Mobile Services


This event will be organized at Aalto School of Science and Technology, Konemiehentie 2, Espoo: House T, room T2. 
Please, register through the link on this page.
Price for one participation in this event is 200 EUR. INFORTE member organisations' staff can participate without additional participation fee. Registrations are taken in the registration order.


Jan Damsgaard, professor and the director of Center for Applied Information and Communication Technology at Copenhagen Business School, Denmark
Jonas Hedman, Associate Professor at Copenhagen Business School, Denmark


9:30  Morning coffee
9:45 - 10:00 Opening
10:00 - 11:30 Session 1: Technology use as consumption behavior: Theory of Consumption Values and Emotions (Jonas Hedman)
11:30 - 12:30 Lunch
12:30 - 14:00 Session 2: The Diffusion and Adoption of Mobile Social Services: The unit of analysis revisited (Jan Damsgaard)
14:00 - 14:30 Coffee
14:30-16:00 Session 3: Evolving technology use: Time-in / time-out (Jonas Hedman)
16:00 Closing


Technology use as consumption behavior: Theory of Consumption Values and Emotions (Jonas Hedman)

This presentation outlines two approaches to understand adoption of technology. First, the role of emotions (Nero-IS) is addressed. Neuro-IS assumes that all behavior, including intention to behave, is elicited by stimuli, emotions and emotional response. The role of emotions is tested in an exploratory setting, namely the adoption of the iPhone in Demark.

The iPhone was chosen as study object, as it had not yet been released in Denmark at the time of the study and thus was a novel study object. A research model that includes stimuli, emotions, emotional response and cognitive processes as latent variables and intention to buy as predictor was developed to test the role of emotions. The hypotheses derived from the research model are tested. Five hypotheses were developed to explain the relationship between the latent variables and the predictor, and the results show that positive emotions elicit the cognitive process constructs "image" and "compatibility" as well as the predictor "intention to buy".

The second approach takes it outset in consumer research and the Theory of Consumption Values (TCV). Data was collected through interviews, focus groups, and surveys from smart phone users during a six month period. We have adopted a narrative approach to analyze our empirical data and present the data as a dialogue between two smart phones. The story presented in the dialogue shows how different consumption values, including functional, epistemic, emotional, social, and conditional values, drive technology use and how they evolve over time. In the beginning, epistemic, emotional, social values drove the use. Later, functional value became the key driver.

Evolving technology use: Time-in / time-out (Jonas Hedman)

This presentation address the topic of evolving use. It is investigated by using the distinction of time-in and time-out usage. This distinction describes how uses of technology within the life-world (i.e. the ordinary, the un-reflected) can be punctuated by time-out use when a user takes out time to consciously use or reflect on a medium. Data was collected through a longitudinal field study involving focus groups, interviews, and surveys from smart phone users during a six-month period. We have adopted a theoretically informed grounded approach to analyze our empirical data and present rich data. The results show how technology use evolves over time and provides theoretical explanation as to why usage changes with time. The time-in/out distinction shows how the value of an "extraordinary device" changes over time, thus  accomplishing sensitivity to the artifact by examining the flow of activities. By repurposing the time-in/out distinction from its origin in media- and communications theory, this paper marks a pragmatic move that allows the distinction to be applied to more deeply understand the adoption and appropriation of technology products.

The Diffusion and Adoption of Mobile Social Services: The unit of analysis revisited (Jan Damsgaard)

Web 2.0 systems and applications are increasingly the preferred manner in which information and knowledge is shared communication across individuals. Web 2.0 is defined loosely as a the aggregations of technologies such as blogs, wiki's, mashups, social bookmarking sites, and others that are build around relations that individuals establish or confirms with each other through these technologies for the purpose of communication, collaboration and coordination of information, knowledge and activities. Web 2.0 is inherently a participative environment where the consumers of information and knowledge are simultaneously the co-creators and producers of new information and knowledge. Most of the Web 2.0 are developing into mobile applications.

Traditionally diffusion and adoption studies have focused on the uptake of innovations by individuals and we know a great deal about the actors that promote or retard the diffusion process. For example the spread of coffee makers or uptake of TV sets is nicely covered by traditional models. This success in explaining and predicting the diffusion and adoption of innovations has led scholars to extend the models to cover others innovations that are quite different than those the models where originally intended for and this has been done without revisiting the assumptions and limitations of the original models.

DOI theory was developed for and thus is especially effective at examining singular monolithic technologies or well-defined systems. Such systems typically rely on economies of scale on the supply side and the use of the system on the demand side is fairly independent of others use of the same systems. For instance, your use of a coffee maker is independent of other individuals' choice of coffee maker.

Web 2.0 technologies become the glue that ties social networks together. Web 2.0 technologies are most often incompatible. So that relations and information shared in one Web 2.0 application is not necessarily available in another. So for each social network there is a tendency to only use one Web 2.0 application for its online coordination and information exchange. The characteristics of the individuals belonging to the social network are therefore subordinated the characteristics of the social network. The best predictor of what application an individual use is consequently the social network that the individual belong to and not his/her individual characteristics as DOI would assume. Different individuals may probe different applications in search of the appropriate but in the end the social network will only adopt one application. We therefore need to shift the unit of analysis from the singular user to the social network. The individual user may prefer a different application but adoption would lead to online social exclusion and therefore the individual will adopt the same application as the rest of the social network regardless of personal preferences and past experiences.