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The chapter provides empirical research results on the peculiarities of social innovation and the specific features that its business model must support. It concludes by proposing a Social Innovation Business Model Canvas and steps towards Social Innovation typologies.

The research is based on the results of a comparative analysis of 25 business case studies and 32 biographies conducted within the SIMPACT research framework. We then implemented a process of reverse engineering to uncover the business models behind the cases which facilitated the creation of a typology for different social innovation business models. Reverse engineering is the application of tools and processes used to study new business ventures in comparison with existing ones. As such, it sheds further light on the broad characteristics of social business models and their value creation mechanisms. The evidence coming from the cases were analyzed within a new business model and clustered to identify a typology of business models of social innovations.

The main SIMPACT findings, resulting from the reverse engineering process and upon which our discussion is based, can be seen in the following distinguishing characteristics of SI business models. SI business models are: configured around finding complementarity between antagonistic assets and seemingly conflicting logics; often structured around a divergence in the allocation of cost, use, and benefit leading to multiple value propositions; modeled on multiactor/multisided business strategies, and developed as frugal solutions and through actions of bricolage. Four typologies of social innovation were identified: beneficiary as actor, beneficiary as customer, beneficiary as user, and community-asset-based models.

While much attention has been placed on for-profit business models, there is little literature on social/not-for-profit business models. This chapter can add to this gap by providing substantial empirical evidence.

Practitioners in the field of social innovation, particularly the growing intermediary sector, could integrate the findings of the research in their work.

The work is also leading to the construction of a future business toolbox for social innovation, which will be even more useful for incubators, accelerators, and supporting structures.

Research presented in this chapter is the result of an extensive comparative analysis across all of Europe, including examples of failure, and the first to propose a typology of SI Business Models.

We investigate how Salesforce’s key people used analogies and metaphors during the deployment of their (then) radical business model innovation. Our analysis shows how Salesforce’s entrepreneurial team skillfully used a mix of analogies and metaphors to communicate its innovations and differentiate the company from its competitors. We also show how business model innovators can weave together analogies and metaphors to create distinct meta-narratives that elicited strong emotions and helped construct a memorable organizational identity that galvanized stakeholders around the firm’s ecosystem appeal. We conclude by discussing the implications of our findings for business model and cognition research.

Digital disruption no longer ensures the security or longevity of established firm structures and business models. Instead, it necessitates that firms reinvent their business models, including business processes, people, and technologies that align with the organizational goals. Despite the exponential growth of digital disruption, prior literature indicates that the concept of business model innovation is poorly understood in developing economies. Furthermore, little is known about how low-tech firms in developing economies should adapt and reinvent their business models to cope with and shape digital disruption as it unfolds. Grounded in two overarching theoretical frameworks, namely the theory of disruptive innovation and the resources–processes–values (RPV) framework, this chapter addresses this void in prior literature. Based on multiple case study analyses of 10 low-tech firms in diverse industries in Sri Lanka, the findings indicate that successful disruptive business model innovation in low-tech firms in Sri Lanka is predicated on an effective technology management strategy, suitable organizational structure, compatible organizational culture, and devoted corporate governance. Moreover, external influences like changing market dynamics, competition, and shifts in consumer behavior also significantly influence disruptive business model innovation of selected firms. This chapter acts as a springboard for future researchers by extending the theory of disruptive innovation and RPV framework to low-tech industries in developing economies.

The European Union’s Digital Markets Act (DMA) calls for far-reaching changes to the way economic activity will occur in EU digital markets. Before its remedies are imposed, it is critical to assess their impacts on individual markets, the digital sector, and the overall European economy. The European Commission (EC) released an Impact Assessment in support of the DMA that purports to evaluate it using cost/benefit analysis.

An economic evaluation of the DMA should consider its full impacts on dynamic competition. The Impact Assessment neither assesses the DMA's impact on dynamic competition in the digital economy nor evaluates the impacts of specific DMA prohibitions and obligations. Instead, it considers benefits in general and largely ignores costs. We study its benefit assessments and find they are based on highly inappropriate methodologies and assumptions. A cost/benefit study using inappropriate methodologies and largely ignoring costs cannot provide a sound policy assessment.

Instead of promoting dynamic competition between platforms, the DMA will likely reinforce existing market structures, ossify market boundaries, and stunt European innovation. The DMA is likely to chill R&D by encouraging free riding on the investments of others, which discourages making those investments. Avoiding harm to innovation is critical because innovation delivers large, positive spillover benefits, driving increases in productivity, employment, wages, and prosperity.

The DMA prioritizes static over dynamic competition, with the potential to harm the European economy. Given this, the Impact Assessment does not demonstrate that the DMA will be beneficial overall, and its implementation must be carefully tailored to alleviate or lessen its potential to harm Europe’s economic performance.

What makes firms innovate their business models? Why do they engage in innovating how they create, deliver, and capture value? And how does such innovation translate into innovation performance? Despite the importance of business model innovation for achieving competitive advantage, existing evidence seems to be confined to firm-level antecedents and pays little attention to the impact of industry structure. This study investigates how different stages of an industry’s life cycle and levels of industry competition affect firms’ business model innovation, and how such innovation translates into innovation performance. Based on a cross-industry sample of 1,242 Austrian firms, we introduce a unique measure for the degree of innovation in a firm’s business model. The results indicate that the degree of business model innovation is highest toward the beginning of an industry life cycle, that is, in the emergent stage. Competitive industry pressures turn out to be negatively related to the degree of business model innovation. Moreover, we find that the degree of a firm’s business model innovation, conditional on it having introduced a new product or process recently, positively influences innovation performance. Our findings contribute to the ongoing dialog on the role of industry structure in business model innovation, and provide implications for the management of business model innovation.

The purposes of this chapter are to propose definitions of innovation, product innovation, business model innovation, marketing innovation, innovation strategy, and strategic innovation, elaborate on their literature and conceptual underpinnings, and provide an overview of the conceptual domains of innovation, innovation strategy, and strategic innovation.

First, certain definitions of innovation, drawn from literature, are presented. Next, certain definitions that incorporate logically incremental refinements in them are presented. Building on these, definitions of innovation, product innovation, business model innovation, and marketing innovation are proposed.

Innovation is the creation of value by using relevant knowledge and resources for conversion of an idea into a new product, process, or practice, or improvements in an existing product, process, or practice. Innovation strategy is an organization’s relative emphasis on different types of innovations and the associated pattern of resource allocation, in alignment with its strategy at the corporate and business unit levels. Strategic innovation is the creation of value by using relevant knowledge and resources for conversion of an idea into a new product, process, or practice with the potential to have a major transformational effect on the evolution of markets and industries.

Over the past several decades, there has been a sustained and high level of interest in issues relating to innovation among academics in a number of disciplines, business and social entrepreneurs, business practitioners, and policy makers. Books, journal articles, and business magazine articles provide a number of definitions of innovation and specific types of innovation. Multiple definitions of a construct can be problematic in certain respects and beneficial in other respects. A potential upside of multiple definitions of innovation is the prospect of each being a source of ideas for one or more innovations that benefit society, and an impetus for research focusing on specific questions.

Implementation of an idea, value creation, and use of relevant knowledge and resources are used as constituent elements in the proposed definitions of innovation, product innovation, business model innovation, marketing innovation, and strategic innovation.

The time is right for a theory on strategic entrepreneurial ecosystems and business model innovation. Both topics have increased substantially during the past couple of years due to their strategic nature. This means they are uniquely placed to provide practical advice but also theoretical development. This chapter discusses the theory in terms of how it bridges strategic planning, innovation management, and entrepreneurship literature. Thereby propelling the field of entrepreneurial ecosystems further by suggesting it has both a strategic and business model perspective. This chapter argues the reasons for a new theory to be developed in order to maintain the relevance and practicality of the entrepreneurial ecosystem literature.

The title of this book suggests the possibility that new ways of managing innovative processes may favour an evolution of the economy towards an altruistic model. This chapter argues that the acceleration of innovative processes at the turn of the millennium has produced, or at least has not avoided, phenomena of the concentration of wealth and power in which it is difficult to discern an altruistic root. It is observed that the cultural models developed to interpret innovative phenomena are also focused on the profit of individual companies and not on altruistic values. The author goes on to indicate the appropriateness of referring to less limited phenomenological models and suggests exploring an analogy of innovation with Darwinian evolution. An outline of this approach is provided.

In this paper, we reflect on an expanding literature that links theories of cognition and business models. Managers hold in their mind perceptual constructs or schemas of the business model. These guide the process of distinguishing between options and making choices. Those familiar with business model development will easily recognise that the perceptual construct provides only a summary of the business model, and that a more complex conceptualisation of how business model elements interact is needed. The business model is then much more than a visualisation. It is a schematic model of theorised interaction that is created, shaped, and shared over time. The underlying processes of this creation, shaping, and sharing are cognitive activities taking place at individual, organisational, and inter-organisational levels. Theories of managerial and organisational cognition are thus critical to understanding the acts of business modelling and business model innovation. Here we suggest some of the ways that business model and cognition literatures can be connected, present existing literature, and reflect on future avenues of research to explore the cognitive foundations of business modelling.

Following the triple helix (TH) model and the way knowledge is transferred into the industry domain, this chapter aims to define features interface that should be implemented in order to facilitate the University–Industry (UI) relationship and thus encourage the spin-off creation.

In order to support this relationship, a new business model configuration of an entrepreneurial ecosystem is proposed, aiming at creating a sustainable environment, where business entities can grow. The field of the Governance of Entrepreneurial Ecosystems is also investigated in order to define a framework for launching, developing, and sustaining a company over time.

This chapter presents a case study developed within the University of Salento (Italy). It capitalizes results from three different research analyses, based on questionnaires and interviews with actors of the spin-off network (professors and researchers, graduating students, admin-tech staff of the Technology Transfer Office, spin-offs’ CEOs/Associates, and R&D managers of external companies) and on results coming from scientific publications and regional/national reports in the innovation context.

A research methodology based on semantic network analysis and sentiment analysis has been applied in order to identify which features an interface should implement in order to facilitate the UI relationship and encourage the spin-off creation.

To support the start-up overcoming the “death valley,” the creation of a link between the strategy used to transfer value to the market and the phase of innovation is proposed inside the business model configuration. Some aspects of a governance model of an entrepreneurial ecosystem were also presented in order to support the business evolution of a single business entity and assuring sustainability over time.