Although the service industry takes up a large percentage in world economies and is situated in the center of all industries,it has been pointed out that its growth rate is smaller compared to the other industries,whi...Although the service industry takes up a large percentage in world economies and is situated in the center of all industries,it has been pointed out that its growth rate is smaller compared to the other industries,which is partly because of its characteristic features:“amorphousness”,“simultaneity”,and“heterogeneity”.Service providers are therefore required to be experienced and have a good business sense to succeed in this field.The aim of this research is to support those who are not experienced or do not have a good business sense,using scientific approach.This research tries to present recommendation,taking customers’value and compatibilities with employees into account,and is based on the assumption that customers and employees have one-to-one contact over a period.A total of 3,447 customers and 133 employees were classified according to their philosophies,needs,and abilities.For each case,customers’purchase histories are first interrelated with the result of questionnaire,and put purchase behavior into marketing using Bayesian network.Then the HUB was examined and extracted features of the data of the questionnaire,and executed the stochastic inference to present the recommendation.This procedure enabled us to extract the features of customers’purchase behavior,and it is turned out that compatibilities of customers and employees are more important than the difference of their values and abilities.展开更多
文摘Although the service industry takes up a large percentage in world economies and is situated in the center of all industries,it has been pointed out that its growth rate is smaller compared to the other industries,which is partly because of its characteristic features:“amorphousness”,“simultaneity”,and“heterogeneity”.Service providers are therefore required to be experienced and have a good business sense to succeed in this field.The aim of this research is to support those who are not experienced or do not have a good business sense,using scientific approach.This research tries to present recommendation,taking customers’value and compatibilities with employees into account,and is based on the assumption that customers and employees have one-to-one contact over a period.A total of 3,447 customers and 133 employees were classified according to their philosophies,needs,and abilities.For each case,customers’purchase histories are first interrelated with the result of questionnaire,and put purchase behavior into marketing using Bayesian network.Then the HUB was examined and extracted features of the data of the questionnaire,and executed the stochastic inference to present the recommendation.This procedure enabled us to extract the features of customers’purchase behavior,and it is turned out that compatibilities of customers and employees are more important than the difference of their values and abilities.
