1. gaining business value from interactive innovations Mobile Business Models Critical Success Factors for the Management of Innovative Mobile Business Models Reinhard Neudorfer

2. Overview. I want to give you the results of an examination of mobile business models in the Austrian market. Content 1.Theoretical Classification 2.Approaches in Technology and Innovation Management 3.Risk-Benefit in the Adoption process (RBA-Model) 4.Empirical Examination of the RBA-Model 5.Recommendations for Action

3. Theoretical Classification. The examined Cellular business models are only a part of Mobile Business. Cellular business models (narrower sense) are services, where the benefit is created by the use of the public cellular network (Video-phoning, mPayment, SMS...). eBusiness Cellular business models mBusiness RF-IDWAP SMS Video-phoning wLAN Cellular business models (broader sense) are services, where the creation of benefit is directly connected to the use of the public cellular network (logos, background images...).

4. Approaches. Different approaches and models exist which try to explain the success of technological innovation. 1.The Adoption or Diffusion- Theory Tries to explain the speed of penetration of innovative technology through certain criteria (Roger‘s: relative advantage, compatibility complexity, trialability, observability) 2.Approaches to the Explanation of User Acceptance Technology Acceptance Model (Davis‘ TAM), Task-Technology-Fit-Model (Goodhue‘s TTFM) 3.The Theory of Perceived Risk (Cox, Cunningham, Bettman) The purchasing decision is affected by the factor of negative purchase consequence and its propability.

5. Approaches. Regarding the theories of Innovation and Technology Management - no theory fits perfectly. TheoryExplanation GoalWeakness Adoption TheoryExplanation of the diffusion of an innovation at the user‘s level Number and missing prioritization of the product qualities Diffusion TheoryExplanation of the diffusion of an innovation at the aggregated level Reasons for the diffusion are not taken into account Models for the Explanation of User Acceptance Mostly an explanation for the reason of (non-)use No model fits entirely to mServices; models partly explain ex post non-use Theory of Perceived RiskExpansion of the adoption theory by the criteria of perceived risk Only takes a look at the risk dimension

6. The RBA-Model. In the RBA-Model, the dimension of expected benefits is compared to the perceived risk in order to analyse the adoption probability. Adoption probability Perceived risk Service risk Cost risk Adoption progress Social benefit Service-specific benefit Economic benefit Benefit dimension Theory of Perceived Risk

7. The RBA-Model. The amount of perceived risk will usually decrease during the adoption process. Risk-reduction effect Perceived risk Risk-recignition effect Non-perceived risk Perceived part of the total risk Awareness stage Opinion forming stage Decision stage Non-perceived part of the total risk Risk Decreased risk Non-perceived residual risk Perceived residual risk Time

8. Empirical Examination. In order to get highly sophisticated results I made a close empirical examination. Three different Cellular business model categories: - Information: SMS-Information Service, mobile Information Retrieval via WAP - Communication: Mobile-phoning, Video-phoning - Transaction: Mobile Ticketing, Mobile Parking Sample construction: quota plan, demographic data from the Austrian regulatory agency (RTR) Each category sample (n=610), 105 questions in a standardized questionnaire, Verification of the RBA model with a sample of n=1830 Time Periode for the empirical examination: September - December 2003 Analytical methods: multiple regression and a causal-analytic examination of the direct and indirect effects

9. Empirical Examination. The empirical examination revealed some unexpected results. The results of the Causal-analytic examinations showed us: -No direct impact of the cost risk (perceived costs) to the adoption probability -The service risk determines the cost risk Adoption probability Service riskCost risk Economic benefit Service- specific benefit Social benefit 0,94 0,69 0,37 0,28 -0,28 0,290,30 0,28 The price of a mobile Service does not influence the adoption probability.

10. Empirical Examination. The gap between the benefit and the risk curve illustrates the market penetration of the different categories in Austria. The user of a mobile Service does not think that he has to face any risk in the information category. Benefit Risk TransactionCommunication Influence of amount on adoption Probability The benefit in the communication category is obvious and mainly responsible for the adoption probability.

11. Recommendations for Action. If the following measures are taken, a greater adoption probability of innovative cellular business models can be expected. 1.Mobile Network Operators (MNO) or Wireless Application Service Providers (WASP) should not stick to reducing the price for the Service, as verified in the empirical examination, as it will not influence the adoption much. 2.Information Class: The social- and the service-specific benefit should be given priority in order to raise the adoption probability (e.g. emphasis on entertainment possibilities). 3.Communication Class: Reduce the risk of not having service (e.g. improvement of the public cellular network, reach the critical mass of mobile devices/video-phones). 4.Transaction Class: Focus on communicating the advantages in comparison to the alternatives (e.g. time which will be saved by using the mobile service).

12. gaining business value from interactive innovations Thank you for your attention!