Mobile search is beset with problems because of mobile terminal constraints and also because its characteristics are different from the traditional Internet search model. This paper analyzes cloud computing technologi...Mobile search is beset with problems because of mobile terminal constraints and also because its characteristics are different from the traditional Internet search model. This paper analyzes cloud computing technologies--especially mass data storage, parallel computing, and virtualization--in an attempt to solve technical problems in mobile search. The broad prospects of cloud computing are also discussed.展开更多
The mobile search, a combination of a web search engine and a mobile communication system, is viewed as the most influential application in the 3G era. Therefore, mobile search service providers are eager to know whic...The mobile search, a combination of a web search engine and a mobile communication system, is viewed as the most influential application in the 3G era. Therefore, mobile search service providers are eager to know which factors most influence user acceptance of mobile searches. Based on the characteristics of mobile searches and a review of previous information technology acceptance research, this study integrates the task technology fit model and the unified theory of acceptance and use of technology model to develop a mobile search acceptance model and empirically tests this model. This study finds that, for mobile searches, the performance expectancy, social influence, and perceived cost all significantly influence use intention and the performance expectancy increases with the increasing user＇s experience and higher tasktechnology fit degree. The effort expectancy is found to not affect the use intention of mobile searches and the users＇ gender does not have a significant moderating effect on the use intention. The results are then used to develop suggestions for mobile search providers to promote their application and development.展开更多
Purpose： This study explores how search motivation and context influence mobile Web search behaviors. Design/methodology/approach： We studied 30 experienced mobile Web users via questionnaires, semi-structured inter...Purpose： This study explores how search motivation and context influence mobile Web search behaviors. Design/methodology/approach： We studied 30 experienced mobile Web users via questionnaires, semi-structured interviews, and an online diary tool that participants used to record their daily search activities. SQLite Developer was used to extract data from the users＇ phone logs for correlation analysis in Statistical Product and Service Solutions （SPSS）. Findings： One quarter of mobile search sessions were driven by two or more search motivations. It was especially difficult to distinguish curiosity from time killing in particular user reporting. Multi-dimensional contexts and motivations influenced mobile search behaviors, and among the context dimensions, gender, place, activities they engaged in while searching, task importance, portal, and interpersonal relations （whether accompanied or alone when searching） correlated with each other. Research limitations： The sample was comprised entirely of college students, so our findings may not generalize to other populations. More participants and longer experimental duration will improve the accuracy and objectivity of the research. Practical implications： Motivation analysis and search context recognition can help mobile service providers design applications and services for particular mobile contexts and usages. Originality/value： Most current research focuses on specific contexts, such as studies on place, or other contextual influences on mobile search, and lacks a systematic analysis of mobile search context. Based on analysis of the impact of mobile search motivations and search context on search behaviors, we built a multi-dimensional model of mobile search behaviors.展开更多
文摘Mobile search is beset with problems because of mobile terminal constraints and also because its characteristics are different from the traditional Internet search model. This paper analyzes cloud computing technologies--especially mass data storage, parallel computing, and virtualization--in an attempt to solve technical problems in mobile search. The broad prospects of cloud computing are also discussed.
基金Supported by the National Natural Science Foundation of China(Nos. 70831003, 70890081, and 70772022the MOE Project of Key Research Institute of Humanity and Social Sciences at Universities (06JJD630014)
文摘The mobile search, a combination of a web search engine and a mobile communication system, is viewed as the most influential application in the 3G era. Therefore, mobile search service providers are eager to know which factors most influence user acceptance of mobile searches. Based on the characteristics of mobile searches and a review of previous information technology acceptance research, this study integrates the task technology fit model and the unified theory of acceptance and use of technology model to develop a mobile search acceptance model and empirically tests this model. This study finds that, for mobile searches, the performance expectancy, social influence, and perceived cost all significantly influence use intention and the performance expectancy increases with the increasing user＇s experience and higher tasktechnology fit degree. The effort expectancy is found to not affect the use intention of mobile searches and the users＇ gender does not have a significant moderating effect on the use intention. The results are then used to develop suggestions for mobile search providers to promote their application and development.
基金supported by the Wuhan International Science and Technology Cooperation Fund (Grant No.:2015030809020371)the Wuhan University Youth Fund of Humanities and Social Sciences
文摘Purpose： This study explores how search motivation and context influence mobile Web search behaviors. Design/methodology/approach： We studied 30 experienced mobile Web users via questionnaires, semi-structured interviews, and an online diary tool that participants used to record their daily search activities. SQLite Developer was used to extract data from the users＇ phone logs for correlation analysis in Statistical Product and Service Solutions （SPSS）. Findings： One quarter of mobile search sessions were driven by two or more search motivations. It was especially difficult to distinguish curiosity from time killing in particular user reporting. Multi-dimensional contexts and motivations influenced mobile search behaviors, and among the context dimensions, gender, place, activities they engaged in while searching, task importance, portal, and interpersonal relations （whether accompanied or alone when searching） correlated with each other. Research limitations： The sample was comprised entirely of college students, so our findings may not generalize to other populations. More participants and longer experimental duration will improve the accuracy and objectivity of the research. Practical implications： Motivation analysis and search context recognition can help mobile service providers design applications and services for particular mobile contexts and usages. Originality/value： Most current research focuses on specific contexts, such as studies on place, or other contextual influences on mobile search, and lacks a systematic analysis of mobile search context. Based on analysis of the impact of mobile search motivations and search context on search behaviors, we built a multi-dimensional model of mobile search behaviors.
