Competitiveness evaluation techniques for cosmeceuticals e-commerce platform

Abstract

Currently, the popularity of cosmeceuticals ecommerce is continuously increasing. A competition level among entrepreneurs is higher precisely, especially in the e-commerce platform. As a result, this situation causes to strengthen the competitiveness of several businesses. However, an evaluation of business operation planning which directly associates with the competitiveness of entrepreneurs is still the main issue. Therefore, this study proposes the methodology to define the cosmeceuticals ecommerce competitiveness through SWOT analysis, useful clustering methods including Self-Organizing Map (SOM) and K-means clustering, and Normalized Weight of Criteria for competitiveness criteria evaluation. The SWOT analysis is a reliable algorithm, which can adequately be used to evaluate the business performance with valid questionnaires. It provides the grouped attributes as 4 groups including Strengths, Weaknesses, Opportunities, Threats. Moreover, the appropriated factors result from the previous step will be clustered by SOM and K-means clustering for better data interpretation. SOM calculated 203 instances into 3 clusters; Low, High, No Class with 18 sec for execution time and 94.98% for accuracy. Meanwhile, K-means clustered previous dataset into 2 groups; high performance business and low performance business with 91.33% accuracy. In addition, the clustered data will be specified by Normalized Weight of Criteria for most influential criteria of Strengths, Weaknesses, Opportunities, and Threats factors to accomplish the high Competitiveness level of entrepreneurs. The results from this analysis can definitely help cosmeceuticals entrepreneurs to enhance the business strategy and advanced planning.