Collaborative decision-making research on customized cultural and creative products considering regret avoidance and fairness degree

Cultural and creative products(CCPs) have gained significant popularity, with platforms like Amazon experiencing notable growth in such customized product sales. However, a mismatch existing in between consumers' cultural and spiritual needs and the supply of CCPs causes reduced consumer satisfaction, weak market demand, and resource waste, among other effects. To address this, we propose a bilateral matching approach that incorporates regret-averse psychological behaviors and personalized needs of consumers. We calculate consumers' willingness to purchase CCPs based on personalized demand weights and manufacturer evaluations. To enhance matching accuracy, we introduce a difference coefficient to refine the fuzzy representations of both parties, amplifying their differences. We then establish a stable, goal-oriented matching model aimed at maximizing satisfaction for both parties, incorporating fairness to improve the model. We analyze three matching scenarios: focusing on satisfaction, fairness, and both satisfaction and fairness. Our findings indicate that the regret-avoidance coefficient and fairness weight are crucial factors influencing the matching outcome. Effective bilateral matching between CCPs and consumers involves aligning preferences with product characteristics and dynamically adjusting fairness and satisfaction weights for long-term optimization. Finally, we validate the effectiveness and feasibility of our model using real data from the Shanghai Museum online gift shop. JEL: C44;D11;D16;M11