Author :
Li, P. ; Tian, Y.Z. ; Qi, Z.Y. ; Jia, Q.
Abstract :
Innovation is becoming an important power for the development of the manufacturing companies. Researchers usually focus on the three factors of competitive priorities: quality (Q), cost (C), and time (T), which comprise the main competence of manufacturing strategy. However, in this paper, we suppose that innovation can be a parallel factor with quality (Q), cost (C) and time (T), we develop a TCQ&I model, which depicts how these four dimensions of competitive priorities affect the manufacturing performance. Based on the literature of manufacturing strategy competitive priorities, we propose that the competitive capacity model consists of time, cost, and quality, including innovation, is superior to the model without the innovation factor. This paper uses the information from the database of the International Manufacturing Strategy Survey (IMSS). Using data from the IMSS, this study uses the empirical methods of exploring and analyzing the relationship model of the four dimensions of manufacturing competence, i.e. quality (Q), cost (C), time (T) and innovation (I), and how they affect the manufacturing performance, focusing on the structural equation model analysis. The research methods of descriptive statistics, model fitting analysis, and multiple regression analysis are used. The statistical analysis tool applied is the LISREL software. The results prove the validity of the hypothesis. This study concludes that the competitive model, which includes innovation, is superior to the model without innovation in both developing countries and developed countries. The effect of innovation to the manufacturing performance is further validated.
Keywords :
innovation management; manufacturing industries; quality management; regression analysis; International Manufacturing Strategy Survey; LISREL software; competitive priorities; cost priority; descriptive statistics; innovation factor; manufacturing competence; manufacturing performance; model fitting analysis; multiple regression analysis; quality priority; statistical analysis tool; structural equation model analysis; time priority; Costs; Databases; Equations; Fitting; Performance analysis; Pulp manufacturing; Regression analysis; Statistical analysis; Technological innovation; Virtual manufacturing; Competitive Priorities; Innovation; Manufacturing Performance; Structural Equation Model Analysis; TCQ&I Model;