Application of neuro-fuzzy networks to forecast innovation performance - The example of Taiwanese manufacturing industry

Expert Systems with Applications

Volumn 37, Issue 2, 2010, Pages 1086-1095

  Chien, Shih Chien ^a   Wang, Tai Yue ^b   Lin, Su Li ^a  

^a SHU TE UNIVERSITY   (Taiwan)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Adaptive neuro fuzzy inference systems; Innovation performance; Sugeno ANFIS

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS METHOD; ARTIFICIAL NEURAL NETWORK; DECISION MAKERS; INNOVATION PERFORMANCE; MANUFACTURING INDUSTRIES; NEURAL NETWORK MODEL; NEURO-FUZZY NETWORK; STATISTICAL TECHNIQUES; TECHNICAL INFORMATION;

FUZZY INFERENCE; FUZZY NEURAL NETWORKS; RESOURCE ALLOCATION;

FUZZY SYSTEMS;

EID: 71749121378     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.06.107     Document Type: Article

References (52)

1. Anonymous. OECD proposed guidelines for collecting and interpreting technological innovation data. Oslo manual (1992), OECD Publication, Paris
2. Ansoff H.I., and Stewart J.M. Strategies for a technology-based business. Harvard Business Review 45 (1967) 71-83
3. Arifovic J., and Ramazan G. Using genetic algorithms to select architecture of a feedback artificial neural network. Physica A (2001) 574-594
4. Chaffee E.E. Three models of strategy. Academy of Management Review 10 1 (1985) 89-98
5. Chang P.C., and Hsieh J.C. A neural network approach for due date assignment in a wafer fabrication factory. International Journal of Industrial Engineering 10 (2003) 55-61
6. Chang P.C., and Lai C.Y. A hybrid system combining selforganizing maps with case-based reasoning in wholesaler's new-release book forecasting. Expert Systems with Applications 29 1 (2005) 183-192
7. Chang P.C., Wang Y.W., and Liu C.H. The development of a weighted evolving fuzzy neural network for PCB sales forecasting. Expert Systems with Applications 32 1 (2007) 86-96
8. Chang P.C., Wang Y.W., and Tsai C.Y. Evolving neural network for printed circuit board sales. Expert Systems with Applications 29 1 (2005) 83-92
9. Chiu S. Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems 2 3 (1994) 267-278
10. Choi D., and Valikangas L. Patterns of strategy innovation. European Management Journal 19 4 (2001) 424-429
11. Elalfi A.E., Haque R., and Elalami M.E. Extracting rules from trained neural network using GA for managing E-businesses. Applied Soft Computing 4 (2004) 65-77
12. Freeman C. The economics of innovation (1974), Penguin, Manchester, England
13. Gopalakrishnan S. Unraveling the links between dimensions of innovation and organizational performance. The Journal of High Technology Management Research 11 1 (2000) 137-153
14. Hall L.A., and Sharmistha B.S. A study of R&D, innovation, and business performance in the Canadian biotechnology industry. Technovation 22 (2002) 231-244
15. Hamel G., and Prahalad C.K. Strategic intent. Harvard Business Review 64 (1989) 63-76
16. Hertz J., Krogh A., and Palmer R. Introduction to the theory of neural computation (1991), Addison-Wesley, Reading, MA
17. Horikawa S., Furahashi T., and Tokumaru H. A real-time learning algorithm using neural fuzzy networks with back-propagation algorithm. IEEE Transactions on Neural Networks 3 (1992) 801-806
18. Irwin J.G., Hoffman J.J., and Lamont B.T. The effect of the acquisition of technological innovations on organizational performance: A resource-based view. Journal of Engineering and Technology Management 15 (1998) 25-54
19. Jang J.-S.R. ANFIS: Adaptive-network-based fuzzy inference system. IEEE Transactions on Systems, Man and Cybernetics 23 3 (1993) 665-685
20. Jang J.-S.R., Sun C.-T., and Mizutani E. Neuro-fuzzy and soft computing (1997), Prentice-Hall International, Inc., Upper Saddle River, NJ
21. Kantardzic M. Data mining: Concepts models methods and algorithms (2002), Wiley-IEEE Press, Hoboken, NJ
22. Kim K.J., and Han I. Genetic algorithms approach to feature discrimination in artificial neural networks for the prediction of stock price index. Expert Systems with Application 19 (2000) 125-132
23. Kuo R.J., and Chen J.A. A decision support system for order selection in electronic commerce based on fuzzy neural network supported by real-coded genetic algorithm. Expert Systems with Applications 26 (2004) 141-154
24. Kwaku A.G. Market orientation and innovation. Journal of Business Research 35 (1996) 93-103
25. Liang R.H. Application of grey relation analysis to hydroelectric generation scheduling. International Journal of Electrical Power and Energy Systems 21 5 (1999) 357-364
26. Lin C., and Lee C.S.G. Neural network-based fuzzy logic control and decision system. IEEE Transactions on Computers 40 12 (1992) 1320-1336
27. Manu F.A., and Sriram Ven. Innovation, marketing strategy, environment, and performance. Journal of Business Research 35 (1996) 79-91
28. Masouka, R., Watanabe, N., & Kawamura, A. (1990). Neuro fuzzy system-fuzzy inference using a structured neural network. In Proceeding of the international conference on fuzzy logic and neural networks, Yokohama, Japan (pp. 173-177).
29. Meeus M.T.H., and Oerlemans L.A.G. Firm behavior and innovative performance: An empirical exploration of the selection-adaptation debate. Research Policy 29 1 (2000) 41-58
30. Miles R.E., and Snow C.C. Organizational strategy, structure, and process (2003), Stanford University Press, California
31. Montana D., and Davis L. Training feed forward neural networks using genetic algorithms. Proceedings of the 11th international joint conference on artificial intelligence (1989), Morgan Kaufmanns, San Mateo, CA 762-767
32. Padmore T., Schuetze H., and Gibson H. Modeling systems of innovation: An enterprise-centered view. Research Policy 26 (1998) 605-624
33. Pakath R., and Zaveri J.S. Specifying critical inputs in a genetic algorithm-driven decision support system: an automated facility. Decision Sciences 26 6 (1995) 749-779
34. Porter M.E. Competitive advantage: Creating and sustaining superior performance (1985), Free Press, New York
35. Prahalad C.K., and Hamel G. The core competence of the corporation. Harvard Business Review 68 3 (1990) 79-91
36. Quadros R., Furtado A., Roberto B., and Franco E. Technological innovation in Brazilian industry: An assessment based on the São Paulo innovation survey. Technological Forecasting and Social Change 67 (2001) 203-219
37. Sexton R.S., and Gupta J.N.D. Comparative evaluation of genetic algorithm and backpropagation for training neural networks. Information Sciences 129 (2000) 45-59
38. Souder W.E. Managing new product innovations (1987), Lexington Books, New York
39. Srinivasan D. Evolving artificial neural networks for short term load forecasting. Neural Computing 23 (1998) 265-276
40. Subramanian A., and Nilakanta S. Organizational innovativeness: Exploring the relationship between organizational determinants of innovation, type of innovations, and measures of organizational performance. International Journal of Management Science 24 6 (1996) 631-647
41. Takagi T., and Sugeno M. Fuzzy identification of systems and its application to modeling and control. IEEE Transactions in Systems, Man and Cybernetics 15 (1985) 116-132
42. Twiss B.C. Forecasting for technologists and engineers: A practical guide for better decisions (1992), Peter Peringrinus, London
43. Uzun A. Technological innovation activities in Turkey: The case of manufacturing industry 1995-1997. Technovation 21 (2001) 189-196
44. Vanston J.H. Technological forecasting: An aid to effective technology management (1995), Technology Futures, Inc., Austin, TX
45. Wang E.H.H. ICT and economic development in Taiwan: analysis of the evidence. Telecommunications Policy 23 (1999) 235-243
46. Wang T.Y., and Chien S.C. Forecasting innovation performance via neural networks - A case of Taiwanese manufacturing industry. Technovation 26 (2006) 635-643
47. Wang, L. X., & Mendel, J. M. (1992). Back-propagation of fuzzy systems as nonlinear dynamic system identifiers. In Proceeding of the IEEE international conference on fuzzy systems, San Diego (pp. 1409-1418).
48. Watts R.J., and Porter A.L. Innovation forecasting. Technological Forecasting and Social Change 56 (1997) 25-47
49. World Economic Forum (WEF) (2006). The global information technology report 2005-2006's. Networked Readiness Index, Geneva, Switzerland.
50. Yager R.R. Essentials of fuzzy modeling and control (1994), Wiley, New York
51. Yao X. Evolving artificial neural networks. Proceedings of the IEEE 87 9 (1999) 1423-1447
52. Zhu D., and Porter A.L. Automated extraction and visualization of information for technological intelligence and forecasting. Technological Forecasting and Social Change 69 (2002) 495-506