Sustainable level of human performance with regard to actual availability in different professions.
BACKGROUND: In a real working environment, workers' performance depends on the level of competence, psychological and health condition, motivation, and perceived stress. These are the attributes of actual availability. It is crucial to identify the most influential attributes to develop an adequate...
| Publicado en: | Work Vol. 65; no. 1; pp. 205 - 214 |
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| Autores principales: | , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=141399270&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141399270 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10519815 3RC jtl: Work issn: 10519815 maglogo: N pubinfo: dt: 2020 vid: 65 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 141399270 141399270 141399270 10.3233/WOR-193050 141399270 ppf: 205 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Sustainable level of human performance with regard to actual availability in different professions. aug: au: Molan, Gregor Molan, Marija affil: Comtrade Digital Services, Ljubljana, Slovenia sug: subj: Job Performance Wellness Work Psychosocial Factors Human Models, Theoretical Artificial Intelligence Decision Trees Algorithms Cluster Analysis Machine Learning Work Environment Stress, Occupational Clinical Assessment Tools Blue Collar Workers Psychosocial Factors White Collar Workers Psychosocial Factors Banks Firefighters Natural Environment Health Personnel Probability Descriptive Statistics Psychological Well-Being Motivation Mental Fatigue Affect Fatigue Investments ab: BACKGROUND: In a real working environment, workers' performance depends on the level of competence, psychological and health condition, motivation, and perceived stress. These are the attributes of actual availability. It is crucial to identify the most influential attributes to develop an adequate level of worker's performance. OBJECTIVE: The purpose of this paper is to upgrade the Availability-Humanization-Model (AH-Model) with an implementation of the artificial intelligence classification tree to identify influencing factors of the well-being attributes on human performance, where the identified influencing factors are gripping points for maintaining sustainable performance in real-life conditions of different professions. METHODS: Well-being attributes are collected with the Questionnaire Actual Availability (QAA) from AH-Model and then analysed by implementation of the decision trees classification algorithms. An embedded clustering analysis of QAA ensures an efficient feature construction and selection. It negates the need of applying tree pruning or any other noise reduction algorithms. RESULTS: An implementation of the machine learning algorithms reflects the real conditions of working environments: (a) real performance of workers depends on the perception of well-being and availability and (b) the most influencing factors explicitly reflect the content of work in a specific domain (Fintech, health, forestry, traffic) with a high level of stress. CONCLUSIONS: The presented approach offers a possibility to identify the most important well-being attributes to determine an adequate efficiency and to improve the performance level in the real working conditions. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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