Resilient sustainable investment in digital education technology: A stakeholder-centric decision support model under uncertainty
Technological Forecasting and Social Change
; 188, 2023.
Article
in English
| Scopus | ID: covidwho-2246565
ABSTRACT
Investment in education technology (EdTech) is a complex decision problem for universities during the post-Covid era. With the objective to assess the quality and adoptability of education supply chain, a novel analytical evaluation model approach is proposed, based on quality function deployment and combinative distance-based assessment. To deal with uncertainty in the evaluation process, fuzzy theory is integrated into the model. To establish the house of quality matrix, technology-based stakeholders' requirements were identified and classified in four dimensions economic and financial, technology adoption, sustainability, competencies. Moreover, nine supplier criteria were assumed. Based on expert evaluations, the results suggest that financial credit and supplier collaboration are the most prominent attributes to evaluate suppliers, while environmental commitment is sorted as the least important criterion. The results reveal that the three dominant suppliers, which provide the best response to the identified criteria, are providers of cloud service technology. © 2022
Decision making; Decision support systems; E-learning; Engineering education; Quality control; Quality function deployment; Sustainable development; Combinative distance-based assessment; Digitalization of education; Distance-based; Education technology; Multi criteria decision-making; Multicriteria decision-making; Multicriterion decision makings; Sustainable investments; Sustainable supplier selections; Uncertainty; decision support system; digitization; educational development; multicriteria analysis; stakeholder; technology adoption; Supply chains; Multi-criteria decision-making; Sustainable supplier selection
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Technological Forecasting and Social Change
Year:
2023
Document Type:
Article
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