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This chapter explores a pathway towards achieving a sustainable and inclusive future through the implementation of systems innovation, systems leadership and systems change. The author highlights the importance of understanding complex systems and identifies several models that can be employed to drive systems change, including the iceberg model and multi-level perspective. The author stresses the significance of systems leadership and innovation in creating a sustainable and inclusive future. This means that leaders and managers need to shift their mindset from reductionism to systems thinking. Reductionism views complex systems as a collection of separate parts that can be studied independently. In contrast, systems thinking acknowledges the interconnectedness of all parts and how they influence each other. When they embrace systems thinking, leaders and managers can make systems innovation and drive systems change to achieve sustainable and inclusive growth. Achieving a sustainable and inclusive future requires a collective effort from individuals, organizations and governments. It demands a comprehensive understanding of the interdependencies and interactions within complex systems, as well as a willingness to adopt new ways of thinking and leading. This chapter presents a compelling case for adopting systems innovation, systems leadership and systems change as critical components in building a sustainable and inclusive future.

Innovation policy and innovation systems undoubtedly play a crucial role in shaping the path of economic development of contemporary economies. A particularly interesting context for studying the evolution of this area is offered by post-transition economies which had to undergo fundamental structural changes and face the global competition where the advances in knowledge and technological progress ultimately decide between success or failure.

The chapter aims to portray and evaluate the key developments in the innovation policy and national innovation system of Poland – one of the largest and most successful post-transition economies.

The methodological framework of the study involves a descriptive analysis of the major changes in the regulatory and institutional settings as well as an analysis of statistical data on the crucial dimensions of Poland's innovation policy and innovation system over the period 2000–2021. Additionally, the overall effects of the policy have been assessed using the data from the European Innovation Scoreboard (over 2015–2022) and the Global Innovation Index (over 2008–2022).

The findings suggest that the significant changes in Poland's innovation policy and innovation system frameworks introduced since the mid-2000s have resulted in a dynamic increase in the intensity of R&D efforts, especially in the business enterprise sector, allowing to narrow the structural gaps dividing the country from more advanced economies and markedly improve its overall research and innovative performance. A key role in this process has been played by the direct and indirect government support for innovative activities.

This chapter first describes the essential aspects of a currently changing world, which is characterised by digitalisation, globalisation and politically unstable situations. Based on this transformation context, key concepts such as leadership, innovation, innovation leadership and leadership competences are introduced, along with a new definition and framework for innovation leadership. The chapter discusses the distinction between innovation leadership and innovation management, and the connecting lines between these two concepts. The innovation leadership framework is described and related to the individual contributions of the authors in the book. The chapter frames these contributions along the dimensions of self-leadership, team leadership, organisational leadership and ecosystem leadership.

The pandemic has brought to light the importance of quickly adopting new technologies and building resilient organisations. Also, the Sustainable Development Goals (SDGs) can be addressed in large part through technological innovations. The development of smart systems which are linked with the Internet of Things (IoT) can create different opportunities to strategically face the barriers linked with the SDGs and make sure that there is an environmentally sustainable, equitable and healthy society. This study has utilised secondary and qualitative data and has adopted the interpretative and deductive approaches. It has given significance to several aspects of the SDGs and has linked them with digital technology such as accessibility to safe and clean portable water, production of sustainable food along with the generation of green energy and its utilisation. This study has evaluated the advantages of digitalisation so that it can catalyse the transition towards SDGs and improve the health of the citizens by giving digital accessibility specifically to the underserved community. The research has selected the most essential themes which are linked to the context of SDGs and has deeply evaluated a lot of information obtained from authentic secondary resources. At last, it provides a conclusion and recommendations where it has suggested several initiatives which could be made for enhancing the overall scenario and has also disguised the limitations that were identified while completing the study.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

This chapter reviews the key findings and innovation leadership insights from this book, as well as pointing out directions for future research. We find a series of learning insights for people engaged in innovation leadership, at the distinct levels of self-leadership, team leadership, organisational leadership, and ecosystem leadership. We also find commonalities across these levels, as well as differences that reflect the complexity of these different leadership arenas. Leadership practice that orchestrates contributions from diverse viewpoints, seeing itself as with the group, rather than above it, is most likely to help turn ideas into value in repeatable ways. We also find evidence that mindset, skills, and behaviours are all important in the make-up of competencies. We point to the requirement for further research at all four levels, to bring further insights in what is still an emerging field; as well as a need for more research into competency development for innovation leadership; and we advocate a research approach that emphasises relational leadership, acknowledging that most leadership practice is shared across people.

Purpose: Innovation is a multi-dimensional phenomenon influenced at the organisational level by internal and external factors that can determine how innovative an organisation can be, determining a firm’s business performance. This chapter measures and predicts how innovative a company can be, considering key internal factors using modern data analytics/science.

Need for Study: The increasing challenge of modern business operations is affected by how quickly, sustainably, effectively, and efficiently companies can innovate to mitigate the dynamic challenges of current business environments and evolving customer needs. The ability to predict, measure, and manage innovation becomes necessary to ensure that businesses are fit for purpose.

Methodology: A model was designed following the study hypotheses and statistically tested. A historical data sample from the OECD global industry dataset for eight years was used for the analysis. The ordinary least square method was used to test for model fit. Also, in machine learning engineering, predictive analysis using the multivariate linear regression analysis method was carried out.

Findings: The results support the hypotheses that an organisation’s capacity to be innovative can be measured and predicted, and it is influenced by a good number of internal factors or independent variables at various degrees.

Practical Implications: Managers must understand how to measure and predict innovation metrics to manage innovation better, ultimately leading to better business outcomes and performance. Also proposed are new measurement matrices for innovation management: innovation capacity (I_C), business innovation value (BIV), innovation creation factor (ICF), and a practical data-driven innovation management and prediction system.

This chapter presents results from initial studies on personal certifications of innovation management professionals, drawing from a Swedish context. The results capture motivations for, as well as effects from, the certification process. They are discussed from the perspective of how this is relevant for developing and enhancing innovation leadership competencies. Increased knowledge, enhanced professional communication, and strengthened self-confidence related to innovation management were identified as outcomes for individuals pursuing the certifications. Further, this laid the ground for increased visibility, expanded network, and thus more opportunities to influence innovation work. An overarching theme appearing in the study is how a certification can contribute to strengthening the legitimacy of working with innovation management, and thus serve as an enabler for innovation management practice and subsequently innovation leadership. Effects from the certification that may be beneficial for successful innovation leadership include the opportunity for practitioners to articulate their own experiences and competencies, in addition to improving the impact of their efforts utilising innovation terminology. For organisations, knowledge of personal certification can be used both for recruitment and for development of existing personnel and their innovation leadership. Through a longer perspective, it can also contribute to decreasing the dependence on a few specific individuals and instead strengthen the long-term organisational innovation capabilities.

This chapter explores the gap between social expectations and actual sustainability performance in the business world and identifies the root causes of this discrepancy. The author reviews corporate social responsibility (CSR) and sustainability, and their relationship with the Sustainable Development Goals (SDGs). This chapter also compares the connections and differences between the Millennium Development Goals (MDGs) and the SDGs. The author analyzes possible solutions to bridge the gap, including renewing the social contract between businesses, society and institutions. This involves rethinking the role of businesses and institutions in promoting sustainability and creating new systems and structures that incentivize sustainable practices. This chapter concludes by discussing the pathway to a sustainable and inclusive world through systems innovation and change. When embracing a systems thinking approach, individuals and organizations can identify and address the root causes of unsustainability, and create more resilient and sustainable systems that benefit both people and the planet.

Within the last two decades, entrepreneurship education has become institutionalized in Germany. It is offered as a stand-alone program or as part of a business degree, combining academic knowledge, practical skills, and personal development to enhance the entrepreneurial success of university graduates. While entrepreneurship education has experienced similar growth worldwide, its emergence in Germany is closely tied to the country’s political and economic developments. The significance of entrepreneurship education for a thriving entrepreneurial ecosystem and contemporary economic policy has been instrumental in advancing its academic recognition. This chapter provides a historical analysis of the academization of entrepreneurship in Germany. It explores the recursive and often idiosyncratic processes involving state and financial institutions, companies, and universities that have created, respecified, and mutually reinforced a subdiscipline and field of study. Academic entrepreneurship knowledge successively not only became relevant for starting a business but also for employment within the entrepreneurial infrastructure and beyond. This chapter follows a chronological order, highlighting three key stages in the academization of entrepreneurship education. First, the academic, financial, and political roots (I) of entrepreneurship up until the 1970s. Second, it explores the transformation (II) of entrepreneurship into a viable policy alternative and the challenges faced in establishing complementary research and education in higher education institutions during the 1980s. Finally, it sketches the institutionalization (III) of entrepreneurship as a central driver of government economic policy, allowing for the late bloom of entrepreneurship education and research at universities around the turn of the millennium.