About me
Julien Cloarec
Julien Cloarec is 𝗔𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗲 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 𝗼𝗳 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 at iaelyon School of Management, Université Jean Moulin Lyon 3, Magellan, France.
He is also Vice-President of the French Society of Management and Board + Council Member of the French Marketing Association.
He holds an M.Eng. in Computer Science, as well as a Ph.D. in Marketing, for which he was awarded the 𝗕𝗲𝘀𝘁 𝗧𝗵𝗲𝘀𝗶𝘀 𝗣𝗿𝗶𝘇𝗲 by the French Foundation for Management Education and a 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗗𝗶𝘀𝘁𝗶𝗻𝗰𝘁𝗶𝗼𝗻 by the French Marketing Association.
As an academic, he seeks to offer insights pertaining to 𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝗽𝗿𝗶𝘃𝗮𝗰𝘆 and 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲. His research was 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝗶𝗻 𝘀𝗲𝘃𝗲𝗿𝗮𝗹 𝗷𝗼𝘂𝗿𝗻𝗮𝗹𝘀, such as 𝘑𝘰𝘶𝘳𝘯𝘢𝘭 𝘰𝘧 𝘉𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩, 𝘗𝘴𝘺𝘤𝘩𝘰𝘭𝘰𝘨𝘺 & 𝘔𝘢𝘳𝘬𝘦𝘵𝘪𝘯𝘨, 𝘛𝘦𝘤𝘩𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯, 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘪𝘤𝘢𝘭 𝘍𝘰𝘳𝘦𝘤𝘢𝘴𝘵𝘪𝘯𝘨 𝘢𝘯𝘥 𝘚𝘰𝘤𝘪𝘢𝘭 𝘊𝘩𝘢𝘯𝘨𝘦, 𝘐𝘯𝘵𝘦𝘳𝘯𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘑𝘰𝘶𝘳𝘯𝘢𝘭 𝘰𝘧 𝘏𝘶𝘮𝘢𝘯 𝘙𝘦𝘴𝘰𝘶𝘳𝘤𝘦 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵, and 𝘍𝘳𝘦𝘯𝘤𝘩 𝘑𝘰𝘶𝘳𝘯𝘢𝘭 𝘰𝘧 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘐𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯 𝘚𝘺𝘴𝘵𝘦𝘮𝘴.
Research
As a researcher, I seek to offer insights pertaining to privacy and new technologies, as well as relevant implications for practice
Privacy
Cloarec, J. (2022), Privacy Controls as an Information Source to Reduce Data Poisoning in Artificial Intelligence-powered Personalization, Journal of Business Research, 152
Cloarec, J., Meyer-Waarden, L. and Munzel, A. (2022), The Personalization–Privacy Paradox at the Nexus of Social Exchange and Construal Level Theories, Psychology & Marketing, 49(3)
Cloarec, J. (2020), The Personalization-Privacy Paradox in the Attention Economy, Technological Forecasting and Social Change, 161
Artificial Intelligence
Meyer-Waarden, L. and Cloarec, J. (2022), “Baby, You Can Drive My Car”: Psychological Antecedents that Drive Consumers’ Adoption of AI-powered Autonomous Vehicles, Technovation, 109
Meyer-Waarden, L, Cloarec, J., Adams, C., Aliman, D. N., and Wirth, V (2021), Home, Smart Home: How Well-Being Shapes the Adoption of AI-Powered Homes in Smart Cities, French Journal of Management Information Systems, 26(4)
Data Science
As an academic and trainer, I share my knowledge of Data Science, an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data
Statistics
Statistics is the discipline that concerns the collection, organization, analysis, interpretation and presentation of data
Machine Learning
Machine learning is the study of computer algorithms that improve automatically through experience and by the use of data
natural language processing
Natural language processing is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language
COMPUTER VISION
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos
Organizations that trusted me for Data Science training
