Transition and innovation ecosystem – investigating technologies, focal actors, and institution in eHealth innovations

2022 ◽  
Vol 175 ◽  
pp. 121369
Author(s):  
Syuan-Yi Jiang
Keyword(s):  
Innovation Ecosystem

Talent-competitiveness of Hungary — Decline without “Fleurs du Mal”

2016 ◽  
Vol 38 (4) ◽  
pp. 537-558
Author(s):  
Olivér Kovács
Keyword(s):  
Economic Policy ◽  
Education System ◽  
Innovation Ecosystem ◽  
Fleurs Du Mal

This paper offers some ammunition to better understand Hungary’s position in the IMD World Talent Report 2015 (IMD WTR 2015). First, it gives a brief overview of the methodology of the IMD WTR by highlighting its main features. Second, it presents the 2015 ranking and puts the focus on Hungary’s withering talent competitiveness. The paper conveys the message that an overarching and consistent reform package is a must in the education system to foster talent utilisation. However, such a package is likely to be insufficient unless economic policy addresses the relevant shortcomings of the Hungarian innovation ecosystem.

METHODOLOGY FOR DETERMINING PRIORITY NTI MARKETS BASED ON THE REGION'S INDUSTRY SPECIALIZATION

2020 ◽  
Vol 2 (9) ◽  
pp. 80-88
Author(s):  
M. M. MARKHAICHUK ◽  
◽  
M. A. TOBIEN ◽  
Keyword(s):  
Regional Development ◽  
Legal Regulation ◽  
Educational Organizations ◽  
Technology Initiative ◽  
Innovation Ecosystem ◽  
Industry Specialization ◽  
Innovation Activities ◽  
Regional Market ◽  
Vladimir Region ◽  
National Technology

The method proposed in this paper allows us to determine the most promising areas of regional development within the framework of The national technology initiative (NTI) concept, taking into account the region's industry specialization. According to this method, the priority NTI markets for the Vladimir region were evaluated, and a map of the innovation ecosystem was compiled for the TechNet market, which received the highest points in the evaluation. The map shows the main stakeholders of the regional market “TechNet”, such as key enterprises in this area; educational organizations that train qualified specialists in this field; regional executive authorities responsible for legal regulation of innovation activities in the region, etc.

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

scholarly journals Characteristics and Classification of Technology Sector Companies in Digital Health for Diabetes

2021 ◽  
Vol 13 (9) ◽  
pp. 4839
Author(s):  
Satoru Kikuchi ◽  
Kota Kadama ◽  
Shintaro Sengoku
Keyword(s):  
Customer Value ◽  
Business Models ◽  
Digital Health ◽  
Information And Communications Technology ◽  
Smart Devices ◽  
Innovation Ecosystem ◽  
Alliance Networks ◽  
Technology Sector ◽  
Ibm Watson ◽  
Start Ups

In recent years, technological progress in smart devices and artificial intelligence has also led to advancements in digital health. Digital health tools are especially prevalent in diabetes treatment and improving lifestyle. In digital health’s innovation ecosystem, new alliance networks are formed not only by medical device companies and pharmaceutical companies but also by information and communications technology (ICT) companies and start-ups. Therefore, while focusing on digital health for diabetes, this study explored the characteristics of companies with high network centralities. Our analysis of the changes in degree, betweenness, and eigenvector centralities of the sample companies from 2011 to 2020 found drastic changes in the company rankings of those with high network centrality during this period. Accordingly, the following eight companies were identified and investigated as the top-ranking technology sector companies: IBM Watson Health, Glooko, DarioHealth, Welldoc, OneDrop, Fitbit, Voluntis, and Noom. Lastly, we characterized these cases into three business models: (i) intermediary model, (ii) substitute model, and (iii) direct-to-consumer model, and we analyzed their customer value.

Book review: Rama Iyer, Innovation Ecosystem in India

2021 ◽  
Vol 25 (2) ◽  
pp. 261-261
Author(s):  
K. Hariharan
Keyword(s):  
Innovation Ecosystem

Rama Iyer, Innovation Ecosystem in India, 2019, Chennai: Notion Press, 80 pp., ₹150. ISBN: 9781647336622 (Paperback).

scholarly journals A model of an agile organization designed to better manage the COVID-19 crisis

2020 ◽  
pp. 084047042098047
Author(s):  
Fabrice Brunet ◽  
Kathy Malas ◽  
Danielle Fleury
Keyword(s):  
Organizational Structure ◽  
Open Innovation ◽  
Health Centre ◽  
Healthcare Organizations ◽  
Innovation Ecosystem ◽  
The People ◽  
Model Of Management ◽  
Agile Organization ◽  
Decentralized Model ◽  
Lack Of Knowledge

COVID-19 strongly hit healthcare organizations due to three factors: the lack of knowledge of this new virus, the fear of the people, and the continuous modifications in the management of the crisis. This situation required flexibility and adaptability of organizations, as our university health centre demonstrated. It relied on a decentralized model of management based on three pillars: a culture of innovation and creativity, an agile organizational structure, and an open innovation ecosystem and network. These assets were already developed prior to the onset of COVID-19 and helped our organization to better respond to the crisis.

scholarly journals Two Sides of the Same Coin. University-Industry Collaboration and Open Innovation as Enhancers of Firm Performance

2021 ◽  
Vol 13 (7) ◽  
pp. 3866
Author(s):  
Joana Costa ◽  
Ana Rita Neves ◽  
João Reis
Keyword(s):  
Firm Performance ◽  
Open Innovation ◽  
Primary Data ◽  
Company Performance ◽  
Innovation Ecosystem ◽  
Industry Collaboration ◽  
And Performance ◽  
Performance Results ◽  
The Impact ◽  
University Industry

Open innovation is proved to be determinant in the rationalization of sustainable innovation ecosystems. Firms, universities, governments, user communities and the overall environment are called to contribute to this dynamic process. This study aims to contribute to a better understanding of the impact of open innovation on firms’ performance and to empirically assess whether university-industry collaborations are complementary or substitutes for this activity. Primary data were collected from a survey encompassing 908 firms, and then combined with performance indicators from SABI (Spanish and Portuguese business information). Econometric estimations were run to evaluate the role of open innovation and university-industry collaboration in the firm innovative propensity and performance. Results highlight the importance of diversity in collaborations with the academia and inbound open innovation strategy as enhancers of firm performance. The two activities reinforce each other. By testing the impact of open innovation practices on company performance, the need for heterogeneity in terms of contact type and university is also demonstrated. Findings cast light on the need to reformulate existing policy packages, reinforcing the ties with academia as well as the promotion of open innovation strategies. The connection to the innovation ecosystem needs to be further encouraged as well as the promotion of persistent connections with the knowledge sources in an open and multilateral framework.

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