Using IQA to Extract Mental Models Concerning Quality Evaluation Factors for Social Networking Services on Smartphones

  • Lee Y
  • Chen L
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Abstract

Although today's users of mobile phones are afforded increasing control as the popularity and richness of information provided by smartphones increases, how these users make choices and evaluations cannot be explicitly expressed. This study uses an acute observation of designers of technology and aesthetics to conduct a mental-model analysis of smartphones with the purpose of explicitly identifying the differences in the schemas of users. This study also modifies the mental model to evaluate the practicability of the mental model. Hence, this study investigates groups of subjects, comparing freshmen and graduating students froma college of design, and adopts a schematized data collection and analysis approach, Interactive Qualitative Analysis (IQA), to ascertain the relationships between factors and establish a complete user mental model. The study results present 11 primary affinity factors: "Pricing," "Advertisement," "User Interface," "In-novation Functions," "System Maintenance," "Privacy," "Utility Functions," "Personalization," "Net-work Performance," "Customer Service," and "Multimedia Contents." The primary driver in evaluating smartphones is found to be "Pricing" for graduating students and "Privacy" for freshmen. The two groups share the same final effect factor, "Multimedia Contents." This study has successfully identified differences between the different mental models of the two groups, supporting the method that using IQA to perform a quality evaluation of social networking for smartphones is effective. Consequently, platform developers can understand user demand through a mental model and can design good platform functions to effectively improve users' experience of smartphones.

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APA

Lee, Y.-L., & Chen, L.-C. (2016). Using IQA to Extract Mental Models Concerning Quality Evaluation Factors for Social Networking Services on Smartphones. Social Networking, 05(01), 16–26. https://doi.org/10.4236/sn.2016.51003

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