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Combining social network and data envelopment analysis: A proposal for a Selection Employment Contracts Effectiveness index in healthcare network applications

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  • Gobbo, Simone Cristina de Oliveira
  • Mariano, Enzo Barberio
  • Gobbo Jr., José Alcides

Abstract

Combining social network analysis (SNA) and data envelopment analysis (DEA) techniques is a recent and relevant trend in the literature. However, although other works have integrated these techniques, none have done so in the way proposed in this study. Seven generic stages were defined to combine these methods and create a new indicator, the Selection Employment Contracts Effectiveness Index, which measures the extent to which the employment contracts selection by a professional is effectively converted into influential social network positioning. Utilising three DEA models (CCR, BCC and RAM with inverted frontier) and choosing a normalization criterion (no normalization, normalization by size, or normalization by size with sensibility factor), this index can be broken down in terms of the quality and quantity of employment contracts selected. These indices were used in a Brazilian healthcare network to demonstrate that: (a) the number of optimal employment contracts of physicians in the network is one; and (b) the Adjusted Selection Employment Contracts Effectiveness Index by quality (ASECEql) correlates negatively with the workload and the number of physician's specialties. This work offers a new means of analysing the nodes in an affiliation network.

Suggested Citation

  • Gobbo, Simone Cristina de Oliveira & Mariano, Enzo Barberio & Gobbo Jr., José Alcides, 2021. "Combining social network and data envelopment analysis: A proposal for a Selection Employment Contracts Effectiveness index in healthcare network applications," Omega, Elsevier, vol. 103(C).
    • Handle: RePEc:eee:jomega:v:103:y:2021:i:c:s0305048320307313
    DOI: 10.1016/j.omega.2020.102377
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    3. Azadi, Majid & Yousefi, Saeed & Farzipoor Saen, Reza & Shabanpour, Hadi & Jabeen, Fauzia, 2023. "Forecasting sustainability of healthcare supply chains using deep learning and network data envelopment analysis," Journal of Business Research, Elsevier, vol. 154(C).

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