A Recommendation System for People Analytics

Nan Wang and Evangelos Katsamakas
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Nan Wang: DeepMacro, USA
Evangelos Katsamakas: Gabelli School of Business, Fordham University, USA

International Journal of Business Intelligence Research (IJBIR), 2021, vol. 12, issue 2, 1-12

Abstract: Companies seek to leverage data and people analytics to maximize the business value of their talent. This article proposes a recommendation system for personalized workload assignment in the context of people analytics. The article describes the system, which follows a novel two-level hybrid architecture. We evaluate the system performance in a series of computational experiments and discuss future extensions. Overall, the proposed system could create significant business value as a decision support system that could help managers make better decisions. The article demonstrates how computational and machine learning approaches can complement humans in improving the performance of organizations.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jbir00:v:12:y:2021:i:2:p:1-12

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