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  • 1.
    Engström, Annika
    et al.
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Mohlin, Alice
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Edh Mirzaei, Nina
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Pittino, Daniel
    Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, Jönköping International Business School, JIBS, Centre for Family Entrepreneurship and Ownership (CeFEO). Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Johansson, Anette
    Jönköping University, Jönköping International Business School, JIBS, Media, Management and Transformation Centre (MMTC). Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Understanding Organizational Tensions During Artificial Intelligence Transformation2022Conference paper (Refereed)
  • 2.
    Engström, Annika
    et al.
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Mohlin, Alice
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Edh Mirzaei, Nina
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Pittino, Daniel
    Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, Jönköping International Business School, JIBS, Centre for Family Entrepreneurship and Ownership (CeFEO). Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Johansson, Anette
    Jönköping University, Jönköping International Business School, JIBS, Media, Management and Transformation Centre (MMTC). Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Understanding Organizational Tensions During Artificial Intelligence Transformation2022In: Proceedings of The Annual Meeting of The Academy of Management, 2022, Vol. 2022, No. 1, Academy of Management , 2022, Vol. Vol. 2022, no 1, p. 12745-Conference paper (Refereed)
    Abstract [en]

    AI has the potential to be a disruptive technology causing paradigm shifts in industries and greatly impacting both operational and strategic decision making. Adopting AI technologies requires proactively engaging both the technical and social system of the organization as processes, workflows, as well as individual employees, are influenced. This paper explores potential tensions between the social and technical systems in the early change process of AI transformation to understand the nature and degree of AI transformation. We do this by analyzing in-depth inquiry from 23 focus groups involving 112 white-collar industrial employees in large multinational industrial firms using a change management perspective. Our study revealed nine categories of tensions divided into tensions between the current and future state and tensions between humans and machines. This stresses the need to adopt a socio-technical perspective in the attempt to understand organizations approaching AI and provides practical implications for organizations considering adopting AI technologies.

  • 3.
    Engström, Annika
    et al.
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Pittino, Daniel
    Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, Jönköping International Business School, JIBS, Centre for Family Entrepreneurship and Ownership (CeFEO). Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Johansson, Anette
    Jönköping University, Jönköping International Business School, JIBS, Media, Management and Transformation Centre (MMTC). Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Mohlin, Alice
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Edh Mirzaei, Nina
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    How AI Transformation triggers new perspectives in organizational learning2022Conference paper (Refereed)
  • 4.
    Mohlin, Alice
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    How to facilitate manufacturing industry learning from problems: a review on advanced technology problem-solving2023In: Journal of Workplace Learning, ISSN 1366-5626, E-ISSN 1758-7859, Vol. 35, no 6, p. 470-489Article, review/survey (Refereed)
    Abstract [en]

    Purpose The purpose of this paper is twofold: to identify and map contemporary research on advanced technology implementations for problem-solving purposes in the manufacturing industry, and to further understand the organizational learning possibilities of advanced technology problem-solving in the manufacturing industry.

    Design/methodology/approach This paper outlines a scoping review of contemporary research on the subject. The findings of the review are discussed in the light of theories of contradicting learning logics.

    Findings This paper shows that contemporary research on the subject is characterized by technological determinism and strong solution-focus. A discussion on the manufacturing industries’ contextual reasons for this in relation to contradicting learning logics shows that a Mode-2 problem-solving approach could facilitate further learning and expand knowledge on advanced technology problem-solving in the manufacturing industry. A research agenda with six propositions is provided.

    Originality/value The introduction of advanced technology implies complex effects on the manufacturing industry in general, while previous research shows a clear focus on technological aspects of this transformation. This paper provides value by providing novel knowledge on the relationship between advanced technology, problem-solving and organizational learning in the manufacturing industry.

  • 5.
    Mohlin, Alice
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Problem-Solving in Manufacturing Industry with Advanced Technology – What Problems Are We Really Solving?2022Conference paper (Refereed)
  • 6.
    Mohlin, Alice
    et al.
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Chatzipanagiotou, N.
    Digital Nomads’ Experiences on the Support of Digital Technologies in Relation to Social Isolation2023Conference paper (Refereed)
  • 7.
    Mohlin, Alice
    et al.
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Engström, Annika
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Work-Integrated-Learning by Inaction – Exploring Organizational Reflections on AI-Transformation in the Manufacturing Industry2024In: Abstract book WIL Conference 2024: 2nd International Conference on Work-Integrated Learning / [ed] U. Lundh Snis, L. Carlsson, P. Assmo & H. Jacobs, Trollhättan: University West , 2024, p. 13-13Conference paper (Refereed)
    Abstract [en]

    Artificial intelligence (AI) has for the last decade been expected to revolutionize the way we work. However, as many industries are facing more complex problems as an effect of technological development and globalizations, companies are experiencing challenges in finalizing AI-projects and fully integrating AI into their operations, not least in the manufacturing industry. To face these challenges, it is suggested that manufacturing industry could benefit from enhancing their work-integrated learning related to AI and AI transformation. In addition, one of the considered success factors in technological development and organizational change is the way that it is reflected on by the organization. This paper employs an action-based perspective, in which learning is generated by and in action, that is, in the reflection on experiences. And so, with a qualitative focus group study, we sought to explore how manufacturing industry organizations reflect on action in a potential AI-transformation. However, the results showed that the participating organizations instead displayed an inaction stance when discussing AI-transformation, demonstrating a general passivity towards the transformation as a concrete change process. We employ theories of psychological safety, maneuver space and sense of coherence to analyze our empirical results. Moreover, we discuss our findings based on the idea of action and inaction as contradictory forces that adverse each other in terms of learning as well as the theoretical and practical implications of our study.

  • 8.
    Ohlson, Nils-Erik
    et al.
    Siemens Energy AB, Sweden.
    Mohlin, Alice
    Jönköping University, School of Engineering, JTH, Supply Chain and Operations Management.
    Evaluating integrated technology-process trust when applying machine learning to a business process case2023Conference paper (Refereed)
    Abstract [en]

    When implementing a technology e.g., machine learning (ML) in a business process, a return of investment is desired if not required. This exploratory study, in a single business process case where ML will be implemented, showed the complexity of trust, where many aspects of trust were addressed by different themes at different times. It also showed that process trust, technology trust and the interaction, integrated trust, are important to consider when applying a new technology in a business process. These critical aspects have been gathered in a model that can be useful for both scholars and practitioners.

     

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