<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sergey A. Yablonsky</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">AI-Driven Digital Platform Innovation</style></title><secondary-title><style face="normal" font="default" size="100%">Technology Innovation Management Review</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Advanced Analytics</style></keyword><keyword><style  face="normal" font="default" size="100%">AI maturity</style></keyword><keyword><style  face="normal" font="default" size="100%">AI value chain</style></keyword><keyword><style  face="normal" font="default" size="100%">AI-driven platform innovation</style></keyword><keyword><style  face="normal" font="default" size="100%">Artificial Intelligence (AI)</style></keyword><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">enterprise platform</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">timreview.ca/article/1392</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Talent First Network</style></publisher><pub-location><style face="normal" font="default" size="100%">Ottawa</style></pub-location><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">4-15</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial Intelligence (AI) innovation becomes useful today when it enriches decision-making that is enhanced by applications of big data (BD), advanced analytics (AA), and some element of human interaction using digital platforms. This research aims to investigate the potential combination of AI, BD and AA for digital business platforms. In doing so, it develops a multi-dimensional AI-driven platform innovation framework with AI/BD/AA innovation value chain and related levels of AI maturity improvement. The framework can be used with a focus on the data-driven human-machine relationship and the application of AI at different levels of an AI-driven digital platform technology stack.</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">St. Petersburg State University
Sergey Yablonsky, PhD in computer science, is an Associate Professor at Graduate School of Management, St. Petersburg State University in St. Petersburg, Russia. Author of more than 200 publications. Co-creator of the Russian WordNet and the Russicon language processor and linguistic resources licensed by Adobe Systems Incorporated, Phoenix Int. (USA), Franklin Electronic Publishers (USA) etc. Engaged in 35 national and international research projects in Russia, and across Europe. Research interests include Digital Economy, Digital Business and Entrepreneurship; Multisided Platforms and Markets; Artificial Intelligence, Digital marketing; Big Data Governance; Computer linguistics and text mining; Semantic and Social Web. Courses taught: Data Governance (Bachelor Program); Digital Marketing &amp; Digital Commerce (Bachelor programs); Digital Business (Master program); Smart Business Transformation in the Digital Age (CEMS Block Seminar); Multi-Sided Platforms and Innovation in a Global Era (CEMS Block Seminar); Digital Economy (EMBA). Visiting professor at WU (Vienna University of Economics and Business) in Austria, Stockholm Business School, Stockholm university in Sweden, Aalto University in Finland, Lappeenranta University of Technology in Finland, Hame University of Applied Sciences in Finland.</style></custom1><section><style face="normal" font="default" size="100%">4</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gregory Sandstrom</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Editorial: Insights (October 2020)</style></title><secondary-title><style face="normal" font="default" size="100%">Technology Innovation Management Review</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Advanced Analytics</style></keyword><keyword><style  face="normal" font="default" size="100%">AI maturity. Data science</style></keyword><keyword><style  face="normal" font="default" size="100%">AI value chain</style></keyword><keyword><style  face="normal" font="default" size="100%">AI-driven platform innovation</style></keyword><keyword><style  face="normal" font="default" size="100%">Artificial Intelligence (AI)</style></keyword><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">business decision-making</style></keyword><keyword><style  face="normal" font="default" size="100%">business model components</style></keyword><keyword><style  face="normal" font="default" size="100%">business models</style></keyword><keyword><style  face="normal" font="default" size="100%">content analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">data-dominant logic</style></keyword><keyword><style  face="normal" font="default" size="100%">dominant logic</style></keyword><keyword><style  face="normal" font="default" size="100%">empirical study</style></keyword><keyword><style  face="normal" font="default" size="100%">enterprise platform</style></keyword><keyword><style  face="normal" font="default" size="100%">industries</style></keyword><keyword><style  face="normal" font="default" size="100%">online communication</style></keyword><keyword><style  face="normal" font="default" size="100%">online data collection</style></keyword><keyword><style  face="normal" font="default" size="100%">organizational and managerial requirements</style></keyword><keyword><style  face="normal" font="default" size="100%">principal component analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">R&amp;D</style></keyword><keyword><style  face="normal" font="default" size="100%">research and development</style></keyword><keyword><style  face="normal" font="default" size="100%">secondary data. Sustainability</style></keyword><keyword><style  face="normal" font="default" size="100%">SMEs. Disruptive innovation</style></keyword><keyword><style  face="normal" font="default" size="100%">sustainable innovation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">timreview.ca/article/1396</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Talent First Network</style></publisher><pub-location><style face="normal" font="default" size="100%">Ottawa</style></pub-location><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">3-3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">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. He completed a PhD from the Faculty of Sociology at St. Petersburg State University and the Sociological Institute of the Russian Academy of Sciences, 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 was affiliated with 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.</style></custom1><section><style face="normal" font="default" size="100%">3</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sergey A. Yablonsky</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multidimensional Data-Driven Artificial Intelligence Innovation</style></title><secondary-title><style face="normal" font="default" size="100%">Technology Innovation Management Review</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Advanced Analytics</style></keyword><keyword><style  face="normal" font="default" size="100%">AI maturity</style></keyword><keyword><style  face="normal" font="default" size="100%">AI value chain</style></keyword><keyword><style  face="normal" font="default" size="100%">Artificial Intelligence (AI)</style></keyword><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">enterprise platform</style></keyword><keyword><style  face="normal" font="default" size="100%">innovation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">timreview.ca/article/1288</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Talent First Network</style></publisher><pub-location><style face="normal" font="default" size="100%">Ottawa</style></pub-location><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">16-28</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This is a critical time for the development and adoption of Artificial Intelligence (AI). The field has existed since the 1950s and is only now emerging as viable for commercial markets. Many enterprises are placing bets on AI that will determine their future. Today AI innovation becomes useful when it enriches decision-making that is enhanced by applying Big Data (BD) and Advanced Analytics (AA), with some element of human interaction using digital platforms. This research investigates an opportunity for cross-fertilization between AI, BD, and AA with related disciplines. The paper aims to investigate the potential relationship of AI, BD, and AA with digital business platforms. In doing so, it develops a multidimensional BD-driven AI innovation taxonomy framework with an AA/BD/AA innovation value chain, related levels of BD, and analytics maturity improvement. This framework can be used with a focus on data-driven human-machine relationships, and applying AI at different levels of data driven automation maturity.</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">St. Petersburg State University
Sergey Yablonsky, PhD in computer science, is an Associate Professor at the Graduate School of Management, St. Petersburg State University in St. Petersburg, Russia. Author of more than 200+ publications. Co-creator of the Russian WordNet and the Russicon language processor, and linguistic resources licensed by Adobe Systems Incorporated, Phoenix Int. (USA), Franklin Electronic Publishers (USA) etc. Engaged in 35 national and international research projects in Russia, and across Europe. Research interests include Digital Economy, Digital Business and Entrepreneurship; Multisided Platforms and Markets; Artificial Intelligence, Digital marketing; Big Data Governance; Computer linguistics and text mining; Semantic and Social Web. Courses taught: Data Governance (Bachelor Program); Digital marketing (Bachelor Program); Digital Commerce (Bachelor Program); Digital Business (Master Program); Smart Business Transformation in the Digital Age (CEMS Block Seminar); Multi-Sided Platforms and Innovation in a Global Era (CEMS Block Seminar); Digital Economy (EMBA). Visiting professor at WU (Vienna University of Economics and Business) in Austria, Stockholm Business School, Stockholm university in Sweden, Aalto University in Finland, Lappeenranta University of Technology in Finland, Hame University of Applied Sciences in Finland.</style></custom1><section><style face="normal" font="default" size="100%">16</style></section></record></records></xml>