Innovation Policy Roadmapping for the Future Finnish Smart City Digital Twins : Towards Finland National Digital Twin Programme

Smart City Digital Twins (SCDTs) emerge as a transforming concept with the ability to redefine the future of cities in the fast-paced evolving landscape of urban development. This qualitative futures research explores thoroughly into the complex interaction of socio-technical dynamics in the Finnish setting, investigating the several ways SCDTs might revolutionise urban spaces and create resilience. By utilizing Innovation Policy Roadmapping (IPRM) method for the first time on SCDTs, it reveals the diverse capacities of SCDTs across domains such as urban planning, scenario developing, What-IF analysis, and public involvement through a rigorous examination of academic literature and multi-level analysis of expert interviews. The research emphasises the critical role of policymakers and sectoral actors in building an environment that allows Finnish SCDTs to survive in the face of technological improvements. Furthermore, it emphasises the convergence of SCDTs and Futures Studies approaches, giving a visionary path to adaptable and forward-thinking urban futures. The contributions of this study extend beyond the scope of Finnish SCDTs, giving inspiration for sustainable smart city transformations, potential foundational insights towards Finland National Digital Twin Programme and paving the way for the incorporation of futures studies methodologies and digital twins to mitigate uncertainties and create resilient urban futures. Longitudinal impact assessments, real-time citizen-centric foresight applications via SCDT, and the investigation of SCDTs' role in disaster mitigation and social well-being are among the identified future research directions, providing a comprehensive roadmap for leveraging SCDTs as transformative tools for building sustainable urban futures

Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions

Artificial intelligence (AI) is a set of rapidly expanding disruptive technologies that are radically transforming various aspects related to people, business, society, and the environment. With the proliferation of digital computing devices and the emergence of big data, AI is increasingly offering significant opportunities for society and business organizations. The growing interest of scholars and practitioners in AI has resulted in the diversity of research topics explored in bulks of scholarly literature published in leading research outlets. This study aims to map the intellectual structure and evolution of the conceptual structure of overall AI research published in Technological Forecasting and Social Change (TF&SC). This study uses machine learning-based structural topic modeling (STM) to extract, report, and visualize the latent topics from the AI research literature. Further, the disciplinary patterns in the intellectual structure of AI research are examined with the additional objective of assessing the disciplinary impact of AI. The results of the topic modeling reveal eight key topics, out of which the topics concerning healthcare, circular economy and sustainable supply chain, adoption of AI by consumers, and AI for decision-making are showing a rising trend over the years. AI research has a significant influence on disciplines such as business, management, and accounting, social science, engineering, computer science, and mathematics. The study provides an insightful agenda for the future based on evidence-based research directions that would benefit future AI scholars to identify contemporary research issues and develop impactful research to solve complex societal problems

COOLEST STUDENT PAPERS AT FINLAND FUTURES RESEARCH CENTRE 2021–2022: Tulevaisuuden tutkimuskeskuksen valittuja opiskelijatöitä 2021–2022

Tärkeä osa maisteriopintojen oppimistavoitteita on osoittaa, että opiskelija pystyy itsenäiseen tutkimustyöhön ja tuottamaan tieteellistä tekstiä artikkeleiden ja muiden julkaisutapojen muodossa. Akateeminen kirjoittaminen on oma osaamisalueensa, ja vaikka sosiaalinen media ja tieteen popularisaatio asettavat erilaisia haasteita ja kanavia tutkimustulosten levittämiseen kuin perinteinen akateeminen julkaiseminen, tiedeyhteisössä vallinnee konsensus siitä, että tutkijoiden on osattava tuottaa akateemista tekstiä. Opintojen on tuettava tämän taidon kehittymistä. Tulevaisuuden tutkimuskeskus on julkaissut vuodesta 2016 lähtien koosteita ansiokkaista opiskelijoiden opintojensa aikana kirjoittamista esseistä, harjoitustöistä ja muista kirjallisista opintosuoritteista. Haluamme tarjota opiskelijoille oikean julkaisukanavan ja auttaa heitä saamaan vaikka sen ensimmäisen julkaisutiedon ansioluetteloon. Tämänvuotinen julkaisumme osoittaa, että pelko opiskelijoiden kirjallisten kykyjen huonontumisesta tai taantumisesta on turhaa. Samalla se todistaa myös opettajiemme onnistuneen opiskelijoiden akateemisen kirjoittamisen taitojen harjaannuttamisessa. Julkaisumme koostuu tulevaisuudentutkimuksen kansainvälisen maisteriohjelman, Turun yliopiston kestävän kehityksen opintokokonaisuuden (KEKO) ja Tulevaisuudentutkimuksen Verkostoakatemian (TVA) opiskelijoiden kirjoituksista. Koska opiskelijatyöt on tehty englanniksi maisteriohjelmassa ja suomeksi KEKO- ja TVA-opinnoissa, julkaisemme työt alkuperäisellä kielellä. Sisällöllisesti aiheet vaihtelevat suuresti, mutta niitä yhdistävä tekijä on tulevaisuussuuntautuneisuus. Samalla ne kertovat tulevaisuuksien moninaisuudesta sekä mahdollisista tavoista ja keinosta ymmärtää tulevaisuuksia. Toivotan mukavia lukuhetkiä!---- An important part of the study goals of master’s studies is that students show that they are able to make works of independent research and produce scientific texts in different forms, like articles and other publication formats. Academic writing is a skill of its own and even if social media and popularisation of science have changed the criteria of dissemination of research results compared to traditional academic publication forums, I believe that the scientific community still would agree that researchers must be able to produce scientific text. Studies have to support the development of writing skills. Finland Futures Research Centre has published since 2016 a collection of the most prominent student papers written during their studies. FFRC wants to offer a real publication forum for students and perhaps help them to get their first publication marked on their list of publications. This year’s collection of papers shows that any fear of declining or worsening academic writing skills of students is groundless. At the same time, it shows that our teachers are succeeding in training of these skills. Our publication consists of writings by students from our Masters Degree Programme in Futures Studies, Sustainable Development Studies at the University of Turku and Finland Futures Academy. These study programs are coordinated by FFRC. Because student papers are originally written in Finnish or English, we publish them in their original language. The contents and context of the papers vary a lot, but the common feature is futures orientation. All of them tell a story of multiple futures and of possible ways and means to understand futures. I hope You enjoy reading our book

Digital Strategy Formulation: An Investigation with Design Sprints and Deep Learning

Since the invention of transistors, digital technologies have continued to have a profound impact on the global economy. Relentless performance improvements combined with convergence of digital technologies such as artificial intelligence, internet of things, and cloud computing has led to a surge in scale and importance as a source for competitive advantage. However, in 2019, only around 16% of companies managed to realize a significant improvement in business performance from digital transformation (DT). The challenges that organizations face in succeeding at DT can be traced back to strategy formulation and execution. Therefore, the aim of this research is to develop insights and tools to enhance the understanding and practice of digital strategy formulation. A comprehensive review of the literature demonstrated that DT, as an emerging body of knowledge, is lacking an in-depth and applied investigation of digital strategy formulation. The main knowledge gaps are: (1) a lack of guidance on digital strategy formulation process activities and outcomes; (2) limited consideration of the iterative nature of digital strategy formulation and validation; and (3) limited empirical investigation of digital strategy archetypes to guide the formulation process. Addressing this research gap was accomplished over three stages. First, an in-depth exploratory case study was conducted by investigating digital strategy formulation process with active participation research over six months. This investigation identified key process activities and highlighted the role of roadmapping in integrating the outcomes. Second, the findings were supplemented with literature review to design a conceptual framework for agile roadmapping to facilitate the digital strategy formulation process. This framework was then tested and calibrated over three pilot studies with companies across Europe attempting to start their DT journey. Finally, deep learning and natural language processing techniques were employed to empirically investigate the digital strategy of Fortune 500 companies from earnings call transcripts. This empirical investigation identified four digital strategy archetypes that are being employed by companies across various sectors. The findings from this research contribute to a better understanding of digital strategy formulation. It was identified that digital strategy formulation is an ongoing search process for an adequate strategic response to the DT of the economy. Specifically, incorporating agility into the formulation process is an effective way of managing the associated uncertainty of DT. Moreover, the findings demonstrated that proactively iterating between strategy formulation and validation can accelerate the realization of the emergent digital strategy. The proposed framework and the digital strategy archetypes provide a baseline for DT professionals toward a more robust digital strategy formulation.Ministry of Education - United Arab Emirate

Knowledge Representation in Engineering 4.0

This dissertation was developed in the context of the BMBF and EU/ECSEL funded projects GENIAL! and Arrowhead Tools. In these projects the chair examines methods of specifications and cooperations in the automotive value chain from OEM-Tier1-Tier2. Goal of the projects is to improve communication and collaborative planning, especially in early development stages. Besides SysML, the use of agreed vocabularies and on- tologies for modeling requirements, overall context, variants, and many other items, is targeted. This thesis proposes a web database, where data from the collaborative requirements elicitation is combined with an ontology-based approach that uses reasoning capabilities. For this purpose, state-of-the-art ontologies have been investigated and integrated that entail domains like hardware/software, roadmapping, IoT, context, innovation and oth- ers. New ontologies have been designed like a HW / SW allocation ontology and a domain-specific "eFuse ontology" as well as some prototypes. The result is a modular ontology suite and the GENIAL! Basic Ontology that allows us to model automotive and microelectronic functions, components, properties and dependencies based on the ISO26262 standard among these elements. Furthermore, context knowledge that influences design decisions such as future trends in legislation, society, environment, etc. is included. These knowledge bases are integrated in a novel tool that allows for collabo- rative innovation planning and requirements communication along the automotive value chain. To start off the work of the project, an architecture and prototype tool was developed. Designing ontologies and knowing how to use them proved to be a non-trivial task, requiring a lot of context and background knowledge. Some of this background knowledge has been selected for presentation and was utilized either in designing models or for later immersion. Examples are basic foundations like design guidelines for ontologies, ontology categories and a continuum of expressiveness of languages and advanced content like multi-level theory, foundational ontologies and reasoning. Finally, at the end, we demonstrate the overall framework, and show the ontology with reasoning, database and APPEL/SysMD (AGILA ProPErty and Dependency Descrip- tion Language / System MarkDown) and constraints of the hardware / software knowledge base. There, by example, we explore and solve roadmap constraints that are coupled with a car model through a constraint solver.Diese Dissertation wurde im Kontext des von BMBF und EU / ECSEL gefördertem Projektes GENIAL! und Arrowhead Tools entwickelt. In diesen Projekten untersucht der Lehrstuhl Methoden zur Spezifikationen und Kooperation in der Automotive Wertschöp- fungskette, von OEM zu Tier1 und Tier2. Ziel der Arbeit ist es die Kommunikation und gemeinsame Planung, speziell in den frühen Entwicklungsphasen zu verbessern. Neben SysML ist die Benutzung von vereinbarten Vokabularen und Ontologien in der Modellierung von Requirements, des Gesamtkontextes, Varianten und vielen anderen Elementen angezielt. Ontologien sind dabei eine Möglichkeit, um das Vermeiden von Missverständnissen und Fehlplanungen zu unterstützen. Dieser Ansatz schlägt eine Web- datenbank vor, wobei Ontologien das Teilen von Wissen und das logische Schlussfolgern von implizitem Wissen und Regeln unterstützen. Diese Arbeit beschreibt Ontologien für die Domäne des Engineering 4.0, oder spezifischer, für die Domäne, die für das deutsche Projekt GENIAL! benötigt wurde. Dies betrifft Domänen, wie Hardware und Software, Roadmapping, Kontext, Innovation, IoT und andere. Neue Ontologien wurden entworfen, wie beispielsweise die Hardware-Software Allokations-Ontologie und eine domänen-spezifische "eFuse Ontologie". Das Ergebnis war eine modulare Ontologie-Bibliothek mit der GENIAL! Basic Ontology, die es erlaubt, automotive und mikroelektronische Komponenten, Funktionen, Eigenschaften und deren Abhängigkeiten basierend auf dem ISO26262 Standard zu entwerfen. Des weiteren ist Kontextwissen, welches Entwurfsentscheidungen beinflusst, inkludiert. Diese Wissensbasen sind in einem neuartigen Tool integriert, dass es ermöglicht, Roadmapwissen und Anforderungen durch die Automobil- Wertschöpfungskette hinweg auszutauschen. On tologien zu entwerfen und zu wissen, wie man diese benutzt, war dabei keine triviale Aufgabe und benötigte viel Hintergrund- und Kontextwissen. Ausgewählte Grundlagen hierfür sind Richtlinien, wie man Ontologien entwirft, Ontologiekategorien, sowie das Spektrum an Sprachen und Formen von Wissensrepresentationen. Des weiteren sind fort- geschrittene Methoden erläutert, z.B wie man mit Ontologien Schlußfolgerungen trifft. Am Schluss wird das Overall Framework demonstriert, und die Ontologie mit Reason- ing, Datenbank und APPEL/SysMD (AGILA ProPErty and Dependency Description Language / System MarkDown) und Constraints der Hardware / Software Wissensbasis gezeigt. Dabei werden exemplarisch Roadmap Constraints mit dem Automodell verbunden und durch den Constraint Solver gelöst und exploriert

Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions

Artificial intelligence (AI) is a set of rapidly expanding disruptive technologies that are radically transforming various aspects related to people, business, society, and the environment. With the proliferation of digital computing devices and the emergence of big data, AI is increasingly offering significant opportunities for society and business organizations. The growing interest of scholars and practitioners in AI has resulted in the diversity of research topics explored in bulks of scholarly literature published in leading research outlets. This study aims to map the intellectual structure and evolution of the conceptual structure of overall AI research published in Technological Forecasting and Social Change (TF&SC). This study uses machine learning-based structural topic modeling (STM) to extract, report, and visualize the latent topics from the AI research literature. Further, the disciplinary patterns in the intellectual structure of AI research are examined with the additional objective of assessing the disciplinary impact of AI. The results of the topic modeling reveal eight key topics, out of which the topics concerning healthcare, circular economy and sustainable supply chain, adoption of AI by consumers, and AI for decision-making are showing a rising trend over the years. AI research has a significant influence on disciplines such as business, management, and accounting, social science, engineering, computer science, and mathematics. The study provides an insightful agenda for the future based on evidence-based research directions that would benefit future AI scholars to identify contemporary research issues and develop impactful research to solve complex societal problems. 2023 The Author(s)Scopu

Analyzing the Impacts of Emerging Technologies on Workforce Skills: A Case Study of Industrial Engineering in the Context of the Industrial Internet of Things

New technologies can result in major disruptions and change paradigms that were once well established. Methods have been developed to forecast new technologies and to analyze the impacts of them in terms of processes, products, and services. However, the current literature does not provide answers on how to forecast changes in terms of skills and knowledge, given an emerging technology. This thesis aims to fill this literature gap by developing a structured method to forecast the required set of skills for emerging technologies and to compare it with the current skills of the workforce. The method relies on the breakdown of the emerging technology into smaller components, so then skills can be identified for each component. A case study was conducted to implement and test the proposed method. In this case study, the impacts of the Industrial Internet of Things (IIoT) on engineering skills and knowledge were assessed. Text data analytics validated IIoT as an emerging technology, thus justifying the case study based on engineering and manufacturing discussions. The set of skills required for IIoT was compared to the current skills developed by Industrial Engineering students at the University of Windsor. Text data analytics was also used to evaluate the importance of each IIoT component by measuring how associated individual components are to IIoT. Therefore, existing skill gaps between the current Industrial Engineering program and IIoT requirements were not only mapped, but they were also given weights

Collaborative approaches in sustainable and resilient manufacturing

Publisher Copyright: © 2022, The Author(s).In recent years, the manufacturing sector is going through a major transformation, as reflected in the concept of Industry 4.0 and digital transformation. The urge for such transformation is intensified when we consider the growing societal demands for sustainability. The notion of sustainable manufacturing has emerged as a result of this trend. Additionally, industries and the whole society face the challenges of an increasing number of disruptive events, either natural or human-caused, that can severely affect the normal operation of systems. Furthermore, the growing interconnectivity between organizations, people, and physical systems, supported by recent developments in information and communication technologies, highlights the important role that collaborative networks can play in the digital transformation processes. As such, this article analyses potential synergies between the areas of sustainable and resilient manufacturing and collaborative networks. The work also discusses how the responsibility for the various facets of sustainability can be distributed among the multiple entities involved in manufacturing. The study is based on a literature survey, complemented with the experience gained from various research projects and related initiatives in the area, and is organized according to various dimensions of Industry 4.0. A brief review of proposed approaches and indicators for measuring sustainability from the networked manufacturing perspective is also included. Finally, a set of key research challenges are identified to complement strategic research agendas in manufacturing.publishersversionpublishe

Coolest Student Papers at Finland Futures Research Centre 2021–2022. Tulevaisuuden tutkimuskeskuksen valittuja opiskelijatöitä 2021–2022

Tärkeä osa maisteriopintojen oppimistavoitteita on osoittaa, että opiskelija pystyy itsenäiseen tutkimustyö-hön ja tuottamaan tieteellistä tekstiä artikkeleiden ja muiden julkaisutapojen muodossa. Akateeminen kir-joittaminen on oma osaamisalueensa, ja vaikka sosiaalinen media ja tieteen popularisaatio asettavat eri-laisia haasteita ja kanavia tutkimustulosten levittämiseen kuin perinteinen akateeminen julkaiseminen, tie-deyhteisössä vallinnee konsensus siitä, että tutkijoiden on osattava tuottaa akateemista tekstiä. Opintojen on tuettava tämän taidon kehittymistä.Tulevaisuuden tutkimuskeskus on julkaissut vuodesta 2016 lähtien koosteita ansiokkaista opiskelijoi-den opintojensa aikana kirjoittamista esseistä, harjoitustöistä ja muista kirjallisista opintosuoritteista. Halu-amme tarjota opiskelijoille oikean julkaisukanavan ja auttaa heitä saamaan vaikka sen ensimmäisen jul-kaisutiedon ansioluetteloon. Tämänvuotinen julkaisumme osoittaa, että pelko opiskelijoiden kirjallisten ky-kyjen huonontumisesta tai taantumisesta on turhaa. Samalla se todistaa myös opettajiemme onnistuneen opiskelijoiden akateemisen kirjoittamisen taitojen harjaannuttamisessa.Julkaisumme koostuu tulevaisuudentutkimuksen kansainvälisen maisteriohjelman, Turun yliopiston kestävän kehityksen opintokokonaisuuden (KEKO) ja Tulevaisuudentutkimuksen Verkostoakatemian (TVA) opiskelijoiden kirjoituksista. Koska opiskelijatyöt on tehty englanniksi maisteriohjelmassa ja suo-meksi KEKO- ja TVA-opinnoissa, julkaisemme työt alkuperäisellä kielellä. Sisällöllisesti aiheet vaihtelevat suuresti, mutta niitä yhdistävä tekijä on tulevaisuussuuntautuneisuus. Samalla ne kertovat tulevaisuuksien moninaisuudesta sekä mahdollisista tavoista ja keinosta ymmärtää tulevaisuuksia. Toivotan mukavia lukuhetkiä!An important part of the study goals of master’s studies is that students show that they are able to make works of independent research and produce scientific texts in different forms, like articles and other publi-cation formats. Academic writing is a skill of its own and even if social media and popularisation of science have changed the criteria of dissemination of research results compared to traditional academic publication forums, I believe that the scientific community still would agree that researchers must be able to produce scientific text. Studies have to support the development of writing skills.Finland Futures Research Centre has published since 2016 a collection of the most prominent student papers written during their studies. FFRC wants to offer a real publication forum for students and perhaps help them to get their first publication marked on their list of publications. This year’s collection of papers shows that any fear of declining or worsening academic writing skills of students is groundless. At the same time, it shows that our teachers are succeeding in training of these skills.Our publication consists of writings by students from our Masters Degree Programme in Futures Stud-ies, Sustainable Development Studies at the University of Turku and Finland Futures Academy. These study programs are coordinated by FFRC. Because student papers are originally written in Finnish or English, we publish them in their original language. The contents and context of the papers vary a lot, but the common feature is futures orientation. All of them tell a story of multiple futures and of possible ways and means to understand futures. I hope You enjoy reading our book!FFRC eBooks 9/202

Technology roadmap for the Creative Industries

This paper discusses the findings of research conducted between 2013 and 2016, which concerned the development of technology roadmaps for the Creative Industries. The roadmap presented in this paper was built based on input from communities of creative and Information and Communication Technologies (ICT) experts collected during the consultation and validation phases of the research. It provides a synthesis of challenges and recommendations from the five creative sectors examined by the project – Architecture, Art, Design, Games, Media and e-Publishing – and proposes research directions for the development of desired future technologies, by highlighting innovative future developments in the Creative Industries, while also assessing their technology maturity in the short, medium and longer terms. By rating the desired technologies as ‘present’ (1–2 years), ‘possible’ (2--5 years), or ‘probable’ (5–10 years or beyond), the roadmap gives orientation towards the development of new technologies and related business models and skills and provides guidance for informed policy-making. The paper thus aims at enabling stakeholders – creators, professionals, SMEs, creative groups, creative communities, associations, organisations and institutions, as well as governments and policy makers – to maximise their benefit and the societal value from the new emerging technology landscape in the Creative Industries