gaining business value from interactive innovations Mobile Business Models Critical Success Factors for the Management of Innovative Mobile Business Models Reinhard Neudorfer 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 Theoretical Classification. The examined Cellular business models are only a part of Mobile Business. Cellular business models mBusiness eBusiness (broader sense) are services, where the creation Cellular business of benefit is directly models connected to the use of the public cellular network WAP RF-ID Video-phoning (logos, background images...). SMS wLAN Cellular business models (narrower sense) are services, where the benefit is created by the use of the public cellular network (Video-phoning, mPayment, SMS...). 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. Approaches. Regarding the theories of Innovation and Technology Management - no theory fits perfectly. Theory Explanation Goal Weakness Adoption Theory Explanation of the diffusion of Number and missing an innovation at the user‘s level prioritization of the product qualities Diffusion Theory Explanation of the diffusion of Reasons for the diffusion are an innovation at the not taken into account aggregated level Models for the Explanation Mostly an explanation for the No model fits entirely to of User Acceptance reason of (non-)use mServices; models partly explain ex post non-use Theory of Perceived Risk Expansion of the adoption Only takes a look at the risk theory by the criteria of dimension perceived risk 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 progress Economic benefit Adoption Service-specific benefit Perceived risk probability Social benefit Service risk Cost risk Benefit dimension Theory of Perceived Risk The RBA-Model. The amount of perceived risk will usually decrease during the adoption process. Risk Risk-reduction effect Decreased Perceived part risk Perceived risk of the total risk Perceived residual Risk-recignition effect risk Non-perceived part of the Non-perceived risk total risk Non-perceived residual risk Awareness Opinion forming Decision Time stage stage stage 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 Empirical Examination. The empirical examination revealed some unexpected results. 0,94 Service risk Cost risk The results of the Causal-analytic examinations showed us: - No direct impact of the cost risk (perceived -0,28 costs) to the adoption probability - The service risk determines the cost risk Adoption probability The price of a mobile Service does not influence the adoption probability. 0,29 0,30 0,28 Service- Economic Social benefit specific benefit benefit 0,69 0,37 0,28 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. 1,20 wahrscheinlichkeit (betragsmäßig) The benefit in the Influence die Adoptions- communication 1,00 Einfluss aufof amount on adoption Probability category is obvious and mainly 0,80 responsible for the Benefit Nutzen adoption 0,60 Risk Risiko probability. 0,40 0,20 0,00 Information Kommunikation Communication Transaktion Transaction 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). gaining business value from interactive innovations Thank you for your attention!
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