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Navigating Unpredictability: Collaborative Networks in Non-linear Worlds

25th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2024, Albi, France, October 28–30, 2024, Proceedings, Part I

Editors: Luis M. Camarinha-Matos, Angel Ortiz, Xavier Boucher, Anne-Marie Barthe-Delanoë

Publisher: Springer Nature Switzerland

Book Series : IFIP Advances in Information and Communication Technology

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Table of Contents

About this book

This two-volume set, IFIP AICT 726 and 727, constitutes the refereed proceedings of the 25th IFIP WG 5.5 Working Conference on Virtual Enterprise, PRO-VE 2024, held in Albi, France, during October 28–30, 2024.

The 56 full papers presented in these two volumes were carefully reviewed and selected from 113 submissions. The papers presented in these two volumes are organized in the following topical sections:

Part I: AI and collaboration; Human-machine collaboration; Emotions and collaborative networks; Collaborative ecosystems: Skills for resilient futures; Collaborative ecosystems: Technologies for resilient futures; Uncertainty and collaboration in supply chain; Collaborative networks as driver of innovation in organizations 5.0: Models; Collaborative networks as driver of innovation in organizations 5.0: Participation; Trust and trustworthy technologies in collaborative networks.

Part II: Empowering vulnerable populations well-being through collaborative networks; Collaborative manufacturing systems in the digital era; Fostering collaborative and interoperable digital models for digital twins: Methods; Fostering collaborative and interoperable digital models for digital twins: Cases; Zero defects and zero waste strategies in industrial collaborative networks; Simulation frameworks; Collaborative decision making; Design of collaborative environments.

Frontmatter

AI and Collaboration

Frontmatter

Hybrid Collaborative Networks in Energy Ecosystems

Abstract

Human-AI collaboration in renewable energy ecosystems can revolutionize the way communities achieve sustainable and efficient energy solutions. This synergistic approach combines the analytical prowess of AI with the expertise of human decision-making, fostering a comprehensive strategy for energy management. AI excels in tasks that are repetitive and mundane, while humans excel at decision-making tasks that reflect their preferences and community dynamics, ensuring that AI-driven solutions are aligned with societal values. This collaborative approach, representing a case of hybrid collaborative network, can lead to optimizing energy use, reducing dependency on the grid, and empowering communities to lead the energy transition, fostering more resilient and sustainable energy ecosystems. In this context, we explore possibilities of achieving “meaningful” energy conservation practices in a Collaborative Energy Ecosystem (CEE) using human-AI collaboration. As such, we expand and discuss the CEE model from the perspective of hybrid human-AI collaboration, present pilot implementation results, and discuss future research directions.

Kankam Okatakyie Adu-Kankam, Luis M. Camarinha-Matos, Eric Obeng

Integrating AI in Supply Chain Management: Using a Socio-Technical Chart to Navigate Unknown Transformations

Abstract

For decades, the collaborative networks community has studied supply chains, focusing on trust, visibility, collaboration, and innovation, with emergent technologies being a key area of research. The rise of digital technologies has led to extensive studies on supply chain digital transformation. With the surge of AI-based technologies, there is an increasing body of research on AI's human and social impact on Supply Chain Management (SCM). However, while Socio-Technical Systems (STS) thinking has been applied to digital transformations, it has not yet addressed AI-induced changes in supply chains. This paper synthesises recent research on AI integration in SCM and the use of STS thinking in AI systems design. We propose a mapping approach for profiling AI-induced supply chain transformations for strategic design. We also present the Supply Chain Socio-Technical AI (SC-STAI) profiling tool in practice, demonstrating how it maps supply chain participants’ current and desired states regarding AI integration.

António Lucas Soares, Jorão Gomes Jr., Ricardo Zimmermann, Donna Rhodes, Verena Dorner

Towards the Integration of Conversational Agents Through a Social Media Platform to Enhance the Agility of BPM

Abstract

Business Processes enable collaboration among various stakeholders, allowing different groups (people, organizations) to work together to achieve common goals. Therefore, optimizing Business Process Management (BPM) is essential for organizational success in today’s dynamic business environment. However, traditional BPM methods often struggle in volatile execution environments characterized by rapid change, dynamic customer demands, and evolving market trends. Innovative strategies are needed to enhance BPM practices and increase the agility of collaborative business processes. To this end, a particularly promising approach is to use Large Language Models (LLM) agents (Artificial Intelligence conversational agents). These AI conversational agents can be integrated into a social media platform to ease the stakeholders’ collaboration by supporting the co-construction, design, modification, execution, and monitoring of collaborative business processes. AI conversational agents in social media platforms democratize BPM by facilitating collaborative process design and execution, streamlining interactions, and fostering seamless communication and personalized assistance, thus enhancing agility.

Lala Aïcha Sarr, Paul Komlan Ayite, Anne -Marie Barthe-Delanoë, Dominik Bork, Guillaume Macé-Ramète, Frederick Benaben

Human-Machine Collaboration

Frontmatter

Human and Machine Complementary Roles in Collaborative Evaluation of Creative Speech

Abstract

This paper explores the complementary roles of humans and machines in the collaborative evaluation of creative speech, aiming to enhance the accuracy, reliability, and efficiency of creativity assessments. Traditional methods of evaluating creative speech primarily rely on human judges, who bring intuition and contextual understanding but are limited by subjectivity and scalability challenges. Conversely, artificial intelligence offers computational power and consistency but lacks the complex judgment that human evaluators provide. This research aims to investigate the divergent and convergent aspects of each evaluation and highlight the importance of co-creative collaboration between humans and machines. We utilize the Torrance Tests of Creative Thinking to assess the 22 creative speech samples of 11 participants, comparing evaluations conducted by human experts, and an AI system (the GPT4). While the results demonstrate a certain degree of correlation between human and AI evaluation especially in evaluating Flexibility, they also reveal the differences in how humans and machines perceive Originality in text.

Sepideh Kalateh, Sanaz Nikghadam-Hojjati, José Barata

Continual Learning for Human-Machine Collaboration in VUCA Environments

Abstract

This study presents a novel approach to enhancing human-machine collaboration (HMC) in volatile, uncertain, complex, and ambiguous (VUCA) environments by emphasizing the importance of continual learning. Addressing the limitations of traditional static systems, the proposed HMC system integrates continual learning and object detection algorithms to enhance error handling, operational efficiency, and resilience. The research aims to establish a new standard for intelligent HMC systems, emphasizing ongoing reciprocal learning between humans and machines to improve decision-making and performance. Practical implementation demonstrates the system’s effectiveness in reducing downtime and increasing adaptability. By integrating human expertise and machine intelligence, the system fosters improved problem-solving capabilities and operational efficiency, making it highly suitable for dynamic and unpredictable industrial settings. This study addresses critical gaps in current methodologies, providing a comprehensive framework for the future of HMC in complex manufacturing environments.

Yuchen Fan, Dario Antonelli, Alessandro Simeone

Associations Between Gender Attributions and Social Perception of Humanoid Robots

Abstract

With the thriving integration of robots in work spaces, user acceptance and trust in robots are particularly important. Both aspects are influenced by various factors, e.g., social perception. Gender considerably affects social perception of humans, however, whether gender attributions to robots hold similar implications is still unclear. We investigated this question with two samples (N₁ = 238, N₂ = 133) who rated four images of humanoid robots in terms of gender and social dimensions, i.e., anthropomorphism, sociability/morality, activity/cooperation, and competence. We found that in both samples gender perception differed significantly, but only perceived competence and sociability/morality varied as a function of gender: More femininity was associated with higher attributions of sociability/morality and lower attributions of competence. We take this as an indicator that gender influences social perception and should be considered as additional aspect when it comes to designing robots. However, gendering robots might also pose ethical risks in terms of deception and unwanted amplification of gender stereotypes.

Sarah Mandl, Jonna S. Laß, Anja Strobel

Emotions and Collaborative Networks

Frontmatter

Emotions in Human-AI Collaboration

Abstract

This exploratory paper addresses the role of emotions in the management of collaborative networks (CNs) amid the rise of hybrid teams consisting of humans and AI agents. Building on previous research that emphasizes the critical role of emotions in fostering trust and preventing conflicts within CNs, we propose expanding these emotional frameworks to accommodate hybrid collaborative networks. The paper reviews the significance of human-AI collaboration, highlighting the complementary strengths of both and identifying three research streams: affective/sentient AI agents, human emotions modelling, and collective hybrid network emotions. Emphasizing the underexplored area of collective emotions, we suggest leveraging these insights to enhance the management and sustainability of hybrid networks. A framework for emotions estimation in CNs is described. Our aim is to identify challenges and guide future research in the integration of emotional intelligence within human-AI collaborative environments.

Filipa Ferrada, Luis M. Camarinha-Matos

Do There Exist an Emotion Trend in Scientific Papers? PRO-VE Conference as a Case

Abstract

Scientific writing aims for formality and objectivity, yet emotions are integral to human communication, decision-making, and collaboration, all of which are fundamental to scientific progress. Existing research on emotion detection has mainly focused on datasets from social media and online platforms, where emotional expressions are abundant. However, scientific texts pose unique challenges due to their formal language and the rarity of explicit emotional words, necessitating specialised investigation. This study investigates the presence and nature of emotions in scientific texts, specifically analysing the abstracts from the PRO-VE conference series from 2012 to 2022. Two emotion detection methods are employed: a lexicon-based approach and a hybrid machine learning-based approach. The lexicon-based approach utilises the NRC Emotion Lexicon to identify and quantify emotions within the PRO-VE abstracts, while the hybrid approach integrates Word2Vec for word embedding generation and a Random Forest classifier for emotion prediction. The findings reveal a predominance of positive emotions, such as trust, anticipation, and joy, in the PRO-VE abstracts, consistent with the objective nature of scientific writing. In light of the PRO-VE conference series’ 25th anniversary, an analysis of trends and patterns in the detected emotions offers insights into the emotional landscape of this prestigious conference series. The study also critically examines the limitations of the experiments, including the dataset size and the prevalence of positive emotions.

Rishitha Venumuddala, Lai Xu, Paul de Vrieze

Integrating Perception and Systemic Theories in Collaborative Networks-Enhancing Adaptability and Resilience in a Nonlinear World

Abstract

This paper explores the integration of Hoffman’s Perception Theory and Klir’s System Theory to enhance Collaborative Networks (CN). Hoffman’s theory emphasizes subjective experiences and cognitive processes, focusing on survival and growth, while Klir’s theory introduces a hierarchical model of systems, highlighting the importance of supportive variables including time and space in dynamic situations. By combining these perspectives, the paper proposes a dual-framework approach to improve adaptability and resilience in CNs. Using the COVID-19 pandemic response and Global Supply Chain Management as case studies, we demonstrate the practical advantages of this integrated model in navigating complex, nonlinear environments.

Javad Jassbi, Mahmood Alborzi, Hamed Jassbi

Collaborative Ecosystems: Skills for Resilient Futures

Frontmatter

Design of a Collaborative Network for Mapping Digital Skills for Industry 5.0

Abstract

This paper outlines a conceptual model of a Future Skills Collaborative Network (FSCN), a multi-stakeholder initiative designed to address the widening digital skill gaps in industry. By utilizing models to map required digital skills—from basic to specialized proficiencies—the FSCN aims to identify and potentiate training pathways that align with industrial needs. Utilizing open data for pilot analyses, this study demonstrates the practical application of the FSCN in identifying trends and relationships between digital skills, job requirements, and technological advancements. The findings underscore foreseen digital skills and the benefits of the FSCN’s potential to significantly address the challenges presented by the digital transformation in Industry 5.0.

Maria Gustavsson, Oliviu Matei, Laura Andreica, Agneta Halvarsson Lundkvist, Daniel Persson Thunqvist

Collaborative Ecosystems for Increasing Automation in Accounting Processes in Small Firms

Abstract

Automation of accounting processes promises various benefits for firms, such as enhanced productivity, improved customer service and job satisfaction. Despite the enhancements, small firms are often reluctant to undertake accounting process automation projects. This research studies how collaborative ecosystems support small firms in adopting accounting automations. The study draws on the Technology Acceptance Model (TAM) and studies the perceived usefulness and ease of use of automation technology in the context of small firms. In this qualitative research, 12 firms joined a collaborative ecosystem to develop automated accounting processes. A year later, 12 semi-structured interviews were conducted to examine the technology uptake by the firms. Our findings indicate that a collaborative ecosystem provides support in the first steps of technology uptake, especially by adding to the perceived usefulness of the automations. However, it did not increase automation-related skills enough to increase the perceived ease of use of the technologies.

Heli Kortesalmi, Lili Aunimo, Eija-Leena Kärkinen

The Innovation Challenge Bootcamp Model

Abstract

Education has responded to industrial demands, to new technological developments and capacities required for the application of concepts to generate models that describe reality. Traditional educational models where the student acts as a recipient of knowledge have been surpassed by the demands of the new automated and connected industrial currents. These educational currents, despite taking advantage of information resources, active learning techniques and team collaboration, are limited by other aspects that hinder their dissemination. Thus, the role of the educator, spaces required, teamwork and available resources must be combined in order to follow the pace of technology adoption and thus cover the new educational paradigms. This article explores an educational model based on challenges that has been implemented with researchers, lecturers, and university students. This model has had a positive impact on the participants in project development and entrepreneurship skills.

Daniel Cortés, Jose-Bernardo Rosas-Fernandez, Arturo Molina

Collaborative Ecosystems: Technologies for Resilient Futures

Frontmatter

Evaluating Privacy Patterns Within Collaborative Frameworks for AI Ecosystem Development

Abstract

Robust data privacy is crucial for mitigating financial, legal, and reputational risks in organizations. While legislative frameworks like the EU GDPR mandate comprehensive data protection measures, integrating these into information systems presents significant challenges. Privacy Patterns (PP) aim to bridge this gap by translating legal requirements into actionable data protection strategies, yet their effectiveness in practical scenarios is not well-documented. This study explores the applicability, effectiveness, and limitations of PP in the collaborative development and operation of an AI-driven ecosystem aimed at automating the handling of legal declarations to enforce consumer rights.

Lukas Waidelich, Marian Lambert, Thomas Schuster

Towards a Reference Architecture for Collaborative Decision Support Systems for Natural Disasters Management

Abstract

Natural disasters (ND) have become increasingly frequent, causing impactful social, economic, and environmental consequences. Civil defenses and related actors are the ones in charge of handling ND throughout their life cycles regarding their different types and intensities. There are plenty of issues that should be considered when facing a ND, including very complex analyses and collaborative decision-making. Studies show an increasing use of decision support systems (DSS) to assist civil defenses in ND. However, it was observed that the numerous DSS for ND cover only isolated parts of the problem, making it difficult to design a complete, scalable, and globally coherent roadmap for civil defenses and software developers. This article proposes a reference architecture aiming at acting as a blueprint for derivation of particular ND DSS. A software prototype has been developed to show a derived DSS based on a civil defense organization. Conclusions and next steps of this work are presented at the end.

Pedro S. Zanchett, Ricardo J. Rabelo

Asset Administration Shell Approach for Modular and Configurable Internet of Things Devices

Abstract

Nowadays, the massive integration of Internet of Things (IoT) devices creates industrial data-rich environments, which makes data extraction a critical task. As such, there is a need to adopt flexible, interoperable, and adaptable solutions for both IoT devices and data collection processes. This paper proposes a modular and reconfigurable approach aligned with the principles of Reference Architectural Model Industrie 4.0 (RAMI 4.0) and Industry 4.0, which explores the concept of Asset Administration Shell (AAS) and how they can smooth collaboration in creating IoT nodes and, consequently, in the data extraction processes. The creation of these nodes encompasses three phases: the design, development, and deployment phases. With the proposed common descriptions for the components of the nodes, it is possible for the different stakeholders to work collaboratively to increase the adoption of their solutions. Hence, the approach aims to improve IoT modules’ digital representation and management, allowing for better integration and dynamic adaptation. The main concepts and practical implications will be discussed, stressing the transformative potential of AAS in modular and reconfigurable IoT devices.

Miguel Arvana, Nelson Freitas, Andre Dionisio Rocha, Jose Barata

Uncertainty and Collaboration in Supply Chain

Frontmatter

Integrating Uncertainty into a Supply Chain Network for Adaptive S&OP Process

Abstract

Instability is the new normal for supply chain networks. In this context, the Adaptive Sales and Operations Planning (AS&OP) process proposed by the Demand-Driven Adaptive-Enterprise model aims to improve the way these supply chain networks manage volatile, uncertain, complex and ambiguous environments. However, the process, as originally defined, relies mainly on a deterministic maximum likelihood approach, thus limiting its scope. The present research work examines existing strategies for integrating uncertainty into the strategic planning and ultimately proposes an original Decision Support System that integrates uncertainty via interval data and scenario-based planning. An illustrative case study validates this proposal and discusses its limitations.

Jean Baptiste Vidal, Raphaël Oger, Matthieu Lauras, Jacques Lamothe

How Best Practices of SCOR DS Model Support Short Supply Chains Management: A Bibliometric Analysis

Abstract

Short Supply Chains are considered as one of the viable alternatives to reduce the environmental impact of economic activities. This work introduces a bibliometric analysis of short and classical supply chains using the 281 best practices from the new Supply Chain Operations Reference Digital Standard (SCOR DS) model. For each best practice, the number of papers related to short and classical supply chains is recorded from a literature analysis. Results show that the three most studied best practices are “Make Or Buy Analysis”, “Supply Market Research”, “Supply Chain Optimization”. Nevertheless, some best practices require further investigation of their applicability in short supply chains.

Gaia Sassone, Taha Arbaoui, Valérie Botta-Genoulaz

Bibliometric Analysis of Immersive Technologies in Supply Chain Strategy: Knowledge-Based Systems Case

Abstract

This bibliometric analysis explores the application of immersive technologies in supporting strategic supply chain decisions. Emphasizing the impact in sustainability, human centered, and antifragile, the study highlights the significance of collaborative approaches in enhancing supply chain strategies. The analysis reveals trends and research gaps, offering insights into the integration of advanced algorithms for sustainable, antifragility supply chain strategic decisions. This work contributes to a deeper understanding of how immersive technology development with knowledge-based tools can drive sustainable and antifragile supply chains at the strategic level of decision.

Beatriz Andres, Rocio de la Torre, Ana Mojica

Impact of a Set of Factors on Order Lead Time: A Case Study of an Apparel Company

Abstract

Apparel supply chain is facing challenges due to recent unexpected market turbulences. This might affect the order lead time with consequences on customers’ satisfaction. It is therefore important to have more control over the supply chain to be more resilient and to respond to market changes. In this context, the distances that products must travel from the production plants can be very significant, influencing order lead times. Consequently, in order to quantitatively measure the effect of distance, as well as other operation independent factors, on order lead time, an empirical model is presented. The data is collected from orders placed by a clothing company that sells its products internationally and outsources production. The results show a significant relationship between lead time, distance or proximity, quantity actually shipped, order cost and product category ordered.

Giulio Mangano, Valérie Botta-Genoulaz, Massimo Rebuglio

Collaborative Networks as Driver of Innovation in Organizations 5.0: Models

Frontmatter

Utilizing Natural Language Processing for Enhancing Collaborative Value-Driven Design of Smart Product Service System: Smart E-Vehicle Application

Abstract

Manufacturing companies are increasingly transitioning from a product-centric to a smart Product Service System (smart PSS) approach to enhance customer satisfaction, service offerings, and product competitiveness through a combination of usage scenarios and digital components. In the context of Industry 5.0 transformation such as developing the Smart Electric Vehicle (SEV), the automotive industry faces the challenge of understanding customers’ descriptions of usage scenarios and translating the qualitative aspects of these scenarios into quantitatively assessed product features for collaborative value co-creation in smart PSS design. This paper addresses this challenge through utilizing Natural Language Processing (NLP) joint with Value-Driven Design (VDD) method for successfully supported a collaborative value exploration of in the smart PSS design stage. A case study was collaborated with a global automotive Original Equipment Manufacturer (OEM), Volkswagen, through proposing a NLP BERT model for VDD of Smart Electric Vehicle (SEV) design. Validation activities were performed by deploying the developed BERT model to the case company based on the scenario design of new car models.

Yan Zhang, Andreas Larsson, Tobias Larsson, Wenchong Tian, Lan Zhang, Wei Wang

Leveraging Collaboration for Industry 5.0: Needs, Strategies and Future Directions

Abstract

This paper analyzes the identified key elements that are needed by the Industrial sector to ensure the seamless transition of enterprises from the “4.0 paradigm” – based on digitalization and technologies, to the “5.0 paradigm” – focused on resilience, “green” mindset and human-centric approach. The basis of this analysis is a research survey conducted within a century-old European technology company, focused on automotive products, with over 20 locations spread on more than 10 countries and on 4 continents. The goal of this paper is to identify both the needs of the Industrial sector concerning the “5.0 Transition” and the focus points for the CoDEMO 5.0 project, concerning what the Industry players expect from this Consortium. Moreover, this paper aims to define a process in which these two elements combine harmoniously so that a continuous positive feedback loop is established and, if implemented on a wider scale, could establish a new way of working among the EU Industrial actors, thanks to the collaborative network that shall be established. Concerning this study, such a collaborative network is composed of a “triple-helix” formed by the Customer (OEM manufacturer), the Supplier (automotive company), and the Academic Partner. Such partnership will enable the OEM to come out with new, and groundbreaking products that stand out from their competitors, thanks to the supplier that is creating these products which in turn, can develop them thanks to the academic partner that prepares highly skilled professionals for the current and future emerging technologies from Industrial sector like Artificial Intelligence, machine learning, blockchain, quantum computing, IIoTs, etc.

Vlad Toncian, Adrian Florea, Alin David, Daniel Morariu, Radu Cretulescu

Towards a Conceptual Model for Enhancing Efficiency and Collaboration in Agile Ramp-Up Projects Planning

Abstract

Agility is a major concern for industries across manufacturing and service sectors for a variety of reasons. For instance, frequent product development to meet evolving customer requirements and changing markets requires efficient and agile processes. Therefore, companies need to capitalize on product and service development and ramp-up projects in order to improve their efficiency as well as time-to-market. This paper provides preliminary results to address this gap by proposing a model covering conceptual underpinnings of agile ramp-up management. The model is developed iteratively following the design science research methodology. A simple excel prototype resulting from the model is developed in order to support agile ramp-up project planning. The model as well as the prototype are expected to help decision makers in scoping ramp-up projects and in improving the consistency of these projects planning. They also support the collaboration within ramp-up project team through sharing a common understanding of the project scope.

Qussay Jarrar, Cheikh S-A-M Taleb, Shervin Kadkhoda-Ahmadi, Khaled Medini

Collaborative Networks as Driver of Innovation in Organizations 5.0: Participation

Frontmatter

Participation as Fuel for Transformation - An Approach to the Interrelations Between Digitalization, Participation and Values in NPOs

Abstract

Non-profit organizations (NPOs) differ from profit-oriented organizations not only in their motivation but also in their internal organizational structures as well as in their network embedding. In the implementation of digital structures within an NPO’s very commonly, managerial methods that were developed for for-profit organizations, are applied because of the lack of suitable alternatives. Yet, it is important to respect the organizational and motivational differences, as they have a crucial impact on the success of digital transformation processes. This paper wants to explore the state-of-the-art, both practical and theoretical, how digitalization transformation and organizational value can be brought together and be assessed by a participative approach, and how this can be a success factor in the development of the organization. The research is based on a mixed-methods approach that includes a literature review and an expert workshop with practitioners.

Julia Friedrich, Vanita Römer, Christian Zinke-Wehlmann

Digital Leadership from the Perspective of Organization 5.0: An Analysis of Key Action Fields towards Green, Resilient, and Human-centered Digitalization

Abstract

Digital leadership is discussed as a success critical factor for collaborative digital transformation of businesses and gained increasing importance in industry 4.0. However, recent dynamics like current crises, disruptive changes in corporate environments and ecological challenges demand further development towards industry 5.0 including the collaborative principles of organization 5.0. The concept of organization 5.0 complements the technology-oriented perspective of 4.0 towards a broader vision considering digitalization as the key enabler for an ecological, resilient, and human-centered transformation of industries and organizations. In the present article, we analyze key action fields of digital leadership gaining relevance in Organization 5.0. These action fields of digital leadership are introduced along the three pillars of Organization 5.0 described as resilience, green and human-centricity.

Philipp Korte, Maria Kobert, Thomas Süße

Skills, Technical and Organizational Support Needed for Collaborative Networks 5.0

Abstract

The transition to Industry 5.0 has redefined the innovation requirements of organisations, emphasising sustainable, resilient and human-centred dimensions. The fifth industrial revolution also prioritises the co-creation of value within Collaborative Networks (CNs). By bringing together different socio-economic actors, organisations can leverage synergies to drive innovation and address complex global challenges more effectively. To operate efficiently within collaborative networks, a collaborative mindset, supported by specific technical and organisational resources, is essential. This study presents the findings of a European survey that investigated the innovation requirements of organizations transitioning towards Industry 5.0 and the resources necessary for collaborative 5.0 networks. The analysis showed that different regions and sectors have different needs, highlighting the necessity of tailoring approaches to each organisation’s context. The results of the study emphasize the urgent requirement for multiple interventions to promote efficient collaboration and innovation in the transition to 5.0 organisations.

Luca Carminati, Fabiana Pirola, Alexandra Lagorio, Chiara Cimini, Arkadiusz Jurczuk, Xavier Boucher

Trust and Trustworthy Technologies in Collaborative Networks

Frontmatter

Navigating Trust: A Morphological Analysis of Blockchain-as-a-Service Providers

Abstract

In various use cases, the blockchain manages to increase trust among participants in the supply chain. Whether it is the origin of critical raw materials or compliance with industry-specific requirements. The majority of companies utilize blockchain as a service providers for this purpose to benefit from the advantages of this technology. Existing classifications in the literature often do not consider the decision-makers’ perspective, which can lead to an incomplete evaluation of the available options. We offer a morphological approach that identifies relevant decision criteria for trust and security. This enables organizations to make informed decisions and increase confidence in their business processes without having to invest their own resources in development and operations.

Eugen Buss, Marc Hübschke, Tobias Hünemeyer, Elmar Holschbach, Stefan Lier

AI-Enhanced QOC-Analysis: A Framework for Transparent and Insightful Decision-Making

Abstract

This paper explores the integration of Artificial Intelligence (AI) into the Questions Options Criteria (QOC) process, enhancing decision making through different levels of AI integration. It elaborates on AI’s role from providing support with insights and suggestions, acting as an additional participant in decision making, to fully autonomously generating and evaluating decision contexts by a network of AI based agents. By integrating AI across these levels, the framework is expanded and offers a traceable AI-enhanced decision making process. The paper discusses three different approaches to integrating AI into the QOC process, where AI is either a supporting element for the participant, AI is a participant in the decision making process, and a fully automated QOC analysis by AI. This progression in understandable and verifiable AI participation marks an advancement in decision support systems, illustrating the potential for sophisticated AI integration in complex decision making processes.

Lambert Schmidt, Marcel Pehlke, Marc Jansen

Sovereign Citizen on Digital Regulated Services Ecosystem

Abstract

The infrastructure and application systems shaping digital society have evolved rapidly over the last two decades, driven by unprecedented collaborative efforts within the industry and motivated by the need to scale. The demand for reduced operational costs and enhanced scalability motivated many to join the pioneers who decided to share their data centers in public clouds. This shift has accelerated new business ventures across various societal sectors. However, the absence of a unified reference model has hindered the creation of a trustworthy digital ecosystem that can be both simple and secure for citizens and companies. A pressing concern remains: how can citizens trust that their data is maintained private by business providers of different scales and following different models? Building on previous research focused on unified mobility payment services and trusted digital services for citizens, this position paper proposes a strategy for a unified model that enables citizens to adopt a service provider to “navigate” across the digital ecosystem. While the payment perspective is included, herein our primary focus is on the data. The key idea is to offer citizens a unified digital identity and a personal “safe vault” on the “digital ecosystem”. This ecosystem is envisioned to develop parallel to the banking system, where a regulated model assures clients that their savings are secured. The paper discusses the Secure Citizen on Digital ecosystem (SCOD) concept and emphasizes the need for an open business-technology ecosystem based on the Collaborative Networks concepts.

A. Luís Osório, Luis M. Camarinha-Matos, Carlos Gonçalves, Tiago M. Dias

Personal Data Sovereignty in Virtual Enterprises: Implementing Data Capsules for Enhanced Privacy and Compliance

Abstract

In the context of Virtual Enterprises (VEs), the intersection between big data analytics, data ownership, and regulatory compliance raises significant challenges. This paper presents a novel framework for redefining data control within VEs by transferring ownership from Data Controller entities to individuals. Central to this framework is the proposed novel notion of the Data Capsule, which empowers individuals with personal data sovereignty i.e., with the ability to dictate the terms and conditions of their data usage directly. The Data Capsule system leverages ontologies, semantic technologies, and blockchain to homogenise heterogeneous data, enable annotation, enforce governance rules, and assure transparency. This framework addresses the unique data management needs of VEs by promoting transparency and allowing all participants to openly state the level and type of engagement permitted with their data. By making individuals the primary custodians of their data, this paper intends to enhance privacy, security, and ethical data handling while avoiding the possible drawbacks of profit-driven approaches. The paper additionally considers compliance with pertinent legislation including the European Union’s General Data Protection Regulation (GDPR), the Data Governance Act and the AI Act. The suggested framework provides considerable benefits to SMEs in VEs, such as competitive advantage and cost savings. This paper outlines a research plan, provides a state-of-the-art analysis, establishes the system’s objectives, and aligns the framework with the needs of VEs.

Vijon Baraku, Iraklis Paraskakis, Simeon Veloudis, Poonam Yadav

Backmatter

Title: Navigating Unpredictability: Collaborative Networks in Non-linear Worlds
Editors: Luis M. Camarinha-Matos
Angel Ortiz
Xavier Boucher
Anne-Marie Barthe-Delanoë
Publisher: Springer Nature Switzerland
Electronic ISBN: 978-3-031-71739-0
Print ISBN: 978-3-031-71738-3
DOI: https://doi.org/10.1007/978-3-031-71739-0