Fuzzy Clustering-Based Credibility Assessment for Biotechnology E-commerce Platforms

Lan Lan
Henan Polytechnic Institute, Nanyang City, Henan Province, China

DOI:https://doi.org/10.5912/jcb1142

Abstract:

This paper introduces the application of fuzzy clustering algorithms to evaluate the credibility of biotechnology e-commerce platforms, which is critical in the highly regulated biotech industry. Fuzzy clustering offers a sophisticated method for extracting and analyzing complex data patterns from these platforms, incorporating elements such as similarity measures, fuzzy set theories, and the fuzzy c-means algorithm supplemented by regression analysis. In the context of biotechnology, where the authenticity and reliability of transactions are paramount, this approach provides a nuanced assessment of platform credibility. The biotech sector, with its unique requirements for accuracy in product listings and regulatory compliance, can benefit significantly from the methodologies discussed. This study illustrates how fuzzy clustering can be tailored to address the challenges faced by e-commerce in the biotech field, particularly in enhancing trust and security for users. By analyzing various biotech platforms, we demonstrate how our proposed method not only identifies credible platforms but also helps in understanding the strategic underpinnings that contribute to their success. This research serves as a benchmark for biotechnology firms aiming to enhance their e-commerce strategies, ensuring that their offerings meet the high standards required in the industry.