Contextual patterns in mobile service usage

Mobile services differ from other services because of their temporal and spatial attributes. Mobile services additionally differ from each other in their value-added to the end-user. Some services—such as emailing and voice—are more business oriented. On the other hand, various free-time oriented services are provided in new smartphones, such as imaging and music playback. The present paper studies how mobile services are used in different contexts. For this, the paper develops a specialized algorithm that can be used with handset-based usage data acquired straight from end-users in an established panel study process. Educated guesses can be drawn on the user context based on the developed algorithm. In the present exercise usage contexts were divided into home, office and “on the move”. The algorithm is used with exemplary data from Finland and the UK covering 324 consumers in 2006. More than 70% of contextual use cases are correctly classified based on raw data. According to exemplary results particularly multimedia services are used “on the move”, whereas legacy mobile services experience more evenly distributed usage across all contexts. The algorithm that identifies context based on raw data provides a new angle to mobile end-user research. In the future, the accuracy of the algorithm will be improved with the integration of seamless cell-id logging and GPS data.

[1]  P. Kotler,et al.  Principles of Marketing , 1983 .

[2]  P. A. Dabholkar.  Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality , 1996 .

[3]  Gregory D. Abowd,et al.  Cyberguide: A mobile context‐aware tour guide , 1997, Wirel. Networks.

[4]  Albert Anghern.  Designing mature Internet business strategies: The ICDT model , 1997 .

[5]  Clayton M. Christensen.  The Innovator's Dilemma , 1997 .

[6]  Mary Jo Bitner,et al.  Self-Service Technologies: Understanding Customer Satisfaction with Technology-Based Service Encounters , 2000 .

[7]  Bill Anckar,et al.  VALUE CREATION IN MOBILE COMMERCE: FINDINGS FROM A CONSUMER SURVEY , 2002 .

[8]  Fernando J. Velez,et al.  Mobile broadband services: classification, characterization, and deployment scenarios , 2002 .

[9]  S. Jarvenpaa,et al.  Exploring the implications of m-commerce for markets and marketing , 2002 .

[10]  Eija Kaasinen,et al.  User needs for location-aware mobile services , 2003, Personal and Ubiquitous Computing.

[11]  George M. Giaglis,et al.  Towards a classification framework for mobile location services , 2003 .

[12]  Irvine Clarke,et al.  Mobile portals: the development of M-commerce gateways , 2003 .

[13]  K. Mitchell,et al.  Location based services: locating the money , 2003 .

[14]  Timo Ojala,et al.  SmartRotuaari - Context-Aware Mobile Multimedia Services , 2003 .

[15]  Kristina Heinonen,et al.  Swedish Mobile Market: Consumer Perceptions of Mobile Services , 2003 .

[16]  Andrea Vitaletti,et al.  Cell-ID location technique, limits and benefits: an experimental study , 2004, Sixth IEEE Workshop on Mobile Computing Systems and Applications.

[17]  Kristina Heinonen.  Time and Location as Customer Perceived Value Drivers , 2004 .

[18]  Jarkko Vesa.  Mobile Services In The Networked Economy , 2005 .

[19]  Mika Raento,et al.  ContextPhone: a prototyping platform for context-aware mobile applications , 2005, IEEE Pervasive Computing.

[20]  Per E. Pedersen,et al.  Intentions to use mobile services: Antecedents and cross-service comparisons , 2005 .

[21]  Nathan Eagle,et al.  Machine perception and learning of complex social systems , 2005 .

[22]  Sirkka L. Jarvenpaa,et al.  Managing the Paradoxes of Mobile Technology , 2005, Inf. Syst. Manag..

[23]  Judy Kay,et al.  Consistent Modelling of Users, Devices and Sensors in a Ubiquitous Computing Environment , 2005, User Modeling and User-Adapted Interaction.

[24]  Hans van der Heijden,et al.  Effects of Context Relevance and Perceived Risk on User Acceptance of Mobile Information Services , 2005, ECIS.

[25]  Shintaro Okazaki,et al.  New Perspectives on M-Commerce Research , 2005 .

[26]  G. S. Mort,et al.  Marketing m-services: Establishing a usage benefit typology related to mobile user characteristics , 2005 .

[27]  E. Cerqueira,et al.  Control of Multi-User Services in Mobile Heterogeneous Environments , 2005 .

[28]  Timo Smura.  COMPETITION BETWEEN EMERGING WIRELESS NETWORK TECHNOLOGIES: CASE HSPA VS. WIMAX IN EUROPE , 2006 .

[29]  Hannu Verkasalo.  Empirical Insights on the Evolution of the Finnish Mobile Market , 2007, 2007 6th Conference on Telecommunication Techno-Economics.

[30]  Heikki Hämmäinen,et al.  A handset‐based platform for measuring mobile service usage , 2007 .

[31]  Hannu Verkasalo,et al.  Handset-Based Monitoring of Mobile Subscribers , 2008 .

[32]  Kristina Heinonen,et al.  Classifying Mobile Services , 2008 .

[33]  Eija Kaasinen,et al.  User Acceptance of Mobile Services , 2009, Int. J. Mob. Hum. Comput. Interact..

[34]  Timo Smura,et al.  A framework for analysing the usage of mobile services , 2009 .

[35]  Wei Li.  Toward a Person-Centric Context Aware System , .