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Great uncertainty accompanies entrepreneurs’ processes of designing promising business models (BMs). Therefore, stabilising factors act as important means in this process. In this study, we examined the impact of cognitive dispositions and visual BM frameworks on the BM process and outcomes. By using partial-least-square structural equation modelling (PLS-SEM) and an experimental setting, our results show that the stabilising function of BM frameworks depends on entrepreneurs’ cognitive dispositions. This finding contributes to the cognitive BM perspective and explains how cognitive dispositions and visual framing effects act as boundary conditions for the theory of stabilising factors. This also has important implications for applying frameworks in practice.

Assessing air cargo strategy from an airport's perspective is relatively novel, and it seems little attention has been paid to this research area. This chapter will address this research gap by introducing an Airport Cargo Strategy Canvas, designed to help build cargo strategies for individual airports.

The Airport Cargo Strategy Canvas can be used as a tool to analyze and improve the air cargo strategy of an airport. The first part of this chapter will explain the different components of the Airport Cargo Strategy Canvas more in detail. The horizontal axis on the canvas differentiates between exogenous and endogenous drivers of airport competitiveness. The vertical axis distinguishes between the airport product and the airport market. The canvas also considers potential disruptors and principal shareholders' objectives. The different components of the canvas allow the analyst to dig into the main features and differentiators of respective airports. The canvas might also be helpful to structure and compare the strategic components and framework of their own or competitors' cargo strategies.

In the second part, the Airport Cargo Strategy Canvas was applied to Brussels Airport to analyze its cargo strategy. The canvas showed several strengths and weaknesses, opportunities and threats in its current cargo strategy. The completed canvas will let Brussels Airport's executives explore and analyze the strategy of their main competitors and peers' strategy and help them identify potential gaps in their strategies.

Lucerne University of Applied Sciences and Arts (LUASA) uses a holistic approach to foster entrepreneurial thinking and behavior of students and employees. Students and participants of the program shall be motivated to start own ventures during the study program or later in the life.

An entrepreneurial eco-system shall be built and a close partnership with regional key actors established.

A combination of Design Thinking and Lean Start-up is used for the entrepreneurial education. Fostering experimentation, early customer feedback, and interdisciplinary teamwork is essential. An enhanced Lean Canvas version is used for having a guideline to work on the important questions and documenting the learnings in the iterative process.

The program “Smart-up” of LUASA is running since three years as a pilot in two departments and is now rolled out to the entire University. Since program start more than 120 start-ups have been founded.

In all study programs, an “entrepreneurial track” is defined and students can earn credits while working on their own projects. Two interdisciplinary modules are offered. The proposed Smart-up Lean Canvas has been proven to be a key tool to develop innovative ideas in start-ups and in existing companies.

The combination of Design Thinking and Lean Start-up in a holistic setup proved that students can learn the methods and tools and are able to use them now or later as entre- or intrapreneurs.

Students are motivated to start their own business, meet role models and participating at different (networking) events.

The combination of Design Thinking and Lean Start-up with analytical approaches like Systems Thinking and Data Analytics supports the problem understanding and solution (product/service and business) design.

This chapter addresses the grand challenge of an aging society and the subsequent growing demand for in-home care for the elderly – often referred to as homecare. It examines how emergent homecare models in England differ from the “time and task” model and how they are shaping the care market. These models offer new approaches regarding what, how, and when care is delivered at home. Homecare providers face rising demand driven not only by population aging but also by market demand for personalized care, choice, continuity of care, and real-time availability. The landscape presents an opportunity for innovative models to become established, by offering a more inducing service design and value propositions that respond to customers' needs. Using the “business model canvas” to guide data collection, this study presents an ethnographic case analysis of four homecare organizations with distinct emergent homecare models. The study includes 14 months of field observation and 33 in-depth interviews. It finds that providers are becoming increasingly aware of evolving customer needs, establishing models such as the “uberization,” “community-based,” “live-in,” and “preventative” described in the chapter. These models are becoming more pervasive and are mostly market-driven; however, some of their innovations are market shaping. The major innovations are in their value propositions, partnership arrangements, and customer segments. Their value propositions focus on well-being outcomes, including choice and personalization for care users; their workforces are perceived to be a major stakeholder segment, and their networks of partners offer access to complementary services, investments, and specialist knowledge.

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.

Fashion/textile small- to medium-sized enterprises (SMEs) are currently adding value to previously discarded textile waste by applying practical skills, knowledge and expertise to rework and reuse this material. As a result, sustainable design strategies such as zero-waste pattern-cutting, design for disassembly and upcycling are beginning to emerge. However, the scope for redesign will always be limited and the complete lifecycle of the material used needs to be considered at the front-end of the innovation process, to optimise material lifespans and reduce consumer waste. Further work is also required to inspire and educate the next generation of designers to the creative potential of reuse, and help the industry to understand its viability, scalability and role in the future. This chapter explores how the principals of the circular economy might support business model innovation within fashion and textiles. To this end, an exploratory canvas tool for SMEs, ‘Circular by Design’, was devised to aid SMEs to embrace closed-loop systems and to identify the most appropriate sustainable design strategies for their business.

Service robots present a new frontier in the provision of services, with far-reaching implications for customers and managers alike. The purpose of this chapter is to examine how service robots impact service providers' current marketing strategies. For this, the authors perform an integrative, nonsystematic review of international gray and academic literature to understand how both practitioners and academics perceive the impacts of the technology. Based on this analysis, the present work identifies three key themes that emerge from the current state of practitioner and academic research, namely (1) service robots demand new core business capabilities and competencies, (2) service robots offer new value propositions, and (3) service robots impact not only service providers' cost structures but also revenue streams. These insights are combined into the Service Robot Innovation Canvas, a visual tool for service providers to identify the impact of service robot implementations on a company's marketing strategy. In addition, based on the analyzed literature, the most pressing questions for researchers are laid out in a research agenda.

In research on the circular economy, business models are often taken as a focal point since their essential functions are both to create value and to capture part of that value. This chapter investigates whether and how circular business models can be “opened up” to creating and capturing value by utilizing a firm’s main asset not only in its own operation but also in other firms’ businesses. We hereby take the perspective of producing companies which face various challenges over the entire product life cycle and empirically analyze a case of five companies which are part of a joint innovation toward circularity in the plastics industry. Building on a grounded theory approach, we propose a new framework for companies which combines insights about open business models with circularity. When moving toward circularity, producing companies are advised to expand their dyadic perspective of suppliers, on the one hand, and customers, on the other hand, to a network perspective and open their business models.

Designing a top-quality research study is a complex challenge. We introduce the research design canvas as a tool to help researchers manage this complexity and create better studies. Completing a research design canvas requires researchers to a priori articulate one or more research questions, identify a gap in the literature in need of closing, select a guiding theory or theories, construct hypotheses, choose a sample, select measures, recognize boundary conditions, plot a data analysis strategy, ascertain a study’s limitations, clarify the value added of key research partners, pinpoint a target journal for potential publication, and think ahead about their backup plans in case the research process goes awry. Many studies are doomed to bad fates by poor decisions about these elements. Using the research design canvas can help researchers ensure that they have selected a valid approach to each element, reason through the interrelationships among each decision point within the canvas to ensure that there is consistency among them, and critically assess whether the design as a whole provides the basis for a new advance. By doing so, scholars may be able to improve their chances of defying the high rejection rates of leading journals.