【論文摘要】Sequence Clustering Analysis of Blood Donation Behavior

Dyantika Putry Mahmud ； Shi-Woei Lin ； Chang-Shiuan Jiang

《管理學術研討會》 第十六屆 (2018/11) Pp. 107-107

https://doi.org/10.29893/NCUTMAN.201811.0019

摘要

Blood transfusion is essential for many medical treatments. In recent years, considerable concern has arisen over the issue of how to maintain stable supply of blood components. While a blood center can either hold blood drive campaigns to recruit new donors or encourage regular donors to return to ensure sufficient supply of blood, having a donor donate blood regularly has been shown to be more valuable than recruiting a new donor. In this study, sequence data which contains blood donation history of donors from year 2010 to 2014 were analyzed. In particular, the donors who donate first time in the first half of 2010 were followed up for five years and model-based clustering methods, including mixture Markov model and mixture hidden Markov model, were used to identify the clusters of the donors. After obtaining and interpreting clusters, logistic regression models and random forest models were also adopted to investigate how demographic characteristics and the short-term behavior affect a donor's long-term return behavior. Results show that the short-term donation behavior is the most important indicator for predicting a donor's long-term donation behavior. Furthermore, ＂age＂ is also significantly associated with a donor's behavior, and those who are older than 40 years old are more likely to return regularly. By identifying the segments of blood donors and the corresponding key transition behaviors in their donation trajectories, this study can help blood centers to make better managerial interventions such as designing better reminding mechanisms or recruitment strategies, and is expected to make substantial contributions to the field of blood supply chain management.

關鍵字

Model-based clustering ； Sequence data ； Mixed Markov model ； Return behavior ； Blood donation