Łukasz Sułkowski – författare

Significant disruption to the educational sector occurred due to the COVID-19 pandemic. This shed a light on the need for new delivery methods and greater collaboration, which has become urgent and obvious as existing structures and traditional channels have struggled to cope or shut down. Higher education institutions often fail to crowdsource successfully because crowds differ in how they are organized compared to traditional sourcing. Instead of managing, higher education institutions work with external contributors who self-select into the process. Crowdsourcing has significant potential to transform the education space by enhancing existing methodologies and offering innovative possibilities to develop new pedagogical techniques. This offers benefits for practitioners, institutions, students and participants. Drawing on theory and best practice, illustrated with a wide range of the examples and cases, Crowdsourcing for Innovation in Higher Education offers invaluable guidance and will be of interest to researchers, academics, policymakers, and students in the fields of higher education, development studies, organizational studies, management science and knowledge management.

Significant disruption to the educational sector occurred due to the COVID-19 pandemic. This shed a light on the need for new delivery methods and greater collaboration, which has become urgent and obvious as existing structures and traditional channels have struggled to cope or shut down. Higher education institutions often fail to crowdsource successfully because crowds differ in how they are organized compared to traditional sourcing. Instead of managing, higher education institutions work with external contributors who self-select into the process. Crowdsourcing has significant potential to transform the education space by enhancing existing methodologies and offering innovative possibilities to develop new pedagogical techniques. This offers benefits for practitioners, institutions, students and participants. Drawing on theory and best practice, illustrated with a wide range of the examples and cases, Crowdsourcing for Innovation in Higher Education offers invaluable guidance and will be of interest to researchers, academics, policymakers, and students in the fields of higher education, development studies, organizational studies, management science and knowledge management.

The reflection on university management is based on the question about the shape of universities of the future. Civic, responsible, sustainable, virtual, digital, and many other universities can be mentioned among the concepts present in the literature. All these names describe an important distinctive feature of a university, which will gain more and more importance in the future. However, given the fundamental importance of the radical change taking place, it seems that the most appropriate name, reflecting the essence of the emerging new formation, is "digital university." This is because of the importance of digital transformation, which has been developing for several decades, bringing deep and multidirectional changes in the areas of technology, economy, society, and culture. It is a disruptive civilizational transition and, although stretched over many decades, it is revolutionary in nature, significantly changing our lives in the Anthropocene.The book has three cognitive and pragmatic objectives: to provide a new perspective on the changing academic organization and management; to reflect on higher education management concepts and methods; and to present an overview of university management, governance, and leadership, useful from the perspective of academic managers, and other stakeholders.The Open Access version of this book, available at www.taylorfrancis. com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

The reflection on university management is based on the question about the shape of universities of the future. Civic, responsible, sustainable, virtual, digital, and many other universities can be mentioned among the concepts present in the literature. All these names describe an important distinctive feature of a university, which will gain more and more importance in the future. However, given the fundamental importance of the radical change taking place, it seems that the most appropriate name, reflecting the essence of the emerging new formation, is "digital university." This is because of the importance of digital transformation, which has been developing for several decades, bringing deep and multidirectional changes in the areas of technology, economy, society, and culture. It is a disruptive civilizational transition and, although stretched over many decades, it is revolutionary in nature, significantly changing our lives in the Anthropocene.The book has three cognitive and pragmatic objectives: to provide a new perspective on the changing academic organization and management; to reflect on higher education management concepts and methods; and to present an overview of university management, governance, and leadership, useful from the perspective of academic managers, and other stakeholders.The Open Access version of this book, available at www.taylorfrancis. com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

In an era marked by increasing globalization, international competition, digitalization, and social and cultural changes, higher education institutions (HEIs) play a pivotal role in establishing the knowledge-based economy of each country, which is perceived as its soft power. The need to explore and highlight the specificity of human resource management (HRM) practices in higher education institutions has become urgent and evident. This book provides new theoretical and practical insights into HRM in HEIs. A profound analysis of the global literature clearly exposes that human resource practices are often applied in academia as single solutions rather than as a systematic approach to planning, attracting, motivating, developing, and retaining scientists. The global trends in academia, such as the need for branding and positioning in higher education ranking systems, growing retention and brain circulation between academia and business, diversity in academia, and the digitalization of teaching, have resulted in challenges such as de-recruitment, academic burnout and ill-being, and technostress, which are also addressed in this book.

In an era marked by increasing globalization, international competition, digitalization, and social and cultural changes, higher education institutions (HEIs) play a pivotal role in establishing the knowledge-based economy of each country, which is perceived as its soft power. The need to explore and highlight the specificity of human resource management (HRM) practices in higher education institutions has become urgent and evident. This book provides new theoretical and practical insights into HRM in HEIs. A profound analysis of the global literature clearly exposes that human resource practices are often applied in academia as single solutions rather than as a systematic approach to planning, attracting, motivating, developing, and retaining scientists. The global trends in academia, such as the need for branding and positioning in higher education ranking systems, growing retention and brain circulation between academia and business, diversity in academia, and the digitalization of teaching, have resulted in challenges such as de-recruitment, academic burnout and ill-being, and technostress, which are also addressed in this book.

Philosophy and Leadership is an ambitious exploration of leadership's philosophical underpinnings from antiquity to the AI-driven future. The book journeys through history, gleaning insights from eminent philosophers and contextualizing their teachings to leadership.The book's foundational premise lies in the symbiosis of philosophy and leadership. Philosophy provides the "why" that drives the practices and decisions in leadership. This intricate connection is unfolded from the teachings of Confucius on virtue and ethics to the contemporary dialogues of Judith Butler on leadership identity. The book also delves into the evolution of leadership concepts through various eras—medieval times highlighting religious and scholastic perspectives, the Renaissance juxtaposing Machiavellian pragmatism with More's utopian ideals, and the Enlightenment era underscoring the importance of duty, skepticism, and rationality. An exciting aspect of the narrative is the amalgamation of evolution and leadership. By drawing parallels between Darwin's natural selection and leadership dynamics or Bergson's vitalism and intuitive leadership, the authors present a merger of biological evolution with leadership's ever-evolving paradigms. Finally, the concluding chapters reside in envisioning the future and reflect upon the impending synergy between AI and leadership. They emphasize the importance of amalgamating philosophical wisdom with the promises and challenges brought about by AI.The book will guide readers from the philosophical epochs of yore to the AI-predicted leadership paradigms of the future. By intertwining the enduring wisdom of philosophers with the dynamic nature of leadership, this book serves as a beacon for anyone aspiring to lead in any era.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Philosophy and Leadership is an ambitious exploration of leadership's philosophical underpinnings from antiquity to the AI-driven future. The book journeys through history, gleaning insights from eminent philosophers and contextualizing their teachings to leadership.The book's foundational premise lies in the symbiosis of philosophy and leadership. Philosophy provides the "why" that drives the practices and decisions in leadership. This intricate connection is unfolded from the teachings of Confucius on virtue and ethics to the contemporary dialogues of Judith Butler on leadership identity. The book also delves into the evolution of leadership concepts through various eras—medieval times highlighting religious and scholastic perspectives, the Renaissance juxtaposing Machiavellian pragmatism with More's utopian ideals, and the Enlightenment era underscoring the importance of duty, skepticism, and rationality. An exciting aspect of the narrative is the amalgamation of evolution and leadership. By drawing parallels between Darwin's natural selection and leadership dynamics or Bergson's vitalism and intuitive leadership, the authors present a merger of biological evolution with leadership's ever-evolving paradigms. Finally, the concluding chapters reside in envisioning the future and reflect upon the impending synergy between AI and leadership. They emphasize the importance of amalgamating philosophical wisdom with the promises and challenges brought about by AI.The book will guide readers from the philosophical epochs of yore to the AI-predicted leadership paradigms of the future. By intertwining the enduring wisdom of philosophers with the dynamic nature of leadership, this book serves as a beacon for anyone aspiring to lead in any era.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Paradigm Shifts in Management Theory is an illuminating exploration of the evolving landscape of management science. This book goes beyond the surface, delving into profound insights and perspectives that redefine traditional paradigms.Through rigorous analysis and reflective narratives, each chapter unveils the transformative shifts shaping organizational leadership, offering a comprehensive understanding of key concepts and methodologies. From classical principles to emerging paradigms, elucidating the future of organizational leadership, readers will gain invaluable insights through empirical evidence and theoretical explorations, fostering a nuanced comprehension of practical applications. Advanced students, researchers, and practitioners will find that this book equips readers with essential knowledge to navigate the complexities of modern management science, fostering critical thinking and innovative approaches in real-world scenarios. Practitioners in organizational leadership benefit from practical insights and innovative perspectives, enhancing strategic decision-making and competitive advantage. Additionally, policymakers and interdisciplinary scholars exploring social phenomena find value in the interdisciplinary exchange facilitated by paradigm shifts. Embracing these shifts is crucial for advancing management science, ensuring its relevance and effectiveness in addressing contemporary challenges.Catering to a diverse audience within academia and professional settings, it serves students and researchers in management studies, offering a robust foundation in theoretical frameworks and research methodologies.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.

This innovative book argues that effective leadership requires partnering human creativity, empathy and ethics with AI’s analytical power. Rather than AI replacing leaders, Łukasz Sułkowski illustrates how it can augment their capabilities by automating routine tasks to allow leaders to focus on vision, innovation and interpersonal skills.Chapters interpret classical theories for the AI era, identifying new competencies in data literacy and technological acumen that are needed for AI-integrated leadership. The book examines international case studies across a breadth of sectors, from healthcare to finance, exploring how the rapid adoption of AI in Asia, ethics-focused regulations in Europe and innovation-driven approaches in North America demonstrate how cultural and policy contexts shape leadership strategies. Looking to the future, Sułkowski addresses issues of bias, fairness, transparency and accountability to ensure that the adoption of this technology remains aligned with human values. AI Leadership is of great benefit to scholars and students of business and management, organizational studies and technology and innovation. Business owners and consultants will also benefit from its practical guidance, such as readiness assessments, AI adoption roadmaps and decision-support tools provided to help integrate AI into organizations.

This book invites readers on an intellectual journey where the great minds of philosophy intersect with contemporary organizational challenges.With classical and modern philosophical thought as its backbone, Philosophy and Management: Great Minds and Organizational Ideas demonstrates that the most renowned thinkers in human history, such as Aristotle, Confucius and Nietzsche, provide timeless wisdom for navigating the complexity of today’s business environments. Combining theoretical insights with practical applications, this book presents philosophical frameworks as robust foundations for decision-making, conflict resolution and leadership strategies. It explores crucial areas such as strategic management, human resources, ethics, corporate governance and innovation, challenging readers to explore management from a reflective and ethical perspective, and shows how philosophy equips leaders to build resilient and morally responsible organizations, which are essential in an age dominated by technological advancement and rapid societal changes.The book fills a significant gap in management literature, which often lacks deep philosophical reflection on organizational practices. It draws on ancient, modern and postmodern thought, connecting these insights to current management theories, thus, making it an invaluable resource for both practitioners and scholars.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.

Epistemology and Methodology of Research in the AI Age maps how artificial intelligence (AI), digital platforms, and big data reshape the foundations of social science and management research. It connects epistemology and research design to the practical choices researchers now face, from defining questions in data-rich environments to handling algorithmic bias and ethical risk.Key features include:• Explains how research paradigms and epistemological assumptions shape digital and AI-enabled inquiry.• Translates validity, reliability, and ethics into concrete decisions about sampling, online data, platform effects, and transparency.• Shows how to frame research questions and hypotheses when automation and analytics influence what counts as evidence.• Guides the literature review in the AI age, including digital search strategies, systematic reviews, and meta-analysis.Written for doctoral students, early-career researchers, and methods instructors, this volume supports dissertation work and methods teaching across sociology, psychology, education, economics, and information science. It also anchors the wider series by setting a shared conceptual and ethical baseline for the volumes that follow.

Research Ethics, Integrity, and Transparency guides researchers through ethics, integrity and transparency when using big data, social media and AI, with practical advice on consent, GDPR, bias and open science.Bringing research ethics into the realities of digital data, this volume helps readers plan, run and publish studies that can stand up to scrutiny. It reframes ethics and transparency as enabling conditions for trustworthy work, not a bureaucratic afterthought, and shows how to translate principles into defensible choices across the full research workflow.Key features include:· Guidance on informed consent and dynamic consent for online and platform-based research· GDPR-aware approaches to data protection, governance, anonymisation, and documentation· Practical routes to transparency, preregistration, data sharing, and reproducibility that still protect confidentiality· Responsible use of AI in research, including disclosure, bias checks, and avoidance of “black box” practice· A clear view of algorithmic accountability and the regulatory landscape shaping research practiceWritten for PhD candidates and early-career researchers across the social sciences and management, this book also supports supervisors, methods instructors, research ethics committees and research offices who need an up-to-date reference for integrity and transparency in the digital age.

Digital Quantitative, Qualitative, and Mixed Methodologies in Social Sciences brings together quantitative analysis, qualitative inquiry, and mixed methods for the digital era. This volume shows how to design robust social science research using online surveys, platform data, digital traces, and computational tools, while keeping theory, context, and interpretation in view.Key features include:• frameworks to plan studies that use online surveys, platform data, and digital traces• coverage of digital quantitative methods, digital qualitative methods such as digital ethnography, and mixed-methods integration• worked examples that connect statistical tools with interpretive analysis, including ways to combine survey results with social media analytics and qualitative coding software• guidance on data quality, privacy, research ethics, transparency, and reproducible reporting.Designed for doctoral students, early-career researchers, and applied researchers across sociology, psychology, education, public policy, communication, and management, it supports graduate methods teaching and real research projects in data-rich digital settings.

Digital Quantitative, Qualitative, and Mixed Methodologies in Social Sciences brings together quantitative analysis, qualitative inquiry, and mixed methods for the digital era. This volume shows how to design robust social science research using online surveys, platform data, digital traces, and computational tools, while keeping theory, context, and interpretation in view.Key features include:• frameworks to plan studies that use online surveys, platform data, and digital traces• coverage of digital quantitative methods, digital qualitative methods such as digital ethnography, and mixed-methods integration• worked examples that connect statistical tools with interpretive analysis, including ways to combine survey results with social media analytics and qualitative coding software• guidance on data quality, privacy, research ethics, transparency, and reproducible reporting.Designed for doctoral students, early-career researchers, and applied researchers across sociology, psychology, education, public policy, communication, and management, it supports graduate methods teaching and real research projects in data-rich digital settings.

Quantitative Methods of Research in Digital Landscape equips social science and management researchers to design, run, and interpret statistical analyses for today’s data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modelling and factor analysis, with a clear focus on transparency and responsible inference.Key features include:· A structured pathway from statistical foundations to advanced quantitative techniques used across digital social research.· Practical guidance on modelling and inference, including linear and logistic regression, multivariate methods, and factor analysis.· Coverage of common pitfalls in interpretation and reporting, including p-values, uncertainty, and claims that overreach the evidence.· An open science and reproducibility lens, with emphasis on clear documentation of data preparation and analytic choices.· A platform-neutral approach that supports readers working across software packages and coding environments.Written for PhD and Masters students, advanced undergraduates, early-career researchers, and practitioners who work with social data in fields such as sociology, management, communication, education, public policy, and media studies, it supports methods training and applied research projects in the digital age.

Quantitative Methods of Research in Digital Landscape equips social science and management researchers to design, run, and interpret statistical analyses for today’s data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modelling and factor analysis, with a clear focus on transparency and responsible inference.Key features include:· A structured pathway from statistical foundations to advanced quantitative techniques used across digital social research.· Practical guidance on modelling and inference, including linear and logistic regression, multivariate methods, and factor analysis.· Coverage of common pitfalls in interpretation and reporting, including p-values, uncertainty, and claims that overreach the evidence.· An open science and reproducibility lens, with emphasis on clear documentation of data preparation and analytic choices.· A platform-neutral approach that supports readers working across software packages and coding environments.Written for PhD and Masters students, advanced undergraduates, early-career researchers, and practitioners who work with social data in fields such as sociology, management, communication, education, public policy, and media studies, it supports methods training and applied research projects in the digital age.

Qualitative Methods in Digital Inquiry shows how to design, conduct, and analyse qualitative research in online and technology-rich settings, from virtual ethnography and netnography to visual and arts-based approaches.Key features include:• Clear, step-by-step coverage of core methods such as ethnography, case study research, grounded theory, phenomenology, and discourse analysis, with guidance on adapting each approach to platform-based data and hybrid field sites.• Direct answers to common problems in online fieldwork, including access, consent, anonymisation, and working with large text or platform archives without losing context.• A balanced approach to research tools, including computer-assisted qualitative data analysis software (CAQDAS) and AI support for coding or text analysis, with emphasis on transparency, reflexivity, and research ethics.Written for PhD students, early-career researchers, and instructors across the social sciences and management, the book also supports applied researchers in UX, market research, and organisational development.

Qualitative Methods in Digital Inquiry shows how to design, conduct, and analyse qualitative research in online and technology-rich settings, from virtual ethnography and netnography to visual and arts-based approaches.Key features include:• Clear, step-by-step coverage of core methods such as ethnography, case study research, grounded theory, phenomenology, and discourse analysis, with guidance on adapting each approach to platform-based data and hybrid field sites.• Direct answers to common problems in online fieldwork, including access, consent, anonymisation, and working with large text or platform archives without losing context.• A balanced approach to research tools, including computer-assisted qualitative data analysis software (CAQDAS) and AI support for coding or text analysis, with emphasis on transparency, reflexivity, and research ethics.Written for PhD students, early-career researchers, and instructors across the social sciences and management, the book also supports applied researchers in UX, market research, and organisational development.

Data Sources, Management, and Digital Infrastructure in Social Sciences and Management shows how to move from raw digital data to usable evidence, with practical guidance on data literacy, documentation, platforms, and workflows that support transparency and reproducibility.Key features include:· Strategies for working with diverse digital data sources, from social media and administrative records to geospatial and sensor data· Data governance and research ethics, including the FAIR principles, privacy, consent, and responsible reuse· Metadata and documentation practices that keep datasets interpretable over time, including codebooks and common standards· Clear introductions to data platforms and infrastructure, including repositories, data warehouses and lakes, APIs, and cloud or high-performance computing· Step-by-step approaches to data pipelines (ETL), quality assurance, provenance, version control, and open science data sharingWritten for postgraduate students and early-career researchers in the social sciences and management, the volume also supports instructors and research support staff who need a grounded, course-ready guide to modern data practices, including links to evidence-based management and real-world research settings.

Data Sources, Management, and Digital Infrastructure in Social Sciences and Management shows how to move from raw digital data to usable evidence, with practical guidance on data literacy, documentation, platforms, and workflows that support transparency and reproducibility.Key features include:· Strategies for working with diverse digital data sources, from social media and administrative records to geospatial and sensor data· Data governance and research ethics, including the FAIR principles, privacy, consent, and responsible reuse· Metadata and documentation practices that keep datasets interpretable over time, including codebooks and common standards· Clear introductions to data platforms and infrastructure, including repositories, data warehouses and lakes, APIs, and cloud or high-performance computing· Step-by-step approaches to data pipelines (ETL), quality assurance, provenance, version control, and open science data sharingWritten for postgraduate students and early-career researchers in the social sciences and management, the volume also supports instructors and research support staff who need a grounded, course-ready guide to modern data practices, including links to evidence-based management and real-world research settings.

AI in Social Sciences Research explains how artificial intelligence is reshaping social inquiry, from data collection and research design through analysis, interpretation, and theory-building. Treating AI as both a toolkit and a methodological shift, the volume offers a clear route into machine learning, natural language processing, simulation, and generative AI for social researchers, while keeping ethics, bias, transparency, and interpretability in view.Key features include:· Practical guidance on integrating AI into social science research workflows, without losing theoretical and contextual judgement· Coverage of core techniques, including machine learning for prediction and pattern discovery, and NLP for large-scale textual and qualitative data· Discussion of explainability and “black box” risks, with approaches for interpretability and responsible use· Cross-disciplinary examples spanning sociology, psychology, anthropology, political science, economics, and management· A critical account of research integrity issues: data quality, bias, privacy, accountability, and the limits of automationDesigned for postgraduate students, early-career researchers, and instructors teaching digital and computational social science methods, the book supports readers who want to use AI with methodological care, not just technical speed.

AI in Social Sciences Research explains how artificial intelligence is reshaping social inquiry, from data collection and research design through analysis, interpretation, and theory-building. Treating AI as both a toolkit and a methodological shift, the volume offers a clear route into machine learning, natural language processing, simulation, and generative AI for social researchers, while keeping ethics, bias, transparency, and interpretability in view.Key features include:· Practical guidance on integrating AI into social science research workflows, without losing theoretical and contextual judgement· Coverage of core techniques, including machine learning for prediction and pattern discovery, and NLP for large-scale textual and qualitative data· Discussion of explainability and “black box” risks, with approaches for interpretability and responsible use· Cross-disciplinary examples spanning sociology, psychology, anthropology, political science, economics, and management· A critical account of research integrity issues: data quality, bias, privacy, accountability, and the limits of automationDesigned for postgraduate students, early-career researchers, and instructors teaching digital and computational social science methods, the book supports readers who want to use AI with methodological care, not just technical speed.

Academic Writing, Visualization, Presentation, and Publishing of Research is a comprehensive guide to scholarly communication in a digital research environment. Written for PhD candidates and early-career researchers in the social sciences and management, it shows how to write with clarity, visualise data with accuracy, present findings with confidence, and navigate publishing with integrity.Rather than treating these as separate skills, the book links them as one workflow: how arguments travel from a dissertation chapter to a figure, from a slide deck to a manuscript, and into peer review and open access publication. It also addresses the realities of modern research communication, including collaborative writing platforms, virtual conferences, preprints, and responsible use of AI tools.Key features include:· Step-by-step guidance on academic writing across genres, including theses, journal articles, and book chapters· Practical support for literature reviews and systematic literature reviews (SLRs), including search strategy, screening, synthesis, and reporting· Principles and best practice for data visualisation, including accessibility, chart selection, and avoiding misleading graphics· A tool-aware overview of visualisation and writing software, from spreadsheets to R and Python, plus collaboration and reference management tools· Guidance on research presentations across formats, including conferences, seminars, posters, and doctoral defences, with advice for virtual delivery· A clear roadmap through publishing, peer review, open access options, and responding to reviewer feedbackWritten for PhD candidates, early-career researchers, and methods instructors in the social sciences and management, this volume also supports research support staff and supervisors who need a course-ready reference on communicating research well across written, visual, and spoken formats.

Academic Writing, Visualization, Presentation, and Publishing of Research is a comprehensive guide to scholarly communication in a digital research environment. Written for PhD candidates and early-career researchers in the social sciences and management, it shows how to write with clarity, visualise data with accuracy, present findings with confidence, and navigate publishing with integrity.Rather than treating these as separate skills, the book links them as one workflow: how arguments travel from a dissertation chapter to a figure, from a slide deck to a manuscript, and into peer review and open access publication. It also addresses the realities of modern research communication, including collaborative writing platforms, virtual conferences, preprints, and responsible use of AI tools.Key features include:· Step-by-step guidance on academic writing across genres, including theses, journal articles, and book chapters· Practical support for literature reviews and systematic literature reviews (SLRs), including search strategy, screening, synthesis, and reporting· Principles and best practice for data visualisation, including accessibility, chart selection, and avoiding misleading graphics· A tool-aware overview of visualisation and writing software, from spreadsheets to R and Python, plus collaboration and reference management tools· Guidance on research presentations across formats, including conferences, seminars, posters, and doctoral defences, with advice for virtual delivery· A clear roadmap through publishing, peer review, open access options, and responding to reviewer feedbackWritten for PhD candidates, early-career researchers, and methods instructors in the social sciences and management, this volume also supports research support staff and supervisors who need a course-ready reference on communicating research well across written, visual, and spoken formats.

This volume of Advanced Series in Management offers cutting-edge research into international migration in Europe.Living and working in a host country is challenging both for the host country (for its institutions, organizations and local people) as well as for the incoming migrants. Therefore, integration activities are essential for easing the transition. The purpose of this book is to examine various practices of integrating migrants in European countries from national, organizational and individual perspectives.This publication will be valuable to researchers in the field, as well as for entrepreneurs, international corporations employing from abroad, trainers preparing employees to work in multicultural teams, as well as for investors who plan to expand their business into foreign markets.

To do so, it integrates studies on the organizational sciences, cross-cultural management, positive psychology and sociology within a single comprehensive framework. They add inter-organizational, institutional and critical perspectives to the analysis within the framework of multinationals and complex, hybrid cultural environments.

To do so, it integrates studies on the organizational sciences, cross-cultural management, positive psychology and sociology within a single comprehensive framework. They add inter-organizational, institutional and critical perspectives to the analysis within the framework of multinationals and complex, hybrid cultural environments.

The aim of this book is to outline the neoevolutionary paradigm emerging in the social sciences and indicate possibilities for its application in the management sciences. This monograph has an interdisciplinary nature and refers to a theory that has been formed on the basis of various social and natural disciplines, including management, psychology, sociology, anthropology, biology, epistemology and cognitivism. The work is targeted at researchers who specialise in management and other social sciences, and for whom the neoevolutionary paradigm can be a valuable point of reference. This book presents the application of evolutionary issues to the social sciences, and especially to the analysis of issues related to the management sciences. The presented framework of paradigm, methodology and research issues, leads to a proposal to distinguish a new research field called ‘evolutionary management’. The issues of evolutionary management would be by definition interdisciplinary; a combination of organising and management with evolutionary psychology and behavioural economics. The paradigm of evolutionary management would be coherent with the neoevolutionary conception of the description of human behaviour. This requires assumption of numerous postulates related to basing the management sciences on the basic evolutionary theories of human behaviour.