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The Grand Challenges for Social Work (GCSW) focuses on big, important and compelling problems for all of American society. Sponsored by the American Academy of Social Work and Social Welfare, the 12 Grand Challenges address issues of healthy youth development, the health gap, family violence, long and productive lives, social isolation, homelessness, changing climate environments, technology for social good, smart decarceration, economic inequity, financial capacity, and equal opportunity and justice. GCSW is designed to promote scientific and transformative innovation in social work, engage the social work profession in strengthening the ties among social work organizations, foster transdisciplinary research, create greater acknowledgement of social work science within the discipline and by other and related disciplines, and expand the student pipeline into the social work profession.

This chapter describes the evolution of social work science in relationship to the development of the Grand Challenges for Social Work Initiative. The two initiatives, which took root in the field in close to the same period, created a mutually supportive, synergistic environment that benefitted both. Social work science, grounded in critical realism, embraces methodological approaches supportive of the fundamental principles of the social work profession and contributes to both the scientific identity needed for the stewards of the profession of social work and the scientific pipeline for the Grand Challenges for Social Work. An initiative of the American Academy of Social Work and Social Welfare, the Grand Challenges for Social Work delineate bold innovations and collective action powered by proven and evolving scientific interventions to address critical social issues facing society today. This chapter discusses how this work helps to both develop and derive support from social work science.

Society faces significant grand challenges—demographic, economic, and environmental. This chapter explores the role that services might play in helping address these grand challenges. The chapter begins by reviewing traditional reasons why manufacturing firms are making a shift to services, identifying five options that firms appears to be pursuing. Next the chapter then turns to the future, looking at the illustrative challenges that society faces—most notably demographic, economic, and environmental—and explores the implications of these challenges for the phenomenon of servitization. Finally, the chapter combines the five servitization options with the previously discussed societal challenges, offering some thoughts on what the future might hold.

People use their cognitive skills to solve a wide range of problems whereas computers solve only a limited number of specific problems. A goal of artificial intelligence (AI) is to build on its previous success in specific environments to advance toward the generality of human level intelligence. People are efficient general-purpose learners who can adapt to many situations such as navigating in spatial environments and communicating by using language. To compare human and machine reasoning the AI community has proposed a standard model of the mind. Measuring progress in achieving general AI will require a wide variety of intelligence tests. Grand challenges, such as helping scientists win a Nobel prize, should stimulate development efforts.

This introduction outlines the argument and contribution of The Quest for Professionalism. At the time, early pioneers in management thinking conceived of management as a science-based professional activity that serves the greater good. Today, however, many organizations appear to be managed by people demonstrating anything but professionalism, resulting in mismanagement of risks as well as a one-dimensional focus on short-term results. Therefore, The Quest for Professionalism is about revitalizing this quest. Subsequently, the professionalization quest is defined and conceptualized in terms of a multi-level framework involving (the alignment between) professional purpose, knowledge, behavior, and expectation. This multi-level framework also serves to view the quest for professionalism in management as a grand societal challenge, on par with, for example, climate change. Finally, four paths for professionalizing management are outlined, and Chapters 1 to 8 are summarized.

Public procurement occurs when public agencies purchase products (goods, services, and systems). The rationale, purpose, and starting point of public procurement should always be to solve societal problems, to satisfy human needs, or to meet global challenges, such as environmental and health problems. This chapter discusses how public procurement can influence the direction and speed of innovation processes, as an instrument of innovation policy operating from the demand side. The chapter focuses on four specific kinds of procurement, namely (1) direct innovation procurement, (2) catalytic innovation procurement, (3) functional regular procurement, and (4) pre-commercial procurement. A conclusion is that functional specification is needed for all four of these different kinds of procurement. Questions addressed are: how can we achieve an increase in the use of innovation-enhancing procurement? What types of procurement initiatives have the potential to influence innovations most? And how can these be designed and implemented?

This chapter comes to grips with the nature of innovation and systems of innovation. It identifies ten specific activities that define systems of innovation. The ten activities are specific elements directly related to the performance of innovation, that collectively shape the way in which innovation takes place in an innovation system. We call this a ‘systems activities approach’, and it is a broad version of the systems of innovation approach. These activities are partly performed by private organizations and partly by public organizations. The theoretical basis for innovation policy proposed in this book is built from the identification of the concrete problems (failures, bottlenecks, weaknesses, etc.) that afflict innovations and their determinants in systems of innovation, including those problems that might be the unintended consequences of policy itself.

The purpose of this chapter is to provide a summary of the main arguments and conclusions in the book, and to highlight its main contributions. Taking the point of departure from the book’s analytical framework, and taking stock of the detailed considerations in its different chapters, this chapter looks into a series of issues related to the design of holistic innovation policy. With this purpose in mind, the chapter summarizes the theoretical foundations of an holistic innovation policy, how policy problems, obstacles, and barriers in innovation systems can be identified, and how policy instruments can be selected. The chapter finishes with a discussion of further avenues for innovation policy and innovation research. This summary chapter can be read independently of the rest of the book.

This chapter introduces the main idea of the book, namely, the theoretical foundations, the problem-oriented approach, and the focus on the instrument choices of an holistic innovation policy. The chapter argues that innovation studies have left unfinished the theoretical foundations for the design of innovation policy. The chapter also argues that a starting point for developing it is the identification of the problems that tend to afflict the performance of innovation systems and the ten determinants of innovation processes. This provides the basis for the choice of innovation policy instruments. The chapter provides a road map of the contents of the book.

This chapter develops the core of the argument regarding the specific assumptions and theoretical propositions about the role and limits of innovation policy. The theoretical basis for the holistic approach to innovation policy proposed in this book is built from a broad version of the systems of innovation approach and the identification of the concrete policy problems that afflict the innovation system, including the unintended consequences of policy. Following from that, the chapter argues that most innovation policies across countries are still partial, not holistic; that innovation policy must be separated from research policy; and that innovation policy-learning can only take place using an analytical model that helps understanding what worked, how, and why.

The purpose of this chapter is to discuss the different types of instruments of innovation policy, to examine how governments and public agencies in different countries and different times have used these instruments differently, to explore the political nature of instrument choice and design (and associated issues), and to elaborate a set of criteria for the selection and design of the instruments in relation to the formulation of holistic innovation policy. The chapter argues that innovation policy instruments must be designed and combined into mixes that address the problems of the innovation system. These mixes are often called ‘policy mixes’, though we prefer the term ‘instrument mix’. The wide combination of instruments into such mixes is what makes innovation policy ‘holistic’.