Harnessing Business Intelligence for Modern Talent Management. Este artículo no está disponible.Harnessing Business Intelligence for Modern Talent Management

In an era where talent drives organizational success, effectively managing the workforce has become increasingly complex and vital. The shift toward data-driven strategies empowers business to better understand employee needs, predict workforce trends, and optimize human resource practices. Business intelligence (BI) enables organizations to make informed, strategic decisions that align talent management with broader business goals. By leveraging BI, companies can enhance recruitment, engagement, and retention in ways that traditional methods cannot. This integration not only strengthens organizational resilience but also fosters a more adaptive and competitive business environment. Harnessing Business Intelligence for Modern Talent Management delves into the ways BI is reshaping the talent management sector, from revolutionizing hiring practices to boosting employee engagement and retention. It explores not only the technology but also the shifts in mindset required to adopt a data-driven culture within human resources. Covering topics such as data-driven workplaces, talent equity, and workforce development, this book is an excellent resource for professionals, researchers, educators, students, academicians, managers, business leaders, and more.

Lamprini Seremeti is a an Assistant Professor in the Department of Agricultural Economics & Rural Development at the School of Applied Economics and Social Science of the Agricultural University of Athens. She holds a PhD in Computer Science with a focus on propagating knowledge in networks of aligned ontologies from Hellenic Open University; a Master in Special Education from University of Rome; a Master in Pure Mathematics from University of Patras; a Bachelor in Mathematics from University of Patras; a Bachelor in Informatics from University of Western Greece; and a Bachelor in Law from University of Nicosia. She has also participated as a researcher in EU-funded projects, in which, her tasks involved mathematical modeling, data processing, knowledge representation and management, and conceptualization of heterogeneous environments (socio-economic, educational, biomedical, ambient intelligent). Her research interests focus on theories applied in interpretation of Law in ambient intelligent environments, knowledge representation and management through ontologies, and mathematical modeling of co-evolving systems.

Panagiotis Liargovas received his BA degree from the University of Athens and his MA and Ph.D degrees in Economics from Clark University, Worcester MA. He has been a Fulbright Scholar, a Bakalas Foundation Scholar, a Teaching Assistant Scholar (Clark University) and a European Commission trainee (Brussels). He has taught in many Universities including Clark University, Bologna University, and University of Strasbourg. He has served as economic advisor to the Greek Ministry of Finance, the Greek Ministry of Foreign Affairs and the Municipality of Athens in many occasions. For the period 2013-18 he was the Head of the Parliamentary Budget Office at the Hellenic Parliament. He is currently Chairman of the Board of the Centre of Planning and Economic Research (KEPE) and of the National Productivity Board. He is also Professor of Economics at the University of Peloponnese. He specializes on International and European Economics, Regional Economics and Economic Development and Policy. He has made more than 100 publications in academic journals and has published more than 20 books. His latest book (Pataki publishers, in Greek) was published in 2020 and was entitled “Ten years of crisis, three memoranda and a pandemic: Greece in search for a way out”.

Christos Papademetriou , teaches at the University of Neapolis in Pafos since 2010. He is an Assistant Professor in Management – Human Resources Management at the School of Economics, Administration and Computer Science. He is a Coordinator of the Distance Master in Business Administration (DMBA). He was teaching in the Department of Business Administration at the Open University of Cyprus (2017-2020). He obtained a ΒΑ (Hons) in Accounting and Business (2001) and MA in International Management (2002) from the University of Sunderland. He was awarded also a BSc (Hons) in Computing and the Postgraduate Certificate in Information Systems from the University of Portsmouth. He also holds an MA in Real Estate from University of Neapolis. He holds a doctorate (PhD) in Social Science from the University of Leicester, UK. The title of his thesis is “Investigating the Impact of Sequential Cross-Cultural Training on the Level of Sociocultural and Psychological Adjustment of Expatriate Mangers”. Furthermore, he obtained a Postdoctoral from the University of Western Macedonia. His research interests are in the areas of Management, Human Resource Management, Organizational Behaviour, Tourism Business Administration, Educational Management, Service Quality and Tourism and Hospitality Management.

Prof. Sofia Anastasiadou is a Professor of Statistics and Research Methodology, Biostatistics and Biomedical Research at the School of Health of the University of Western Macedonia (UOWM), Department of Midwifery. She is the Deam of School of Health of UOWM, and a Member of the Dean of the School of Economics of the University of Western Macedonia. She is also a Member of the Senate and a MODIP Member of the same University. Since 2020 she is the President of Greek Society of Data Analysis (GSDA). She has been a founding Member since 2001. She has been Secretary General since 2016. Sofia Anastasiadou makes a constant effort for the development and dissemination of Data Analysis and Multidimensional Statistical Analysis methods, such as Principal Component Analysis, Factor Analysis, Factor Analysis of Correspondences, Symbolic Analysis, Inductive Statistics, Discriminant Analysis, Cluster Analysis, Implicative Statistical Analysis and new fields that can be developed based on relevant international developments in statistical science. She can be contacted at email: sanastasiadou@uowm.gr