Practical and Ethical Perspectives on AI-Based Employee Performance Evaluation
Author
Abstract
Suggested Citation
DOI: 10.31219/osf.io/29yej
Download full text from publisher
References listed on IDEAS
- Keyur Patel & Karan Sheth & Dev Mehta & Sudeep Tanwar & Bogdan Cristian Florea & Dragos Daniel Taralunga & Ahmed Altameem & Torki Altameem & Ravi Sharma, 2022. "RanKer : An AI-Based Employee-Performance Classification Scheme to Rank and Identify Low Performers," Mathematics, MDPI, vol. 10(19), pages 1-21, October.
- Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Milan Miric & Nan Jia & Kenneth G. Huang, 2023. "Using supervised machine learning for large‐scale classification in management research: The case for identifying artificial intelligence patents," Strategic Management Journal, Wiley Blackwell, vol. 44(2), pages 491-519, February.
- Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.
- Manav Raj & Justin Berg & Rob Seamans, 2023. "Art-ificial Intelligence: The Effect of AI Disclosure on Evaluations of Creative Content," Papers 2303.06217, arXiv.org.
- Jing Wang & Zeyu Xing & Rui Zhang, 2023. "AI technology application and employee responsibility," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
- Shengxing Yang, 2022. "A systematic literature review on the disruptions of artificial intelligence within the business world: in terms of the evolution of competences [Une revue systématique de la littérature sur les bo," Post-Print hal-03694170, HAL.
- Mengmeng Wang & Xiaoming Pan, 2022. "Drivers of Artificial Intelligence and Their Effects on Supply Chain Resilience and Performance: An Empirical Analysis on an Emerging Market," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
- Oduro, Stephen & De Nisco, Alessandro & Mainolfi, Giada, 2023. "Do digital technologies pay off? A meta-analytic review of the digital technologies/firm performance nexus," Technovation, Elsevier, vol. 128(C).
- Prentice, Catherine & Wong, IpKin Anthony & Lin, Zhiwei (CJ), 2023. "Artificial intelligence as a boundary-crossing object for employee engagement and performance," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-AIN-2023-06-26 (Artificial Intelligence)
- NEP-BIG-2023-06-26 (Big Data)
- NEP-CMP-2023-06-26 (Computational Economics)
- NEP-HRM-2023-06-26 (Human Capital and Human Resource Management)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:29yej. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.