Addressing a decision problem through a bipolar Pythagorean fuzzy approach: A novel methodology with application in digital marketing

Abstract

Decision-making in real-world scenarios often faces the challenge of uncertainty. Traditionally, fuzzy theory has been a means to represent and navigate such uncertainty. In this study, we propose a pioneering approach that incorporates a bipolarity analysis into multi-criteria decision-making processes, with a focus on its application in digital marketing. The proposal allows the analysis to be more encompassing by considering both the positive and negative dimensions of data, leading to better-informed decisions. A cornerstone of our contribution is integrating bipolarity into Pythagorean fuzzy soft matrices, a fresh mathematical framework that broadens the utility of bipolar fuzzy theory. Through rigorous computational experimentation, we determine the prioritization of alternatives, ultimately identifying the most effective strategy for digital marketing platforms. In our study, Facebook emerges as the foremost platform for implementing digital marketing strategies. When compared to existing techniques, our approach showcases significant advantages, underlining its potential to improve decision-making in uncertain scenarios. Our research offers profound insights for businesses aiming to refine their digital marketing strategies in an ever-evolving digital landscape.