Digital transformation, open innovation and circular business model transition: The role of effectual logic

Open innovation and open business models have received a lot of attention during the last decade both from practitioners and academia since Henry Chesbrough launched the two concepts respectively in 2003 and 2006 (Chesbrough, 2003a and 2006a). Careful observation of publications about these two concepts reveals that most researchers as well as practitioners do not make a proper distinction between them. In this chapter, we intend to clarify the distinction between the two concepts and, more importantly, to extend the range of potential innovation strategies by combining open innovation and open business models in different ways. This should lead to a comprehensive classification of possible innovation strategies in which open/closed innovations are combined with open/closed business models. The classification starts with simple combinations of open or closed innovations and traditional vs. open business models in their new product development. Combinations of open innovation and open business models generate interesting models to create and capture value, which to our knowledge are not specified before in the open innovation literature. The classification will also illustrate that (open) innovation targeting new product or new business development is just one possible strategy how firms can create a competitive advantage. Product innovation may not be an option for companies producing commodities (e.g. crude oil) but the competitive drivers in these industries (e.g. finding the best oil wells) may be affected by the product innovations of their (technology) partners (e.g. new technologies to explore oil wells more effectively). Reframing open innovation in this way allows us to shed light on innovation networks in which the instigators of the network are not the innovators themselves, but they nevertheless form the hubs in a broader innovation ecosystem in which they benefit from the innovations of their technology partners. OUP UNCORRECTED PROOF – FIRSTPROOFS, Fri May 3

Evolving a Value Chain to an Open Innovation Ecosystem: The Cognitive Influence of Stakeholders in Customizing Medical Implants

With the advent of the Fourth Industrial Revolution, businesses are adapting to the use of digitalisation which requires the digital transformation of their existing business models. However, there is limited empirical research on this phenomenon. The purpose of this study is twofold: (i) to develop a framework for businesses to digitally transform their business models and (ii) to examine literature in order to identify and analyse the constructs underlying the three concepts of Digitalisation, Digital Transformation and Business Model Innovation. The study is qualitative in nature and is based on a narrative review. Relevant articles were identified by using international bibliographic databases and scrutinised using thematic analysis. The findings reveal that the first two constructs require digital capabilities and a digital strategy. The third construct requires digital transformation in the realm of customer-centricity, resources, processes and profit. A set of propositions was formulated and the commonalities were mapped. Based upon this map, a conceptual framework was developed. The findings will assist in the development of future instruments that can guide businesses to digitally transform existing business model elements. This study aims to fill the gap on how business model innovation should be pursued through digital transformation by developing a conceptual framework.

The purpose of this contribution is to explore the concept of ‘open innovation’ in the context of the energy transition and the development of low carbon technologies. The chapter explores the interaction between energy law and intellectual property (IP) law in the ecosystem of the energy sector and in relation to the development of low carbon technologies. The research question investigated is how IPRs in the energy sector ecosystem are currently and should be regulated in the future as open innovation (OI) models develop. To answer this question, the chapter begins by briefly defining the concept of open innovation (Section 2), before analysing how the development of low carbon technologies is increasingly reliant on OI models (Section 3). This includes a categorisation of some existing OI models and an analysis of the legal framework that applies to them. The chapter then critically discusses the implications of OI models on IP law and energy market regulation (Section 4). In doing so, it reflects on the inter-regulation between IP law and energy law to support SDG 7 (Section 5).

Digital transformation as a catalyst for sustainability and open innovation

Open Innovation remains the process of enabling inflow and outflow of knowledge, ideas, design, plus technologies throughout the organization during the various stages of the innovation process. This Innovation consists of inbound and outbound open innovations, whereby inbound open Innovation is the influx of knowledge, while outbound open innovation remains the outward flow of knowledge. Previously, studies related to open innovation have only focused specifically on the business world, the industrial sector while less focused on strategy and its implementation in the education sector. This study aims to fill this gap by studying open innovation in ordinary day secondary schools due to their significant contribution to development Malaysian education. Based on an open innovation model and a theory of views based on resources, this study will analyse the role of open and innovative innovation activities government support in determining the innovative capabilities of secondary schools. In this conceptual paper, the author develops the conceptual model that will be used in further research activities in education sector and will contribute to a better understanding of open innovation activities and their practices in secondary schools in Malaysia.

The literature argues that a real digital transformation of firms requires holistic changes of the business model. Despite knowledge about this ambitious goal, understanding of how digital business model transformation can be achieved is still very limited. In this article, we explore how firms achieve digital business model transformation. We apply a case study design to investigate how incumbents have changed their respective business model dimensions during digital transformation. Our findings center on interview data and complementary archival records from 15 cases. We present a framework for digital business model transformation along the dimensions of value proposition, value creation, and value capture. Our results emphasize the importance of a preparatory phase in which the strategic course is set. Furthermore, our findings demonstrate that transforming a company's business model is most effective when a single person, namely the Chief Digital Officer, is responsible. Our findings contribute to the business model literature, by providing a more holistic view on how business model innovation can be utilized during digital transformation.

The explicit goal of the inaugural World Open Innovation Conference (WOIC) was to attract both leading academic researchers in open innovation and leading industry practitioners of open innovation, seeking to get these two groups to engage with one another. This introductory article sets the intellectual context of the WOIC, summarizes the "top" four articles resulting from the conference, and provides a research agenda based on a high-level view of all the submissions and sessions.

ABSTRACT: Digital transformation (DT) is the use and integration of digital technologies in all areas of an organization, leading to profound changes in its activities, operations and value creation for customers. It has become a matter of survival for organizations across all sectors, geographies and sizes. Despite its widespread adoption, DT success is not achieved by investing in technology alone; it is necessary to analyze the factors that influence success and understand why some companies gain a competitive advantage while others fail. This study examines three key factors of DT: business model innovation, digital technology integration and digital talent management, and their relationship to performance. In addition, we examine the environment in which each organization operates, considering the technological intensity of the sector as a potential moderating factor between these factors and performance. The study focuses on Spanish manufacturing companies, using data from the ESEE. By analyzing a panel data set of 9215 observations between 2011 and 2017, we provide evidence that the technological intensity of the sector significantly affects the relationship between business model innovation, digital technology integration, the development of new competencies and performance. The study shows that companies in medium- and low-tech sectors can benefit more quickly from investments aimed at business model innovation, digital technology integration and the development of new competencies, and achieve better short-term results compared to companies in high-tech sectors. These results suggest that, despite their limited investment in R&D, companies in medium- and low-tech sectors have resources and capabilities that compensate for their innovation activities.ABSTRACT: Digital transformation (DT) is the use and integration of digital technologies in all areas of an organization, leading to profound changes in its activities, operations and value creation for customers. It has become a matter of survival for organizations across all sectors, geographies and sizes. Despite its widespread adoption, DT success is not achieved by investing in technology alone; it is necessary to analyze the factors that influence success and understand why some companies gain a competitive advantage while others fail. This study examines three key factors of DT: business model innovation, digital technology integration and digital talent management, and their relationship to performance. In addition, we examine the environment in which each organization operates, considering the technological intensity of the sector as a potential moderating factor between these factors and performance. The study focuses on Spanish manufacturing companies, using data from the ESEE. By analyzing a panel data set of 9215 observations between 2011 and 2017, we provide evidence that the technological intensity of the sector significantly affects the relationship between business model innovation, digital technology integration, the development of new competencies and performance. The study shows that companies in medium- and low-tech sectors can benefit more quickly from investments aimed at business model innovation, digital technology integration and the development of new competencies, and achieve better short-term results compared to companies in high-tech sectors. These results suggest that, despite their limited investment in R&D, companies in medium- and low-tech sectors have resources and capabilities that compensate for their innovation activities. Keywords: Digital transformation; performance of Spanish manufacturing firms; business model innovation; digital technology integration; digital talent management; industry’s technological intensity. Keywords: Digital transformation; performance of Spanish manufacturing firms; business model innovation; digital technology integration; digital talent management; industry’s technological intensity.

Considering the large amounts of harmful waste produced in the Mediterranean olive sector, entrepreneurial initiatives creating value from olive waste and by-products via circular bio-economy approaches are reviewed. These circular business models aim to enhance the functionality use of olive trees beyond traditional patterns for value creation. The study focuses on business drivers and value creation mechanisms, and specifically on conversion pathways of olive waste towards new value propositions. In total, 41 cases are analyzed mainly according to the Business Model Canvas components with NVivo, based on data gathered from an extensive online search mainly of company websites and reports, online articles, research project reports, professional websites, and newsletters. Results indicate that some innovative businesses have emerged specializing in the domain of olive waste valorization, driven by environmental concerns and mainly focusing on bioenergy production. However, the overall olive biomass potential yet seems to be under-valorized. A more radical and systemic change will be needed for effective implementation of circular business models contributing to sustainable development in the Mediterranean olive sector, with adequate subsidies, common regulations, more collective actions for creating economies of scale, and marketing strategies to increase consumer awareness for bio-based products.

The role of artificial intelligence (AI) in achieving sustainability goals has garnered attention in academic literature. While AI has been argued to be crucial in addressing circularity challenges, organizations face challenges in configuring a business model. Designing new business calls for insights on how AI can be integrated into value creation and capture mechanisms. There is a lack of clarity on how organizations deploy AI as they transition to circular business model innovation. The purpose of the study is to explore how AI is integrated into organizational processes while adopting circular business models. We conducted online open‐ended interviews with 55 participants to explore the potential role of AI in enabling the adoption of circular business models. Our findings have implications for theory building relating to AI business model innovation and provide a novel avenue for further research on business model innovation literature. Building on a natural resource‐based view, the findings indicate that while implementing a circular business model is challenging, AI enables organizations to create, transfer, and capture value through resource efficiency and the reuse of resources. As AI technologies continue to evolve, organizations must develop adaptive capabilities to continually explore opportunities. AI enables organizations to reduce costs, develop novel value‐creation strategies, and capture opportunities, resulting in improved efficiency. Transitioning to a circular business model requires developing routines, and organizations must adapt existing systems to ensure these systems result in pollution prevention, product stewardship, and sustainable development. It is important for managers to develop organizational resources and capabilities that enable the development of AI capabilities.

Relevance. Digital transformation has been one of the key driving forces in the economy over the past few years, and the introduction of digital technologies is becoming an essential condition for an efficient, competitive and sustainable business. The article is devoted to the formation of the concept of digital transformation in the modern business environment, with a focus on the growing new challenges from the external environment. A wide range of studies devoted to this issue highlights various aspects, including barriers, strategies, elements and other components of this complex definition, which leads to the existence of multiple variations of approaches, both to the vision of the essence of digital transformation and its resulting parameters. The purpose of the study is theoretical and methodological elaboration of the issues of the essence of the categorical apparatus of the category "digital transformation of business" and the disclosure of its structural components, as well as clarification for further strategic management and reduction of the consequences of risk determinants. Objectives: analysis of statistical data on the level of digitalization of business in Russia; identification of key elements of digital business transformation; consideration of digital transformation as a business process. Methodology. As part of the study, materials from world rating reports and news agencies were used, as well as developments by representatives of the national scientific school, which was the basis for a critical analysis. Standard methods of statistical processing, generalization, and comparison were used. The method of classification and comparative analysis, as well as methods of structural-functional and strategic analysis are applied. Results. The article presents the main trends of digitalization of business in Russia. The author's approach to understanding the definition of "digital transformation of business" is formulated, its key elements are highlighted. A conceptual model of digital business transformation in the conditions of practical implementation of the basic development strategy is proposed. Conclusions. The technologies that form the basis of digital transformation are revolutionary in themselves, and in their synergetic effect are capable of radically transforming business and society, destroying old business models, thereby contributing to the increase of competitive opportunities and rapid adaptation to chaotically changing market requirements.

Business models have a crucial role to play in the transition to a circular economy. Circular business model innovation provides an arena for studying the creation of such circular business models and enables companies the possibility to identify new value creation opportunities, such as capitalizing on embedded value of products over multiple lifecycles. In comparison with the trajectory of traditional business model innovation literature, circular business model innovation is underdeveloped, and this paper aims to make a contribution to the ongoing theoretical discussion. Through review and categorization of 140 circular business model case examples, this paper makes a first attempt to verify previous literature and unify academic and industry understanding of circular business models. The findings are expected to be useful in advancing the field of circular business model innovation and assisting practitioners in the design and development of new circular business models. While the results suggest convergence around three circular business model types: ‘Access/Performance Model’, ‘Extending Product Value’, and ‘Extending Resource Value’, other previously identified circular business model types should not be discounted.

In the past 10 years, numerous interesting articles, book chapters, and books have been written on open innovation strategies in mainly large companies. While closed innovation models have resulted in important breakthrough innovations, many large companies have abandoned vertical integration strategies in recent years and have moved toward a combination of both closed and open innovation models that are used for reaching different sets of innovative goals. The definition of open innovation as proposed by Chesbrough is still the most commonly used notion of the concept. However, several respectable open innovation researchers have added to the theory and have offered valuable extensions to Chesbrough's widely used definition. While the open innovation literature strongly builds on important existing theories of innovation, there are several new contributions of the open innovation literature to the established body of literature: a strong focus on external technology commercialization; the positioning of the business model as the connection between a firm's innovation efforts and strategy; and the appreciation of the value associated with recognizing false negatives. Open innovation strategies are potentially useful in several different settings: in product innovation and in commodities; in high‐tech industries as well as in low‐tech sectors; and in small and large companies. However, research also shows that in all of these settings companies that have the necessary internal conditions in place find open innovation models to be the most useful. For the next 10 years, there are several interesting research themes in open innovation for researchers, both established scholars and young researchers, to explore.

Meta-organizing for open innovation under environmental and social pressures in the oil industry