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Data describing the regional Industry 4.0 readiness index.

ABSTRACT: The data article presents a dataset suitable to measure regional Industry 4.0 (I4.0+) readiness. The I4.0+ dataset includes 101 indicators with 248 958 observations, aggregated to NUTS 2 statistical level) based on open data in the field of education (ETER, Erasmus), science (USPTO, MA-Graph, GRID), government (Eurostat) and media coverage (GDELT). Indicators consider the I4.0-specific domain of higher education and lifelong learning, innovation, technological investment, labour market and technological readiness as indicators. A composite indicator, the I4.0+ index was constructed by the Promethee method, to identify regional rank regarding their I4.0 performance. The index is validated with economic (GDP) and innovation indexes (Regional Innovation Index).

SUBMITTER: Honti G

PROVIDER: S-EPMC7649474 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Data describing the regional Industry 4.0 readiness index.

Honti Gergely G Czvetkó Tímea T Abonyi János J

Data in brief 20201027

The data article presents a dataset suitable to measure regional Industry 4.0 (I4.0+) readiness. The I4.0+ dataset includes 101 indicators with 248 958 observations, aggregated to NUTS 2 statistical level) based on open data in the field of education (ETER, Erasmus), science (USPTO, MA-Graph, GRID), government (Eurostat) and media coverage (GDELT). Indicators consider the I4.0-specific domain of higher education and lifelong learning, innovation, technological investment, labour market and techn ...[more]

PMID: 33204779

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Project description:BackgroundAs Industry 4.0 debuted roughly a decade ago, it is now necessary to examine how it affects various aspects of the discipline. It is the responsibility of the education sector to guarantee that the next generation is equipped mentally, physically, and cognitively to face unforeseen challenges. Numerous educational institutions are outfitted with Industry 4.0 technology-based learning. Industry 4.0 fosters advancements in learning methodologies, especially for language enhancements. Learners may gain knowledge at their base, providing them an opportunity for independent study. The majority of subjects have been acquired through Industry 4.0. This research chapter explores the intersection of Industry 4.0 and education, specifically focusing on the SmallTalk AI tool. It investigates how technological and digital innovations within the context of Industry 4.0 can serve as powerful tools to enhance language learning outcomes.MethodsThis article presents a comprehensive analysis of statistical data and empirical evidence to support the positive impact of Industry 4.0 technology of SmallTalk on language acquisition particularly speaking. The study also determines the relationship among participants' usage through the technology acceptance model (TAM). Furthermore, it examines the challenges and opportunities associated with integrating these innovations into language learning pedagogies, offering insights for educators and policymakers to harness the potential of Industry 4.0 in fostering language proficiency. The research employs quantitative analysis. The data obtained from educational institutions has been analyzed using the SPSS and AMOS software.ResultsThe results indicate that Industry 4.0 has had an important effect on English language acquisition. This self-supported adaptable system of education facilitates effective student learning. This study also suggests that future research into the utility of Industry 4.0 be conducted elsewhere internationally.

Project description:The growing global concern with sustainability has driven companies to rethink their business model and seek new ways to operate and face this challenge. Industry 4.0 (I4.0) has shown itself capable of contributing to the development or reformulation of organizational processes to make them more competitive and sustainable. Thus, this article aims to propose drivers for the development of corporate sustainability via I4.0. To this end, a literature review and content analysis were used as research methods to identify and analyze, in recent scientific literature, boosting elements that enable organizational processes to become more sustainable via I4.0. Based on these elements, six drivers were systematized and proposed: strategy; product and process design; energy and material resources; people; smart production; and supply chain. Each driver was discussed in light of the scientific literature to generate recommendations for companies to develop the economic, social, and environmental dimensions of sustainability. The main theoretical-scientific contribution of this work is the deepening and expansion of the knowledge block that articulates corporate sustainability with I4.0, which strengthens the basis for the development of new research on these topics and creates a reference for the analysis and discussion of empirical studies. As an applied-managerial contribution, the drivers proposed in this work will provide organizations and their managers with a point of reference to effectively move towards sustainability, making their businesses greener, fairer, and more profitable. A limitation of this study is that the proposed drivers were based on the 30 most cited articles and did not consider other sources, such as documentation from companies. Therefore, for future studies, we suggest increasing the article base and include organizational repositories and identify how SMEs can become sustainable through I4.0 in a way that strengthens the social dimension of sustainability.

Dataset Information

Data describing the regional Industry 4.0 readiness index.

Publications

Data describing the regional Industry 4.0 readiness index.

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