Until now, research on consumers’ purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers’ self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

The purpose of this study is to reveal and compare the differences in the types and characteristics of purchase channel journeys of MZ generation consumers. In this study a survey was conducted on the purchase channel journey of 20 women in the MZ generation using the ethnographic method of in-depth interviews and observations. As a result, three purchase channel journeys were identified: mobile, multi-channel, and offline. These were variously subdivided according to the characteristics of the MZ generations. Gen Z’s journey was categorized into types: fashion platform app, Youtube, multi-channel supplement, multi-channel non-planned store visit, offline loyalty store, and impulsive offline store. Gen M’s journey was categorized as: an online community bond, portal site, online loyalty store, multi-channel brand involvement, multi-channel efficiency, a multi-channel conversion, offline efficiency and offline task. The difference in mobile journey between generations was found in the time and length of the purchase. Gen M recognized both online and offline search processes to be tiring, while Gen Z enjoyed the search process using the online path. In the offline journey Gen Z began with their own intention to purchase, while Gen M sometimes recognized that purchasing fashion products necessary for work was a cumbersome task.

Digital channels are becoming increasingly important in consumer purchase decisions. Yet, the availability of several different channels present consumers the opportunity to switch between one and another, such a phenomenon is called cross-channel free riding. This research aims therefore at exploring whether cognitive dissonance and opportunistic behavior are relevant antecedents of cross-channel free riding.

This study examined motivation to use omni-channel services on mobile devices in fashion stores and the effects of such usage motivation on brand purchase intention through continuous and affective commitment. Data were collected on consumers in their 20s and 30s who experienced omni-channel services during shopping for or purchasing fashion products. An online survey asked 413 consumers to rate their brand purchase intention. Sub-levels of each variable were examined using SPSS 25.0, followed by confirmatory factor analysis using AMOS 19.0. In addition, path analysis using structural equation modeling was applied to analyze associations between variables. The statistical results were mixed. First, only two dimensions of usage motivation for omni-channel services, hedonic and relational motivation, had positive effects on continuous and affective commitment. Second, continuous commitment had a greater effect on purchase intention of brands that provided omni-channel services than it did on affective commitment. Third, of the dimensions of usage motivation, utilitarian motivation had a direct influence on purchase intention in the modified model, while social motivation did not affect service commitment and purchase intention. Finally, our findings suggest that brand loyalty can be built by encouraging service commitments through hedonic and relational motivation, based on the usability of omnichannel services.