International Journal of Innovation Management

Aiming at fostering digital innovation for value creation, incumbent firms have largely adopted dedicated and separated structures for innovation and new business creation. While these structures have been successful in enabling exploration, bringing digital innovations to scale remains a challenge. By employing a qualitative case study of an incumbent bank, with individual projects as the unit of analysis, this study investigates the practices and challenges of transitioning digital innovations developed in separate structures to operationalisation or commercialisation in the core of the organisation, a shift essential for enabling innovations to reach scale. Our key contribution is in presenting a dual business-technology transition-to-scale model defined by the intensity of integration and explaining how innovation managers deviate from this model by adopting coping actions aimed at overcoming innovation and organisational transition challenges. With this, we further highlight the challenges of managing an aligned dual business-technology transition in the context of an incumbent firm undergoing digital transformation.

Digital transformation is confronting traditional industrial companies with the challenge of not only optimising their internal processes, but also establishing entirely new, digital business models (DBM). In some cases, this requires different competences than in traditional business. In the AgilHybrid research project, a model of 20 key competences that are critical to the success of DBM development was developed. These competences can be bundled into the five areas of entrepreneurial capabilities, adaptability, agile capabilities, collaborative capabilities and digital capabilities. In a CATI survey of 200 German industrial companies, the relevance of the selected competences for DBM development was validated. A multivariate regression model reveals that in particular the equipment of the companies with digital competences as well as the use of agile development methods influence the probability that a company offers digital business models successfully on the market. These competences seem to contribute as important enablers to the dynamic capabilities of seizing and transforming in the context of developing new DBM.

Companies now face two challenges in order to remain innovative and competitive. The first is to digitally transform their production, products and services. Second is to address sustainability topics to reduce their global footprint. However, introducing new digital technologies may contradict company’s sustainability goals, for example, introducing a digital technology improves assembly lines, but increases energy consumption. This paper introduces a sustainability-enabled assessment framework for digital technologies (SAFT) supporting companies to choose the best digital technology for them. The SAFT framework assesses digital technologies in terms of sustainability factors as well as crucial aspects such as technology potential, and the fit to the company. The paper concludes with a case study in which the SAFT framework is applied to a company in the construction industry.

In this paper, a responsible business model innovation process is developed based on the existing process of the St. Gallen Business Model Navigator. For its development, a literature review was conducted to formulate requirements that a responsible business model innovation process should fulfil. In particular, the four guiding principles of responsible research and innovation were considered: anticipation, inclusion, reflection, and responsiveness. Based on these findings, several aspects were added to the Business Model Navigator. The focus was on extending the description of a business model along the magic triangle with two additional levels, the environmental one and the social one. Additionally a new step was added in the initiation phase to make the purpose of the process more visible. The results contribute to the current understanding of a responsible business model innovation process, where ethical, social, and environmental aspects are included as core parts of the business model itself.

In product engineering, the development of new innovations is a big challenge due to the high complexity of nowadays systems. Research results are a high-potential input for companies to still advance their technologies and solutions. However, using research as a source of new knowledge and technologies is a non-trivial process that can often be neglected by many companies. The goal of this investigation is to gain and provide an understanding of the specific triggers and reasons for corporate product engineers to use research results as input in their development process. Based on nine semi-structured interviews with experts from different engineering companies, we present a model that explains these reasons, triggers, and situations to use research results. We believe that our model will help to raise the awareness of corporate product engineers to the potential of using research results within their design activities. Furthermore, the outcome of this investigation provides a basis for further research to improve the usability and actual usage of research results in corporate product engineering. Therefore, in our further research, we will use these results for developing decision support for corporate engineers to decide when to look into research.

To support market success, it is important to identify customer needs, and the relation between customer needs and customer purchasing behaviour. This paper provides an overview over existing, already established approaches to determine the relevance of customer benefits. Then, an approach utilising artificial neural networks to correlate the attributes of battery electric vehicles and their sales performance is presented. This approach is discussed in relation to needs expressed by customers in surveys as well as typical user behaviour of passenger cars. It seems that, for example, charging speed of electric vehicles is more important than operational range despite customers regularly expressing operational range as their greatest concern. The presented approach can be integrated into the reference process for developing product profiles and can be coupled with drive system optimisation methods, to consider sales performance alongside vehicle performance, efficiency and costs in the early stage of product generation engineering.

Over the past decade, Open Innovation (OI) literature has extended its scope beyond strictly economical contexts to the context of societal value creation. This has given rise to the notion of distributed knowledge as a driver for sustainable innovation development. Over the past 15 years, the concept of Urban Living Labs (ULLs) has gained popularity to put social OI into practice. Hence, this concept is often applied in urban environments to support transition processes that try to tackle so-called wicked problems. However, a fuzzy understanding of this ULL concept still exists, due to an unclear understanding of its value creation mechanics. Therefore, this paper aims to both conceptualise and gain a better understanding of how ULLs are instrumentalised and create value. This is studied from the perspective of “ecosystem stakeholders” that participate in ULL projects. These insights are obtained through a case study with a multimethod qualitative research approach. The main data sources are a series of 20 semi-structured key-informant interviews, four focus groups, and participatory observation. The results show that the value creation for the participating stakeholders can be summarised in two main clusters: (1) the ULL as a way to build and strengthen the capacities of participating stakeholders; and (2) the ULL as a way to facilitate purpose driven fulfilment in urban transition processes.

Co-creation is recognised in the literature as fostering successful collaboration between academia and industry. Although models do exist, they only contain general principals and provide no details about the process from ideation to value creation. Moreover, they are established based on a consideration that industry submits a problem and the university provides solutions. However, with increasing pressure on researchers for their research to lead to tangible applications, universities must now also turn to firms to pinpoint their needs and practices. The purpose of this paper is to understand how a researcher can implement and manage a co-creation project in collaboration with firms to foster innovation. A university research team in food science and technology, in response to the issue of allergen management in the food service industry, more specifically the use of eggs in pastries, has led a co-creation project with six professional pastry chefs to improve cake formulations, in which eggs were replaced with legume puree. Based on the results and the literature, a model to manage the co-creation process between academia and industry that incorporates a collaboration platform is proposed. This paper also identifies the concrete practices that foster creativity and interaction among participants and that lead to innovation.

Creativity has been identified as a critical activity in distributed product development. Various methods and tools support distributed product development and distributed teams in general, but none with a focus on creative problem solving. To tackle this challenge, a systematic literature review has been conducted to gather the influencing factors on distributed creativity to be used as a starting point for supporting creativity in distributed product development teams. Within this submission, an impact model is developed, focusing on the success factors of creativity. Furthermore, the interconnection between the factors is modelled. Barriers to creative problem solving are included as well but will be the focus of a following publication.

This study focuses on high-tech startups in the Norwegian context and investigates the use of data and/or big data to support validation at the early stage of development. Early-stage startups often fail due to lack of validation and incur loss to all the stakeholders involved in the process. Early validation through a lean or agile approach can help these young companies to manoeuvre through a turbulent external environment. The results from the study show that big data and/or data can act as a support at this stage but is not necessarily the sole solution to the problem. There are various barriers that need to be addressed for successful data-based validation. Based on multi-case study research method, this study proposes an early validation user guide (EVU) to overcome these barriers and make data adoption easier. The EVU can provide startups support to show how and when to use data and/or big data depending on the market context. The study thus contributes to the current body of knowledge of innovation and entrepreneurship concerning validation for early stage startups and can also guide practitioners in validating their startup ideas.