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Hierarchical network systems: An application to high-technology industry in China

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  • Zhang, Linyan
  • Chen, Kun

Abstract

In real world situations, there is a hierarchical structure exists in a specific organization and each component has its network process. However, such hierarchical network system has not been well studied in previous literature, and misleading results often are produced. The current paper discusses a data envelopment analysis (DEA) modelling technique for a network structure where a hierarchical system consists of components having two-stage series processes. An additive network DEA is proposed to evaluate the performance of this type of network structure. The overall and divisional efficiencies of the system and each component can be derived, and the relationship between system efficiency, divisional efficiency and the ones of components is discussed. The newly developed additive network DEA is nonlinear and cannot be converted into a linear program. A semidefinite programming (SDP) approach is developed for effectively solving this model and the global solution can be guaranteed. Another linear multiplicative network DEA also developed for this hierarchical system. The two newly developed models are illustrated with a case of the performance evaluation of high-technology industry in China.

Suggested Citation

  • Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    • Handle: RePEc:eee:jomega:v:82:y:2019:i:c:p:118-131
    DOI: 10.1016/j.omega.2017.12.007
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    3. Ya Wang & Jiaofeng Pan & Ruimin Pei & Guoliang Yang & Bowen Yi, 2020. "A Framework for Assessing Green Capacity Utilization Considering CO 2 Emissions in China’s High-Tech Manufacturing Industry," Sustainability, MDPI, vol. 12(11), pages 1-25, May.
    4. Kremantzis, Marios Dominikos & Beullens, Patrick & Kyrgiakos, Leonidas Sotirios & Klein, Jonathan, 2022. "Measurement and evaluation of multi-function parallel network hierarchical DEA systems," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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