Imputed Expert Decision Recommendation System for QFD-based Omnichannel Strategy Selection for Financial Services

Abstract

In this study, a novel hybrid fuzzy decision-making model is constructed for the effective omnichannel strategy selection of financial services. The first phase of this model is related to inputting missing expert decisions for the quality function deployment (QFD) stages and omnichannel service strategies. The QFD stages of financial services are then weighted by bipolar [Formula: see text]-rung orthopair fuzzy ([Formula: see text]-ROF) multi-stepwise weight assessment ratio analysis ([Formula: see text]-SWARA) based on the golden ratio. The QFD-based omnichannel strategy alternatives for financial services are then ranked using bipolar [Formula: see text]-ROF ELECTRE. These calculations are also performed by considering PFSs and IFSs. Finally, the TOPSIS methodology is used to rank the alternatives so that comparative results can be obtained. The main contribution of this study is the creation of effective omnichannel strategies to improve financial services using a novel hybrid fuzzy decision-making methodology based on bipolar [Formula: see text]-rung orthopair fuzzy sets ([Formula: see text]-ROFSs), [Formula: see text]-SWARA, ELECTRE, and the imputation of expert evaluations with collaborative filtering. The analysis results obtained will facilitate determination of the most appropriate omnichannel strategies for businesses to provide effective financial services. In this manner, companies will be able to determine appropriate marketing strategies without incurring excessive costs. Because the analysis results are the same for all fuzzy sets, the proposed model is coherent and reliable. The findings demonstrate that online financial services are the most critical strategy for improving omnichannel. Thus, companies should prioritize online channels to provide financial services that are more effective.