Self-service technologies (SSTs) are becoming popular in mobile devices. Therefore, we examine the availability of mobile services with regard to wire-line device and user trust in these services as the moderating variables in order to determine the relative importance of the perceived usefulness (PU) and perceived ease of use (PEU) for users adopting new SSTs on mobile devices. We collected data from two distinctive mobile services: mobile banking and location-based ("finding my friend") services in Korea. The findings of this study reveal that when new services are available with existing wire-line services, PEU is more important than PU in driving the adoption of new SSTs. In contrast, when mobile services are relatively brand new, PU is more important than PEU in the adoption of new SSTs. Further, trust in services does not significantly change the relative importance of PEU for users adopting mobile services that are available in wire-line devices, whereas user trust in services strengthens the influence of PU in their adoption of mobile services that are not available in wire-line devices. These findings can help explain the causal structure whereby SSTs are adopted on mobile devices. We also provide managerial guidance in order to promote the adoption as well as the use of SSTs.
Due to the introduction of text mining, studies have been conducted to analyze meaningful topics and trends in document collections. Trend analysis using Latent Dirichlet Allocation (LDA) in text mining is adopted as one of the trend analysis methods with high accuracy. In this paper, we propose a trend analysis method using LDA. The method is composed of 5 steps and the trend analysis is performed by topic using the extracted result combining LDA and Top 10 keywords. By applying our method and LDA to international standards documents, we performed topic modeling and checked the trend of international standards using extracted topics.
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