Ressearch
Current Project of the mBusiness lab:
Local browsing
Next to email, information browsing is the most successful Internet application on computers. On mobile devices, it is likely to be the same. However, the application on computers cannot be directly “copied” to mobile devices for two main reasons. Firstly, mobile devices limit the way to input information. Secondly, users’ behaviors are significantly different when accessing/using the Internet on a mobile phone as compared to on a computer.
Considering that an Internet user on a mobile device is likely to be more interested on information related to his/her own position, we are interested in the development of suitable solutions that allow the user to accurately discover information relevant to his/her local environment. Such a discovery can be on a small or large scale of his/her local environment, for example, browsing inside a large building such as an airport or a shopping mall.
Reality mining for advertisement
The success or failure of an advertisement primarily depends on the kind (typology) of advertisement, the product to be advertised, the targeted population and the situation (context) when the advertisement takes place. We are mainly interested in the last two factors because mobile phones are almost inseparable from their respective owners. Therefore, by analyzing a variety of data provided by ones’ mobile devices, we can effectively understand and predict the current and future needs of the mobile phones’ owners. Consequently, the efficiency and effectiveness of mobile Internet advertisements can be significantly improved.
Mobile Targeted Advertisements & Privacy Issues
The Management Information Systems Group (www.mis.ethz.ch) has developed a distributed system allowing to dispatch targeted advertisements to Smartphone users. A field study is planned to study the acceptance of the technology the users’ behavior, and privacy issues. During a certain period of time our prototype will be used by hundred of users in a real file experiment. Users will receive daily offers filtered by the system depending on their profiles. In order to collect quantitative data for our study, the prototype will send daily statistical information to our central server. Once the experiment ended, we will analyze the collected data and to establish the influence of the privacy issue in delivering targeted advertisement, the technology acceptance, the quality of the targeting algorithm and the ability of the software to constructs a social network.
P2P Mobile Commerce
Suppose, someone receives an SMS from a merchant about a product discount, will he/she go visit the shop and purchase that product? Now, suppose instead of receiving this SMS from a merchant, he/she receives this SMS from a member of a virtual community that he/she has joined before, will he/she make a purchase? About half of the Internet users associated with any virtual communities joined those communities so as to be connected with people who share the same interests with them (Horrigan 2001). This project aims to tap into these communities to examine the effectiveness of peer-to-peer mobile commerce as compared to the existing merchant-to-customer mobile commerce.