Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

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Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Transfer Learning for Facial Emotion Recognition on Small Datasets
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 1-5)

How to Link Educational Purposes and Immersive Video Games Development? An Ontological Approach Proposal
Nathan Aky
(pages: 6-13)

Application of Building Information Modeling (BIM) in the Planning and Construction of a Building
Renata Maria Abrantes Baracho, Luiz Gustavo da Silva Santiago, Antonio Tagore Assumpção Mendoza e Silva, Marcelo Franco Porto
(pages: 14-19)

Transformative, Transdisciplinary, Transcendent Digital Education: Synergy, Sustainability and Calamity
Rusudan Makhachashvili, Ivan Semenist
(pages: 20-27)

New Online Tools for the Data Visualization of Bivalve Molluscs' Production Areas of Veneto Region
Eleonora Franzago, Claudia Casarotto, Matteo Trolese, Marica Toson, Mirko Ruzza, Manuela Dalla Pozza, Grazia Manca, Giuseppe Arcangeli, Nicola Ferrè, Laura Bille
(pages: 28-32)

Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine
Olena Kopishynska, Yurii Utkin, Ihor Sliusar, Leonid Flehantov, Mykola Somych, Oksana Yakovlieva, Olena Scryl
(pages: 33-40)

D-CIDE: An Interactive Code Learning Program
Lukas Grant, Matthew F. Tennyson, Jason Owen
(pages: 41-46)

Interdisciplinary Digital Skills Development for Educational Communication: Emergency and Ai-Enhanced Digitization
Rusudan Makhachashvili, Ivan Semenist, Ganna Prihodko, Irina Kolegaeva, Olexandra Prykhodchenko, Olena Tupakhina
(pages: 47-51)

Interdisciplinarity in Smart Systems Applied to Rural School Transport in Brazil
Renata Maria Abrantes Baracho, Mozart Joaquim Magalhães Vidigal, Marcelo Franco Porto, Beatriz Couto
(pages: 52-59)

Peculiarities of the Realization of IT Projects for the Implementation of ERP Systems on the Path of Digitalization of Territorial Communities Activities
Olena Kopishynska, Yurii Utkin, Ihor Sliusar, Khanlar Makhmudov, Olena Kalashnyk, Svitlana Moroz, Olena Kyrychenko
(pages: 60-67)


 

Abstracts

 


ABSTRACT


Strategic Data Pattern Visualisation

Carol E. Cuthbert, Noel J. Pearse


Data visualisation reveals patterns and provides insights that lead to actions from management, thereby playing a mediating role in the relationship between the internal resources of a firm and its financial performance. In this chapter, contingent resource-based theory is applied to the analysis of big data, treating its visualisation as a mode of interdisciplinary communication. In service industries in general and the legal industry in particular, big data analytics (BDA) is emerging as a decision-making tool for management to achieve competitive advantage. Traditionally, data scientists have delved into data armed with a hypothesis, but increasingly they explore data to discern patterns that lead to hypotheses that are then tested. These big data analytics tools in the hands of data scientists have the potential to unlock firm value and increase revenue and profits, through pattern identification, analysis, and strategic action. This exploratory mode of working can increase complexity and thereby diminish efficient management decision-making and action. However, data pattern visualisation reduces complexity, as it enables interdisciplinary communication between data scientists and managers through the translation of statistical patterns into visualisations that enable actionable management decisions. When data scientists visualise data patterns for managers, this translates uncertainty into reliable conclusions, resulting in effective management decision-making and action.

Informed by contingent resource theory and viewing these primary and secondary resources as independent variables and performance outcomes such as revenue and profitability as dependent variables, a conceptual framework is developed. The contingent resource-based theory highlights capabilities emerging from the interrelationship between primary and secondary resources as being central to competitiveness and profitability. Data decision-making systems are viewed as a primary resource, while complementary resources are (1) their completeness of vision (i.e., strategy and innovation) and (2) their ability to execute (i.e., operational capabilities). Data visualisation is therefore crucial as a resource facilitating actionable decisions by management, which in turn enhances firm performance. The balance between expert agents’ self-reliance and central control, the entity’s values, task attributes, and risk appetite all moderate the type of data visualisation produced by data scientists.

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