Social Acceptance and Usage Experiences from a Mobile Location-Aware Service Environment

Klein, Bernhard; Pérez, Juan; Guggenmos, Christian; Pihlajamaa, Olli; Heino, Immo; Ser, Javier Del

doi:10.1007/978-3-642-29479-2_14

“…Then, initial and long-term service usage should be compared in order to identify entry barriers. Correlated with this analysis, is the grouping of logging data according to the technical technical experience (see technical adoption model described by Rogers [12]). By comparing innovators, early adopters, early majority, late majority and laggards a reasonable priority list of future service modifications can be determined.…”

Section: A the Assessment Processmentioning

confidence: 99%

Analysis of Log File Data to Understand Mobile Service Context and Usage Patterns

Klein¹,

Pretel²,

Vanhecke³

et al. 2013

IJIMAI

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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 service

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“…Then, initial and long-term service usage should be compared in order to identify entry barriers. In a subsequent step, the logging data of trial users shall be clustered according to the technical diffusion model from Rogers [12] to see how technical experience can influence mobile service usage. By comparing innovators, early adopters, early majority, late majority and laggards a reasonable priority list of future service modifications can be determined.…”

Section: The Assessment Processmentioning

confidence: 99%

The Behaviour Assessment Model for the Analysis and Evaluation of Pervasive Services

Klein

¹

,

Pretel

²

,

Reips

³

et al. 2013

Advances in Intelligent Systems and Computing

Self Cite

0

View full text Add to dashboard Cite

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.

show abstract