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.
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.
The “policy mix” concept has gained popularity among science, technology and innovation policy communities over the past two decades in a context of growing policy complexity and need for policy evidence. Pressing societal challenges are also prompting governments to rethink policy making in order to better align public intervention across policy domains and leverage the transformative potential of system innovations. Governments faced multiple obstacles in implementing a policy mix approach in policy making and evaluation. Based on a comparative analysis of international STI policy repositories, a conceptual framework is proposed, as well as structuring principles and operational guidelines for mapping the composition of a policy mix, identifying interactions among components and translating the mapping into measurement. In that view, a range of new policy mix metrics is introduced. Finally, the discussion focuses on the need for moving towards a new data management paradigm and enlarging the measurement mix.
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.
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.
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.