2 research outputs found
A Dynamic Structural Model of User Learning in Mobile Media Content
Consumer adoption and usage of mobile communication and multimedia
content services has been growing steadily over the past few years in
many countries around the world. In this paper, we develop and estimate
a structural model of user behavior and learning with regard to content
generation and usage activities in mobile digital media environments.
Users learn about two different categories of content – content
from regular Internet social networking and community (SNC) sites and
that from mobile portal sites. Then they can choose to engage in the
creation (uploading) and consumption (downloading) of multi-media
content from these two categories of websites. In our context, users
have two sources of learning about content quality – (i) direct
experience through their own content creation and usage behavior and
(ii) indirect experience through word-of-mouth such as the content
creation and usage behavior of their social network neighbors. Our model
seeks to explicitly explain how direct and indirect experiences from
social interactions influence the content creation and usage behavior of
users over time. We estimate this model using a unique dataset of
consumers' mobile media content creation and usage behavior over a
3-month time period. Our estimates suggest that when it comes to user
learning from direct experience, the content that is downloaded from
mobile portals has the highest average quality level. In contrast,
content that is downloaded by users from SNC websites has the lowest
average quality level. Besides, the order of magnitude of accuracy of
signals for each content type from direct experiences is consistent with
the order of the quality levels. This finding implies that in the
context of mobile media users make content choices based on their
perception of differences in both the average content quality levels and
the extent of content quality variation. Further we find that signals
about the quality of content from direct experience are more accurate
than signals from indirect experiences. Potential implications for
mobile phone operators and advertisers are discussed
A Dynamic Structural Model of User Learning in Mobile Media Content
Consumer adoption and usage of mobile communication and multimedia
content services has been growing steadily over the past few years in
many countries around the world. In this paper, we develop and estimate
a structural model of user behavior and learning with regard to content
generation and usage activities in mobile digital media environments.
Users learn about two different categories of content – content
from regular Internet social networking and community (SNC) sites and
that from mobile portal sites. Then they can choose to engage in the
creation (uploading) and consumption (downloading) of multi-media
content from these two categories of websites. In our context, users
have two sources of learning about content quality – (i) direct
experience through their own content creation and usage behavior and
(ii) indirect experience through word-of-mouth such as the content
creation and usage behavior of their social network neighbors. Our model
seeks to explicitly explain how direct and indirect experiences from
social interactions influence the content creation and usage behavior of
users over time. We estimate this model using a unique dataset of
consumers' mobile media content creation and usage behavior over a
3-month time period. Our estimates suggest that when it comes to user
learning from direct experience, the content that is downloaded from
mobile portals has the highest average quality level. In contrast,
content that is downloaded by users from SNC websites has the lowest
average quality level. Besides, the order of magnitude of accuracy of
signals for each content type from direct experiences is consistent with
the order of the quality levels. This finding implies that in the
context of mobile media users make content choices based on their
perception of differences in both the average content quality levels and
the extent of content quality variation. Further we find that signals
about the quality of content from direct experience are more accurate
than signals from indirect experiences. Potential implications for
mobile phone operators and advertisers are discussed