Deep Collaborative Innovation Product Decision-Making Model Based on Multi-Objective Optimization

Abstract

With the advancement of societal living standards, the cultural and creative industry (CCI) facing the challenge of balancing user demands, market demands, and the preservation of traditional culture. This study explores how co-innovation subjects contribute to this balance by participating in the early stages of cultural and creative product (CCP) development. Stakeholders engage in product design process (PDP) in task-based orders currently. It falls short of fully leveraging the potential of each collaborative innovation entity. Therefore, this study proposes a theoretical framework that combines a non-dominated sorting genetic algorithm (NSGA-II) and a technique for order preference by similarity to ideal solution (TOPSIS) algorithms. This framework helps to balance the relationships among stakeholders, such as users, commercial institutions, community members, and government departments. A Shandong CCP design project case study shows that early stakeholder involvement in product design promotes deep collaborative innovation, resulting in solutions that better meet stakeholder needs and verifying the method’s effectiveness.

Keywords

• Collaborative innovation
• product design
• multi-objective optimization (MOO)
• decision-making
• TOPSIS
• cultural heritage