Convergent Innovation in Emerging Healthcare Technology Ecosystems: Addressing Complexity and Integration

Phillips, Mark A.; Harrington, Tomás Seosamh; Srai, Jagjit Singh

doi:10.22215/timreview/1105

Cited by 16 publications

(9 citation statements)

References 33 publications

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“…Another way to understand this difficulty is that personalized medicine is "underpinned" by convergent, cross-industry innovation. This naturally results in complexity, and uncertainty in terms of organization ( [7]: p. 44). The question becomes how best to innovate given this challenge of cross-industry integration.…”

Section: Challenges Of Human-machine Innovationmentioning

confidence: 99%

“…In this context, the management of risk might best be replaced with addressing uncertainty, understanding that in an emerging ecosystem of convergent innovation, comprehensive understanding is lacking. Approaches that embrace complexity rather than just managing it might prove more effective, specifically by adopting numerous measures to address the divergent factors in cross-industry innovation ( [7]: pp. 51-52).…”

Section: Challenges Of Human-machine Innovationmentioning

confidence: 99%

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The Machine-Human Collaboration in Healthcare Innovation

Kela-Madar¹,

Kela²

2020

Toward Super-Creativity - Improving Creativity in Humans, Machines, and Human - Machine Collaborations

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The biopharma industry is in crisis, demonstrated by unsustainable research and development (R&D) costs. In parallel, the healthcare system suffers from skyrocketing costs, driven by the prevalence of chronic diseases and increased life expectancy. Innovative technologies have the potential to alleviate challenges both in the biopharma R&D model and in healthcare. This chapter considers how Big Data analysis based on artificial intelligence and machine learning offer opportunities to drive greater efficiency across the entire R&D value chain, enhance the quality of assets produced, and improve the time and cost to bring products to market. We also consider the unique challenges that arise with the integration of these fields into healthcare and medicine, specifically, the initially high costs when new medical and healthcare technologies are brought to the marketplace; widening socioeconomic health inequalities due to high marketplace costs; and unique methodological challenges presented by cross industry innovation, research, development, and implementation.

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Section: Challenges Of Human-machine Innovationmentioning

confidence: 99%

Section: Challenges Of Human-machine Innovationmentioning

confidence: 99%

The Machine-Human Collaboration in Healthcare Innovation

Kela-Madar¹,

Kela²

2020

Toward Super-Creativity - Improving Creativity in Humans, Machines, and Human - Machine Collaborations

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“…Digitalisation within healthcare doesn't just relate to wearable-devices, it is about the convergence of multiple technologies (Phillips, Harrington and Srai 2017). Crucially, with a future focus on niche and personalised products serving new and multi-faceted markets, updated distribution and production methods will be required (Srai & Alinaghian, 2013).…”

Section: Technology Developmentsmentioning

confidence: 99%

Connecting digital pharma and e-healthcare value networks through product-service design: a conceptual model

Harrington

Burge

2018

IJEH

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With the move towards more 'outcome' and 'value'-based treatment regimensincreasingly tailored for the individual patientthere is growing pressure on healthcare systems and the pharmaceutical sector to collaborate and co-develop innovative models of care and medication. This paper focuses on the impact disruptive digital technologies may have on the UK Pharma/National Health Service (NHS) ecosystem, and is set within the boundaries of treating chronic diseases. A comprehensive generic model for designing more 'connected' value networks is developed, and validated by an expert panel in the specific case of type 2 diabetes. An underlying 'disconnection' between e-healthcare and pharma value networks, operating as independent entities, is demonstrated. Moreover, the extant literature details only simple product-fee relationships, without considering the value potential of more digitally connected partnerships. Hence, we explore the potential for emerging product-service system (PSS) concepts involving, for example, health information exchange mechanisms, interoperability and data analytics, wearable technologies, and patient Apps. Scenarios involving more distributed 'make-to-order' service models are also represented by the model-demonstrating the potential for technologies, such as 3D printing, to enable localised and personalised medication manufacture Underpinned by the literature on digital/IoT-based business models and PSSs, the conceptual model reduces complexity and provides practical guidance on future operating principles and protocols to be used in the design and implementation of improved e-healthcare solutions. In turn, this enables stakeholders to better understand potential relationships, serviceable aspects, data flows and revenue streams. Through use of the model, various disparities in key stakeholder perspectives are also captured in this paper. Findings include concerns on the collection and use of patient data, except if partnering mechanisms with the NHS were in place, and when devices/services could be provided for free. Stakeholder viewpoints expressing a preference to be at the centre of data collection, disagreement over data ownership and financial models, and the difficulty in establishing partnerships from a wearables technology provider perspective are highlighted.

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Section: Managerial Contributionmentioning

confidence: 99%

“…The illustration of the ecosystem business model creates an opportunity for shared sensemaking, thus acting as a cognitive tool for business model design. Thus, it can provide firms a conceptual tool (Magretta, 2002;Osterwalder et al, 2005;Wirtz et al, 2016) for orchestrating the activities among the different actors (Pikkarainen et al, 2017) and for addressing complexity and integration in the ecosystem (Phillips et al, 2017).Application of service-dominant logic to IoT ecosystems can provide highly relevant avenues for practitioners in the IoT. Lusch and Nambisan (2015) argue that, in service co-creation, it is necessary not only to define the roles but also to create supportive environments for the integration of resources.…”

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confidence: 99%

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2018

TIM Review

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Except where otherwise noted, all content is licensed under a Creative Commons Attribution 3.0 License. The PDF version is created withScribus, an open source desktop publishing program. OverviewThe Technology Innovation Management Review (TIM Review) provides insights about the issues and emerging trends relevant to launching and growing technology businesses. The TIM Review focuses on the theories, strategies, and tools that help small and large technology companies succeed.Our readers are looking for practical ideas they can apply within their own organizations. The TIM Review brings together diverse viewpoints -from academics, entrepreneurs, companies of all sizes, the public sector, the community sector, and others -to bridge the gap between theory and practice. In particular, we focus on the topics of technology and global entrepreneurship in small and large companies.We welcome input from readers into upcoming themes. Please visit timreview.ca to suggest themes and nominate authors and guest editors. ContributeContribute to the TIM Review in the following ways:• Read and comment on articles.• Review the upcoming themes and tell us what topics you would like to see covered.• Write an article for a future issue; see the author guidelines and editorial process for details.• Recommend colleagues as authors or guest editors.• Give feedback on the website or any other aspect of this publication.• Sponsor or advertise in the TIM Review.• Tell a friend or colleague about the TIM Review.Please contact the Editor if you have any questions or comments: timreview.ca/contact About TIMThe TIM Review has international contributors and readers, and it is published in association with the Technology Innovation Management program (TIM; timprogram.ca), an international graduate program at Carleton University in Ottawa, Canada. Technology Innovation Management ReviewMarch 2018 (Volume 8, Issue 3) 3 timreview.ca tion, even when complete opening is not the main goal. The author highlights the scholarly contribution of the study and provides general recommendations for innovation managers.Finally, Flavia Luciane Scherer, Italo Fernando Minello, Cristiane Krüger, and Andréa Bach Rizzatti from the Federal University of Santa Maria in Brazil describe a technology startup's failed early attempt at internationalization and the lessons its founders are applying as they contemplate a second attempt to grow beyond the Brazilian market. Drawing on the literature on internationalization (especially the Uppsala model), export barriers, and the origin and concept of startups, the authors share insights from the case and derive recommendations to help technology startups in emerging economies successfully internationalize.In April, we will examine the theme of Frugal Innovation with Guest Editors Deepak S. Gupta, Executive Director of Applied Research, Innovation and Entrepreneurship Services (ARIES) at Centennial College in Toronto, Canada, and Mokter Hossain, Assistant Professor in the Center for Industrial Production at Aalborg Univer...

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Convergent Innovation in Emerging Healthcare Technology Ecosystems: Addressing Complexity and Integration

Cited by 16 publications

References 33 publications

The Machine-Human Collaboration in Healthcare Innovation

The Machine-Human Collaboration in Healthcare Innovation

Connecting digital pharma and e-healthcare value networks through product-service design: a conceptual model

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