TY - JOUR
T1 - Systems-thinking skills preferences evaluation model of practitioners using hybrid weight determination and extended VIKOR model under COVID-19
AU - Tazzit, Siham
AU - Jing, Liting
AU - Ma, Junfeng
AU - Jaradat, Raed
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/8
Y1 - 2023/8
N2 - The COVID-19 pandemic has resulted in changes in the working environment which shifted the type of systems thinking skills needed for practitioners. These changes include the utilization of a digitalized work environment. To reliably assess practitioners' systems thinking (ST) skills/abilities in a digitalized environment, such as the case of COVID-19, we propose an evaluation approach based on the hybrid weight determination and extended VIKOR model to assess the systems skills of practitioners concerning 7-dimensions of systems thinking. The proposed methodology consists of three phases: the first phase uses a rough set theory to process the assessment data of candidates' systems thinking skills, the ideal interval references of seven systems thinking skills criteria (7-dimension) of practitioners required by an organization is extracted. The second phase is to build a comprehensive weight solution model based on BWM (best-worst method) and entropy weight method (EWM) and analyze the employer's needs under each systems thinking skills dimension. The third phase is to build a new group utility index based on the weight and digital reference and form an extended Vlsekriterijumska Optimizacija I Kompromisno Resenje (E-VIKOR) model to complete the prioritization of practitioners' systems thinking skillset. A case study containing 108 practitioners is conducted to verify the effectiveness of the proposed decision-making model and carry out sensitivity analysis and methods comparison. The results show that the proposed model provides more reliable and robust results for selecting the most appropriate practitioner for the required digitalized job requirements.
AB - The COVID-19 pandemic has resulted in changes in the working environment which shifted the type of systems thinking skills needed for practitioners. These changes include the utilization of a digitalized work environment. To reliably assess practitioners' systems thinking (ST) skills/abilities in a digitalized environment, such as the case of COVID-19, we propose an evaluation approach based on the hybrid weight determination and extended VIKOR model to assess the systems skills of practitioners concerning 7-dimensions of systems thinking. The proposed methodology consists of three phases: the first phase uses a rough set theory to process the assessment data of candidates' systems thinking skills, the ideal interval references of seven systems thinking skills criteria (7-dimension) of practitioners required by an organization is extracted. The second phase is to build a comprehensive weight solution model based on BWM (best-worst method) and entropy weight method (EWM) and analyze the employer's needs under each systems thinking skills dimension. The third phase is to build a new group utility index based on the weight and digital reference and form an extended Vlsekriterijumska Optimizacija I Kompromisno Resenje (E-VIKOR) model to complete the prioritization of practitioners' systems thinking skillset. A case study containing 108 practitioners is conducted to verify the effectiveness of the proposed decision-making model and carry out sensitivity analysis and methods comparison. The results show that the proposed model provides more reliable and robust results for selecting the most appropriate practitioner for the required digitalized job requirements.
KW - Multi-criteria decision approach
KW - Rough set
KW - Systems-thinking skill
KW - Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR)
UR - http://www.scopus.com/inward/record.url?scp=85166017410&partnerID=8YFLogxK
U2 - 10.1016/j.aei.2023.102107
DO - 10.1016/j.aei.2023.102107
M3 - Article
AN - SCOPUS:85166017410
SN - 1474-0346
VL - 57
JO - Advanced Engineering Informatics
JF - Advanced Engineering Informatics
M1 - 102107
ER -