TY - JOUR T1 - Call for Papers: Distributed Ledger Technologies for Smart Digital Economies JF - Technology Innovation Management Review Y1 - 2021 KW - artificial intelligence KW - blockchain KW - cybersecurity KW - digital economy KW - distributed ledger technology KW - smartification PB - Talent First Network CY - Ottawa VL - 11 UR - timreview.ca/article/1422 IS - 2 ER - TY - JOUR T1 - Can Artificial Intelligence be a Critical Success Factor of Construction Projects? Practitioner perspectives JF - Technology Innovation Management Review Y1 - 2021 A1 - Virender Kumar A1 - Amrendra Pandey A1 - Rahul Singh KW - artificial intelligence KW - Construction Projects KW - Critical Success Factors KW - Project Success AB - The construction sector has not been altogether successful in adopting automated systems. Related research on artificial intelligence has mainly been confined to the development of software models for a specific subset of construction work. This study aims to identify whether artificial intelligence is a potential critical success factor for construction project success. Data were collected through semi-structured interviews and analyzed using content analysis. The interviewees were selected on the basis of convenience and included highly experienced project managers from the global community with expertise in project management working on large construction projects. Our research shows that senior project managers perceive artificial intelligence as different from information technology and advanced project management software. Major drawbacks of artificial intelligence were found to be (i) lack of soft skills, (ii) lack of intelligence to interpret things in various ways like human beings, and (iii) lack of human relationship capabilities, including the ways people manage projects. The interviewees believe that artificial intelligence is still years away from becoming self-aware. This study improves the understanding of artificial intelligence as a success factor for construction projects and provides future directions for research in this field. PB - Talent First Network CY - Ottawa VL - 11 UR - timreview.ca/article/1471 IS - 11-12 U1 - Birla Institute of Management and Technology Virender Kumar is a senior business manager and a certified project professional (IPMA- B) with complex project management certification from France. He has more than 28 years of professional work experience in engineering design and supervision, construction, and project management consulting work. His professional experience includes working at senior roles in leading firms like AECOM, EGIS, Yooshin Engineering corporation etc. in India. He is a research scholar at Birla Institute of Management Technology. His research focuses on critical success factors, artificial intelligence, project management and project success. U2 - Gitam University Dr. Amrendra Pandey is Assistant Professor at the Kautilya School of Public Policy, GITAM University. He is an economist and researcher with expertise in text mining, machine learning, monetary economics, macroeconomic policy regulation, and econometrics. He has been a Visiting Professor at the Indian Institute of Management, Lucknow, and a Course Coordinator for the PGDM program at Birla Institute of Management and Technology. Dr. Pandey has numerous research papers and articles to his credit. U3 - Birla Institute of Management and Technology Dr. Rahul Singh is Professor of Strategy and Globalization, and Chair of Strategy, Innovation and Entrepreneurship Area at Birla Institute of Management Technology. He is also a European Higher Education Expert for the European Union, as well as visiting professor at FH Joanneum University, Austria and KEDGE Business School, France. His primary areas of research are in Strategic Management, Globalization, Emerging Markets and Sustainability. He has published in top-tier journals and has been the founding Editor-in-Chief of two international journals. ER - TY - JOUR T1 - Distributed Ledger Technologies and Social Machines: How to “smartify” the economy with blockchain-based digital extension services? JF - Technology Innovation Management Review Y1 - 2021 A1 - Gregory Sandstrom KW - artificial intelligence KW - blockchain KW - digital economy KW - digital platform KW - distributed ledger technology KW - economic development KW - extension services KW - extension thinking KW - innovation diffusion KW - Internet of Things KW - ledger community KW - smartification KW - social machines KW - web science AB - This paper examines the broad impact of digitalization on economic development. More specifically, it addresses the computer science-derived notion of "social machines", along with the invention of distributed ledger technologies (DLTs) (or blockchain), as potential signposts on the pathway to "smart(er) digital economies". The paper investigates blockchain-based ecosystems as examples of social machines that assist in economic "smartification" and development. It looks at distributed ledger-based communities (DLCs) that provide examples of functioning social machines for a variety of business and personal network communications purposes. It then analyses the scaleup of DLT-based social machines by comparison with "extension services", largely in education and agriculture, which are currently undergoing processes of digitalization. Overall, this conceptual study examines the general horizons and potential impact of blockchain and social machines on the provision of online products and services, across a range of sectors and industries. The paper offers interpretative assistance to managers, entrepreneurs, technology experts, and academics with lingering questions about blockchain in and for business and economic development. PB - Talent First Network CY - Ottawa VL - 11 UR - timreview.ca/article/1449 IS - 6 U1 - Technology Innovation Management Review Gregory Sandstrom is Managing Editor of the TIM Review. He is a former Associate Professor of Mass Media and Communications at the European Humanities University (2012-2017), and Affiliated Associate Professor at the Social Innovations Laboratory, Mykolas Romeris University (2016-2017) in Vilnius, Lithuania. His PhD is from St. Petersburg State University and the Sociological Institute of the Russian Academy of Sciences. He interned at the S.I. Vavilov Institute for the History of Science and Technology, St. Petersburg, sector on Sociology of Science (2010). He was a Postdoctoral Research Fellow at the Lithuanian Science Council (2013-2015), for which he conducted research visits to the Copernican Centre for Interdisciplinary Studies (Krakow), the University of Edinburgh's Extended Knowledge Project, Cambridge University's History and Philosophy of Science Department, and Virginia State University's Science and Technology Studies program. He worked for the Bard College Institute for Writing and Thinking, leading student and faculty language and communications workshops, most recently (2013, 2014, 2017) in Yangon, Myanmar. His current research interests are distributed ledger technology (blockchain) systems and digital extension services. ER - TY - JOUR T1 - Reinvigorating the Discourse on Human-Centered Artificial Intelligence in Educational Technologies JF - Technology Innovation Management Review Y1 - 2021 A1 - André Renz A1 - Gergana Vladova KW - artificial intelligence KW - design for value approach. KW - educational technology KW - human-centered AI KW - intelligent tutoring systems AB - The increasing relevance of artificial intelligence (AI) applications in various domains has led to high expectations of benefits, ranging from precision, efficiency, and optimization to the completion of routine or time-consuming tasks. Particularly in the field of education, AI applications promise immense innovation potential. A central focus in this field is on analyzing and evaluating learner characteristics to derive learning profiles and create individualized learning environments. The development and implementation of such AI-driven approaches are related to learners' data, and thus involves several privacies, ethics, and morality challenges. In this paper, we introduce the concept of human-centered AI, and consider how an AI system can be developed in line with human values without posing risks to humanity. Because the education market is in the early stages of incorporating AI into educational tools, we believe that this is the right time to raise awareness about the use of principles that foster human-centered values and help in building responsible, ethical, and value-oriented AI. PB - Talent First Network CY - Ottawa VL - 11 UR - timreview.ca/article/1438 IS - 5 U1 - Weizenbaum Institute for the Networked Society André Renz holds a Ph.D. in the field of economics and behavioral sciences from the University of Bayreuth. Using a trans- and interdisciplinary research approach, he combines methods in sociology, psychology, and economics to gain a deeper understanding of everyday phenomena and market changes. Since 2018, he has led the research group Data-Driven Business Model Innovation at the Weizenbaum Institute for the Networked Society in Berlin. In 2020, he was a resident scientist at the University of California, Berkeley, where he focused on the transatlantic comparison between the US and the German EdTech markets. Currently, his focus is on the topic of artificial intelligence in education, learning analytics, data-based EdTech solutions, and digital transformation and innovation in education and knowledge transfer. U2 - University of Potsdam and Weizenbaum Institute for the Networked Society Gergana Vladova is a postdoctoral researcher at the University of Potsdam and head of the Research Group Education and Advanced Training in the Digital Society at the Weizenbaum Institute for the Networked Society in Berlin. She holds a master's degree in international economic relations from the University of National and World Economy (Sofia, Bulgaria), a master's degree in communication sciences and economics (FU Berlin), and a PhD in business informatics (University of Potsdam). Her main topics of interest are learning and competence development in the context of digitalization, knowledge, and innovation management. During her research stays at Stellenbosch University (South Africa) and Hong Kong Polytechnic University, she was (and still is) actively involved in international and interdisciplinary research and teaching projects. ER - TY - JOUR T1 - Correlation between Entrepreneurial Orientation and Implementation of AI in Human Resources Management JF - Technology Innovation Management Review Y1 - 2020 A1 - Rico Baldegger A1 - Maurizio Caon A1 - Kreshnik Sadiku KW - artificial intelligence KW - entrepreneurial orientation KW - Human Resource Management AB - This paper develops the concept of adopting artificial intelligence (AI) in human resources management (HRM) through a research questionnaire and reports the results of a study designed to investigate the perception of adopting and introducing AI in HRM processes. In addition, it investigates the correlation between entrepreneurship orientation (EO) and AI in HRM processes. A survey was conducted with a sample of 310 firm members in the HR Section Romande, as well as a literature review on the adoption of new technologies. The results indicate a perceived positive value of introducing AI in HRM and a correlation between the level of a company's EO and the introduction of AI in HRM. This means that the more a company is entrepreneurially oriented, the more it tends to implement or include already implemented AI projects and tools in HRM processes. The perceived value of AI in HRM was evaluated by comparing answers to research questions involving the introduction of AI in HRM tools, and expectations of widely implementing AI in the next five years. The main barrier of adopting AI in HRM appeared to be a lack of skills and training. In addition, potential features of implementing AI in HRM were identified as potential steps toward introducing AI as a new technology. Questions regarding the evaluation of EO were based on a research Colvin Slevin (1989). It is important for SMEs to invest in information technology to set the basis for further development. Owing to intensified competitive pressures and the necessity of entering global markets, SMEs are incrementally employing Information Technology (IT) to create substantial benefits. Most prior research has focused more on IT adoption in large organizations, yet when regarding the limited resources of SMEs, the IT adoption process is considerably different. (Ghobakhloo, Sabouri, Hong and Zulkifli, 2011). PB - Talent First Network CY - Ottawa VL - 10 UR - timreview.ca/article/1348 IS - 4 U1 - School of Management Fribourg Prof. Rico Baldegger is Director and Professor of Strategy, Innovation and Entrepreneurship at the School of Management Fribourg (HEG-FR), Switzerland. He has studied at the Universities of St. Gallen and Fribourg, Switzerland. His research activities concentrate on innovative start-ups, the entrepreneurial behavior of individuals and organizations, as well as the phenomenon of rapid-growth companies. He has published several books and articles and, since the beginning of the 1990s, he has been the manager of a business for company development. Moreover, he is a business angel and serial entrepreneur, as is demonstrated by the many companies he has created. U2 - School of Management Fribourg Maurizio Caon is currently Associate Professor and Leader of the Digital Business Center at the School of Management Fribourg, member of the University of Applied Sciences and Arts Western Switzerland (HES-SO). He is also lecturer at the College of Engineering Fribourg, director of design and innovation at the HumanTech Institute and member of Centre Compétences Numériques (also part of HES-SO). He holds a Ph.D. in Computer Science issued by the University of Bedfordshire, UK, and a Master’s degree in Telecommunications and Computer Engineering issued by the University of Perugia, Italy. His research interests include human-computer interaction, human factors in digital technologies and digital transformation. U3 - School of Management Fribourg Kreshnik Sadiku graduated in the MSc in Business Administration major Entrepreneurship in HES-SO. He published a book “Path toward Entrepreneurship” on 2012 and works currently as Regional Manager in a company that provides financial services. ER - TY - JOUR T1 - Editorial: Insights (January 2020) JF - Technology Innovation Management Review Y1 - 2020 A1 - Stoyan Tanev A1 - Gregory Sandstrom KW - AI KW - artificial intelligence KW - B2B sales KW - big data KW - business-to-business sales KW - data-based value KW - digital solutions KW - ecosystem KW - ecosystems KW - Ethics KW - Gujarat State KW - Indian IT industry KW - innovation KW - IT clusters KW - Knowledge Innovation clusters KW - Networks Analysis KW - regional development KW - Roboethics KW - Smart robot KW - strategy KW - Systematic literature review KW - technology KW - value capture KW - value creation KW - value sales PB - Talent First Network CY - Ottawa VL - 10 UR - timreview.ca/article/1298 IS - 1 U1 - Technology Innovation Management Review Stoyan Tanev, PhD, MSc, MEng, MA, is Associate Professor of Technology Entrepreneurship and Innovation Management associated with the Technology Innovation Management (TIM) Program, Sprott School of Business, Carleton University, Ottawa, ON, Canada. Before re-joining Carleton University, Dr. Tanev was part of the Innovation and Design Engineering Section, Faculty of Engineering, University of Southern Denmark (SDU), Odense, Denmark. Dr. Tanev has a multidisciplinary background including MSc in Physics (Sofia University, Bulgaria), PhD in Physics (1995, University Pierre and Marie Curie, Paris, France, co-awarded by Sofia University, Bulgaria), MEng in Technology Management (2005, Carleton University, Ottawa, Canada), MA in Orthodox Theology (2009, University of Sherbrooke, Montreal Campus, QC, Canada) and PhD in Theology (2012, Sofia University, Bulgaria). Dr. Stoyan Tanev has published multiple articles in several research domains. His current research interests are in the fields of technology entrepreneurship and innovation management, design principles and growth modes of global technology start-ups, business analytics, topic modeling and text mining. He has also an interest in interdisciplinary issues on the interface of the natural and social sciences. U2 - Technology Innovation Management Review Gregory Sandstrom is Managing Editor of the Technology Innovation Management Review. Former Associate Professor of Mass Media and Communications at the European Humanities University and Affiliated Associate Professor at the Social Innovations Laboratory, Mykolas Romeris University in Vilnius, Lithuania. PhD from St. Petersburg State University and the Sociological Institute of the Russian Academy of Sciences, sector on Sociology of Science. Postdoctoral Research Fellow at the Lithuanian Science Council and Autonomous National University of Mexico's Institute for Applied Mathematics and Systems. Promoter and builder of blockchain distributed ledger technology systems and digital extension services. ER - TY - JOUR T1 - Editorial: Insights (November 2020) JF - Technology Innovation Management Review Y1 - 2020 A1 - Stoyan Tanev A1 - Gregory Sandstrom KW - AI innovation and maturity KW - and diaspora entrepreneurs. KW - artificial intelligence KW - confidential information KW - criminal law KW - digitally enhanced teamwork KW - economic espionage KW - entrepreneurship KW - health technology KW - immigrants KW - Innovation management KW - living labs KW - migration KW - Multidisciplinarity KW - situated practice KW - small and medium-sized enterprises KW - stakeholder participation KW - sustainability KW - trade secrets KW - transnationals PB - Talent First Network CY - Ottawa VL - 10 UR - timreview.ca/article/1404 IS - 11 U1 - Technology Innovation Management Review Stoyan Tanev, PhD, MSc, MEng, MA, is Associate Professor of Technology Entrepreneurship and Innovation Management associated with the Technology Innovation Management (TIM) Program, Sprott School of Business, Carleton University, Ottawa, ON, Canada. Before re-joining Carleton University, Dr. Tanev was part of the Innovation and Design Engineering Section, Faculty of Engineering, University of Southern Denmark (SDU), Odense, Denmark. Dr. Tanev has a multidisciplinary background including MSc in Physics (Sofia University, Bulgaria), PhD in Physics (1995, University Pierre and Marie Curie, Paris, France, co-awarded by Sofia University, Bulgaria), MEng in Technology Management (2005, Carleton University, Ottawa, Canada), MA in Orthodox Theology (2009, University of Sherbrooke, Montreal Campus, QC, Canada) and PhD in Theology (2012, Sofia University, Bulgaria). Stoyan has published multiple articles in several research domains. His current research interests are in the fields of technology entrepreneurship and innovation management, design principles and growth modes of global technology start-ups, business analytics, topic modeling and text mining. He has also an interest in interdisciplinary issues on the interface of the natural and social sciences. U2 - Technology Innovation Management Review Gregory Sandstrom is Managing Editor of the TIM Review. He is a former Associate Professor of Mass Media and Communications at the European Humanities University (2012-2017), and Affiliated Associate Professor at the Social Innovations Laboratory, Mykolas Romeris University (2016-2017) in Vilnius, Lithuania. His PhD is from St. Petersburg State University and the Sociological Institute of the Russian Academy of Sciences. He interned at the S.I. Vavilov Institute for the History of Science and Technology, St. Petersburg, sector on Sociology of Science (2010). He was a Postdoctoral Research Fellow at the Lithuanian Science Council (2013-2015), for which he conducted research visits to the Copernican Centre for Interdisciplinary Studies (Krakow), the University of Edinburgh's Extended Knowledge Project, Cambridge University's History and Philosophy of Science Department, and Virginia State University's Science and Technology Studies program, as well as previously at the Autonomous National University of Mexico's Institute for Applied Mathematics and Systems (2010-2011). He worked for the Bard College Institute for Writing and Thinking, leading student and faculty language and communications workshops, most recently (2013, 2014, 2017) in Yangon, Myanmar. His current research interests are distributed ledger technology (blockchain) systems and digital extension services. ER - TY - JOUR T1 - The Effect of Machine Learning on Knowledge-Intensive R&D in the Technology Industry JF - Technology Innovation Management Review Y1 - 2020 A1 - Daniel Viberg A1 - Mohammad H. Eslami KW - artificial intelligence KW - explicit knowledge KW - knowledge integration KW - ML KW - tacit knowledge KW - technological firm AB - The impact of such current state-of-the-art technology as machine learning (ML) on organizational knowledge integration is indisputable. This paper synergizes investigations of knowledge integration and ML in technologically advanced and innovative companies, in order to elucidate the value of these approaches to organizational performance. The analyses are based on the premise that, to fully benefit from the latest technological advances, entity interpretation is essential to fully define what has been learned. Findings yielded by a single case study involving one technological firm indicate that tacit and explicit knowledge integration can occur simultaneously using ML, when a data analysis method is applied to transcribe spoken words. Although the main contribution of this study stems from the greater understanding of the applicability of machine learning in organizational contexts, general recommendations for use of this analytical method to facilitate integration of tacit and explicit knowledge are also provided. PB - Talent First Network CY - Ottawa VL - 10 UR - timreview.ca/article/1340 IS - 3 U1 - Linköping University Daniel Viberg has a M.Sc in Industrial Engineering and Management and a B.Sc in Mechanical Engineering from Linköping University in Sweden. He has experience in computer science from various spare time projects connected to both commercial and research purposes. U2 - Jönköping University Mohammad H. Eslami is an Assistant professor at Jönköping International Business School in Sweden. His research interests are in the field of innovation management and knowledge integration. His research has been published in Industrial Marketing management, Journal of engineering and technology management, international journal of innovation management and etc. ER - TY - JOUR T1 - An Ethical Framework for Smart Robots JF - Technology Innovation Management Review Y1 - 2020 A1 - Mika Westerlund KW - AI KW - artificial intelligence KW - Ethics KW - Roboethics KW - Smart robot AB - This article focuses on “roboethics” in the age of growing adoption of smart robots, which can now be seen as a new robotic “species”. As autonomous AI systems, they can collaborate with humans and are capable of learning from their operating environment, experiences, and human behaviour feedback in human-machine interaction. This enables smart robots to improve their performance and capabilities. This conceptual article reviews key perspectives to roboethics, as well as establishes a framework to illustrate its main ideas and features. Building on previous literature, roboethics has four major types of implications for smart robots: 1) smart robots as amoral and passive tools, 2) smart robots as recipients of ethical behavior in society, 3) smart robots as moral and active agents, and 4) smart robots as ethical impact-makers in society. The study contributes to current literature by suggesting that there are two underlying ethical and moral dimensions behind these perspectives, namely the “ethical agency of smart robots” and “object of moral judgment”, as well as what this could look like as smart robots become more widespread in society. The article concludes by suggesting how scientists and smart robot designers can benefit from a framework, discussing the limitations of the present study, and proposing avenues for future research. PB - Talent First Network CY - Ottawa VL - 10 UR - timreview.ca/article/1312 IS - 1 U1 - Carleton University Mika Westerlund, DSc (Econ), is an Associate Professor at Carleton University in Ottawa, Canada. He previously held positions as a Postdoctoral Scholar in the Haas School of Business at the University of California Berkeley and in the School of Economics at Aalto University in Helsinki, Finland. Mika earned his doctoral degree in Marketing from the Helsinki School of Economics in Finland. His research interests include open and user innovation, the Internet of Things, business strategy, and management models in high-tech and service intensive industries. ER - TY - JOUR T1 - Integrated AI and Innovation Management: The Beginning of a Beautiful Friendship JF - Technology Innovation Management Review Y1 - 2020 A1 - Nina Bozic Yams A1 - Valerie Richardson A1 - Galina Esther Shubina A1 - Sandor Albrecht A1 - Daniel Gillblad KW - AI innovation KW - AI maturity KW - artificial intelligence KW - IMS ISO 56002 KW - Innovation management KW - maturity model AB - There is a growing consensus around the transformative and innovative power of Artificial Intelligence (AI) technology. AI will transform which products are launched and how new business models will be developed to support them. Despite this, little research exists today that systematically explores how AI will change and support various aspects of innovation management. To address this question, this article proposes a holistic, multi-dimensional AI maturity model that describes the essential conditions and capabilities necessary to integrate AI into current systems, and guides organisations on their journey to AI maturity. It explores how various elements of the innovation management system can be enabled by AI at different maturity stages. Two key experimentation stages are identified, 1) an initial stage that focuses on optimisation and incremental innovation, and 2) a higher maturity stage where AI becomes an enabler of radical innovation. We conclude that AI technologies can be applied to democratise and distribute innovation across organisations. PB - Talent First Network CY - Ottawa VL - 10 UR - timreview.ca/article/1399 IS - 11 U1 - Research Institutes of Sweden (RISE) Nina is a Senior Researcher in Innovation Management and the Future of Work at RISE. She has a PhD in Innovation Management and 16 years of experience working as an innovation enabler and explorer, both in companies and public sector organizations. After starting her career as a management consultant at Deloitte and building an entrepreneurship centre CEED Slovenia, she moved to Sweden where she continued her work as an innovation consultant and participatory action researcher, working with organizations, such as Nacka, Eskilstuna and Västerås municipalities, ABB, Electrolux, Ericsson, GodEl and others. In the last two years she has been researching the future of work, and how we can integrate innovation management with other disciplines, such as AI, new models of organizing, and future studies to prepare organizations for the future in a more holistic way. U2 - Gradient Descent Valerie is an AI Strategist & Partner at Gradient Descent. She is an experienced leader and advisor in digital disruption and transformation with over 20 years at Google and General Electric, helping companies in multiple industries solve strategic and operational problems in an integrated way across multiple technology domains. Her expertise includes defining digital strategies and developing digital operating models with a focus on providing practical solutions to complex technology challenges for executives. She has a specific interest in emergent technologies, including AI and IoT. Valerie most recently led a digital division of General Electric, advising large industrial operations on how to implement cloud-based enterprise IoT software, data analytics, machine learning and AI to increase productivity, reduce costs and improve competitiveness. U3 - Gradient Descent Galina is an AI Technologist & Partner at Gradient Descent. She spent 16 years in the tech industry, over a decade of it at Google as a software engineer, data scientist and manager working on everything from ML-based advertising products to highly scalable distributed systems (four years in Silicon Valley). She spent the last 6 years working on AI strategy: alternating between building her own data and AI teams and strategy consulting on how to integrate data and AI into companies. In her last corporate job, she built the software and AI team for the electrical battery start-up, Northvolt. She is the founder of Women in Data Science - Sweden, a community of 700+ women in the field of data science, machine learning, AI and data analytics. U4 - Research Institute of Sweden (RISE) & WALP Sandor, PhD, is a community ecosystem builder and change driver. He is passionate about innovation and technology incubation. Currently, he is at the Knut and Alice Wallenberg Foundation and RISE Computer Science, working with people that explore new ways of connecting human beings, industries and technologies, all in the pursuit of making it more secure and enjoyable to work and live in a sustainable world. He worked at Ericsson for twenty years in Hungary and Sweden as a leader in product development and corporate research. He was the founder and head of Ericsson Garage, Ericsson’s global innovation and incubation platform. He received his Master of Science in Electrical Engineering from Budapest University of Technology and Economics in 1993, and his PhD from the same institution in 2004. He also holds a Master of Applied Science from the University of British Columbia in Canada and a Master of Business Administration from Central European University Business School, Budapest, Hungary. U5 - Research Institutes of Sweden (RISE) and AI Sweden Daniel is Director of AI Research at RISE, Research Institutes of Sweden and co-director for Scientific Vision of AI Sweden. He has a background in AI, machine learning, data analytics and their practical applications, and has for many years been working with digital- and research strategies in industry and academia. He holds a PhD in Machine Learning and a MSc in Electrical Engineering, both from KTH, Royal Institute of Technology in Stockholm, and has lead research projects, groups and laboratories for almost 15 years. Daniel is an appointed member of the Swedish government advisory board on Digitalization, and has initiated, coordinated and co-edited the Swedish AI agenda. ER - TY - JOUR T1 - The 3S Process: A Framework for Teaching AI Strategy in Business Education JF - Technology Innovation Management Review Y1 - 2019 A1 - Navneet Bhalla KW - 3S Process KW - artificial intelligence KW - Business Education KW - design thinking KW - Harvard Case Method AB - A gap has emerged in teaching artificial intelligence (AI) in business education, where a style of curriculum based on strategy is missing. This article presents a new framework, the 3S Process, as a method for teaching leaders how to strategically adopt AI within their organizations. At a high-level, the 3S Process consists of three stages (Story, Strategy, and Solution), which are described in detail in the article. Stage 1: Story in the process is inspired by the Harvard Case Method to provide context for a problem. Stage 2: Strategy uses Design Thinking to produce candidate solutions. The substage of Empathy in Design Thinking plays a crucial role to reduce bias in designing AI. Virtualization technology is a tool for students to experience hands-on learning in prototype development. Stage 3: Solution is where students advocate for their conceptual AI solution in the context of the case study. AI is a type of complex system; therefore, students should consider feedback loops and the potential for unintended biases to enter a deployed solution. The presentation of the 3S Process in this article is conceptual. Further empirical studies, including evaluations of the 3S Process in classroom settings, will be considered in the future. PB - Talent First Network CY - Ottawa VL - 9 UR - timreview.ca/article/1290 IS - 12 U1 - University College London & Cetana AI Navneet Bhalla, PhD, is a Senior Honorary Research Associate at University College London, in the Department of Computer Science, and a member of Intelligent Systems Group. He is also the founder of Cetana AI Inc., a consultancy specializing in artificial intelligence. Prior to starting the consultancy, Navneet was a postdoctoral fellow at Harvard University (in the Department of Chemistry and Chemical Biology), at Cornell University (in the Department of Mechanical and Aerospace Engineering), and at the Universität Paderborn (in the Department of Computer Science). His research interests include self-assembling systems, machine learning, soft robotics, mechanical design, composite materials, and innovation management. ER - TY - JOUR T1 - Artificial Intelligence for Innovation in Austria JF - Technology Innovation Management Review Y1 - 2019 A1 - Erich Prem KW - AI KW - AI innovation management KW - artificial intelligence KW - Austria KW - innovation KW - SME AB - It has been claimed that Artificial Intelligence (AI) carries enormous potential for service and product innovation. Policy makers world-wide nowadays aim to foster environments conducive for AI-based innovation. This paper addresses the current lack of empirical data for evidence-based innovation policies and the management of AI-based innovation. It focuses on “AI and innovation management” in addressing the question whether innovation that is based on new AI technology requires a management approach different from other forms of IT innovation. We present results from a study of Austrian companies on the degree of use and implementation of AI, and on challenges related to AI-based innovation management. This study used a keyword-list approach to define “Artificial Intelligence” and to find AI-based innovation projects in research databases. These projects facilitated the identification of experts from organisations developing AI-based innovation. In total, eleven experts were interviewed about their AI-based innovation activities. The results show that AI is a very fast emerging technology that is being applied in many sectors. A broad range of innovative solutions are being developed and some have already reached the market. Specific AI business models are, however, less clear and still developing. Companies are facing multiple challenges from regulation to human resources and data collection. Managing AI-based innovation will be particularly difficult for smaller enterprises, where problems are often more pronounced than in larger industries. Explicit challenges for managing AI-based innovations include the necessary attention to managing expectations and ensuring historic metadata expertise essential for many AI-based solutions. Policies to support AI-based innovation therefore should focus on human aspects. This includes increasing the availability of AI experts, but also concerns the development of new job profiles, such as experts in AI training. AI innovators also require clear AI regulation and research investments in key challenges, such as explainable AI. PB - Talent First Network CY - Ottawa VL - 9 UR - timreview.ca/article/1287 IS - 12 U1 - eutema gmbH Dr. Erich Prem is chief RTI strategy advisor and CEO of eutema GmbH. He is an expert in international research and innovation management with a focus on information technology. Erich Prem is a certified managerial economist and works scientifically in artificial intelligence, research politics, innovation research, and epistemology. He has published more than 70 scientific articles and was a guest researcher at the Massachusetts Institute of Technology. He received his Dr. phil. (epistemology) from the University of Vienna, and his Dr. tech. (computer science) from TU Vienna, where he also completed his master’s in computer science (Dipl. Ing). He received his MBA in General Management from Donau University. He is a lecturer at TU Vienna’s Informatics Innovation Center. ER - TY - MAP T1 - Connected Health Innovation: Data Access Challenges in the Interface of AI Companies and Hospitals Y1 - 2019 A1 - Laura Kemppainen A1 - Minna Pikkarainen A1 - Pia Hurmelinna-Laukkanen A1 - Jarmo Reponen KW - artificial intelligence KW - connected health KW - Data access KW - data management KW - governance KW - information mobility KW - innovation KW - orchestration KW - patient- centered AB - The purpose of this paper is to explore the challenges and potential solutions regarding data access for innovation in the realm of connected health. Theoretically, our study combines insights from data management and innovation network orchestration studies, taking thereby a new approach into issues that have emerged in these research streams. Empirically, we study these issues in the context of a development endeavor involving an AI-driven surgery journey solution in collaboration with hospitals and companies. Our study indicates that the challenges and solutions in data access can be categorised according to the level where they emerge: individual, organisational, and institutional. Depending on the level, the challenges require solutions to be searched from different categories. While solutions are generally still scarce, organizational level solutions seem The purpose of this paper is to explore the challenges and potential solutions regarding data access for innovation in the realm of connected health. Theoretically, our study combines insights from data management and innovation network orchestration studies, taking thereby a new approach into issues that have emerged in these research streams. Empirically, we study these issues in the context of a development endeavor involving an AI-driven surgery journey solution in collaboration with hospitals and companies. Our study indicates that the challenges and solutions in data access can be categorised according to the level where they emerge: individual, organisational, and institutional. Depending on the level, the challenges require solutions to be searched from different categories. While solutions are generally still scarce, organizational level solutions seem to hold wide-ranging potential in addressing many challenges. By discussing these dynamics, this paper provides new knowledge for academics and practitioners on the challenges and solutions for data access and management in networked contexts. The greatest challenges among healthcare providers and health technology companies lay on uncertainties and interpretations concerning regulation, data strategy, and guidelines. Creating guidelines for data use and access in a hospital can be a first step to creating connected health innovations in collaboration with AI companies. For their part, these companies need to put effort into gaining in-depth knowledge and understanding of the processes and standards in healthcare context. Our paper is one of the first to combine data management and innovation network orchestration literatures, and to provide empirical evidence on data access related issues in this setting.to hold wide-ranging potential in addressing many challenges. By discussing these dynamics, this paper provides new knowledge for academics and practitioners on the challenges and solutions for data access and management in networked contexts. The greatest challenges among healthcare providers and health technology companies lay on uncertainties and interpretations concerning regulation, data strategy, and guidelines. Creating guidelines for data use and access in a hospital can be a first step to creating connected health innovations in collaboration with AI companies. For their part, these companies need to put effort into gaining in-depth knowledge and understanding of the processes and standards in healthcare context. Our paper is one of the first to combine data management and innovation network orchestration literatures, and to provide empirical evidence on data access related issues in this setting. JF - Technology Innovation Management Review PB - Talent First Network CY - Ottawa VL - 9 UR - timreview.ca/article/1291 IS - 12 U1 - University of Oulu M.Sc. Laura Kemppainen is a Doctoral Candidate at Martti Ahtisaari Institute of Global Business and Economics at the AACSB accredited Oulu Business School, Finland. She holds a M.Sc. in Marketing from Oulu Business School. Laura's research interests include platform business models, human-centered personal data management, digital innovations and value creation. In her doctoral dissertation, the aim is to build understanding about the creation, capture and co-creation of value in the emerging data- and platform-driven ecosystems through the lens of service-dominant logic of marketing. U2 - VTT Technical Research Centre & University of Oulu Minna Pikkarainen, is a joint Connected Health professor of VTT Technical Research Centre of Finland and University of Oulu / Oulu Business School, Martti Ahtisaari Institute and Faculty of Medicine. As a professor of connected health Minna is doing on multidisciplinary research on innovation management, service networks and business models in the context of connected health service co-creation. Professor Pikkarainen has extensive record of external funding, her research has been published large amount of journal and conference papers e.g. in the field of innovation management, software engineering and information systems. During 2006-2012 Professor Minna Pikkarainen has been working as a researcher in Lero, the Irish software engineering research centre, researcher in Sirris, collective “centre of the Belgian technological industry” and business developer in Institute Mines Telecom, Paris and EIT (European Innovation Technology) network in Paris and Helsinki. Her key focus areas as a business developer has been in healthcare organizations. Previously, Minna’s research has been focused on the areas of agile development, software innovation and variability management. U3 - University of Oulu Dr. Pia Hurmelinna is a Professor of Marketing, especially International Business at the Oulu Business School, University of Oulu, and an Adjunct Professor (Knowledge Management) at the Lappeenranta University of Technology, School of Business and Management. She has published over 70 refereed articles in journals such as Journal of Product Innovation Management, Industrial and Corporate Change, Industrial Marketing Management, International Business Review, R&D Management, and Technovation. She has contributed to book chapters, over 160 conference papers, and other scientific and managerial publications. She is a member of editorial boards of, e.g., Industrial Marketing Management and Journal of Innovation Management. She also has been serving as a quest editor and a reviewer for many journals and conferences. Most of her research has involved innovation management and appropriability issues, including examination of different knowledge protection and value capturing mechanisms. The research covers varying contexts like internationalization and inter-organizational collaboration. U4 - University of Oulu Jarmo Reponen, MD, PhD, Radiologist and Professor of Practice in Health Information Systems at Research Group of Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Finland. He has more than 30 years of experience in implementing and teaching the usage of digital systems in health care environment. His current research focus is on assessment of hospital information systems from a clinical perspective, including studies of user experience, decision support systems and artificial intelligence. ER - TY - JOUR T1 - Editorial: Insights (November 2019) JF - Technology Innovation Management Review Y1 - 2019 A1 - Stoyan Tanev A1 - Gregory Sandstrom KW - artificial intelligence KW - competitive advantage KW - cybersecurity KW - deep learning KW - Deepfake KW - design rules KW - digitalization KW - entrepreneurial ecosystems KW - entrepreneurial university KW - entrepreneurship KW - entrepreneurship education KW - fake news KW - innovation KW - international entrepreneurship KW - leadership KW - Learning Capabilities KW - marketing KW - motivation KW - new venture teams KW - quadruple helix KW - sanctions KW - SMEs KW - teamwork KW - triple helix KW - university business incubation PB - Talent First Network CY - Ottawa VL - 9 UR - timreview.ca/article/1278 IS - 11 U1 - Technology Innovation Management Review Stoyan Tanev, PhD, MSc, MEng, MA, is Associate Professor of Technology Entrepreneurship and Innovation Management associated with the Technology Innovation Management (TIM) Program, Sprott School of Business, Carleton University, Ottawa, ON, Canada. Before re-joining Carleton University, Dr. Tanev was part of the Innovation and Design Engineering Section, Faculty of Engineering, University of Southern Denmark (SDU), Odense, Denmark.
Dr. Tanev has a multidisciplinary background including MSc in Physics (Sofia University, Bulgaria), PhD in Physics (1995, University Pierre and Marie Curie, Paris, France, co-awarded by Sofia University, Bulgaria), MEng in Technology Management (2005, Carleton University, Ottawa, Canada), MA in Orthodox Theology (2009, University of Sherbrooke, Montreal Campus, QC, Canada) and PhD in Theology (2012, Sofia University, Bulgaria).
Dr. Stoyan Tanev has published multiple articles in several research domains. His current research interests are in the fields of technology entrepreneurship and innovation management, design principles and growth modes of global technology start-ups, business analytics, topic modeling and text mining. He has also an interest in interdisciplinary issues on the interface of the natural and social sciences. U2 - Technology Innovation Management Review Gregory Sandstrom is Managing Editor of the Technology Innovation Management Review. Former Associate Professor of Mass Media and Communications at the European Humanities University and Affiliated Associate Professor at the Social Innovations Laboratory, Mykolas Romeris University in Vilnius, Lithuania. PhD from St. Petersburg State University and the Sociological Institute of the Russian Academy of Sciences, sector on Sociology of Science. Postdoctoral Research Fellow at the Lithuanian Science Council and Autonomous National University of Mexico's Institute for Applied Mathematics and Systems. Promoter and builder of blockchain distributed ledger technology systems and digital extension services. ER - TY - JOUR T1 - The Emergence of Deepfake Technology: A Review JF - Technology Innovation Management Review Y1 - 2019 A1 - Mika Westerlund KW - artificial intelligence KW - cybersecurity KW - deep learning KW - Deepfake KW - fake news AB - Novel digital technologies make it increasingly difficult to distinguish between real and fake media. One of the most recent developments contributing to the problem is the emergence of deepfakes which are hyper-realistic videos that apply artificial intelligence (AI) to depict someone say and do things that never happened. Coupled with the reach and speed of social media, convincing deepfakes can quickly reach millions of people and have negative impacts on our society. While scholarly research on the topic is sparse, this study analyzes 84 publicly available online news articles to examine what deepfakes are and who produces them, what the benefits and threats of deepfake technology are, what examples of deepfakes there are, and how to combat deepfakes. The results suggest that while deepfakes are a significant threat to our society, political system and business, they can be combatted via legislation and regulation, corporate policies and voluntary action, education and training, as well as the development of technology for deepfake detection, content authentication, and deepfake prevention. The study provides a comprehensive review of deepfakes and provides cybersecurity and AI entrepreneurs with business opportunities in fighting against media forgeries and fake news. PB - Talent First Network CY - Ottawa VL - 9 UR - timreview.ca/article/1282 IS - 11 U1 -

Carleton University

 
Mika Westerlund, DSc (Econ), is an Associate Professor at Carleton University in Ottawa, Canada. He previously held positions as a Postdoctoral Scholar in the Haas School of Business at the University of California Berkeley and in the School of Economics at Aalto University in Helsinki, Finland. Mika earned his doctoral degree in Marketing from the Helsinki School of Economics in Finland. His research interests include open and user innovation, the Internet of Things, business strategy, and management models in high-tech and service-intensive industries.

 

ER - TY - JOUR T1 - Convergent Innovation in Food through Big Data and Artificial Intelligence for Societal-Scale Inclusive Growth JF - Technology Innovation Management Review Y1 - 2018 A1 - Laurette Dubé A1 - Pan Du A1 - Cameron McRae A1 - Neha Sharma A1 - Srinivasan Jayaraman A1 - Jian-Yun Nie KW - artificial intelligence KW - convergent innovation KW - food KW - social media KW - user-generated content AB - Inclusive innovation has not yet reached societal scale due to a well-entrenched divide between wealth creation and social equity. Taking food as the initial test bed, we have proposed the convergent innovation model to address such challenges still facing 21st century society by bridging sectors and disciplines around an integrated goal on both sides of the social-economic divide for innovations that target wealth creation with an upfront consideration of its externalities. The convergent innovation model is empowered by two key enablers that integrate an advanced digital infrastructure with leading scientific knowledge on the drivers of human behaviour in varying contexts. This article discusses the structure, methods, and development of an artificial intelligence platform to support convergent innovation. Insights are gathered on consumer sentiment and behavioural drivers through the analysis of user-generated content on social media platforms. Empirical results show that user discussions related to marketing, consequences, and occasions are positive. Further regression modelling finds that economic consequences are a strong predictor of consumer global sentiment, but are also sensitive to both the actual price and economic awareness. This finding has important implications for inclusive growth and further emphasizes the need for affordable and accessible foods, as well as for consumer education. Challenges and opportunities inspired by the research results are discussed to inform the design, marketing, and delivery of convergent innovation products and services, while also contributing to dimensions of inclusion and economic performance for equitable health and wealth. PB - Talent First Network CY - Ottawa VL - 8 UR - http://timreview.ca/article/1139 IS - 2 U1 - McGill University Laurette Dubé is a Full Professor and holds the James McGill Chair of Consumer and Lifestyle Psychology and Marketing at the Desautels Faculty of Management of McGill University in Montreal, Canada. Her research interest bears on the study of affects and behavioural economic processes underlying consumption and lifestyle behaviour and how such knowledge can inspire more effective health and marketing communications in both real life and technology-supported media. She is the Founding Chair and Scientific Director of the McGill Centre for the Convergence of Health and Economics (MCCHE). The MCCHE was created to foster partnerships among scientists and decision makers from all sectors of society to encourage a more ambitious notion of what can be done for more effective health management and novel pathways for social and business innovation. U2 - McGill University Pan Du is a Research Associate in the Department of Computer Science and Operational Research at the Université de Montréal, Canada. Before that, Pan was an Assistant Professor at the Chinese Academy of Sciences. He received his PhD from the Institute of Computing Technology of the Chinese Academy of Sciences. His research interests lie in text mining, information retrieval, machine learning, and social network analysis. He has published academic papers in various conferences and journals. He is a recipient of the 2016 “Science and Technology Progress Award” of the Chinese Institute of Electronics for his contribution to a web-scale text mining system. U3 - McGill University Cameron McRae is a Senior Research Analyst at the McGill Centre for the Convergence of Health and Economics in Montreal, Canada. Since joining the centre in 2014, he has led many translational research projects to support innovation in the agricultural, food, and health sectors. Cameron has strong interdisciplinary training at the nexus of science, technology, and management, with a Bachelor of Science in Pharmacology from McGill University, a Graduate Certificate in Business Administration from John Molson School of Business, and a Master of Health Informatics from the University of Toronto. Previously, Cameron has worked in both the public and private sectors to support strategy and practice in the areas of governance, business development, and business/market intelligence related to life sciences and digital health. U4 - McGill University Neha Sharma is currently pursuing her PhD at the Department of Bioresource Engineering at McGill University in Montreal, Canada. She completed her Master’s degree in Biochemical Engineering from Harcourt Butler Technical University, India. The title of her Master’s research project was “Optimization of Process parameters for Bacterial solid-state fermentation of Nattokinase to prevent myocardial infarction”, which culminated in principles of food processing, microbiology, and bioprocessing. Her Bachelor’s degree in Biotechnology is from IMS Engineering College, India, where she took various courses in molecular biology, genetic engineering, bioprocess engineering, fermentation biotechnology, food biotechnology, and environmental biotechnology, etc. In her final year, her Bachelor’s project was based on the study of plant extracts and their antimicrobial properties. U5 - McGill University Srinivasan Jayaraman is a Research Associate/Visiting Scholar at the Desautels Faculty of Management, at McGill University in Montreal, Canada. He obtained his Bachelor’s degree in Electronics and Instrumentation Engineering from Bharathidasan University, India, his MTech degree in Biomedical Engineering from SASTRA University in Thanjavur, India, and his doctorate from the School of Bioscience at the Indian Institute of Technology Madras in Chennai, India. Previously, he has held roles at TCS Innovation Labs, the University of Nebraska Lincoln, the New Jersey Institute of Technology, and INRS-EMT Canada. His research interests include human behavioural and performance modelling, ontology, ergonomics, personalized diagnosis systems, wearable devices, biosignal processing, and human-machine interfaces. In 2011, he won the MIT-TR35 young innovator award Indian edition and was recognized as one among the Top 50 most impactful social innovators (global listing) by World CSR Congress & World CSR Day at 2016. ER - TY - JOUR T1 - Impact of Business Intelligence Solutions on Export Performance of Software Firms in Emerging Economies JF - Technology Innovation Management Review Y1 - 2018 A1 - Michael Neubert A1 - Augustinus Van der Krogt KW - artificial intelligence KW - business intelligence KW - emerging markets KW - global marketing KW - international business KW - international entrepreneurship KW - international management KW - machine learning KW - Paraguay KW - software industry AB - The article is written with the aim of understanding how well software firms in emerging economies perform when exporting their goods. Focusing on Paraguay as a representative context, a multiple-case-study research design was adopted using different sources of evidence, including 15 in-depth interviews with founders, shareholders, and CEOs. The data were analyzed using grounded theory in order to develop patterns and categories, and to understand differences and regularities. The revised Uppsala internationalization process model was used as a theoretical framework. This article highlights the experts’ views of the impact of business intelligence on the export performance of software firms in Paraguay. Although only a few of the interviewees currently use business intelligence solutions to support international strategic decision-making processes, most of them reveal a desire to use them because they expect it will have a positive impact on export performance and international competitiveness. The main factors for selecting a business intelligence solution are transparency of cost and benefits, excellent client service, and an attractive pricing model. The study results apply to all stakeholders who support the impact of business intelligence systems on the export performance of software firms in emerging economies. The article fulfils an identified need and call for research to study the use and impact of business intelligence on the way an emerging country’s exportation of goods actually performs, and the ability of its software firms to globalize successfully. PB - Talent First Network CY - Ottawa VL - 8 UR - https://timreview.ca/article/1185 IS - 9 U1 - International School of Management Michael Neubert is a Professor at the International School of Management in Paris, France, where he obtained his PhD and is now also Chair of the Strategic Management Committee. He teaches international business, intercultural communication, doing business in foreign markets, and international finance. His research interests concern the internationalization of high-tech startups. Michael is a member of the Academy of International Business, and he is a partner of a private equity firm that invests in high-tech startups and supports them in the development of new foreign markets. Michael is also the CEO of C2NM, a Swiss consulting firm specializing in the field of international and intercultural management. U2 - Universidad Paraguayo Alemana Augustinus (Stijn) Van Der Krogt is the Dean of the Faculty of Business Administration at the Universidad Paraguayo Alemana in San Lorenzo, Paraguay. He is also a Director of the consulting firm Changing Values International, which accompanies private and public organizations in their process of change by providing tailor-made strategic advice and executive training and coaching. ER - TY - JOUR T1 - The Impact of Digitalization on the Speed of Internationalization of Lean Global Startups JF - Technology Innovation Management Review Y1 - 2018 A1 - Michael Neubert KW - artificial intelligence KW - big data analytics KW - digitalization KW - global marketing KW - international business KW - international business development KW - international entrepreneurship KW - international management KW - lean global startup KW - machine learning AB - Lean global startups need to internationalize early and fast. The digitalization of new foreign market development helps them to more efficiently identify new market opportunities in global markets. With this approach, they are saving resources while developing the most attractive markets. This article examines how lean global startups develop new foreign markets more rapidly due to digitalization. Thus, the aim is to understand the impact of digitalization on speed of internationalization of lean global startups. The study addresses a gap in the scholarly literature and a practical need to evaluate new foreign markets and business opportunities more quickly and more regularly and to understand what helps lean global startups react more quickly to opportunities and threats with respect to changing market attractiveness. Furthermore, it outlines why and how digitalization is important throughout the internationalization process. The research followed a multiple case-study design using different sources of evidence, including 73 interviews with senior managers of lean global startups. The findings reveal that digitalization allows lean global startups to increase decision-making efficiency and to optimize strategies and processes for evaluating international markets. The findings suggest that lean global startups can benefit from the use of digital technologies by applying a more efficient foreign market development process with regular reviews and a reduced workflow, by faster mediation between local market realities and strategic goals, by analyzing all foreign markets instead of just a sample of them, and by optimizing decision-making processes including the ability to make long-term, strategic decisions due to better market information. PB - Talent First Network CY - Ottawa VL - 8 UR - http://timreview.ca/article/1158 IS - 5 U1 - International School of Management Michael Neubert is a Professor at the International School of Management in Paris, France, where he obtained his PhD and is now also Chair of the Strategic Management Committee. He teaches international business, intercultural communication, doing business in foreign markets, and international finance. His research interests concern the internationalization of high-tech startups. Michael is a member of the Academy of International Business, and he is a partner of a private equity firm that invests in high-tech startups and supports them in the development of new foreign markets. Michael is also the CEO of C2NM, a Swiss consulting firm specializing in the field of international and intercultural management. ER - TY - JOUR T1 - Using Artificial Intelligence and Web Media Data to Evaluate the Growth Potential of Companies in Emerging Industry Sectors JF - Technology Innovation Management Review Y1 - 2017 A1 - Andrew Droll A1 - Shahzad Khan A1 - Ehsanullah Ekhlas A1 - Stoyan Tanev KW - analytics KW - artificial intelligence KW - business intelligence KW - entrepreneurship KW - online textual data KW - precision medicine sector KW - startup growth potential AB - In this article, we describe our efforts to adapt and validate a web search and analytics tool – the Gnowit Cognitive Insight Engine – to evaluate the growth and competitive potential of new technology startups and existing firms in the newly emerging precision medicine sector. The results are based on two different search ontologies and two different samples of firms. The first sample includes established drug companies operating in the precision medicine field and was used to estimate the relationship between the firms’ innovativeness and the extent of online discussions focusing on their potential growth. The second sample includes new technology firms in the same sector. The firms in the second sample were used as test cases to determine whether their growth-related web search scores would relate to the degree of their innovativeness. The second part of the study applied the same methodology to the real-time monitoring of the firms’ competitive actions. In our findings, we see that our methodology reveals a moderate degree of correlation between the Insight Engine’s algorithmically computed relevance scores and independent measures of innovation potential. The existence of such correlations invites future work in attempting to analyze company growth potential using techniques founded in web content scraping, natural language processing, and machine learning. PB - Talent First Network CY - Ottawa VL - 7 UR - http://timreview.ca/article/1082 IS - 6 U1 - Gnowit Inc. Andrew Droll is Lead Data Scientist at Gnowit in Ottawa, Canada. Andrew holds PhD and MSc degrees in pure mathematics from Queen’s University in Kingston, Canada, and he holds a BSc degree in Mathematics and Physics from Carleton University in Ottawa, Canada. His peer-reviewed publications span the fields of physics, mathematics, and computer science. Currently, Andrew works on development and management of Gnowit’s research and engineering projects. U2 - Gnowit Inc. Shahzad Khan is the CTO of Gnowit Inc. in Ottawa, Canada, that provides personalized, real-time web intelligence for individuals and corporations. The firm employs artificial intelligence to automatically gather data from fragmented web sources in near-real-time and filter the data using human-like synthetic cognitive methods to provide highly curated intelligence to their clients. He has a PhD in Computer Science from the University of Cambridge, United Kingdom, an MSc in Information Studies from Syracuse University in New York, USA, and a BSc (Hons) in Computer Science from the Lahore University of Management Science (LUMS) in Lahore, Pakistan. His research interests lie in semantic analysis on big data repositories using natural language processing and machine learning at scale. U3 - University of Southern Denmark Ehsan Ekhlas is a student and entrepreneur completing studies in Technology Entrepreneurship and Business Innovation at the University of Southern Denmark. Ehsan is also Founder & CEO of Mimac IVS, a company focused on fashion accessories for Apple products. In his research, Ehsan uses technological and big data tools to try to discover insights about how people do work in the real world. U4 - Southern Denmark University Stoyan Tanev is an Associate Professor in the Department of Technology and Innovation, Faculty of Engineering, Southern Denmark University (SDU) in Odense. Dr. Tanev is leading the Technology Entrepreneurship stream of the Master Program of Product Development and Innovation at SDU. He is also an Adjunct Research Professor in the Sprott School of Business at Carleton University in Ottawa, Canada, where he is associated with the Technology Innovation Management Program. He has a MSc and a PhD in Physics jointly from the University Pierre and Marie Curie, Paris, France, and the University of Sofia, Bulgaria, a PhD in Theology from the University of Sofia, Bulgaria, an MEng in Technology Innovation Management from Carleton University, Canada, and an MA from the University of Sherbrooke, Canada. He has multidisciplinary research interests with a focus on the fields of global technology entrepreneurship, technology innovation management, business model design, and value co-creation. Dr. Tanev is Senior IEEE member, as well as member of the editorial boards of the Technology Innovation Management Review, the International Journal of Actor-Network Theory, and Technological Innovation. ER -