancy Bocken (Ed.), NBM 2023: Proceedings of the 8th International Conference on New Business Models. Paper presented at 8th International Conference on New Business Models (NBM2023), Building partnerships for more sustainable, resilient and regenerative business models, Maastricht, The Netherlands, June 22-23, 2023. Maastricht: Maastricht University Press
Open this publication in new window or tab >>Mobilizing Service Ecosystems for Sustainability – the Case of Polestar
2023 (English)In: NBM 2023: Proceedings of the 8th International Conference on New Business Models / [ed] Abel Diaz Gonzalez; Juliette Koning; Nancy Bocken, Maastricht: Maastricht University Press , 2023Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
Maastricht: Maastricht University Press, 2023
Keywords
Service ecosystems, electric vehicles, entrepreneurial experimentation, legitimation, resource mobilization, knowledge development, market formation
National Category
Business Administration
Research subject
Smart Cities and Communities
Identifiers
urn:nbn:se:hh:diva-51142 (URN)10.26481/mup.2302 (DOI)
Conference
8th International Conference on New Business Models (NBM2023), Building partnerships for more sustainable, resilient and regenerative business models, Maastricht, The Netherlands, June 22-23, 2023
Projects
OSMaaS
Funder
Knowledge Foundation
Available from: 2023-06-29 Created: 2023-06-29 Last updated: 2023-07-05Bibliographically approved
Sjöberg, J., Byttner, S., Wärnestål, P., Burgos, J. & Holmén, M. (2023). Promoting Life-Long Learning Through Flexible Educational Format for Professionals Within AI, Design and Innovation Management. In: Eva Brooks; Jeanette Sjöberg; Anders Kalsgaard Møller; Emma Edstrand (Ed.), Design, Learning, and Innovation: 7th EAI International Conference, DLI 2022, Faro, Portugal, November 21–22, 2022, Proceedings. Paper presented at Design, Learning, and Innovation: 7th EAI International Conference, DLI 2022, Faro, Portugal, November 21–22, 2022 (pp. 38-47). Cham: Springer
Open this publication in new window or tab >>Promoting Life-Long Learning Through Flexible Educational Format for Professionals Within AI, Design and Innovation Management
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2023 (English)In: Design, Learning, and Innovation: 7th EAI International Conference, DLI 2022, Faro, Portugal, November 21–22, 2022, Proceedings / [ed] Eva Brooks; Jeanette Sjöberg; Anders Kalsgaard Møller; Emma Edstrand, Cham: Springer, 2023, p. 38-47Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, the concept of lifelong learning has been emphasized in relation to higher education, with a bearing idea of the possibility for the individual for a continuous, self-motivated pursuit of gaining knowledge for both personal and professional reasons, provided by higher education institutions (HEI:s). But how can this actually be done in practice? In this paper we present an ongoing project called MAISTR, which is a collaboration between Swedish HEI:s and industry with the aim of providing a number of flexible courses within the subjects of Artificial intelligence (AI), Design, and Innovation management, for professionals. Our aim is to describe how the project is setup to create new learning opportunities, including the development process and co-creation with industry, the core structure and the pedagogical design. Furthermore, we would like to discuss both challenges and opportunities that come with this kind of project, as well as reflecting on early stage outcomes. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Place, publisher, year, edition, pages
Cham: Springer, 2023
Series
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, ISSN 1867-8211, E-ISSN 1867-822X ; 493
Keywords
AI education, Flexible education, Learning for professionals, Lifelong learning, Pedagogical design
National Category
Other Social Sciences not elsewhere specified
Research subject
Smart Cities and Communities, LeaDS - Learning in a Digitalised Society
Identifiers
urn:nbn:se:hh:diva-50399 (URN)10.1007/978-3-031-31392-9_3 (DOI)2-s2.0-85161436060 (Scopus ID)978-3-031-31391-2 (ISBN)978-3-031-31392-9 (ISBN)
Conference
Design, Learning, and Innovation: 7th EAI International Conference, DLI 2022, Faro, Portugal, November 21–22, 2022
Available from: 2023-05-02 Created: 2023-05-02 Last updated: 2023-07-06Bibliographically approved
Gharaie, A., Holmén, M. & Hoveskog, M. (2022). Challenges of Data-driven Service Development in Manufacturing Industries – a Review. In: Laura Michelini; Anna Minà; ‪Pierfrancesco Alaimo Di Loro (Ed.), Sustainable Business Model Challenges : Economic Recovery and Digital Transformation: 7th International Conference on New Business Models. Paper presented at 7th International Conference on New Business Models: Sustainable Business Model Challenges: Economic Recovery and Digital Transformation, Rome, Italy, 23-24 June, 2022 (pp. 419-428). Roma: LUMSA University
Open this publication in new window or tab >>Challenges of Data-driven Service Development in Manufacturing Industries – a Review
2022 (English)In: Sustainable Business Model Challenges : Economic Recovery and Digital Transformation: 7th International Conference on New Business Models / [ed] Laura Michelini; Anna Minà; ‪Pierfrancesco Alaimo Di Loro, Roma: LUMSA University , 2022, p. 419-428Conference paper, Published paper (Refereed)
Abstract [en]

This literature review aims to identify the existing challenges of data-driven service development in manufacturing industries, and a general approach to manage the challenges. The three primary categories are technological, ecosystem- and business model-related. Those are identified and categorized through the lens of data-driven service taxonomy framework. Digital twin was identified as one overarching approach with the potential to solve some of the identified challenges. Future research can focus on exploring the different level of importance of the existing challenges.

Place, publisher, year, edition, pages
Roma: LUMSA University, 2022
Keywords
Data-driven service, Manufacturing, Challenge, Business model, Ecosystem, Digital twin
National Category
Business Administration
Research subject
Smart Cities and Communities
Identifiers
urn:nbn:se:hh:diva-47376 (URN)979-12-210-1188-3 (ISBN)
Conference
7th International Conference on New Business Models: Sustainable Business Model Challenges: Economic Recovery and Digital Transformation, Rome, Italy, 23-24 June, 2022
Projects
OSMaaS
Funder
Knowledge Foundation
Available from: 2022-06-24 Created: 2022-06-24 Last updated: 2022-10-06Bibliographically approved
Björkdahl, J., Fallahi, S. & Holmén, M. (2022). Explaining business model innovation processes: A problem formulation and problem solving perspective. Industrial Marketing Management, 105, 223-239
Open this publication in new window or tab >>Explaining business model innovation processes: A problem formulation and problem solving perspective
2022 (English)In: Industrial Marketing Management, ISSN 0019-8501, E-ISSN 1873-2062, Vol. 105, p. 223-239Article in journal (Refereed) Published
Abstract [en]

This study explains the business model innovation processes in industrial firms. Drawing on three case studies of leading business-to-business firms shifting from product-based to service-based business models, it introduces problems as a theoretical concept to explain business model innovation processes. We show how formulating and solving problems guide the search for a viable business model and why some problem formulation and solving activities lead firms to shift between backward-looking and forward-looking searches. The decision to shift to a forward-looking search is triggered by the perception of failure to continue with an established way of working, while the shift to a backward-looking search is based on the perception of high alternative costs. We contribute to the business model innovation and servitization literature by theorizing the process of business model innovation and providing implications for managers. © 2022 The Authors

Place, publisher, year, edition, pages
New York: Elsevier, 2022
Keywords
Backward-looking search, Business model innovation, Forward-looking search, Problem formulation, Problem solving, Search
National Category
Business Administration
Identifiers
urn:nbn:se:hh:diva-50032 (URN)10.1016/j.indmarman.2022.05.012 (DOI)000838703300006 ()2-s2.0-85132515211 (Scopus ID)
Available from: 2023-03-06 Created: 2023-03-06 Last updated: 2023-03-06Bibliographically approved
Florén, H., Barth, H., Gullbrand, J. & Holmén, M. (2021). Additive manufacturing technologies and business models – a systematic literature review. Journal of Manufacturing Technology Management, 32(1), 136-155
Open this publication in new window or tab >>Additive manufacturing technologies and business models – a systematic literature review
2021 (English)In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786, Vol. 32, no 1, p. 136-155Article, review/survey (Refereed) Published
Abstract [en]

Purpose: This paper reviews research on the intersection between additive manufacturing technologies (AMTs) and business models (BM). The purpose of the review is to synthesize past research for the benefit of researchers, to describe the dominant research themes and aggregated research questions and to identify research gaps in the literature. Design/methodology/approach: A systematic literature review of secondary data was conducted. The 288 publications in the review appeared in peer-reviewed journal articles, conference proceedings papers and book chapters. All publications are listed in this paper by publication year and publication source. The review also distinguishes between empirical and non-empirical studies, describes methodological approaches and categorizes the publications by unit of analysis and by theme. Findings: Research on the intersection between AMT and BM, which has increased significantly in the last three years, reflects firms' and industries' growing interest in digital manufacturing processes. This review identifies twelve dominant themes in the literature that contribute important insights to the field. Aggregated research questions are identified in each theme. Research advances and gaps are presented. Four themes relate directly to BM: (1) BM types, (2) BM and technology, (3) BM design and processes and (4) BM value and supply chains. Originality/value: This review is the first systematic literature review on the intersection between AMT and BM. As such, the review provides a guide for researchers as they explore gaps in the research and develop research questions on an aggregated level. The review also supports users of such technologies as they review their business practices and models in the so-called Digital Revolution. © 2020, Emerald Publishing Limited.

Place, publisher, year, edition, pages
Bingley: Emerald Group Publishing Limited, 2021
Keywords
3D printing, Additive manufacturing, Industry 4.0
National Category
Business Administration
Identifiers
urn:nbn:se:hh:diva-46094 (URN)10.1108/JMTM-01-2020-0009 (DOI)000598380100001 ()2-s2.0-85097314961 (Scopus ID)
Funder
Knowledge Foundation, 20160304
Available from: 2021-12-14 Created: 2021-12-14 Last updated: 2021-12-14Bibliographically approved
Holmén, M. & Long, V. (2021). Conclusions (1ed.). In: Vicky Long; Magnus Holmén (Ed.), Technological Change and Industrial Transformation: (pp. 232-244). Abingdon: Routledge
Open this publication in new window or tab >>Conclusions
2021 (English)In: Technological Change and Industrial Transformation / [ed] Vicky Long; Magnus Holmén, Abingdon: Routledge, 2021, 1, p. 232-244Chapter in book (Refereed)
Abstract [en]

Chapter 12, “Conclusions”, conceptualizes industrial transformation as consisting of qualitative changes in the structure of inter-firm activities and relations. The authors stress that industrial transformation consists of uncertain endogenous processes of qualitative state changes, limiting the role of increasing returns. However, uncertainty can be managed or reduced by increasing control. By distinguishing the book’s chapters into research, design and development (RD&D), production and distribution, the authors show how digitalization increases control and becomes a powerful driver of industrial transformation. The authors compare the seminal work of Allyn Young (1928) to explain how demand changes, digitalization and industrial transformation coevolve cumulatively.

Place, publisher, year, edition, pages
Abingdon: Routledge, 2021 Edition: 1
Series
Routledge Studies in Innovation, Organizations and Technology (RIOT!)
National Category
Business Administration
Identifiers
urn:nbn:se:hh:diva-45987 (URN)2-s2.0-85114659827 (Scopus ID)9780429423550 (ISBN)9781138390034 (ISBN)
Available from: 2021-12-01 Created: 2021-12-01 Last updated: 2021-12-01Bibliographically approved
Holmén, M., Lauri, P. & Hoveskog, M. (2021). Data-driven Business Models for Sustainability in Emerging Fields.
Open this publication in new window or tab >>Data-driven Business Models for Sustainability in Emerging Fields
2021 (English)Other (Other (popular science, discussion, etc.))
Publisher
p. 435-436
National Category
Business Administration
Identifiers
urn:nbn:se:hh:diva-45673 (URN)
Note

Included in: Proceedings of the 6th International Conference on New Business Models: New Business Models in a Decade of Action: Sustainable, Evidence-based, Impactful. Halmstad, Sweden, 9-11 June 2021.

Available from: 2021-09-30 Created: 2021-09-30 Last updated: 2024-02-07Bibliographically approved
Projects
Managing Additive Manufacturing for Professional Engineers (MAMPE) [2018-03822_Vinnova]; Halmstad UniversityAutomatic Idea Detection: Implementing artificial intelligence in medical technology innovation (AID); Halmstad University
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0560-7392

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