1,720,963 research outputs found
Integrated knowledge visualization and the enterprise digital twin system for supporting strategic management decision
No full textPurpose This paper proposes an integrated knowledge visualization and digital twin system for supporting strategic management decisions. The concepts and applications of strategic architecture have been illustrated with a concrete real-world case study and decision rules of using the strategic digital twin management decision system (SDMDS) as a more visualized, adaptive and effective model for decision-making. Design/methodology/approach This paper integrates the concepts of mental and computer models and examines a real case's business operations by applying system dynamics modelling and digital technologies. The enterprise digital twin system with displaying real-world data and simulations for future scenarios demonstrates an improved process of strategic decision-making in the digital age. Findings The findings reveal that data analytics and the visualized enterprise digital twin system offer better practices for strategic management decisions in the dynamic and constantly changing business world by providing a constant and frequent adjustment on every decision that affects how the business performs over both operational and strategic timescales. Originality/value In the digital age and dynamic business environment, the proposed strategic architecture and managerial digital twin system converts the existing conceptual models into an advanced operational model. It can facilitate the development of knowledge visualization and become a more adaptive and effective model for supporting real-time management decision-making by dealing with the complicated dependence of constant flow of data input, output and the feedback loop across business units and boundaries.Purpose This paper proposes an integrated knowledge visualization and digital twin system for supporting strategic management decisions. The concepts and applications of strategic architecture have been illustrated with a concrete real-world case study and decision rules of using the strategic digital twin management decision system (SDMDS) as a more visualized, adaptive and effective model for decision-making. Design/methodology/approach This paper integrates the concepts of mental and computer models and examines a real case's business operations by applying system dynamics modelling and digital technologies. The enterprise digital twin system with displaying real-world data and simulations for future scenarios demonstrates an improved process of strategic decision-making in the digital age. Findings The findings reveal that data analytics and the visualized enterprise digital twin system offer better practices for strategic management decisions in the dynamic and constantly changing business world by providing a constant and frequent adjustment on every decision that affects how the business performs over both operational and strategic timescales. Originality/value In the digital age and dynamic business environment, the proposed strategic architecture and managerial digital twin system converts the existing conceptual models into an advanced operational model. It can facilitate the development of knowledge visualization and become a more adaptive and effective model for supporting real-time management decision-making by dealing with the complicated dependence of constant flow of data input, output and the feedback loop across business units and boundaries
Knowledge-based decision support system for improving e-business innovations and dynamic capability of IT project management
No full textEmployability skills of the next generation of Chinese factory workers
No full textPurpose
The main purpose of this study was to develop and test an employability scale in a Chinese context. Moreover, the authors investigated how socioeconomic status indicators (education and occupation of parents, household income and
hukou
, i.e. household registration location) affect the endowment and development of adolescents' employability skills in China.
Design/methodology/approach
Data were collected via paper-based surveys from 1,146 vocational school students in rural and urban areas in China at two points in time one year apart. The authors developed a scale to measure employability skills in China and conducted general linear modeling to test the hypotheses.
Findings
The findings indicate that adolescents whose parents have more education, highly skilled occupations, relatively affluent household income and urban
hukou
are more likely to attain higher employability skills than those from lower socioeconomic status backgrounds. Moreover, adolescents with these background characteristics tend to improve their employability skills more than those without such characteristics. This suggests that social capital may further widen the inequality gap among adolescents.
Research limitations/implications
The framework of employability skills focuses on the general basic transferable employability skills of vocational students. Future studies could develop measures of employability skills for college graduates and widen the measurements of social capital based on the study’s findings. The findings suggest that higher education institutions should be encouraged to integrate resources to improve education inequality between rural and urban regions to the disparity in adolescents' employability skills development.
Originality/value
Building on Western frameworks, the study defines and develops an employability scale in the Chinese context that can be a practical measurement tool for researchers, educators and policymakers. The authors investigated the endowment and development of employability skills in relation to social capital. Exposure to social capital tends to affect an individual's skills and capability development at an early stage, and in the long term, this calls attention to access to quality education between rural and urban youth
Evaluating the Collaborative Ecosystem for an Innovation-Driven Economy: A Systems Analysis and Case Study of Science Parks
No full textNational policies for science parks and innovation have been identified as one of the major driving forces for the innovation-driven economy, especially for publicly funded science parks. To investigate this collaborative ecosystem (government-academia-industry) for growth and sustainable development, this paper proposes a nation-wide economic impact analysis of science parks and innovation policy based on historical data drawn from one of the globally recognized high-technology industrial clusters in Taiwan. Systems thinking with causal loop analysis are adopted to improve our understanding of the collaborative ecosystem with science park policies. First, from a holistic viewpoint, the role of government in a science parks and innovation ecosystem is reviewed. A systems analysis of an innovation-driven economy with a science park policy is presented as a strategy map for policy implementers. Second, the added economic value and employment of the benchmarked science parks is evaluated from a long range perspective. Third, the concepts of government-academia-industry collaboration and policies to innovation ecosystem are introduced while addressing the measures and performance of innovation and applied R&D in the science parks. We conclude with a discussion of lessons learned and the policy implications of science park development and an innovation ecosystem
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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