Comparing ANFIS and SEM in linear and nonlinear forecasting of new product development performance

  • Authors:

  • Yung-Ching Ho;Ching-Tzu Tsai

  • Affiliations:

  • Department of Business Administration, National Chung Cheng University, No.168, University Road, Min-Hsiung, Chia-Yi, Taiwan, ROC;Department of Business Administration, National Chung Cheng University, No.168, University Road, Min-Hsiung, Chia-Yi, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

Though the hi-tech industry has focused on value innovation and improving the quality of the new product development (NPD) process to drive new product performance, new product success has not changed dramatically over the years. This study presents a novel approach based on structural equation modeling (SEM) and adaptive neuro-fuzzy inference system (ANFIS) to forecast value innovation and the effects of the quality of the NPD process on NPD performance. Results demonstrate that value innovation directly affects NPD performance as well as the nonlinear relationships between the quality of NPD processes and NPD performance, and that ANFIS achieves better forecasting performance than the SEM technique. The ANFIS model effectively explains the nonlinear relationships that SEM cannot. This paper thus offers a new perspective on forecasting and modeling useful to both researchers and practitioners.