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| 003 | | OCoLC |
| 005 | | 20240307140500 |
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▼a 2023004693 |
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▼a 9781003304616
▼q electronic book |
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▼a 1003304613
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▼a 9781000912630
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▼z 9781032303413
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▼z 9781032303420
▼q paperback |
| 024 | 7 |
▼a 10.4324/9781003304616
▼2 doi |
| 035 | |
▼a 3627922
▼b (N$T) |
| 035 | |
▼a (OCoLC)1369032304 |
| 037 | |
▼a 9781003304616
▼b Taylor & Francis |
| 040 | |
▼a DLC
▼b eng
▼e rda
▼c DLC
▼d OCLCF
▼d TYFRS
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▼d YDX
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▼a KJMV6
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▼a 650.0285
▼2 23/eng/20230203 |
| 245 | 00 |
▼a Impact of artificial intelligence in business and society :
▼b opportunities and challenges /
▼c edited by Francesco Paolo Appio, Davide La Torre, Francesca Lazzeri, Hatem Masri and Francesco Schiavone. |
| 246 | 30 |
▼a Impact of AI in business and society |
| 264 | 1 |
▼a Abingdon, Oxon ;
▼a New York, NY :
▼b Routledge,
▼c 2024. |
| 264 | 4 |
▼c 짤2024 |
| 300 | |
▼a 1 online resource (xiv, 279 pages) :
▼b illustrations. |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b c
▼2 rdamedia |
| 338 | |
▼a online resource
▼b cr
▼2 rdacarrier |
| 490 | 1 |
▼a Routledge studies in innovation, organizations and technology |
| 504 | |
▼a Includes bibliographical references and index. |
| 520 | |
▼a "Belonging to the realm of intelligent technologies, it is increasingly accepted that AI has evolved from being merely a development standpoint in computer science. Indeed, recent reports and academic publications show that we are clearly on the path towards pervasive AI in both business and society. Organizations must adopt AI to maintain a competitive advantage and explore opportunities for unprecedented innovation. This book focuses on understanding the wide range of opportunities as well as the spectrum of challenges AI brings in different business contexts and society at large. The book highlights novel and high-quality research in data science and business analytics and examines the current and future impact of AI in business and society. The authors bridge the gap between business and technical perspectives and demonstrate the potential (and actual) impact on society. Embracing applied, qualitative and quantitative research as well as field experiments and data analysis, the book covers a broad range of topics including but not limited to: human-centered AI, product and process innovation, corporate governance, AI and ethics, organizational performance, and entrepreneurship. This comprehensive book will be a valuable resource for researchers, academics and postgraduate students across artificial intelligence, technology and innovation management and a wide range of business disciplines"--
▼c Provided by publisher. |
| 545 | 0 |
▼a Francesco Paolo Appio is a Full Professor of Innovation at Paris School of Business, Paris, France. He earned his Ph.D. in Management from Scuola Superiore Sant'Anna in Italy. He has recently visited important international academic institutions such as Bocconi University (Italy), MIT Sloan School of Management (USA), and K.U. Leuven (Belgium). His research is interdisciplinary in nature and mainly revolves around the impact of digital transformation on innovation at multiple levels (ecosystems, city, organization, teams), taking into account different perspectives such as sustainability, socio-technical systems, technological change, and innovation capabilities. He has recently been appointed as a member of the Editorial Board for the journals like Journal of Product Innovation Management, Technological Forecasting and Social Change, and IEEE Transactions on Engineering Management. His research has been published in Journal of Product Innovation Management, Long Range Planning, Technological Forecasting and Social Change, International Journal of Production Research, Industrial Marketing Management, among others. He is guest editor of multiple special issues in journals like Journal of Product Innovation Management, Organization Studies, Technological Forecasting and Social Change, IEEE Transactions on Engineering Management, and Journal of Urban Technology. Davide La Torre, Ph.D., HDR, is a Mathematician and Full Professor of Applied Mathematics and Computer Science at SKEMA Business School, Sophia Antipolis Campus, France. He is qualified in the French national university system as Professeur des Universite?s in Applied Mathematics (CNRS 26), Computer Science (CNRS 27), and Economics (CNRS 5) as well as in the Italian national university system as Professore Ordinario in Mathematical Methods for Economics (13 D4), Political Economy (13 A2), and Public Economics (13 A3). His research and teaching interests include Applied Mathematics, Artificial Intelligence, Business Analytics, Mathematical Modeling, and Operations Research. He got his HDR (Habilitation a? Diriger des Recherches) in Applied Mathematics from the Universite? Co?te d'Azur, Nice, France (2021) and a Doctorate in Computational Mathematics and Operations Research from the University of Milan, Milan, Italy (2002) as well as professional certificates in Analytics from the Massachusetts Institute of Technology, USA. In the past, he held permanent and visiting university professor positions in Europe, Canada, Middle East, Central Asia, and Australia. He also served as Associate Dean, Departmental Chair, and Program Head at several universities. He has more than 190 publications in Scopus, most of them published in high IF journals ranging from Engineering to Business. Francesca Lazzeri, Ph.D., is a data and machine learning scientist with extensive experience in academic research, tech innovation, and engineering team management. She is the author of a few books on machine learning and applied data science, and many other publications, including technology journals and conferences. Francesca is a Professor of Python for machine learning and AI at Columbia University and Principal Data Scientist Director at Microsoft Cloud + AI, where she leads an organization of data scientists and machine learning engineers building intelligent applications on the Cloud, utilizing data and techniques spanning from generative AI, time series forecasting, experimentation, causal inference, computer vision, natural language processing, reinforcement learning. Before joining Microsoft, she was a Research Fellow at Harvard University in the Technology and Operations Management Unit. Francesca is also Advisory Board Member of the AI-CUBE (Artificial Intelligence and Big Data CSA for Process Industry Users, Business Development and Exploitation) project, the Women in Data Science (WiDS) initiative, machine learning mentor at the Massachusetts Institute of Technology, and active member of the AI community. Hatem Masri is a Professor of Business Analytics and Vice President for Academic Affairs and Development at the Applied Science University, Kingdom of Bahrain. He received a Ph.D. in Management Science in 2004 and Master's in Operations Research in 1999 from the University of Tunis, Tunisia. His research interests include business analytics, supply chain management, financial engineering, and Islamic finance. He published more than 30 articles and six books among them a textbook on Islamic business administration. Hatem is founder and chair of the INFORMS Bahrain International Group, past president of the African Federation of Operational Research Societies, general secretary of the Tunisian Decision Aid Society, member of INFORMS and IEEE, and volunteer/mentor with the AACSB. Francesco Schiavone is a Full Professor of Management at University Parthenope, Naples, Italy. He received Ph.D. degree in Network Economics and Knowledge Management from the Ca' Foscari University of Venice (Italy) in 2006. He is also an Affiliated Professor at Emlyon and Paris School of Business (France) and University of South Pacific (Fiji Island). Currently, his main research areas are technology management, strategic innovation, communities of practice, and healthcare management and innovation. Prof. Schiavone is the scientific director of VIMASS, the research lab in healthcare management and innovation, established at University Parthenope. |
| 588 | |
▼a Description based on online resource; title from digital title page (viewed on August 29, 2023). |
| 590 | |
▼a WorldCat record variable field(s) change: 050 |
| 650 | 0 |
▼a Business
▼x Decision making
▼x Data processing. |
| 650 | 0 |
▼a Business enterprises
▼x Technological innovations. |
| 650 | 0 |
▼a Artificial intelligence
▼x Data processing. |
| 650 | 7 |
▼a Artificial intelligence
▼x Data processing.
▼2 fast
▼0 (OCoLC)fst00817255 |
| 650 | 7 |
▼a Business
▼x Decision making
▼x Data processing.
▼2 fast
▼0 (OCoLC)fst00842316 |
| 650 | 7 |
▼a Business enterprises
▼x Technological innovations.
▼2 fast
▼0 (OCoLC)fst00842646 |
| 650 | 7 |
▼a BUSINESS & ECONOMICS / General
▼2 bisacsh |
| 650 | 7 |
▼a BUSINESS & ECONOMICS / Business Ethics
▼2 bisacsh |
| 650 | 7 |
▼a BUSINESS & ECONOMICS / Information Management
▼2 bisacsh |
| 655 | 4 |
▼a Electronic books. |
| 700 | 1 |
▼a Appio, Francesco,
▼e editor. |
| 700 | 1 |
▼a La Torre, Davide,
▼e editor. |
| 700 | 1 |
▼a Lazzeri, Francesca,
▼e editor. |
| 700 | 1 |
▼a Masri, Hatem,
▼d 1964-,
▼e editor. |
| 700 | 1 |
▼a Schiavone, Francesco,
▼e editor. |
| 776 | 08 |
▼i Print version:
▼a La Torre, Davide.
▼t Impact of artificial intelligence in business and society
▼d Abingdon, Oxon ; New York, NY : Routledge, 2023
▼z 9781032303413
▼w (DLC) 2023004692 |
| 830 | 0 |
▼a Routledge studies in innovation, organization and technology. |
| 856 | 40 |
▼3 EBSCOhost
▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3627922 |
| 938 | |
▼a EBSCOhost
▼b EBSC
▼n 3627922 |
| 990 | |
▼a 관리자 |
| 994 | |
▼a 92
▼b N$T |