Developing ecological index for identifying roles of ICT industries in mobile ecosystems: The inter-industry analysis approach

Suh, Yongyoon; Lee, Hakyeon

doi:10.1016/j.tele.2016.06.007

Cited by 15 publications

(10 citation statements)

References 24 publications

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“…Among those, investments, corporate strategy, corporate approach, and resource for realization are challenged in industry 4.0 projects. The rest of those are basically seen in reviews and maturity models (see, e.g., [14][15][16][17]).…”

Section: Strategic Viewmentioning

confidence: 99%

A Taxonomy of Industry 4.0 and Related Technologies

Öztemel¹,

Gürsev²

2020

Industry 4.0 - Current Status and Future Trends

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Industry 4.0 and related technologies will remain at the top agenda of manufacturing systems until respective digital transformation is completed. In order to increase the speed of the transformation and the respective performance, a taxonomy of industry 4.0 is proposed in this chapter. The taxonomy is defined through four aspects including strategic understanding, managerial practices, technological infrastructure and developments, as well as human intervention with respective skills and competencies. Each aspect of these is defined and further subcategorized in order to reveal the real dynamics of industry 4.0 and respective implementations. Generating the taxonomy would also easy the categorization of the respective efforts and make the assessment processes to be carried out more effectively. It is also believed that the proposed taxonomy will be the source of generating a maturity model of industry 4.0. Note that the proposed taxonomy and respective components are defined by reviewing 620 papers, maturity models, and industry 4.0 projects.

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Section: Strategic Viewmentioning

confidence: 99%

A Taxonomy of Industry 4.0 and Related Technologies

Öztemel¹,

Gürsev²

2020

Industry 4.0 - Current Status and Future Trends

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“…As a matter of fact, we believe that the network theory presents the best methodological frame for describing and analyzing the business or industrial ecosystems. Indeed, many ecosystem studies represent their ecosystems with various networks (e.g., [4], [5], [6], [7], [24], [34], [35]). The network approach is also flexible enough to represent and deal with different levels of ecosystems (e.g., at the firm or industry level) in a consistent way.…”

Section: Literatures and Research Backgroundsmentioning

confidence: 99%

“…Then, equation ⑴ can be transformed as follows. (called multiplier or spill-over effect in [18], [35]).…”

Section: Io Modelmentioning

confidence: 99%

Understanding the Robot Ecosystem: Don't lose sight of either the trees or the forest

Kim

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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The robot sector in many countries has thrived recently thanks to government supports and innovations in various industries. This study, using the patent database to define the robot sector, reconfigures IO (Input-Output) data to analyze the relationships among various sectors. In particular, we consider the internal description of the robot sector (mesoscopic view-the trees) as well as the relationship between the robot and the non-robot sectors (macroscopic view-the forest), so that we can not only understand robot ecosystems in various dimensions, but also develop policy insights. For the sake of systematic analysis of the intra-and inter-sector relations as well as the meso-macro links, this study constructs network models and employs several network measures. Our model and analysis present a good case study to understand the nature of the robot sector in terms of the business ecosystem. This novel approach also contributes to finding out a promising path that leverages the strengths of intrasector relations and spreads the impact of the robot sector across the macro relations.

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“…The most commonly considered by researchers stakeholders are a (mobile) platform provider (MPP, 12 studies), a mobile device manufacturer (MDM, 10 studies), a mobile network operator (MNO, 10 studies), an application developer (DEV, 10 studies), and a content provider (CP, 8 studies). (Karhu et al, 2014) CP, DEV, MDM, MNO, MPP; ad service provider (Oh et al, 2015) DEV, MPP (MNO and MDM) (Gao and Krogstie, 2015) CP, DEV, MDM, MNO, MPP; regulators, end users (Lee et al, 2016) DEV, MDM, MNO, MPP; network & infrastructure providers, internet service providers (Suh and Lee, 2017) CP, DEV, MDM, MNO, MPP; silicon vendors & component providers, media service providers, internet service providers (Nieborg and Helmond, 2018) CP, MPP; end users, advertisers, and "others" Surprisingly, the main stakeholders of the mobile ecosystem have not significantly changed since the early mobile ecosystem studies 1 (Basole and Karla, 2011;Xia et al, 2010). However, the function and ownership of mobile platforms have considerably evolved.…”

Section: Past Evolution Of the Mobile Ecosystemmentioning

confidence: 99%

Technology and value network evolution in telehealth

Vesselkov

Hämmáinen

Töyli

2018

Technological Forecasting and Social Change

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Vesselkov, Hämmäinen, and Töyli formed the idea, constructed models and scenarios. Vesselkov conducted the interviews and wrote the paper. Hämmäinen and Töyli edited the text.Publication IV: "Design and governance of mHealth data sharing" Vesselkov formed the idea, collected the data, conducted interviews and wrote the paper. Hämmäinen and Töyli provided comments on the analysis and edited the text.Publication V: "Internet of things (IoT) platform competition: consumer switching versus provider multihoming" Basaure and Vesselkov formed the idea. Basaure designed the model, run the simulations, and wrote most of the paper. Vesselkov supported the modeling, wrote Sections 2.5 and 2.6, commented other sections, and edited the text. Töyli provided comments on the analysis and edited the text. Publication VI: "Technology and Value Network Evolution in Telehealth"Vesselkov, Hämmäinen, and Töyli formed the idea. Vesselkov collected the data and wrote the paper. Hämmäinen and Töyli provided comments on the analysis and edited the text. RQ1. How do mobile IoT usage patterns differ from consumer devices and across industries?RQ2. How could embedded SIM technology affect the mobile ecosystem? RQ3. How could collaboration and competition be governed in emerging consumer IoT data platforms and particularly mobile health data platforms? RQ4. How could mobile platform providers acting as mobile health data platform providers position themselves in the ecosystem of the healthcare industry?

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Developing ecological index for identifying roles of ICT industries in mobile ecosystems: The inter-industry analysis approach

Cited by 15 publications

References 24 publications

A Taxonomy of Industry 4.0 and Related Technologies

A Taxonomy of Industry 4.0 and Related Technologies

Understanding the Robot Ecosystem: Don't lose sight of either the trees or the forest

Technology and value network evolution in telehealth

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