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

Wei Gu
Donlinks School of Economics and Management
University of Science and Technology Beijing
Thomas Saaty
Joseph M. Katz Graduate School of Business
University of Pittsburgh
United States
Lirong Wei
Department of Statistics
University of Pittsburgh
United States

Publication date: Jan, 2018

Journal: International Journal of Information Technology & Decision Making
Vol.: 17- Issue: 1- Pages: 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, ANP, Evaluation, TIC, Analytic Network Process