Exploring the Relationship between Abusive Management, Self-Efficacy and Organizational Performance in the Context of Human–Machine Interaction Technology and Artificial Intelligence with the Effect of Ergonomics

Basit Öğe Kaydı
dc.authorid0000-0002-3900-0337
dc.authorid0000-0002-6495-4378
dc.authorid0000-0002-2358-0699
dc.contributor.authorLin, Shanyu
dc.contributor.authorSipahi Döngül, Esra
dc.contributor.authorUygun, Serdar Vural
dc.contributor.authorÖztürk, Mutlu Başaran
dc.contributor.authorHuy, Dinh Tran Ngoc
dc.contributor.authorTuan, Pham Van
dc.date.accessioned2022-02-23T11:39:26Z
dc.date.available2022-02-23T11:39:26Z
dc.date.issued2022
dc.departmentSağlık Bilimleri Fakültesi
dc.description.abstractOur study aims to explore the impact of abusive management and selfefficacy on corporate performance in the context of artificial intelligence-based human–machine interaction technology in enterprise performance evaluation. (2) Methods: Surveys were distributed to 578 participants in selected international companies in Turkey, Taiwan, Japan, and China. To reduce uncertainty and errors, the surveys were rigorously evaluated and did not show a normal distribution, as it was determined that 85 participants did not consciously fill out the questionnaires, and the questionnaires from the remaining 493 participants were used. By using the evaluation model of employee satisfaction based on a back propagation (BP) neural network, we explored the manifestation and impact of abusive management and self-efficacy. Using the listed real estate businesses as an example, we proposed a deep learning BP neural network-based employee job satisfaction evaluation model and a human–machine technology-based employee performance evaluation system under situational perception, according to the design requirements of human– machine interaction. (3) Results: The results show that the human–machine interface can log in according to the correct verbal instructions of the employees. In terms of age and education level variables, employees’ perceptions of leaders’ abusive management and self-efficacy are significantly different from their job performances, respectively (p < 0.01). (4) Conclusions: artificial intelligence (AI)-based human–machine interaction technology, malicious management, and self-efficacy directly affect enterprise performance and employee satisfaction.
dc.identifier.doi10.3390/su14041949
dc.identifier.endpage-en_US
dc.identifier.issn2071-1050
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage-en_US
dc.identifier.urihttps:/dx.doi.org/10.3390/su14041949
dc.identifier.urihttps://hdl.handle.net/20.500.12451/9215
dc.identifier.volume14en_US
dc.identifier.wosWOS:000768980000001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMDPI
dc.relation.ispartofSustainability (Switzerland)
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAbusive Management
dc.subjectArtificial Intelligence
dc.subjectBP Neural Network
dc.subjectEnterprise Performance
dc.subjectErgonomics
dc.subjectHuman– Machine Interface Performance
dc.subjectHuman–machine Interaction Technology
dc.titleExploring the Relationship between Abusive Management, Self-Efficacy and Organizational Performance in the Context of Human–Machine Interaction Technology and Artificial Intelligence with the Effect of Ergonomics
dc.typeArticle

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
lin-shanyu-2022.pdf
Boyut:
4.71 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
[ X ]
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu