Evidence map›Paper›PMID 38370194›Full record

ArticleHeliyon2024

Exploring business models for managing uncertainty in healthcare, medical devices, and biotechnology industries.

Ehsan Javanmardi, Petra Maresova, Naiming Xie, Rafał Mierzwiak

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ehsan JavanmardiCollege of Economics & Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Petra MaresovaFaculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic.
Naiming XieCollege of Economics & Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Rafał MierzwiakFaculty of Engineering Management, Poznan University of Technology, Poznan, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The medical devices, biotechnology, and healthcare industries are closely tied to innovation, with companies relying on research and development and new product introduction. However, innovation activities like research and development can be costly, and commercializing new products faces complexities. Having effective business models (BMs) aligned with such innovation activities is crucial. This study delves into the intricacies of BMs in these innovator companies, emphasizing the pivotal role of effective BMs in navigating uncertainties and fostering innovation. This study conducted a systematic literature review to synthesize knowledge on BMs in innovator health-tech companies and compare models on dimensions like infrastructure, offering, customers, and finances. The review of 34 recent papers revealed 9 key BMs - open innovation, sustainable, dynamic, dual, spin-off, frugal, high-tech entrepreneurial content marketing, back-end, and product-service systems BMs. The analysis found open innovation, sustainability, and dynamicity as foundational models that can serve as a basis when combined with others. The paper unveils a tailored Dynamic Sustainable Business Model (DSBM) for Health-Tech, designed to integrate adaptability and sustainability, providing a framework for companies to leverage emerging technologies effectively. Additionally, a conceptual framework outlining 28 groups of uncertainty factors in BMs was developed to aid risk management in health-tech. The findings offer crucial insights for companies in health-tech industries, aiding them in managing innovation and value creation amidst a rapidly evolving landscape.

Indexed as

Business modelsHealthcareHealth-techInnovationSustainabilityUncertainty

Identifiers

PMID38370194
PMCPMC10869869

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.