Abstract
Purpose– The purpose of this article is to investigate urban and rural differences for online activities and e-payment behavior patterns. Design/methodology/approach– This study applied the MLCA model to investigate Internet usage patterns from 11 online applications among 10,909 Taiwan residents in 25 different regions. Findings– The results showed that online behavior patterns exhibited regional differences, as the regional segments affected the individual segments of different use patterns. For instance, the urban area comprised a higher proportion of members who were accustomed to internet applications and skilled in online shopping by using a credit card. The rural area made up a higher proportion of members who only occasionally used online services. Moreover, rural region residents used other payment methods (excluding credit cards) more often than urban region residents. As expected, users’ personal characteristics also dictated the online behavior pattern. For instance, people with higher-level income spent relatively more money for online shopping and often used various internet applications than others. Practical implications– The findings herein should help Internet service providers form an applicable guideline for developing service strategies of higher service satisfaction regarding products and users’ needs. Originality/value– This study implemented a multilevel latent class model to investigate online behavior patterns that exhibited urban and rural differences, with the goal of providing service providers an understanding and mastery of their target users.
Purpose– The purpose of this article is to investigate urban and rural differences for online activities and e-payment behavior patterns. Design/methodology/approach– This study applied the MLCA model to investigate Internet usage patterns from 11 online applications among 10,909 Taiwan residents in 25 different regions. Findings– The results showed that online behavior patterns exhibited regional differences, as the regional segments affected the individual segments of different use patterns. For instance, the urban area comprised a higher proportion of members who were accustomed to internet applications and skilled in online shopping by using a credit card. The rural area made up a higher proportion of members who only occasionally used online services. Moreover, rural region residents used other payment methods (excluding credit cards) more often than urban region residents. As expected, users’ personal characteristics also dictated the online behavior pattern. For instance, people with higher-level income spent relatively more money for online shopping and often used various internet applications than others. Practical implications– The findings herein should help Internet service providers form an applicable guideline for developing service strategies of higher service satisfaction regarding products and users’ needs. Originality/value– This study implemented a multilevel latent class model to investigate online behavior patterns that exhibited urban and rural differences, with the goal of providing service providers an understanding and mastery of their target users.
