A Business Model Framework for Crowd-Driven IoT Ecosystems

Ziouvelou, Xenia; McGroarty, Frank

doi:10.4018/ijsesd.2018070102

Cited by 4 publications

(3 citation statements)

References 49 publications

(12 reference statements)

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“…, 2021). By introducing cutting-edge technology such as artificial intelligence (AI) and BCT into the mHealth care system, I4.0 principles can link the virtual network with the actual environment; this also addresses the various barriers related to intellectual technologies (Ziouvelou and McGroarty, 2018). Kamble et al .…”

Section: Literature Reviewmentioning

confidence: 99%

“…Industry 4.0 was established through the application of contemporary information technologies, including cyber-physical systems, the Internet of things and data analytics (big data) (Madanian et al, 2019a(Madanian et al, , 2019bSimeone et al, 2021). By introducing cutting-edge technology such as artificial ISM analysis of barriers of mHealth adoption intelligence (AI) and BCT into the mHealth care system, I4.0 principles can link the virtual network with the actual environment; this also addresses the various barriers related to intellectual technologies (Ziouvelou and McGroarty, 2018). Kamble et al identified twelve challenges to the adoption of Industry 4.0 in various manufacturing sectors in 2018.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Continuous improvements in technology relating to wireless technology, Internet of things (IoT) and artificial intelligence have led to the emergence of a hyper-connected world. This has enabled practitioners and researchers to develop methods of practical implementation of intellectual technologies in mobile healthcare services (Ziouvelou and McGroarty, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Swain

Muduli

Luthra³

2023

IJIEOM

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PurposeThe goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.Design/methodology/approachPotential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.FindingsThe study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.Practical implicationsPromoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.Originality/valueAt this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Swain

Muduli

Luthra³

2023

IJIEOM

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Interconnected business models: present debates and future agenda

Jocevski

Arvidsson

Ghezzi

2020

JBIM

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Purpose The purpose of this study is to provide a review of the emergent literature to advance the current understanding of the business model (BM) concept in a context in which more than one actor is actively involved in the development and delivery of a joint offer based on information and communication technologies. Design/methodology/approach The paper uses a systematic literature review approach. The review is based on 25 systematically selected publications published from 2000 to 2018 and retrieved from bibliographic databases and through a process of snowballing. Findings The authors found several alternative conceptualizations of a BM at a network level, which highlighted different elements as core components. Based on this, authors’ findings suggest the literature has a fragmented view of what the BM concept entails at a network level, and of which actors are relevant. Conversely, there is a consensus that a single-firm view is inadequate for describing and studying joint value architectures because of its inability to consider all involved actors and their activities and resources. Therefore, a network-oriented view, as a relational aggregator, is seen as a possible way forward. Originality/value The study contributes to the current understanding of a BM concept at a network level and suggests three viewpoints from which to interpret value architectures at different levels of analysis: single-firm view, dyadic-level view and network-oriented view. Furthermore, the authors highlight several gaps to be studied and provide avenues for future research opportunities for scholars.

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Smart City IoT Services Creation Through Large-Scale Collaboration

Cirillo¹,

Gómez²,

Díez

et al. 2020

IEEE Internet Things J.

112

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Smart cities solutions are often monolithically implemented, from sensors data handling through to the provided services. The same challenges are regularly faced by different developers, for every new solution in a new city. Expertise and know-how can be re-used and the effort shared. In this article we present the methodologies to minimize the efforts of implementing new smart city solutions and maximizing the sharing of components. The final target is to have a live technical community of smart city application developers. The results of this activity comes from the implementation of 35 city services in 27 cities between Europe and South Korea. To share efforts, we encourage developers to devise applications using a modular approach. Single-function components that are re-usable by other city services are packaged and published as standalone components, named Atomic Services. We identify 15 atomic services addressing smart city challenges in data analytics, data evaluation, data integration, data validation, and visualization. 38 instances of the atomic services are already operational in several smart city services. We detail in this article, as atomic service examples, some data predictor components. Furthermore, we describe real-world atomic services usage in the scenarios of Santander and three Danish cities. The resulting atomic services also generate a side market for smart city solutions, allowing expertise and know-how to be re-used by different stakeholders.

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A Business Model Framework for Crowd-Driven IoT Ecosystems

Cited by 4 publications

References 49 publications

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Interconnected business models: present debates and future agenda

Smart City IoT Services Creation Through Large-Scale Collaboration

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