The aim of this article is to complement research on transformations towards sustainability by drawing upon the innovation systems (IS) framework. The IS framework already serves as a suitable and influential basis for research on processes of technological innovation and economic change. We argue that improving the capacity of an IS framework for dealing with wicked problems and the normative complexity of sustainability requires a fundamental paradigm shift because in the current IS paradigm innovations are considered as per se desirable and in mostly technological terms. Therefore, we call for IS dedicated to transformations towards sustainability by opening up for systemic innovations beyond the technological dimension and by acknowledging that stakeholders have conflicting visions, interests, norms, and expectations with regard to sustainability goals. Taking the normative dimension of transformations towards sustainability seriously thus requires more explicit and integrative research on directionality, legitimacy, responsibility, and their interrelation in IS. The article concludes by proposing suggestions for future research based on IS-related approaches that can serve as building blocks for an IS framework capable of incorporating legitimate goal-orientation for transformative innovation by and for society.

The concept of identity was introduced into the neoclassical utility maximising framework by Akerlof and Kranton in an analysis which draws directly from social psychology's social identity approach and self-categorisation theory. This paper examines their analysis, and compares the social identity approach and an alternative social psychology identity framework called the sociological approach to identity. Using this comparison, the paper argues that their treating identity as an argument in the utility function leaves unaddressed how individuals' different social identities are related. The paper suggests a framework for addressing this issue by embedding their utility function in a personal identity objective function. The general context for the paper is the Akerlof–Kranton analysis as an example of ‘recent economics’ defined as a collection of new competing research programmes that make departures from neoclassical economics.

We study the projected impact of automation on employment in the forthcoming decade, both at the macro-level and in actual (types of) sectors. Hereto, we unite an evolutionary economic model of multisectoral structural change with labor economic theory. We thus get a comprehensive framework of how displacement of labor in sectors of application is compensated by intra- and intersectoral countervailing effects and notably mopped up by newly created, labor-intensive sectors. We use several reputable datasets with expert projections on employment in occupations affected by automation (and notably by the introduction of robotics and AI) to pinpoint which and how sectors and occupations face employment shifts. This reveals how potential job loss due to automation in “applying” sectors is counterbalanced by job creation in “making” sectors as well in complementary and quaternary, spillover sectors. Finally, we study several macro-level scenarios on employment and find that mankind is facing “the usual structural change” rather than the “end of work”. We provide recommendations on policy instruments that enhance the dynamic efficiency of structural change.

Innovation networks have become a persistent organisational phenomenon in industrial innovation processes. However, in economics they were considered in the first place only as a temporary hybrid phenomenon between markets and a hierarchical organisation within a single firm. The main focus of traditional neo‐classical analysis simply was on cost reduction of R&D within a network. Only with the coming up of evolutionary economics with its prevailing knowledge orientation, learning and synergistic partnering also move to the centre of interest. Without a consideration of the roles strong uncertainty, heterogeneity as well as the historical character of time play in innovation, networks cannot be explained as a self‐organisational persistent phenomenon. The present paper brings together different strands of the new theory of innovation and develops an evolutionary theory of innovation networks.