Customer satisfaction evaluation for drugs: A research based on online reviews and PROMETHEE-Ⅱ method

PLoS One. 2023 Jun 22;18(6):e0283340. doi: 10.1371/journal.pone.0283340. eCollection 2023.

Abstract

Online reviews of consumers after purchasing drugs online reflect the factors affecting their satisfaction. How to understand customer satisfaction through online reviews and tapping their needs to improve satisfaction has become an urgent issue facing pharmaceutical e-commerce companies. Based on the online reviews of Alibaba Health Pharmacy, six representative OTC online medicines were selected for this study, including the following categories: tonics, anti-cold drugs, rheumatism and orthopaedic drugs, skin drugs, gastrointestinal drugs, vitamins, and calcium. By training and testing the LDA topic model, five potential topics are extracted as factors affecting customer satisfaction, including drug efficacy, drug cost performance, online customer service, logistics and transportation, and packaging. In this paper, Sentiment Analysis is used to process the review text to quantify the sentiment tendency of the review, and determine the evaluation scale value. Then, the random dominance among various drug factors is determined based on the Stochastic Dominance Rules. Finally, the PROMETHEE-Ⅱ method is used to determine the ranking value of the importance of each factor. The results suggest that the factors in different types of OTC drugs rank differently, which is also rationalized in this paper. This study provides a significant reference for improving customer satisfaction with pharmaceutical e-commerce.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Consumer Behavior
  • Personal Satisfaction
  • Pharmaceutical Preparations
  • Pharmaceutical Services*
  • Pharmacies*

Substances

  • Pharmaceutical Preparations

Grants and funding

This work was supported by the Project sponsored by “Liaoning BaiQianWan Talents Program”, the Innovation Talent Support Plan of colleges and universities in Liaoning Province in 2020, the Young and Middle-aged Science and Technology Innovation Talent Plan of Shenyang in 2020 (Grant No.RC200498), the Natural Science Foundation of Liaoning Province (Grant No. 2020-MS-194), the Career development support plan for Young and Middle-aged teachers of Shenyang Pharmaceutical University (Grant No.ZQN2018010), and the “Research on regulatory risk analysis model and application of pharmaceutical enterprises based on blockchain technology” supported by the subject construction project of School of Business Administration of Shenyang Pharmaceutical University in 2021 (Grant No.2021-sygsxk-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.