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To meet their ambitious targets for a circular economy, multinationals need to speed up their innovation efforts. This requires experimentation capability. But it is not clear what this capability entails, and how companies can build it. The purpose of this paper is to give companies guidance on how they might develop experimentation capability for the circular economy.

We conduct in-depth interviews with innovators in frontrunner multinationals, H&M, IKEA and Philips. We use the Gioia method to analyse our data.

This article identifies novel institutional, strategic, and operational actions that build experimentation capability for a circular economy.

The identified actions help innovation managers experiment and speed up their innovation efforts for a circular economy.

To reverse environmental degradation, multinationals need to transform their dominant linear take-make-waste business models. This research provides actions that help them organize this transformation.

This article is based on extensive research with leading multinationals and reveals novel insights on how to innovate for a circular economy.

This paper aims to explore how digital technologies have forced small- to medium-sized enterprises (SMEs) to reconsider and experiment with their business models (BMs) and how this contributes to their innovativeness and performance.

An empirical study has been conducted on 338 European SMEs actively using social media and big data to innovate their BMs. Four in-depth case studies of companies involved in BM innovation have also been carried out.

Findings show that the use of social media and big data in BMI is mainly driven by strategic and innovation-related internal motives. External technology turbulence plays a role too. BMI driven by social media and big data has a positive impact on business performance. Analysis of the case studies shows that BM is driven by big data rather than by social media.

Research into big data- and social media-driven BMs needs more insight into how components are affected and how SMEs are experimenting with adjusting their BMs, specifically in terms of human and organizational factors.

Findings of this study can be used by managers and top-level executives to better understand how firms experiment with BMI, what affects business model components and how implementation might affect BMI performance.

This paper is one of the first research contributions to analyse the impact of digitalization, specifically the impact of social media and big data on a large number of European SMEs.

This study aims to investigate how configurations of boundary objects (BOs) support innovation teams in developing innovative product concepts. Specifically, it explores the effectiveness of different artefact configurations in facilitating collaboration and bridging knowledge boundaries during the concept development process.

The research is based on data from ten undergraduate innovation teams working with an industry partner in a creative industry. Six categories of BOs are identified, which serve as tools for collaboration. The study applies fsQCA (fuzzy-set qualitative comparative analysis) to analyse the configurations employed by the teams to bridge knowledge boundaries and support the development of innovative product concepts.

The findings of the study reveal two distinct groups of configurations: product envisioning and product design. The configurations within the “product envisioning” group support the activities of visioning and pivoting, enabling teams to innovate the product concept by altering the product vision. On the other hand, the configurations within the “product design” group facilitate experimenting, modelling and prototyping, allowing teams to design the attributes of the innovative product concept while maintaining the product vision.

This research contributes to the field of innovation by providing insights into the role of BOs and their configurations in supporting innovation teams during concept development. The results suggest that configurations of “product envisioning” support bridging semantic knowledge boundaries, while configurations within “product design” bridge pragmatic knowledge boundaries. This understanding contributes to the broader field of knowledge integration and innovation in design contexts.

The article explores what forms of disruption are prioritized by top executives of large manufacturing companies in Finland and what strategies they consider appropriate for the management of disruptive threats and opportunities.

The empirical study was based on interviews with top executives in some of Finland's largest manufacturing companies.

Based on the data, we identify exploitative and explorative strategies in four dimensions that executives consider important in anticipating and responding to disruptions: internal development efforts, stance on new entrants, ecosystems and institutional change. Due to the presence of multiple potential disruptions, which often generate conflicting demands, executives have to consider them simultaneously and balance between them when making strategic decisions. They therefore do not necessarily have a specific response strategy, but their aim is to develop their companies' capabilities so that they are well-placed to face the future with confidence.

The findings indicate that the executives envision a disruption landscape that is more complex than typically described in the literature. In addition, it answers the call for a more systematic understanding of incumbents' response strategies by linking different disciplinary views with well-grounded empirical data.

Mastering innovation in highly regulated markets might require companies to overcome significant barriers. Rules, laws and limitations on social, economic and institutional dimensions can hinder the ability of a company to transfer knowledge within and across organizational boundaries. However, as recent research in innovation management increasingly advocates user involvement and early understanding of user needs as best practices, the inability to freely interact with customers due to highly regulated market restrictions can hinder the company’s capability to innovate. Hence, this paper aims to shed light on how an emerging managerial approach, such as Design Sprint, can support companies operating in highly regulated markets to overcome user involvement limitations and boost human-centered innovation.

This paper sheds light on how to boost innovation in a highly regulated market by leveraging an in-depth case study. The study investigates the use of the Design Sprint approach adopted by the pharmaceutical multinational Johnson & Johnson to revise the way its R&D department orchestrates the new product development process, overcoming the user involvement challenges of highly regulated markets.

In analyzing six different projects undertaken in the past two years, the findings illustrate three microfoundational dimensions of the Design Sprint approach in highly regulated markets, the so-called 3T model: team, time and tools. Indeed, deploying the Design Sprint in a highly regulated market has proven that being able to experiment in the early stages, building rough prototypes in real-time and openly collaborating with partners is crucial to boost innovation and anticipate constraints.

The paper sheds light on the Design Sprint approach by initially grounding an emerging managerial approach on organizational and management theory, leveraging the lens of microfoundations. In doing so, this study suggests how Design Sprint is based on the pillars of experimentation, knowledge transfer and co-creation usually neglected in highly regulated markets where user involvement is challenging. Finally, this study discloses the importance of using a design-based methodology in fostering innovation in highly regulated markets.

Within digital innovation, there are two significant consequences of the pervasiveness of digital technology: (1) the increasing connectivity is enabling a wider reach and scope of innovation structures, such as innovation networks and (2) the unprecedented availability of digital data is creating new opportunities for innovation. Accordingly, there is a growing domain for studying data-driven innovation (DDI), especially in contemporary contexts of innovation networks. The purpose of this study is to explore how DDI processes take form in a specific type of innovation networks, namely federated networks.

A multiple case study design is applied in this paper. We draw our analysis from data collected over six months from four cases of DDI. The within-analysis is aimed at constructing the DDI process instance in each case, while the crosscase analysis focuses on pattern matching and cross-case synthesis of common and unique characteristics in the constructed processes.

Evidence from the crosscase analysis suggests that the widely accepted four-phase digital innovation process (including discovery, development, diffusion and post-diffusion) does not account for the explorative nature of data analytics and DDI. We propose an extended process comprising an explicit exploration phase before development, where refinement of the innovation concept and exploring social relationships are essential. Our analysis also suggests two modes of DDI: (1) asynchronous, i.e. data acquired before development and (2) synchronous, i.e. data acquired after (or during) development. We discuss the implications of these modes on the DDI process and the participants in the innovation network.

The paper proposes an extended version of the digital innovation process that is more specifically suited for DDI. We also provide an early explanation to the variation in DDI process complexities by highlighting the different modes of DDI processes. To the best of our knowledge, this is the first empirical investigation of DDI following the process from early stages of discovery till postdiffusion.