2019Expert SystemsRequires access

China's high‐tech industry efficiency measurement with virtual frontier data envelopment analysis and Malmquist productivity index

Xin Liu, Jingkai Huang

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Abstract

Abstract Data envelopment analysis (DEA) is a widely used non‐parametric method in efficiency measurement with multiinputs and multioutputs. Malmquist productivity measures the efficiency change in different periods and decomposes the general efficiency change into technical efficiency change and frontier shift. In this paper, we choose a driving industry in social development, the high‐tech industry, as an example to illustrate a new method, virtual frontier DEA model, in the aspect of improvement of the traditional DEA model. Additionally, we decompose the Malmquist productivity index with virtual frontier DEA model to find out the driving force of high‐tech efficiency change.

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What this paper is about

Abstract Data envelopment analysis (DEA) is a widely used non‐parametric method in efficiency measurement with multiinputs and multioutputs. Malmquist productivity measures the efficiency change in different periods and decomposes the general efficiency change into technical efficiency change and frontier shift. In this paper, we choose a driving industry in social development, the high‐tech industry, as an example to illustrate a new method, virtual frontier DEA model, in the aspect of improvement of the traditional DEA model. Additionally, we decompose the Malmquist productivity index with virtual frontier DEA model to find out the driving force of high‐tech efficiency change.

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Available abstract

Abstract Data envelopment analysis (DEA) is a widely used non‐parametric method in efficiency measurement with multiinputs and multioutputs. Malmquist productivity measures the efficiency change in different periods and decomposes the general efficiency change into technical efficiency change and frontier shift. In this paper, we choose a driving industry in social development, the high‐tech industry, as an example to illustrate a new method, virtual frontier DEA model, in the aspect of improvement of the traditional DEA model. Additionally, we decompose the Malmquist productivity index with virtual frontier DEA model to find out the driving force of high‐tech efficiency change.

Key concepts: Data envelopment analysis, Malmquist index, Productivity, Frontier, Efficient frontier, Index (typography), Computer science, Technical change

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