Measuring efficiency of the high-tech industry using uncertain multi-stage nonparametric technologies

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Elsevier Ltd

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As an important role in China's economy, the high-tech industry should evaluate and analyze the innovation activities from a systematic perspective to obtain innovation efficiency, thus improving high-quality development. In fact, for the efficiency assessment system of the high-tech industry, the indicators information is imprecise due to the inherent randomness, measurement error, incomplete information on economic phenomena, etc. However, few studies to date have considered and described the imprecise information. Moreover, data indivisibilities and the economic scale of the high-tech industry cause nonconvex technologies. However, little research has been conducted using the nonconvex measure to estimate innovation efficiency. In this regard, this paper is the first to combine convex and nonconvex technologies with uncertainty theory in a multi-stage system to compare the efficiency of the high-tech industry. More specifically, this paper first divides the innovation activities of the high-tech industry into a technological development stage and an economic transformation stage from the perspective of the innovation value chain. Second, uncertainty theory is adopted to express imprecise information, and uncertain multi-stage nonparametric frontier techniques are constructed to measure the innovation efficiency of the high-tech industry. Third, the high-tech industrial efficiency evaluation based on two-stage nonparametric techniques is established. Empirical results indicate that efficiency in the technology development stage is higher, particularly under nonconvex. Furthermore, the inefficiency of the whole system is mainly due to the inefficiency in the economic transformation under nonconvex, while under convex, the primary reason becomes the joint inefficiency of the two stages. © 2022 Elsevier Ltd


Anahtar Kelimeler

Efficiency Evaluation, High-Tech Industry, Nonparametric Frontier Technologies, Uncertainty Theory


Expert Systems with Applications

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Liu, X., Chen, X., Wu, Q., Deveci, M., & Delen, D. (2022). Measuring Efficiency of the High-Tech Industry Using Uncertain Multi-Stage Nonparametric Technologies. Expert Systems with Applications, 119490.