Big data contributions to human resource management: a systematic review

García-Arroyo, José A.; Segovia, Amparo Osca

doi:10.1080/09585192.2019.1674357

Cited by 83 publications

(86 citation statements)

References 51 publications

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“…Across different disciplinary boundaries, research into algorithmic surveillance (Newlands, 2020), people analytics (Gal et al, 2020;Marler & Boudreau, 2017;Tursunbayeva et al, 2018), human resource management (HRM) algorithms (Cheng & Hackett, 2021), and algorithmic control (Kellogg et al, 2020;Veen et al, 2020) is gaining traction. Moreover, these various concepts are studied alongsideand at times interchangeably with -related phenomena including Big Data (Garcia-Arroyo & Osca, 2019), artificial intelligence (Strohmeier & Piazza, 2015;Tambe et al, 2019) and online labor platforms (Duggan et al, 2020;Newlands, 2020;Veen et al, 2020). These terms and developments are often loosely linked to, or aggregated as, 'digital HRM' which, as a broad notion covers a multitude of topics and issues with unclear and ambiguous relations between them (Strohmeier, 2020b).…”

Section: Introductionmentioning

confidence: 99%

Algorithmic human resource management: Synthesizing developments and cross-disciplinary insights on digital HRM

Meijerink

Boons

Keegan

et al. 2021

The International Journal of Human Resource Management

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Section: Introductionmentioning

confidence: 99%

Algorithmic human resource management: Synthesizing developments and cross-disciplinary insights on digital HRM

Meijerink

Boons

Keegan

et al. 2021

The International Journal of Human Resource Management

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“…1-6) and employees (Nos. [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. Based on the features of the management team, we can check company-related information (e.g., the scale of the company) rather than employee-related information.…”

Section: B Data Sourcesmentioning

confidence: 99%

“…Notably, in the field of HRM, researchers are interested in the application of big data. The analysis of big data facilitates better decision-making processes in various HRM practices, including competitiveness, innovation, and efficiency in an organization [15,16]. In addition, recent studies have shown that the application of various analysis methods has led to the identification of latent patterns or relationships [17,18].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Framework for Multi-Level Classification of Company Revenue

Choi

Kim

et al. 2021

IEEE Access

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The planning and execution of a business strategy are important aspects of the strategic human resource management of a company. In previous studies, machine learning algorithms were used to determine the main factors correlating employees with company performance. In this study, we introduced a method based on machine-learning algorithms for the classification of company revenue. Both annual and integrated datasets were examined to evaluate the classification performance of the framework under both binary and multiclass conditions. The performance of the proposed method was validated using six evaluation metrics: accuracy, precision, recall, F1-score, receiver operating characteristic curve, and area under the curve. As the experimental results indicate, the XGBoost classifier displayed the best classification performance among the three algorithms (XGBoost classifier, stochastic gradient descent classifier, and logistic regression) used in this study. Moreover, we confirmed the important features of the trained XGBoost model in accordance with variables focusing on human resource management studies. These results demonstrate that the proposed framework has strength in terms of both classification and practical implementation. This study provides novel insights into the relationship between employees and the revenue levels of their employer.

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“…(Marler & Boudreau, 2017).BD put forward countless opportunities for the HR and it has become extremely helpful for the organizations who considers their human resource to be the most valuable. (Garcia-Arroyo & Osca, 2019).To achieve the business goals organizations are using big data and it permits the management of employees in the most systematic manner. Big data helps organization in:…”

Section: Big Datamentioning

confidence: 99%

Human Resource Management in Industrial Revolution 4.O

Rafique¹

2021

PSSR

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The study highlights the influence of Fourth Industrial Revolution in HRM (Human Resource Management). To find the effect of Fourth Industrial Revolution on HRM functions such as Induction, training and development, recruitment and selection, performance management a quantitative approach was adopted where an online survey through questionnaire was conducted to highlight the views of HR professionals regarding Industry 4 impact on their organizations. The data was collected by HR experts working in different organizations having different experiences and working in different sectors. SPSS was used to analyze the study. The findings of this paper are organizations are incorporating Industry 4.0 components to make their HR functions more efficient and quicker. Direct impact on Industry 4 using Big data and artificial intelligence is foreseen in HR practice

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Big data contributions to human resource management: a systematic review

Cited by 83 publications

References 51 publications

Algorithmic human resource management: Synthesizing developments and cross-disciplinary insights on digital HRM

Algorithmic human resource management: Synthesizing developments and cross-disciplinary insights on digital HRM

Machine Learning Framework for Multi-Level Classification of Company Revenue

Human Resource Management in Industrial Revolution 4.O

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