Innovation Management

Scholars have recently argued that startups and incumbents play differential roles in the disruptive transformations of industries toward sustainability and that the transformations are only likely to succeed if both startups and incumbents contribute. To understand their respective contributions and, thus, to understand how industries make the transition toward sustainability, comparative studies of incumbents versus startups during this transformation have been identified as a central pursuit, but yet they are mostly lacking. Since business models have become a principal way of characterizing firms, the present study takes a business model perspective and derives business model archetypes in the electrical power sector from an analysis of 280 startups and incumbents in three different countries. The selected countries (USA, UK, and India) represent three different energy profiles and leading instances of disruption in the energy sector. The article, then, undertakes a comparative analysis of startups and incumbents based on the empirically distilled business model archetypes and develops propositions on startups, incumbents, and business models in industry transformations. This analysis produces several important insights. First, incumbents do not seem to engage in less business model experimentation than startups. Second, incumbents have adopted several new business models that are not pursued by startups. Third, startups have espoused some business models that are not pursued by incumbents. Fourth, foreign firms can also affect the ‘green’ transformation of an industry in a focal country. Finally, the identified business model archetypes are likely to be of interest to scholars and practitioners who are seeking an improved understanding of business models in the electrical power industry and the industry’s competitive landscape. https://doi.org/10.1016/j.indmarman.2021.04.003

Without fundamental institutional change, such as a change in laws and regulations, many new technologies cannot achieve their full potential. Efforts to induce institutional change in favor of such technologies are, therefore, increasingly critical for innovative firms. To study how German automotive firms induce change that accommodates autonomous driving (AD) solutions, we conducted a case study research encompassing analysis of 31 interviews, internal archival documents, and media data. Taking the firm as the level of analysis, we identify ten practices employed by innovating incumbents in the three steps of creating saliency for change, mitigating reservations against the desired change, and institutionalizing it. We find that these practices involve shaping-oriented and adaptation-oriented knowledge flows. Through the combined use of these practices throughout the three steps, firms ‘open up’ their development process, utilizing purposive inflows and outflows of knowledge to advance innovation. Our findings contribute to the literature on open innovation and institutional entrepreneurship and suggest that future open innovation research can profit from adopting an institutional entrepreneurship perspective. 

Are stakeholder management and innovation substitutes or complements in affecting firm performance? Extant research provides support for both positions and thus leaves us with a puzzle. We conduct an exploratory fuzzy set qualitative comparative analysis (fsQCA) of 204 publicly listed European firms combining survey and archival data to formulate theory on how stakeholder management and innovation work (in)effectively together. Distinguishing between internal and external stakeholders and exploitative and exploratory innovation, we elaborate that managing for stakeholders and innovation can be both substitutes and complements depending on a set of contingencies. We discuss boundary conditions and implications for future research.

Artificial Intelligence (AI) reshapes companies and how innovation management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel management to rethink a company’s entire innovation process. In response, we review and explore the implications for future innovation management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for innovation management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of innovation. We conclude our study by exploring directions for future research. doi: 10.1016/j.techfore.2020.120392

Prominent political and societal stakeholders argue that business models (BMs) are pivotal in making a successful transition to a circular economy (CE). However, the existing CE literature has paid little attention to design choices that allow companies to implement circular business models (CBMs) that meet the requirements of their specific situations. Resource sharing (alternatively called asset sharing) is a key practice in making the transition to a CE. The present article, therefore, seeks to gain deeper insights into the CBMs of firms that orchestrate resource-sharing solutions. For this purpose, it uses a qualitative multiple case-study approach and analyzes nine firms that orchestrate virtual power plants in Germany and Switzerland. Specifically, the article explores the design choices with which firms are faced when they implement CBMs, and it examines different implementation strategies that flow from making certain design choices. The article also identifies transition pathways that enable firms to move between different implementation strategies in order to increase economic and environmental gains. The present article can serve as a stimulus for further detailed analyses of other BMs that are important to a CE in the future.

This study systematically analysed 237 frugal innovation cases in
order to understand the consequences and implications of market choice on the
characteristics of a successful frugal innovation. The results demonstrate that
this type of innovation is disruptive to its respective target market. Further, the
study shows that firms that want to achieve such innovation tend to focus either
on activities along the value chain or the solution (product/service) itself. This
distinction yielded four clusters of frugal innovation, which are described in
detail, including aspects regarding strategy, organisation, processes and
technology.

We investigated the state of artificial intelligence (AI) in pharmaceutical research and development
(R&D) and outline here a risk and reward perspective regarding digital R&D. Given the novelty of the
research area, a combined qualitative and quantitative research method was chosen, including the
analysis of annual company reports, investor relations information, patent applications, and scientific
publications of 21 pharmaceutical companies for the years 2014 to 2019. As a result, we can confirm that
the industry is in an ‘early mature’ phase of using AI in R&D. Furthermore, we can demonstrate that,
despite the efforts that need to be managed, recent developments in the industry indicate that it is
worthwhile to invest to become a ‘digital pharma player’.

Transformation through digital innovation is becoming an imperative for every city. The ‘Smart City’ concept promises to solve the most urgent queries of progressive urbanization in the area of mobility, energy, water supply, security, housing deprivation, and inclusion. Despite the exploitation of existing potential in lighthouse-cities that include Barcelona, London, Munich, Lyon, and Vienna, the less tenacious pursuit of smart city possibilities in the majority of municipalities has resulted in major discrepancies between leading smart cities and those that are less aspirational. Although the necessity of action is frequently recognized, an appropriate path of action remains obscure.

Smart Cities: Introducing Digital Innovation to Cities offers answers, with clarifying examples, to questions that have remained unanswered for many cities. The book identifies and addresses the core elements and potential of smart cities, best practice methods and tools to be implemented, as well as how diverse stakeholders might be effectively integrated.

Based on perennial international research in the field of smart cities, this book brings together the authors' collective experience in practice-based political, administrative, and economic projects to provide a common framework to guide and engage key stakeholders in the transformation and realization of smart cities.