Evaluating and Optimizing Technological Innovation Efficiency of Industrial Enterprises Based on Both Data and Judgments

Wei Gu (), Thomas L. Saaty () and Lirong Wei ()
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Wei Gu: Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, P. R. China
Thomas L. Saaty: Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, 15260 PA, USA
Lirong Wei: Department of Statistics, University of Pittsburgh, Pittsburgh, 15260 PA, USA

International Journal of Information Technology & Decision Making (IJITDM), 2018, vol. 17, issue 01, 9-43

Abstract: Technological innovation as one of the most important competitive strategies for companies has attracted the attentions of companies and governments. In this paper, we present an evaluation method based on data and judgments to rank the technological innovation capability and technological innovation efficiency of enterprises of various sizes in China. Furthermore, based on the efficiency measures, we design a model for the government to optimally allocate innovation resource to businesses, i.e. prioritize public expenditures dedicated to innovation. In evaluating the efficiency of industrial enterprises, we employ the “input-process-output” perspective to identify multiple criteria. We also take into account the cost of technological innovation in efficiency assessment. The optimization model proposed for government is to maximize the overall efficiency of resources utilization. We adopt the genetic algorithm as the solution methodology to solve the optimization model. Simulation is conducted to validate the model and the algorithm. The research framework proposed in paper can be adapted for government in many countries to better distribute resources for technological innovation and development.

Keywords: Technological innovation capability (TIC); the analytic network process (ANP); evaluation; optimization (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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DOI: 10.1142/S0219622017500390

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