Tesi etd-09302024-223542
Link copiato negli appunti
Tipo di tesi
Dottorato
Autore
JENNES, PHILIPP
URN
etd-09302024-223542
Titolo
Unlocking the Potential of Collaborative Robots: Adoption Dynamics and Implementation Challenges in Modern Industry
Settore scientifico disciplinare
SECS-P/08
Corso di studi
Istituto di Management - PHD IN MANAGEMENT - INNOVATION, SUSTAINABILITY AND HEALTHCARE
Commissione
relatore DI MININ, ALBERTO
Membro Prof. Paavo Ritala
Membro Prof.ssa Agnieszka Radziwon
Membro Dott. Giulio Ferrigno
Membro Prof. Paavo Ritala
Membro Prof.ssa Agnieszka Radziwon
Membro Dott. Giulio Ferrigno
Parole chiave
- Adoption
- AMT
- Challenges
- Cobots
- Collaborative robots
- Implementation
- Industry 4.0
- Innovation
Data inizio appello
25/11/2024;
Disponibilità
completa
Riassunto analitico
This dissertation investigates the adoption and implementation of collaborative robots (cobots) within various organizational settings, focusing on both small and medium-sized enterprises (SMEs) and large firms. In the era of Industry 4.0, cobots represent a pivotal technology, facilitating human-robot collaboration (HRC) that leverages the strengths of both humans and machines. Despite their potential, the integration of cobots presents numerous technical, organizational, and cultural challenges. The three research papers in this dissertation provide a comprehensive investigation into the drivers, barriers, and success factors of cobot adoption, offering both theoretical insights and practical guidance for future implementation.
Paper 1: Mapping the Landscape of Collaborative Robots: A Systematic Literature Review of Industrial Implementation, Challenges, and Future Directions
This paper provides a systematic review of 94 academic articles, addressing three key questions:
1. What are the thematic trends in the literature on cobot implementation?
2. What are the barriers to cobot integration?
3. How can these barriers be addressed in future research?
The review identifies seven thematic clusters, including Evaluation, Human-Robot Interaction (HRI), and Risk Assessment, which offer a broad view of the current state of cobot research. Recurring challenges such as cognitive ergonomics, safety concerns, and long-term performance assessments are highlighted. The paper proposes a structured framework for future research, focusing on how organizations can overcome technical and operational hurdles through improved training, safety protocols, and organizational change management. It emphasizes that successful cobot adoption requires strategic alignment between technological innovations, workforce readiness, and organizational structures.
Paper 2: Cobots in SMEs: Implementation Processes, Barriers, and Success Factors
This paper explores the unique challenges and enablers that SMEs face when adopting cobots. The following research questions guide the investigation:
1. What specific barriers do SMEs face during cobot adoption?
2. What success factors enable SMEs to overcome these barriers?
Through qualitative analysis of five SMEs, the study uncovers three primary clusters of barriers: technical (e.g., programming complexity and safety requirements), organizational (e.g., job redesign and knowledge integration), and cultural (e.g., fear of job displacement and distrust of new technologies). The research identifies open innovation, employee involvement, and pilot testing as key enablers that help SMEs navigate the complexities of cobot integration. By collaborating with external partners and empowering their workforce, SMEs can modernize their production processes in a cost-effective manner. The findings suggest that cobots offer SMEs a way to enhance flexibility, reduce labor costs, and stay competitive in the evolving landscape of Industry 4.0.
Paper 3: From Knowledge to Confirmation: A Stage-Based Analysis of Collaborative Robot Adoption in Manufacturing
This paper applies Rogers' Diffusion of Innovation (DOI) model, complemented by the Technology-Organization-Environment (TOE) framework, to trace the cobot adoption process across five stages: Knowledge, Persuasion, Decision, Implementation, and Confirmation. The paper addresses the following questions:
1. What are the drivers motivating the adoption of cobots in manufacturing?
2. What barriers and enablers emerge during the cobot adoption process?
3. How do these determinants influence the stages of cobot adoption?research?
A key contribution of this paper is the mapping of enablers and barriers across the DOI stages, with ambivalent themes emerging throughout the adoption process. These themes—Driving Forces, Culture and Leadership, Strategic Financial Management, Pilot Testing, Regulatory Navigation, Ecosystem Collaboration, Validation, and Lessons Learned from Failure Cases—illustrate how the interaction between leadership, financial strategies, and external partnerships shapes cobot outcomes. This stage-based approach offers a dynamic view of cobot integration, showing how human factors become more prominent as organizations move from initial knowledge acquisition to post-installation stages. The paper advocates for sector-specific research to refine the DOI-TOE framework in industries with lower automation levels.
The dissertation employs a systematic literature review (SLR) in Paper 1 and qualitative multiple case studies in Papers 2 and 3. The SLR offers a broad overview of existing research trends and methodologies, ensuring a transparent and replicable approach to understanding cobot adoption. The case studies in Papers 2 and 3 use semi-structured interviews, observations, and document analysis to provide in-depth insights into the specific challenges and strategies faced by SMEs and large firms. By integrating theoretical frameworks with real-world data, the research produces both academic and practical contributions to the field of collaborative robotics.
This dissertation contributes to both theory and practice by:
• Mapping thematic trends and identifying barriers in cobot adoption literature.
• Offering insights into the specific challenges SMEs face and the enablers that facilitate their cobot integration.
• Developing a stage-based framework for cobot adoption, illustrating the interaction of enablers and barriers at each stage.
• Proposing actionable frameworks that help organizations align technological advancements with human and organizational factors to optimize cobot adoption and implementation.
The research offers valuable insights for both academia and industry. Academically, it integrates human factors into established adoption frameworks such as DOI and TOE, offering fresh perspectives on how organizations manage cobot integration. It also emphasizes the need for interdisciplinary research that addresses both technical and human elements of adoption.
Practically, the findings provide industry practitioners with tools for overcoming challenges in cobot integration. By mapping barriers and enablers at different stages, the research equips organizations with strategies to achieve both operational efficiency and workforce engagement.
Paper 1: Mapping the Landscape of Collaborative Robots: A Systematic Literature Review of Industrial Implementation, Challenges, and Future Directions
This paper provides a systematic review of 94 academic articles, addressing three key questions:
1. What are the thematic trends in the literature on cobot implementation?
2. What are the barriers to cobot integration?
3. How can these barriers be addressed in future research?
The review identifies seven thematic clusters, including Evaluation, Human-Robot Interaction (HRI), and Risk Assessment, which offer a broad view of the current state of cobot research. Recurring challenges such as cognitive ergonomics, safety concerns, and long-term performance assessments are highlighted. The paper proposes a structured framework for future research, focusing on how organizations can overcome technical and operational hurdles through improved training, safety protocols, and organizational change management. It emphasizes that successful cobot adoption requires strategic alignment between technological innovations, workforce readiness, and organizational structures.
Paper 2: Cobots in SMEs: Implementation Processes, Barriers, and Success Factors
This paper explores the unique challenges and enablers that SMEs face when adopting cobots. The following research questions guide the investigation:
1. What specific barriers do SMEs face during cobot adoption?
2. What success factors enable SMEs to overcome these barriers?
Through qualitative analysis of five SMEs, the study uncovers three primary clusters of barriers: technical (e.g., programming complexity and safety requirements), organizational (e.g., job redesign and knowledge integration), and cultural (e.g., fear of job displacement and distrust of new technologies). The research identifies open innovation, employee involvement, and pilot testing as key enablers that help SMEs navigate the complexities of cobot integration. By collaborating with external partners and empowering their workforce, SMEs can modernize their production processes in a cost-effective manner. The findings suggest that cobots offer SMEs a way to enhance flexibility, reduce labor costs, and stay competitive in the evolving landscape of Industry 4.0.
Paper 3: From Knowledge to Confirmation: A Stage-Based Analysis of Collaborative Robot Adoption in Manufacturing
This paper applies Rogers' Diffusion of Innovation (DOI) model, complemented by the Technology-Organization-Environment (TOE) framework, to trace the cobot adoption process across five stages: Knowledge, Persuasion, Decision, Implementation, and Confirmation. The paper addresses the following questions:
1. What are the drivers motivating the adoption of cobots in manufacturing?
2. What barriers and enablers emerge during the cobot adoption process?
3. How do these determinants influence the stages of cobot adoption?research?
A key contribution of this paper is the mapping of enablers and barriers across the DOI stages, with ambivalent themes emerging throughout the adoption process. These themes—Driving Forces, Culture and Leadership, Strategic Financial Management, Pilot Testing, Regulatory Navigation, Ecosystem Collaboration, Validation, and Lessons Learned from Failure Cases—illustrate how the interaction between leadership, financial strategies, and external partnerships shapes cobot outcomes. This stage-based approach offers a dynamic view of cobot integration, showing how human factors become more prominent as organizations move from initial knowledge acquisition to post-installation stages. The paper advocates for sector-specific research to refine the DOI-TOE framework in industries with lower automation levels.
The dissertation employs a systematic literature review (SLR) in Paper 1 and qualitative multiple case studies in Papers 2 and 3. The SLR offers a broad overview of existing research trends and methodologies, ensuring a transparent and replicable approach to understanding cobot adoption. The case studies in Papers 2 and 3 use semi-structured interviews, observations, and document analysis to provide in-depth insights into the specific challenges and strategies faced by SMEs and large firms. By integrating theoretical frameworks with real-world data, the research produces both academic and practical contributions to the field of collaborative robotics.
This dissertation contributes to both theory and practice by:
• Mapping thematic trends and identifying barriers in cobot adoption literature.
• Offering insights into the specific challenges SMEs face and the enablers that facilitate their cobot integration.
• Developing a stage-based framework for cobot adoption, illustrating the interaction of enablers and barriers at each stage.
• Proposing actionable frameworks that help organizations align technological advancements with human and organizational factors to optimize cobot adoption and implementation.
The research offers valuable insights for both academia and industry. Academically, it integrates human factors into established adoption frameworks such as DOI and TOE, offering fresh perspectives on how organizations manage cobot integration. It also emphasizes the need for interdisciplinary research that addresses both technical and human elements of adoption.
Practically, the findings provide industry practitioners with tools for overcoming challenges in cobot integration. By mapping barriers and enablers at different stages, the research equips organizations with strategies to achieve both operational efficiency and workforce engagement.
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