• Fashion & Textile Research Journal
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• v.19 no.3
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• pp.280-288
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• 2017

This study tested how the mobile impulse buying(m-impulse buying) of fashion products was related to shopping motives and mobile applications(apps) browsing in the context of mobile shopping. A total of 316 self-administered questionnaires were obtained from college students who had experienced m-impulse buying of fashion products during the most recent six months. A structural equation model using a correlation matrix with maximum likelihood was estimated for examining the relationships among shopping motives(e.g., hedonic shopping motive and utilitarian shopping motive), apps browsing, and m-impulse buying of fashion products(e.g., fashion-oriented impulse buying and pure impulse buying) by AMOS 21.0. Findings showed that hedonic shopping motive and utilitarian shopping motive had significant effects on apps browsing in their mobile shopping. Apps browsing had a significant effect on fashion-oriented impulse buying, but did not significantly effect on pure impulse buying of fashion products. Additionally, the hedonic shopping motive had directly significant effects on both fashion-oriented impulse buying and pure impulse buying, whereas the utilitarian shopping motive significantly effected on only the pure impulse buying of fashion products in their shopping. This study suggests that the hedonic shopping motive played an important role to determine the m-impulse buying of fashion products and the utilitarian shopping motive played a role in activating apps browsing relevant to mobile shopping for fashion products. Managerial implications are discussed for retailers related to the fashion products in mobile shopping.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.561-570
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• 2010

The purpose of this study is to develop an Android smartphone app providing analysis capabilities of remote sensing images, by using mobile browsing open sources of gvSIG, open source remote sensing software of OTB and open source DBMS of PostgreSQL. In this app, five kinds of remote sensing algorithms for filtering, segmentation, or classification are implemented, and the processed results are also stored and managed in image database to retrieve. Smartphone users can easily use their functions through graphical user interfaces of app which are internally linked to application server for image analysis processing and external DBMS. As well, a practical tiling method for smartphone environments is implemented to reduce delay time between user's requests and its processing server responses. Till now, most apps for remotely sensed image data sets are mainly concerned to image visualization, distinguished from this approach providing analysis capabilities. As the smartphone apps with remote sensing analysis functions for general users and experts are widely utilizing, remote sensing images are regarded as information resources being capable of producing actual mobile contents, not potential resources. It is expected that this study could trigger off the technological progresses and other unique attempts to develop the variety of smartphone apps for remote sensing images.