TY - JOUR
KW - Analysis
KW - Mobile Services
KW - Human-Computer Interaction (HCI)
AU - Bernhard Klein
AU - Ivan Pretel
AU - Sacha Vanhecke
AU - Ana Lago
AU - Diego Lopez-de-Ipiña
AB - Several mobile acceptance models exist today that focus on user interface handling and usage frequency evaluation. Since mobile applications reach much deeper into everyday life, it is however important to better consider user behaviour for the service evaluation. In this paper we introduce the Behaviour Assessment Model (BAM), which is designed to gaining insights about how well services enable, enhance and replace human activities. More specifically, the basic columns of the evaluation framework concentrate on (1) service actuation in relation to the current user context, (2) the balance between service usage effort and benefit, and (3) the degree to which community knowledge can be exploited. The evaluation is guided by a process model that specifies individual steps of data capturing, aggregation, and final assessment. The BAM helps to gain stronger insights regarding characteristic usage hotspots, frequent usage patterns, and leveraging of networking effects showing more realistically the strengths and weaknesses of mobile services
IS - Special Issue on Improvements in Information Systems and Technologies	
M1 - 3
N2 - Several mobile acceptance models exist today that focus on user interface handling and usage frequency evaluation. Since mobile applications reach much deeper into everyday life, it is however important to better consider user behaviour for the service evaluation. In this paper we introduce the Behaviour Assessment Model (BAM), which is designed to gaining insights about how well services enable, enhance and replace human activities. More specifically, the basic columns of the evaluation framework concentrate on (1) service actuation in relation to the current user context, (2) the balance between service usage effort and benefit, and (3) the degree to which community knowledge can be exploited. The evaluation is guided by a process model that specifies individual steps of data capturing, aggregation, and final assessment. The BAM helps to gain stronger insights regarding characteristic usage hotspots, frequent usage patterns, and leveraging of networking effects showing more realistically the strengths and weaknesses of mobile services
PY - 2013
SP - 15
EP - 22
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Analysis of Log File Data to Understand  Mobile Service Context and Usage Patterns
UR - http://www.ijimai.org/journal/sites/default/files/files/2013/06/ijimai20132_3_2_pdf_26595.pdf
VL - 2
SN - 1989-1660
ER -