Business model innovation and Business Model Canvas, as well-known business model architectures, have gradually become an essential topic in entrepreneurship education. The application of Business Model Canvas is considered an effective and reliable unit of analysis to measure companies business operations and performance. It helps students to first analyze the Business Model Canvas of an existing business and then create their own business idea. Although the Business Model Canvas helps students to get a quick view on the business operations through the creation, delivery and capture of value, in practice, entrepreneurs need to adapt and change their business operations constantly in order to grow and remain viable. Considering the need to capture the business dynamics in business model framework, the aim of this paper is to propose a dynamic business model framework as an alternative tool. Engineering students at Delft University of Technology were asked to critically assess the limitations of the existing business model canvas, and then students gave input and assessed an alternative dynamic business model. The results show that the current Business Model Canvas cannot capture the business model innovation of companies and the proposed framework improves student's understanding of business model innovation and in particular their dynamic nature.

@en

The transition to a circular economy is increasingly recognized as being vital for the sustainable development of industries. Indeed, the emergence of new green and digital technologies, such as Internet of Things, artificial intelligence, precision agriculture and renewable energy solutions, drives businesses to undergo multiple transformations. With the adaption of their business models and the enhancement of customer orientation, these technologies facilitate the creation of new business solutions and services that promote business circularity. Several factors have been identified in the emerging literature on the circular economy that could potentially impact the operationalization of the circular economy. It is, however, still unclear how these factors interact to result in the implementation of circularity. Hence, the purpose of this study is to explore the various configurations of enabling conditions that lead to successful circular economy operationalization. By using a fuzzy set qualitative comparative analysis (fsQCA), we examine the impact of different configurations of “digitalization”, “servitization”, “business model innovation”, “green practices”, and “customer participation” conditions on achieving circular economy. Based on survey data obtained from Dutch AgriTech companies, multiple paths to successful circular economy adoption are observed. The findings underscore the complexity of achieving circular economy, demonstrating that no single strategy is sufficient. Instead, a combination of several factors must synergize in order to ensure sustained circularity. Therefore, this study contributes to both the literature on digital servitization and circular economy, while providing insight to practitioners and policy makers seeking to promote circularity.@en

Purpose: Context characteristics of emerging economies differ significantly from those in developed economies. Considering this substantial difference, this study aims to identify the drivers and barriers for new product development (NPD) success in the context of an emerging economy by drawing on the resource-based view. Design/methodology/approach: Data was collected from firms in different sectors in the Aegean Region of Turkey using the Wageningen Innovation Assessment Tool. Of 189 responses, 94 fit the criteria and used for statistical analysis. The data is analyzed using a two-step procedure, namely, a confirmatory factor analysis followed by a binary logistic regression that is used to model the probability in the study of the success of NPD. Findings: The results reveal that along with the context characteristics of an emerging economy setting, internal capabilities matter for NPD success. Based on interviews with NPD managers, it was found that, among other factors, the close relationship with local customers is key for new product success, while introducing high innovative products to the market of an emerging economy may not be appropriate due to the specific conditions of such economies. Practical implications: This study will be useful to the managers to understand the extent to which the degree of newness of a product affects NPD success in an emerging economy setting. It also highlights the importance of securing firm resources before starting an innovation activity in this setting where resources such as financial resources, knowledge and physical resources are limited. From a policy perspective, this study provides certain insights as well. That is, government officials in emerging economies should be very careful about their informal actions that might disrupt the investment and innovation environment. Originality/value: Emerging economies are important for large firms seeking growth. They initiate manufacturing activities and increasingly perform innovation activities in those countries. However, the conditions to innovate are different from those in developed economies. Research into the factors that drive innovation is largely in an embryonic state. This study offers NPD researchers a deeper understanding of the drivers and barriers to innovation, particularly internal ones that may affect the NPD success in an emerging economy setting, in this case, that of Turkey. The results provide suggestions for policymakers to consider during the development of new innovation policies. For practitioners, this study outlines novel combinations of internal factors that lead to NPD success.

@en

Academic spin-off facilitators support high-tech academic spin-offs and help them to navigate various barriers and critical junctures during their growth stages. In this article we draw on stage-gate models, the path-dependency, and resource based view to identify start-ups' resource needs as perceived by both facilitators and by entrepreneurs. Using qualitative data based on in-depth interviews with 18 academic spin-off facilitators and nine spin-off founders, from three technical universities in the Netherlands, we explore the critical junctures and key support activities. The results show that founders appreciate milestones and direct interface regarding business support, business plan development, and legal support during the early growth stages. In all stages, in particular during the later stages, founders appreciate different type of network support (e.g., start-up network and industry) and when facilitators act as intermediaries to guide them in the network. This helps spin-offs to gain credibility and reach out to the market. This article adds to current research on academic facilitators and in particular incubators by providing a more comprehensive explanation for the low usage of the incubator's resources. By matching key resources and support activities that can navigate particular critical junctures, we try to promote the successful transition from one stage to the other. Our findings offer significant implications, both theoretical and practical, for academic entrepreneurship literature.

@en

Farmers may vary in their response to or anticipation of agrifood market changes, which probably depends on their entrepreneurial degree and networks. This paper aims to investigate the effects of farmers’ entrepreneurial degree and network content (i.e., business ties, technology ties, and network heterogeneity) on farm performance (i.e., innovative performance and financial performance). The data set was gathered through a survey of 262 vegetable farmers in West Java, Indonesia. Our findings reveal that more entrepreneurial farmers (106) have more business ties, technology ties, and heterogeneous networks compared to less entrepreneurial farmers (156). Further analyses using OLS regression confirm that farmers who are more entrepreneurial and have more business ties obtain both enhanced innovative and financial performance, while farmers who link to heterogeneous networks obtain only enhanced innovative performance. Overall, the findings of this study demonstrate that more entrepreneurial farmers with networks that are rich in business ties and diverse contacts have better farm performance.@en

The growth of modern agrifood markets, especially in Indonesia, has stimulated entrepreneurially oriented farmers to seize business opportunities through innovation. This paper aims to investigate in a dynamic agrifood market if entrepreneurial orientation enhances innovation adoption and generation and if both of these actions enhance product innovation and, eventually, farm revenues of vegetable farmers in West Java, Indonesia. The findings demonstrate that entrepreneurial orientation enhances innovation adoption and generation, which in turn enhance product innovation. Finally, product innovation enhances farm revenues. The findings contribute to a better understanding of the role of innovation in facilitating entrepreneurially oriented farmers to perform better when facing a dynamic market. Entrepreneurial orientation enables farmers to innovate by taking risks to anticipate future demand, through either adoption of available innovations or generation of their own innovations, and both options result in new or improved products and eventually enhanced farm revenues.

@en

This chapter deals with small high-technology firms introducing sustainable energy inventions to the market. The focus is on university spin-offs, which typically show weak skills in management and marketing, but strong technology skills – in this chapter, solar photovoltaics, wind energy, biomass and hydro-power. A simplified conceptual model is explored by focusing on institutional aspects (countries) and network access as well as firms’ entrepreneurial orientation. The exploration of time to market draws on a selected sample of spin-offs in northwest Europe using rough-set analysis. The results show that the highest probability for quick market introduction occurs in an ‘innovation leader’ country (Sweden, Denmark, Finland) and among spin-offs’ involved in multiple networks, followed by those with a practical orientation and access to substantial investment. There are no differences between entrepreneurial ecosystems in metropolitan areas and remote/small urban places. Rather, the results indicate a trend for compensation in ‘thin regions’ through long-distance networks and ‘workplace learning’.@en

Knowledge resources, mainly due to their causal ambiguity and inimitability, play a central role in shaping the competitive advantage of organizations. This chapter aims to illustrate a correspondence between knowledge types and organizational types in open innovation (OI) networks. It maps the knowledge types that shape diverse institutions of the economy as presented by the Triple Helix model: episteme at the academia, techne at the industry, and phronesis at the government. Each organization - beyond its institutional knowledge specialization - diversifies to incorporate the other two knowledge types in its knowledge integration portfolio. For example, a university may develop technologies and conduct responsible research and/or a firm may conduct scientific research and engage in corporate social responsibility activities. The implications of these institutional specialization and organizational diversification in OI networks are twofold: (a) organizations can gain a competitive edge by diversifying into a unique portfolio of knowledge integration encompassing a novel proportion of episteme, techne, and phronesis and (b) to achieve the highest level of knowledge integration, organizations belonging to diverse institutions can engage in inter-organizational knowledge sharing to meta-integrate their institutionally specialized and organizationally diversified knowledge types.@en

Organizations collaborate with external actors in order to acquire knowledge resources they cannot develop internally for economic and/or technical reasons. Mode 2 and Triple Helix models have examined the role of different organizational types in collaborative creation and knowledge use. This paper is an empirical investigation on whether universities differ from business-oriented or industrial organization types with regard to the extent of their knowledge collaborations. Using SEM methodology, it demonstrates the role of universities in knowledge collaboration through a survey of 472 organizations in the 7th Framework Programme for Research and Technological Development of the European Commission, Energy theme (FP7-Energy). In line with the Triple Helix model, universities are found to exhibit more extensive knowledge collaboration than businesses. Also, between-university collaborations are found to be more extensive knowledge collaboration relationship types than between-business relationships. The findings imply that (1) publically funded consortia should be aware that universities are more conducive and hence more effective in inter-organizational knowledge collaboration networks than other organizational types, particularly compared to for-profit business organizations. Universities should be included in these consortia. (2) Business organizations that do not have an extensive relationship with universities need to reconsider their partner portfolio and extend the knowledge collaboration of their network by connecting to more universities.(3) Policymakers should not only involve academic organizations but also include groups of more than one university per consortium to enable between-university knowledge collaboration to boost collaborative knowledge exploration and exploitation of the consortia.

@en

Responsible research and innovation (RRI) has become an important topic in the academic community and in policy circles, but it has not yet been systematically included in the innovation process of companies. We discuss how companies can integrate RRI into their corporate social responsibility (CSR) policies and business strategy. To this end, we developed a conceptual model that links a company's RRI strategy to its context, and that helps to translate the RRI strategy into activities that result in RRI outcomes. We also propose a process for developing company-specific RRI key performance indicators (KPIs) that can support companies to measure RRI outcomes.

@en

There is a wide gap between the need for science-based start-ups to purchase or gain access to test equipment and the willingness of investors to provide the necessary funding for that. Most science-based start-ups, and in particular young biotech firms, do not have the resources needed to buy or lease the expensive facilities they need to validate their research results. Investors are reluctant to provide additional capital to these high-tech start-ups in order to acquire state-of-the-art testing equipment. Without owning or having access to the research equipment, these start-ups cannot demonstrate their scientific results effectively and are unable to seize the claims and opportunities flowing from their disclosures. Because they often lack collateral, a track record, stable cash flow and/or operational profits, science-based start-ups have to find alternative sources and channels of finance. A new government-backed funding scheme to hire and purchase and/or share research equipment, called Mibiton, was developed for the Dutch biotechnology sector to address this problem. We examine the motivation to join and participate in the Mibiton scheme, look into its (dis)advantages and evaluate its additionalities through an exploratory study among its investees. The main findings are that an active investment fund providing relatively small investments, with competitive interest rates, makes start-ups more proactive, allowing them to accelerate product development and market testing in their time-to-market race. Mibiton’s investments make the start-up firms more professional, better prepared financially and, with their claims tested and validated, more future-proof. The affiliation with the Mibiton scheme also sends out a strong quality signal to the venture capital community, hereby increasing the likelihood that the start-ups will succeed in obtaining additional funding in the future.

@en

In this paper we study the influence of the network of actors on the chances that a start-up will be successful in commercializing a platform. Scholars that study platform wars have conducted multiple studies of factors that influence platform dominance where the focus lies on factors that can be influenced by the firm (firm-level factors) and factors that are given in specific industries which can hardly be influenced by firms (environmental factors). Few studies have included views from platforms and entrepreneurship to understand the successful commercialization of new platform. A common research approach in both fields of platforms and entrepreneurship is network analyses. In this paper we conceptualize how entrepreneurs can apply network strategies to successfully commercialize their new products in an emerging market in the first phases of the technology dominance process. We illustrate our ideas by means of several examples.@en

In today's society a variety of challenges need attention because they are considered to affect our well-being. Many of these challenges can be addressed with new innovations, yet they may also introduce new challenges. Communication of these new innovations is vital. This importance is also addressed by the concept of Responsible Research and Innovation. In the present commentary we draw on a dataset of 196 research projects and discuss the two research streams of Science Communication and Responsible Research and Innovation and how they are complements to each other. We conclude with suggestions for practitioners and scientists.@en

Open innovation is a relatively new approach to developing a business model for managing innovation within companies and public organizations. It was introduced by Chesbrough1as a business model concept with a more flexible approach to innovation management that would stimulate the flow of external knowledge into the company as well as the transfer of internal know-how and technology to external parties. This in turn would increase the effectiveness of innovation management and thus the innovation outcome and eventual revenue and profits.This open innovation approach has added a new perspective on conducting innovation activities. Before, innovation was mainly an internal, in-house R&D activity for most firms.In particular, for large firms in the 1980s and early 1990s, the main strategy was to grow larger through diversifying into related markets. The internal R&D department then contributes through developing platform technologies that are applied in a variety of products in each of the lines of business. Following this strategy, R&D departments could learn from one line of business and apply that to another line of business. In this approach the company would benefit from R&D department economies of scope. The returns of R&D are then expected to be high, since the findings from single R&D activities could benefit various kinds of products and multiple lines of business.Despite these positive contributions of internal R&D and closed innovation, the open innovation approach has gained much interest among firms, especially among large firms.Similarly, smaller firms such as SMEs (small and medium-sized enterprises) and start-ups and research organisations such as universities and academic institutes do benefit as well from the trend of more open innovation. The search for more flexibility in their R&D activities has turned the interest of established firms toward small and innovative firms that are developing new technologies, as well as research organisations that are conducting basic research and new technology development. These considerations result in a number of interesting questions to investigate, such as, what are the reasons that large companies changed their innovation toward a more flexible and open innovation approach? What actually is an“open innovation” approach and how does it differ from traditional in-house R&D and innovation activities? What are the (dis)advantages and the associated challenges of open innovation?Furthermore, it is an approach that emerged in developed countries. The question at hand is also how it manifests in emerging countries. Is it relevant as well and how do SMEs in emerging countries engage in open innovation activities? In order to answer these questions, we discuss the principles of open innovation and how it becomes more beneficial for mostly small firms within emerging economies. We then discuss the case of Turkey and the effects of innovation strategy and university collaboration on the performance of Turkish SMEs.@en