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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Academia.edu
(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

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Quantitative Endosurgery Process Analysis by Machine Learning Method
Bojan Nokovic, Andrew Lambe
(pages: 1-7)

Modelling Student Performance in a Structural Steel Graduate-Based Module: A Comparative Analysis Between K-Nearest Neighbor and Dummy Classifiers
Masengo Ilunga, Omphemetse Zimbili, Phahlani Mampilo, Agarwal Abhishek
(pages: 8-15)

Interoperable Digital Skills for Foreign Languages Education in the COVID-19 Paradigm
Rusudan Makhachashvili, Ivan Semenist, Iryna Vorotnykova
(pages: 16-20)

Education, Training and Informatics Go Hand in Hand in (Foreign) Higher Education Institutions (HEIs) – Case Studies From Live and Online Classrooms
Ekaterini Nikolarea
(pages: 21-29)

Enhancing Pedagogical and Digital Competencies Through Digital Tools: A Proposal for Semi-schooled Language Teaching Programs in Oaxaca, Mexico
José de Jesús Bautista Hernández, Eduardo Bustos Farías, Norma Patricia Maldonado Reynoso
(pages: 30-35)

Railway Track Degradation Modelling Using Finite Element Analysis: A Case Study in South Africa
Ntombela Lunga, Masengo Ilunga
(pages: 36-50)

Continuum of Academic Collaboration: Issues of Inconsistent Terminology in Multilingual Context
Cristo Leon, James Lipuma, Marcos O. Cabobianco, Maria B. Daizo
(pages: 51-62)

Peat Resource Management and Climate Change Mitigation Issues – Case of Latvia
Anita Titova, Natalja Lace
(pages: 63-70)

Using Geospatial Computation Intelligence for Mapping Temporal Evolution of Urban Built-up in Selected Areas of the Ekurhuleni Municipality, South Africa
Jo-Anne Correia, Masengo Ilunga
(pages: 71-80)

Cybernetics and Informatics of Generative AI for Transdisciplinary Communication in Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 81-88)

Navigating Psychological Riptides: How Seafarers Cope and Seek Help for Mental Health Needs
Coleen Abadicio, Stella Louise Arenas, Rosette Renee Hahn, Angel Berry Maleriado, Ramon Miguel Mariano, Rodolfo Antonio Ma. Zabella, Genejane Adarlo
(pages: 89-98)


 

Abstracts

 


ABSTRACT


Attrition of Knowledge Workforce in Healthcare in Northern parts of India – Health Information Technology as a Plausible Retention Strategy

Indrajit Bhattacharya, Anandhi Ramachandran, R.K. Suri, S.L. Gupta


Faced with a global shortage of skilled health workers due to attrition, countries are struggling to build and maintain optimum knowledge workforce in healthcare for delivering quality healthcare services. Forces that affect healthcare professionals’ turnover needs to be addressed before a competent uniformly adoptable strategy could be proposed for mitigating the problem. In this study we investigate the effects of the socio–demographic characteristics on attrition of healthcare knowledge workforce in northern parts of India that have a wide gradient of rural and urban belt, taking into account both public and private healthcare organizations. For this purpose healthcare professional attrition tracking survey (HATS) was designed. The data has been collected from a random sample of 807 respondents consisting of doctors, nurses, paramedics and administrators to explore the relationships between various factors acting as antecedents in affecting the job satisfaction, commitment and intention of a healthcare professional to stay in the job. Structured questionnaires were utilized as the data collection tools. Descriptive statistics, factor analysis and path analysis were carried out using multiple regression and correlation to propose a model that best explains the theoretical assumption of factors leading to attrition. Six factors of attrition namely compensation and perks, work life balance, sense of accomplishment, work load, need for automation and technology improvement, substandard nature of work have been identified as the main factors with a data reliability of 0.809%. It has also been identified that the intention to shift is a major decision maker that affects attrition and in turn affected by job satisfaction dimensions. Based on the survey response and analysis, a highly possible strategy of utilizing information technology implementation for increasing worker motivation, job satisfaction and commitment to reduce attrition has been proposed.

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