The surveying of the effect of the incentive pays to the degree of the attraction of resources in bank branches through the data mining technique

Massrur, Razieh; Nejad, Akbar Farhoodi; Sami, Ashkan

doi:10.1109/iraniancis.2014.6802590

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Novel applications of ML within performance management include detection of subjectivity in performance appraisal process using text analysis and natural language processing (Abed and El-Halees, 2017), estimation of expertise level of employees using data mining and ordinal regression clustering (Horesh et al , 2016), analysing the impact of financial incentives on efficiency of employees using classification algorithms (Massrur et al , 2014) and profiling of employees to develop customized incentives using classification technique (Petruzzellis et al , 2006).…”

Section: Detailed Analysis Of the Resultsmentioning

confidence: 99%

A review of machine learning applications in human resource management

Garg

Sinha

Kar

et al. 2021

IJPPM

152

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PurposeThis paper reviews 105 Scopus-indexed articles to identify the degree, scope and purposes of machine learning (ML) adoption in the core functions of human resource management (HRM).Design/methodology/approachA semi-systematic approach has been used in this review. It allows for a more detailed analysis of the literature which emerges from multiple disciplines and uses different methods and theoretical frameworks. Since ML research comes from multiple disciplines and consists of several methods, a semi-systematic approach to literature review was considered appropriate.FindingsThe review suggests that HRM has embraced ML, albeit it is at a nascent stage and is receiving attention largely from technology-oriented researchers. ML applications are strongest in the areas of recruitment and performance management and the use of decision trees and text-mining algorithms for classification dominate all functions of HRM. For complex processes, ML applications are still at an early stage; requiring HR experts and ML specialists to work together.Originality/valueGiven the current focus of organizations on digitalization, this review contributes significantly to the understanding of the current state of ML integration in HRM. Along with increasing efficiency and effectiveness of HRM functions, ML applications improve employees' experience and facilitate performance in the organizations.

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Section: Detailed Analysis Of the Resultsmentioning

confidence: 99%