This article seeks to undertake a critical assessment of the changing position of public science in the entrepreneurial ecosystem of the countries on the periphery of European research. These countries are driven by new innovation paradigm based on entrepreneurship, which are implemented within the European Smart specialization strategy (S3). This article argues that S3 is widely implemented in the cohesion countries and, while it provides substantial resources for science, technology, and innovation, it fails to provide sustainability in the public research sector. This has direct implications for policies concerning innovation and entrepreneurial ecosystems. In order to prove the thesis, the article provides theoretical argumentation for emergence of a new innovation paradigm, driven by the rise of the entrepreneurial ecosystem, its incorporation into S3, and a consequent retreat of science policy in favor of entrepreneurial policy. The empirical analysis is focused on the funding trends seen in the business and public research sectors over the last decade (2008–2017), which have clearly shown that S3 has not contributed, despite expectations, to an increase in public expenditure for science. This signifies S3's neglect of public research within entrepreneurial ecosystems and challenges the ability of S3 to reduce wide disparities in research and innovation performance across the European Union. This ultimately endangers the innovation potential of the entrepreneurial ecosystem itself.
Portable ramps are generally used by wheelchair users, provide temporary solution to increase accessibility in their daily lives. Portable ramps should allow for modifications in terms of weight, length, load bearing capacity, ease of handling, storage and further design parameters. Different types of portable ramps can be found in the market; however, their modifications cannot go beyond just length modification, or they allow to select just some restricted width options. However, portable ramps are quite suitable for mass customization concept which helps to satisfy customer while being involved in design step. This study aims to determine the wheelchair users’ expectations and correspondingly to offer a smart mass customization design tool which potential users are able to interact with easily. To this end, a case study is conducted with a rollable ramp which is designed and developed within the scope of 1512 – Entrepreneurship Multi-phase Programme (Teknogirişim Sermaye Desteği Programı) of The Scientific and Technological Research Council of Turkey (TÜBİTAK). The methodology and its implementation are described elaborately, and example of a parametric smart customization tool design are illustrated in this study. First, the preliminary study is explained briefly. Afterward, the desired modification parameters are determined with literature and patent survey as well as observation and interviews with the potential users. After systematic review and evaluation of user experiences, the model is assessed.
The High Technology Small Firms (HTSF) conference is a “boutique” conference, small compared to thematically broader entrepreneurship conferences such as the Babson Kauffman Entrepreneurship Research conference (BKERC) and the Research in Entrepreneurship and Small Business conference (RENT), but specialized on the topics of the emergence and the management of HTSFs.
This paper aims to provide a detailed case study of a corporate foresight for innovation (CFI) project done by the Higher School of Economics’ (HSE) (Moscow, Russia) corporate foresight (CF) unit for a large state-owned Russian service company. It demonstrates how CFI methods lead to recommendations and how these recommendations result in decisions.
Drawing from being part of the project team, review of the project documents and interviews, the case describes a multi-phased CFI project which incorporated several CF methods. Techniques used for the project itself included grand challenges and trend analysis, analysis of best practices through use of benchmarking and horizon scanning, interviews, expert panels, wild card and weak signals analysis, cross impact analysis, SWOT and backcasting. The project used a broad-base of secondary information, expert panels consisting of company experts and HSE CF team personnel, interviews with senior management and an extensive literature review using HSE’s propriety iFORA system.
In all 17 CFI recommendation and over 100 implementation recommendations were made; 94 per cent of the CFI recommendations were accepted with most implemented at the time this case was written. The case also identifies five enabling factors that collectively both helped the CFI project and led to a high rate of recommendation acceptance and one factor that hindered CFI project success.
The case study provides detailed information and insight that can help others in conducting CF for innovation projects and establishes a link between CF methods and innovation-based recommendations and subsequent decisions.
In-depth case studies that show academe and practitioners how CFI leads to recommendations and is linked to subsequent decisions have been identified as a gap in the literature. This paper therefore seeks to address this need by presenting a detailed CF case for a corporate innovation project.
Due to the recent rise in economic development the family sizes in developing countries have become small. This phenomenon demands several policy considerations. Is India ready for it? In this perspective, the paper investigates the impact of a higher level of economic development on average household size in India from 1991 to 2011. Variables such as a higher level of education, health outcomes, the extent of inequality, and urbanization have a negative effect on the average household size. The lower level of poverty is associated with lower level family size in the long run, whereas, infrastructure has a mixed effect. Results show that different religious and social groups have an effect on the family size in India. The results are consistent in state and household level analysis and conclude that a higher level of economic development reduces the family size. Smaller family size faces several problems such as child-rearing, higher divorce rates due to marital conflicts, degradation of children's mental health, land and property disputes, and a low transfer of financial support from children to elderly parents. Therefore, not only the government needs to take cognizance and solve these problems, but also needs to find an appropriate balance between work and family, which is missing currently. This lesson can be useful for many other developing countries to cope up with the reduction in family sizes.
The purpose of this study is to discuss the possibility of setting up a platform for inclusive policymaking process drawing upon the blockchain concept. The study posits that blockchain also has great potentials in non-financial applications, such as in policymaking, where there is a need for bottom-up approaches with more decentralized, distributed and evidence-based processes.
The study makes use of an analogy-based creative design methodology. The design science paradigm has its roots in engineering and the sciences of the artificial (Simon, 1996). As a problem-solving paradigm for solving complex engineering issues, design science seeks to create innovations that define the ideas, practices, technical capabilities and products through which the analysis, design, implementation and use of information systems can be effectively and efficiently accomplished. In the present study, the policy development theories and the logic of blockchain are synthesized to prepare a task model for the “IdeaChain” concept as a platform for creating, sharing and validating novel ideas as well as converting them into policies or new ventures through the funding mechanisms.
The IdeaChain concept is designed and demonstrated through its use in the domain of science, technology and innovation (STI) policy, which can be extended to cover all innovative activities linking the whole process from their emergence, funding, development, implementation and impact upon policy.
Blockchain is mostly discussed in literature with its impact on financial sector. IdeaChain is the first attempt to explore the potentials of blockchain in STI policymaking.
This paper investigates the association between internal barriers to innovation and the propensity of technology-based SMEs to cooperate with universities and research institutes (URIs). We examine empirically two types of internal company barriers – financial and knowledge obstacles to innovation. The data source is the latest edition of the Brazilian Innovation Survey (PINTEC). We analyse the full sample of technology-based SMEs as well as the subsamples of high-tech manufacturing companies and knowledge-intensive business services (KIBS). Financial obstacles are shown to be strongly related to the propensity of KIBS to collaborate with URIs. Knowledge obstacles are moderately related to the propensity of high-tech manufacturing SMEs to collaborate with URIs. We conclude that while URIs have other important roles in the techno-economic system, their perceived contribution to alleviating internal innovation barriers for technology-based SMEs may be less prominent than policy decision-makers in emerging economies may expect.
University-industry innovation networks (UIINs) are important agents of innovation, as they bring together the unique profiles of higher education and industry partners. Knowledge growth in these networks does not happen automatically. We analyze the impact of network density and heterogeneity on knowledge growth in UIINs. Knowledge grows through knowledge transfer, spillover, and knowledge innovation. Knowledge growth is a function of each agent's initial knowledge level, network density, and agent heterogeneity. To analyze these correlates of knowledge growth, we use a knowledge growth model based on multiple agents and simulate knowledge growth in a UIIN. Our results show that network density positively influences knowledge growth. Initially, this positive impact increases and then disappears with a further increase in network density. We also find that heterogeneity moderates the relationship between density and knowledge growth. Through the positive moderating effect of its impact on knowledge innovation, it promotes new knowledge generation in the entire innovation network, thus providing a basis for subsequent knowledge transfer. Our study supports and enriches the contingency view of knowledge growth in innovation networks.
Many startups use Lean Startup (LS). But is it effective? While there are emerging qualitative findings, quantitative evidence does not yet exist. To address this gap, we developed an operationalization of the degree to which startups use LS (Lean Startup Capability, LSC). We then analyzed the LSC-performance relationship. We found a strong and robust relationship. A discussion contextualizes our findings. The LSC operationalization is relevant for research as future efforts can build on and extend it. The contribution to entrepreneurial practice is that we carved out the element of LSC, and showed that LS is indeed linked to performance.
The globalisation trend of the past few decades, driven to a large extent by the proliferation of GVCs, has led to a set of significant changes in patterns of technology upgrading and new modes of interaction between domestic technology efforts and external sources of technological knowledge. Whether this new dynamic will lead to continuing increase in the economic importance of emerging economies will ultimately depend on whether their productivity growth will be driven by technology upgrading, requiring active and coordinated activity orchestrated by a variety of state and non-state actors under diverse sectoral, regional and national innovation systems. The new dynamic also reinforces the focus on local–global interfaces which becomes ever more important once we recognize that in the 21st century technology upgrading challenges depend much more on improvements in connectivity and on the industrial ecosystem. Still, the globalization process experienced in the past few decades—reflected in this collection of papers—may need to be recalibrated in the face of the drastic geopolitical changes that the process itself has brought about.
Research partnerships between university researchers and industry partners are becoming increasingly prevalent. For university researchers, maintaining autonomy is crucial. We explore how researchers strategically manage autonomy in collaborative research partnerships, using a framework to distinguish strategically planned and opportunity-driven behaviour in the process of selecting partners and executing research in partnerships. We then focus on the management of autonomy in setting research directions and managing the research process. We draw on insights from 14 management scholars engaged in collaborative Ph.D. research projects. Based on our analysis, we show that researcher autonomy has two facets: operational and scientific. Researchers are willing to compromise their operational autonomy as a price for industry collaboration. They have a strong need for scientific autonomy when deciding on research direction and research execution. Although they need funding, entering a specific relationship with industry and accepting restrictions on their operational autonomy is a choice. We conclude that researchers’ orientations towards practice and theory affects their choices in partnerships as well as modes of governance.
This book addresses the issue of modern medical innovations management through an inductive approach by looking into cases before putting forward solutions in terms of strategies and tools. It provides a model for the designing and implementation of effective healthcare technology management (HTM) systems in hospitals and healthcare provider settings, as well as promotes a new method of analysis of hospital organization for decision-making regarding technology to show how systematic management using a strategy that balances bottom-up and top-down driven innovations, can deliver better medical technological advances.
Managing Medical Technological Innovations is organized in three parts. Part 1 covers innovation strategies, laying the groundwork and concepts in design thinking. Part 2 follows by presenting the tools available for implementation. And finally, Part 3 uses the case studies of pharmaceutical firms in China and hospital medical record management in Holland to illustrate how these ideas and methodologies have been applied.
As technological innovation plays an important role in today's knowledge economy, the most important output of technology development is intellectual property, which is highly valued for generating a monopoly position in providing payoffs to innovation. In this context, this paper considers Intellectual Property Management (IPM) efficiency based on the Patent Portfolio Model (PPM) to help organizations identify, enhance, and evaluate their technological strength. The Patent Portfolio Model (PPM) is built to assess the advantages and disadvantages of an organization, to identify the opportunities of development potentials and optimal distribution, to support the decision-making for optimizing resource allocation, and to develop a layout for the technical field. The case study of the Research Institute of China shows that this method is feasible and fulfills the needs of different institutions to provide suggestions for R&D technology management. The main finding of the paper is that PPM is an effective tool to be used in strategic planning because it identifies the technology advantages to define offensive and defensive strategies against competitors. The use of IPM and PPM helps decision-makers to visualize and simplify complex decision-making problems.
This study analyzes the conditions for the commercialization of public technologies transferred to the private sector and the subsequent effect on business growth. We focus on the commercial exploitation of technologies transferred by universities and public research institutes (U&PRIs) to companies. The empirical analysis uses detailed information regarding an extensive set of actual instances of public-private technology transfer in Korea (514 cases of technologies transferred by 43 major U&PRIs) to highlight the role of company absorptive capacity and internal innovation capabilities, cooperation with U&PRIs, and the intensity of market competition in determining commercialization success and business growth. We find that the intensity of market competition significantly influenced the paths along which absorptive capacity and internal innovation capacity affected successful commercialization, and successful commercialization in turn affected business growth. Effective partnership is a key factor of the successful commercialization of transferred technologies irrespective of market situations. Absorptive capacity contributes to their short-term success and long-term growth when market competition is strong.
This paper discusses the challenges of technological entrepreneurship education in the current education system and the questions that need to be answered to improve the efficacy and efficiency of technological entrepreneurship education. The nature of technological entrepreneurship requires a diversified set of skills for success; however, the traditional education system focuses on single discipline. Consequently, it is difficult for either engineers and scientists who are lacking managerial skills or management students who are lacking of engineer or science oriented knowledge to be successful. A further concern is that different communities have entirely different perceptions of how entrepreneurship is defined often causing both confusion and disagreement in communications between researchers and educators with each other. The paper considers the existing literature and develops a series of comprehensive questions that still need to be addressed. By answering these questions, the traditional education methods can be transformed to be more appropriate and useful for technological entrepreneurship education.
Universities have become both increasingly entrepreneurial and international over the past few decades. We still, however, know little about the relationship between the two trends. This paper investigates the effect of international exposure of university faculty members on university entrepreneurial culture.
Using a specially constructed dataset of the entrepreneurial activities of 507 computer science faculty members—among whom 138 are returnees—from 21 research-intensive universities in China during 2007–2017, the study empirically investigates the relationship between foreign experience and academic entrepreneurial activity back home. We control for characteristics of the faculty member and the location of the university.
Academic tenure overseas is found to positively affect academic entrepreneurship. The length of stay abroad also affects the relationship: returnee academics with foreign Ph.D. degrees are more likely to start new businesses than returnee academics with shorter postdoc experience overseas. The economic gap between the host (foreign) and home country (China) does not have a statistically significant effect on returnee academic entrepreneurial activity.
To the best of our knowledge, this study is the first to empirically investigate returnee academic entrepreneurship. It provides indications on how foreign educational background affects academics entrepreneurial activities.
Big data projects, including smart-city-related big data projects, are facing an alarmingly high percentage of failure. The reasons behind this phenomenon and the lessons learned from it are well researched. However, big data projects are still failing, as there is a lack of effective models to leverage the lessons learned from previous projects to evaluate an organization’s readiness for a big data project.
In this paper, the authors introduce a novel readiness assessment model. This model leverages the lessons learned from previous projects and the experience of experts to be better prepared for an upcoming smart-city-related big data project. Cities can use the model to evaluate their readiness for this type of project in a structured and comprehensive way that will allow for higher chances of conducting a successful big data project.
To develop the model, hierarchical decision modeling (HDM) and expert judgment quantification were used to provide the categorization and relative ranking of factors that influence smart-city-related big data projects. HDM is an effective way to understand the relationship between multiple factors and allows for expert panels to prioritize those factors. Moreover, desirability functions were used to extend the understanding of the factors’ dynamics and what needs to be done to better prepare for the challenges associated with each factor. Finally, the model was tested by applying it to several smart-city-related big data projects to show its value.
This research highlights the importance of readiness assessment for conducting big data projects and provides a readiness assessment model that cities can use to prepare for an upcoming big data project.