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Investigating Factors Affecting Actual Usage Patterns of Mobile Data Services

Investigating Factors Affecting Actual Usage Patterns of Mobile Data Services. Maria Bina, Dimitrios Karaiskos, George M. Giaglis ISTLab Wireless Research Group Athens University of Economics and Business {mbina, dimkar, giaglis}@aueb.gr. Outline. Explaining MDS adoption Theoretical setting

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Investigating Factors Affecting Actual Usage Patterns of Mobile Data Services

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  1. Investigating Factors Affecting Actual Usage Patterns of Mobile Data Services Maria Bina, Dimitrios Karaiskos, George M. Giaglis ISTLab Wireless Research Group Athens University of Economics and Business {mbina, dimkar, giaglis}@aueb.gr

  2. Outline • Explaining MDS adoption • Theoretical setting • Decomposing the Triandis model to explain MDS use • Survey Research • Design • Demographics • Descriptive Statistics • Differentiating users from non-users • Conclusions • Further Research

  3. Focusing on MDS • Mobile Data Services - all non-voice value-adding services accessible through mobile networks • e.g. mobile e-mail, downloads to devices, access to content through a mobile phone, premium-priced SMS/MMS • Designated to augment end-user experience with mobility and enrich mobile business models for operators, service providers and other industry constituents • Adoption curves across different regions are not the same • Asia-Pacific vs. Europe/America gradient

  4. How to explain the diversity? • A plethora of research directions • Fit theoretical frameworks like Innovation Diffusion Theory and Technology Acceptance Model to the MDS context • Analyze industry and actor dynamics under a strategic or value chain perspective • Identify the potential effect of the social and cultural context, as well as the social implications of MDS use

  5. Theoretical Setting • Introducing the Triandis theory to explain MDS use • It separates the affective from the cognitive components of attitude • It suggests that habit, as well as intention, are predictors of human behavior

  6. Decomposing Triandis (1) • Intentions: a predictor of behavior having three antecedents • Affect • “feelings of joy, elation, or pleasure, or depression… associated … with a particular act” • Complements the inability to rationally explain why behaviors that have positive consequences are not adopted and why valueless, albeit joyful, behaviors are performed • Social Factors • “… internalization of the reference group’s subjective culture …” • Capture how the human part of an individual’s environment affects one in performing a specific behavior • Perceived Consequences (of the behavior) • The higher the perceived value of the consequences, the higher the likelihood that an individual will perform a behavior

  7. Decomposing Triandis (2) • Habit • “a behavior that is or has become automatic in a given situation” • Measured by the frequency of behavior occurrence • Strong predictor of behavior when it is well established • Facilitating Conditions • “objective factors, out there in the environment …” such as geographic and resource limitations • Behavior • Duration, intensity, and frequencyas behavior differentiators • Factors, like action, target, context, and time, impact the strength of the relationship between intention and behavior

  8. Mapping the Triandis model to the MDS context (1) Motives

  9. Mapping Triandis model to the MDS context (2) Barriers • Beyond Triandis: Perceived-ease-of-use • “the degree to which a person believes that using a particular system would be free of effort” • Functional complexity of operating devices and using services

  10. The Model • Objective: to confirm the suitability of the theory for studying MDS adoption and usage

  11. Survey Research Design • Questionnaire based on earlier operationalizations of the concepts • Pre-test procedure with selected informants • Collection of empirical data during the 2006 Worldwide Mobile Data Services Survey • A global web-based survey designed to explore customer behaviour and the market environment for Mobile Data Services around the world • Reporting the Greek part of the survey • 365 usable responses over a period of one month

  12. Demographic Statistics • MDS adoption curve still at its early stages • Only entertainment service users outnumber respective non-users • Demographic profiles of users and non-users more or less similar • Exceptions: entertainment services and women, m-commerce services and the 35-50 age group

  13. Descriptive Statistics • Utilitarian and hedonic aspects of MDS appeal to users • Anticipations for social approval are a minor motive • Security/privacy and financial concerns are the major inhibitors • Barriers are more or less a matter of the bearing network or market environment

  14. Differentiating Users from Non-Users (*** p < 0.001, ** p < 0.01, * p <0.05)

  15. Differentiating Users from Non-Users

  16. Conclusions • The adoption and usage of MDS is dependent on the value-for-money dimension • Shaped by the experiential nature of MDS • MDS benefits can only be discerned while using them and understood only after some time • The Triandis perspective is suitable for investigating MDS usage patterns • The delineated factors reflect the contents of the underlying theoretical concepts • However, technology barriers are questioned in terms of their applicability • The demarcation of four service categories in line with Triandis’ suggestion that the combination of individual idiosyncrasies and specific situations needs to be put into place to understand human behaviour

  17. Further Research • Apply the proposed model to specific standalone services picking up a critical mass of users, e.g. mobile email, MMS • Elaborate on the model through introducing additional concepts or inter-construct relationships • Cross-cultural surveyto shed light on the controversy surrounding current trends in MDS uptake • Longitudinal investigations of the interplay between intentions, habit, and actual behaviour

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