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This paper presents a theoretical model to analyze the privacy issues involved in business models for location-based mobile services. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving the net payoff to users of mobile businesses. We found that (1) the personal data disclosed by users has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect, on user payoff; and (3) the amount of control over a user's personal data has a direct and positive effect, as well as a moderating effect, on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model, we derive a set of guidelines to design a privacy-friendly business model pattern for thirdparty services. We discuss four examples to show how the mobile platform can play a key role in the implementation of these new business models.

A novel thiolane polymer, poly[1,2,4,5-tetrakis(propylthio)benzene] (PTPB), was synthesized by facile oxidative-coupling polymerization, characterized by FT-IR, XPS, XRD, TGA and EA, and tested as cathode active material in rechargeable lithium batteries. The FT-IR, XPS and elemental analysis confirm the occurrence of polymerization and show the existence of C-S-C bonds. The results show that the thiolane polymer has electrochemical activity as cathode material in lithium batteries and thioether bonds may be the centers of the electrode reaction. A maximum specific capacity of 200 mAh g -1 was obtained and this agrees roughly with the theoretical prediction. In addition, high voltage efficiency was obtained first time from sulfide polymer.

In recent years, Sina Weibo, a Twitter-like social network service in China, has attracted attention from scholars in the domain of information systems, as the spread and influence of users' opinions are increasingly important, particularly in the tourism industry. This study examined the behaviors of Chinese tourists in Switzerland by adopting a semantic-based linked data methodology. A total of 103,778 Weibo messages shared with Swiss locations were collected between January 2013 and April 2015. We addressed questions about Chinese travelers' profiles, trends in keywords, and differences between first time and repeat visitors. Moreover, we implemented a semantic search engine by employing linked data technologies to provide useful information about Chinese tourists in Switzerland, both for the tourism industry and individual tourists.