Analysing repeat blood donation behavior via big data

Abstract

Purpose

Although blood banks have recently started to recruit blood donors through social media platforms, including WeChat, to increase recruitment effectiveness, few researchers have studied their effects on blood donation behavior. The aim of this study is to examine the influence of using official WeChat accounts on repeat blood donation behavior.

Design/methodology/approach

This paper used the backstage operation data of official WeChat accounts and blood supply chain management system data from the blood bank for the study to analyze the changes in repeat blood donation behavior. First, to analyze the changes in the average frequency of blood donation per year, average volume of single blood donation and blood eligible rate of repeat blood donors before and after following the official WeChat accounts by difference-in-differences model combined with propensity score matching (PSM-DID). Second, we examined the impact of official WeChat accounts on the proportion of repeat blood donors through survival analysis.

Findings

The results show that following WeChat accounts increases the average frequency of blood donation and blood eligible rate of repeat blood donors by 14.36% and 1.19%, respectively, and have no significant effect on the average volume of single blood donation. Further, WeChat accounts have a more significant impact on the average frequency of blood donations per year for workers, farmers, medical staff and groups with education levels of junior high school. In addition, official WeChat accounts can effectively increase the proportion of repeat donors.

Originality/value

The results provide a quantitative basis for the influence of official WeChat accounts on repeat blood donation behaviors. On the one hand, it is of great significance to guide the publicity and recruitment of unpaid blood banks. On the other hand, it provides an evidence for the promotion of official WeChat accounts.

Citation

Chen, X., Liu, L. and Guo, X. (2021), "Analysing repeat blood donation behavior via big data", Industrial Management & Data Systems, Vol. 121 No. 2, pp. 192-208. https://doi.org/10.1108/IMDS-07-2020-0393