5 Conclusions
Mobile data services potential has not yet been exploited. We tried to
understand what motivates users to use or not these services by using
the Triandis model for human behaviour in the mobile data service
adoption problem.
We found that the current offer still does not add enough value
compared to the cost to be sustained from the user point of view. We
have also seen in a technology acceptance model perspective that
technologically advanced mobile phones promote the use of mobile
data services.
During this exploration process we have also identified in information
and communication services the most used ones. This knowledge
helped us to choose what services had to be implemented: news
services, weather forecasting, private and social messaging and event
management.
We identified the most popular services on the web to guide the
service feature selection. We explored the world of social networking
websites, RSS feed technology and event management to understand
what made these services successful on the web and if it was possible
to mash up them directly to build up a new service best suited for
mobile use.
We proposed the conversation model to aggregate messages incoming
from disparate sources. Conversations were listed by providing the
interlocutor user identity constituting also a visual representation of
the user social network.
News, weather forecasts and You Tube! mobile video clips were
grouped by using the concept of channel. This grants the user a unique
point of access. News are served according to the user language and
location and weather forecasts are served according to the user home
address. This avoids to present excess information that is not
meaningful to the user.
Without having usage data on the Biim social platform we can
evaluate the developed platform on the basis of the Triandis model.
The resulting application adheres to the principle of being ease to use,
since all the interactions are made by using only two buttons or the
key pad while writing messages. The utilitarian value as well is
positively influenced by the news provisioning service (including
weather forecasts). The hedonic value is augmented with You Tube!
videos and with the potential development of social event
management.
Hoping that the financial barriers will be overcomed by the diffusion
of flat price models we believe that the Biim social platform has the
potential to expand the limit of the possible within the structure of
users' everyday life.
Bibliography
1: Jan Rupnik, Finding community structure in social network analysis- overview, 2006
2: Martino Francesco and Spoto Andrea, Social Network Analysis: A brief theoretical review and further perspectives in the study of Information Technology, 2006
3: Watts, D. J. and Strogatz, S. H., Collective dynamics of 'small world' networks, 1998
4: Ackland, R., Mapping the U.S. Political Blogosphere: Are Conservative Bloggers More Prominent?, 2005
5: Adamic, L.A., Adar, E., How to search a social network, 2005 6: Licoppe, C., Smoreda, Z., Are social networks technologically embedded? How networks are changing today with changes in communication technology, 2005
7: boyd, d. m., & Ellison, N. B., Social Network Sites: Definition, History, and Scholarship, 2007
8: Scott Golder, Dennis Wilkinson and Bernardo A. Huberman, Rhythms of Social Interaction: Messaging within a Massive Online Network, June 28-30, 2007
9: Lee Humphreys, Mobile social networks and social practice: A case study of Dodgeball., 2007
10: Maria Bina, Dimitrios Karaiskos, George M. Giaglis, Investigating Factors Affecting Actual Usage Patterns of Mobile DataServices, 2007 11: Christer Carlsson, Frida Hyvönen, Petteri Repo and Pirkko Walden, Adoption of Mobile Services across Different Technologies, 2005
User Acceptance of Information Technology, 1989
13: Triandis, H.C., Values, attitudes, and interpersonal behavior, 1980 14: Roy Thomas Fielding, Architectural Styles and the Design of Network-based Software Architectures, 2000
15: , Facebook, http://en.wikipedia.org/wiki/Facebook 16: , MySpace, http://en.wikipedia.org/wiki/MySpace 17: , Twitter, http://en.wikipedia.org/wiki/Twitter
18: Danah Boyd, Viewing American class divisions through Facebook and MySpace, 2007 June 24
19: Hargittai Eszter, Whose space? Differences among users and non-users of social network sites,
20: Akshay Java, Xiaodan Song, Tim Finin, Belle Tseng, Why We Twitter: Understanding Microblogging Usage and Communities, August 12, 2007 21: Tim Bray, Jean Paoli, C. M. Sperberg-McQueen, Eve Maler, François Yergeau, Extensible Markup Language (XML) 1.0 (Fourth Edition),
http://www.w3.org/TR/2006/REC-xml-20060816 22: Dave Winer, RSS 2.0 Specification,
http://cyber.law.harvard.edu/rss/rss.html
23: Alejandro Abdelnur, Patrick Chanezon, Elaine Chien, Project ROME, https://rome.dev.java.net/
24: Network Working Group, The Atom Syndication Format (RFC 4287), 25: WikiMedia, YouTube, http://en.wikipedia.org/wiki/YouTube
26: Tiwari R., Buse, S., The Mobile Commerce Prospects: A Strategic Analysis of Opportunities in the Banking Sector, 2007
27: Rayport, J., Sviokla J., Managing in the Marketspace, 1994 28: Wikimedia, Wikipedia, Geocoding,
