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Human resource allocation or recommendation based on multi-factor criteria in on-demand and batch scenarios

Author

Listed:
  • Michael Arias
  • Jorge Munoz-Gama
  • Marcos Sepúlveda
  • Juan Carlos Miranda

Abstract

Dynamic resource allocation is considered a major challenge in the context of business process management. At the operational level, flexible methods that support resource allocation and which consider different criteria at run-time are required. It is also important that these methods are able to support multiple allocations in a simultaneous manner. In this paper, we present a framework based on multi-factor criteria that proposes a recommender system which is capable of recommending the most suitable resources for executing a range of different activities, while also considering individual requests or requests made in blocks. To evaluate the proposed framework, a number of experiments were conducted using different test scenarios. These scenarios provide evidence that our approach based on multi-factor criteria successfully allocates the most suitable resources for executing a process in real and flexible environments. In order to demonstrate this assertion, we use a help-desk process as a real case study. [Received: 19 May 2017; Revised: 23 October 2017; Accepted: 31 January 2018]

Suggested Citation

  • Michael Arias & Jorge Munoz-Gama & Marcos Sepúlveda & Juan Carlos Miranda, 2018. "Human resource allocation or recommendation based on multi-factor criteria in on-demand and batch scenarios," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 12(3), pages 364-404.
    • Handle: RePEc:ids:eujine:v:12:y:2018:i:3:p:364-404
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    Cited by:

    1. Michael Arias & Eric Rojas & Santiago Aguirre & Felipe Cornejo & Jorge Munoz-Gama & Marcos Sepúlveda & Daniel Capurro, 2020. "Mapping the Patient’s Journey in Healthcare through Process Mining," IJERPH, MDPI, vol. 17(18), pages 1-16, September.
    2. Rong Liu & Akhil Kumar & Juhnyoung Lee, 2022. "Multi-level Team Assignment in Social Business Processes: An Algorithm and Simulation Study," Information Systems Frontiers, Springer, vol. 24(6), pages 1949-1969, December.

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