Daniel Mandel Gandrita, PhD, is a university lecturer, researcher, author, andmanagement professional with a strong academic and professional background instrategic management, organizational strategy, leadership, artificial intelligence,and organizational transformation.He holds a PhD in Management from Universidade Europeia, completed in 2024, witha doctoral thesis entitled Rethinking the Strategic Planning Paradigm: A DynamicCapabilities Perspective. He also holds a Master's degree in Management and BusinessStrategy and a Bachelor's degree in Management, specializing in Business Management.Daniel currently teaches management-related subjects at the Portuguese MilitaryAcademy and has also taught at Universidade Lusófona, including StrategicManagement, Management Planning and Control, Human Resources Management,Research Methods, and Introduction to Management. He is also a researcher at IntrepidLab and CETRAD – Centre for Transdisciplinary Development Studies, where hisresearch interests focus particularly on strategy, innovation, leadership, organizationalperformance, and the impact of artificial intelligence on organizations.His research has been published in international academic journals, including theEuropean Business Review, Thunderbird International Business Review,Administrative Sciences, Technology in Society, EuroMed Journal of Business, andJournal of Financial Reporting and Accounting. His work examines topics such asstrategic planning, dynamic capabilities, AI integration, workplace inclusion, leadership,employee attitudes, and organizational decision-making.He is also co-author of the book The AI Leadership: Finding Algorithm between Headand Heart and has contributed to international scientific publications addressing theevolving role of leadership and artificial intelligence in management.In addition to his academic work, Daniel serves as a reviewer for several internationalscientific journals, including Long Range Planning, Thunderbird InternationalBusiness Review, Acta Astronautica, Behavioral Sciences, Sustainability, andNature, and is a member of the editorial boards of several management and businessjournals.His academic and professional profile combines research, teaching, managementpractice, and strategic analysis, with a particular interest in understanding howorganizations can strengthen their strategic capabilities and adapt to rapidly changingtechnological and competitive environments.

Title: When Does Workplace AI Improve Job Satisfaction? A Configurational Perspective on Self-Evaluation and Social Comparison - Abstract: The rapid advancement of technology has rendered artificial intelligence (AI)increasingly ubiquitous, presenting significant challenges for the workforce and theability to determine job satisfaction. The purpose of this research is to determine whetherand how the use of artificial intelligence (AI) in the workplace influences employees’ jobsatisfaction, with focus on the role of self-evaluations and social comparison processes.A quantitative research design was employed via online survey using a conveniencesample among European employees and a cross-sectional approach testing deductive-hypothesis techniques. We analyzed 250 valid questionnaires using hybrid analysismeasurements (PLS-SEM and FsQCA) representing a 49,8% response rate. Furthermore,reliability, convergent validity, and discriminant validity were assessed. Additionally,mediation effects on self-evaluation and social comparison on the relationship betweenworkplace AI and job satisfaction were examined. Our findings. The investigationcontributes theoretically by explaining the mechanisms linking AI to employeesatisfaction and the focus on self-evaluations and offers practical guidance for companiesseeking the implementation of AI without compromising employee satisfaction and theevaluations format.