A hybrid approach to resolve ambiguity in new product development

Feng Lang Liu, Li Chih Chien, Ting Yu Chang, Cooper Cheng Yuan Ku, Ching Ter Chang*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

Abstract

Improving technological innovation (TI) capabilities is an integral component of government policies aimed at improving the competitiveness of small and medium enterprises (SMEs). This study aims to address implementation challenges arising from the use of Qualitative Forecasting Method (QFM) in new product development programs and proposes a novel method to aid decision makers (DMs) in their decision-making process. To tackle this issue, a hybrid method is proposed, incorporating Fuzzy Delphi method (FDM), Fuzzy Analytic Hierarchy Process (FAHP), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Multi-Choice Goal Programming with utility function (MCGP-U), while introducing prospect theory as a novel approach. is proposed. The proposed method offers several advantages, including effective early planning, accurate identification of key success factors (KSFs), selection of the most suitable project leader, and estimation of the most reasonable resource investment, all of which are critical factors for success in TI for enterprises. The research results show that (1) the proposed method reduces project execution time by 20% compared to the original manual planning, (2) it facilitates the acquisition of KSFs using a rational approach to ensure project success, and (3) it increases the financial returns of the company by 17% compared to the company's forecast. In summary, this paper makes a significant contribution to practical applications and additionally contributes to decision-making field by introducing prospect theory into the proposed hybrid method.

Original languageEnglish
Pages (from-to)1359-1378
Number of pages20
JournalJournal of Intelligent and Fuzzy Systems
Volume46
Issue number1
DOIs
StatePublished - 10 01 2024

Bibliographical note

Publisher Copyright:
© 2024 - IOS Press. All rights reserved.

Keywords

  • decision-making model
  • fuzzy
  • MCGP
  • Technological innovation

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