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
(broader sense) are
services, where the creation
of benefit is directly
connected to the use of the
public cellular network
(logos, background
images...).
mBusiness
eBusiness
Cellular business
models
WAP
Video-phoning
SMS
RF-ID
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
an innovation at the user‘s level
Number and missing
prioritization of the product
qualities
Diffusion Theory
Explanation 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 Risk
Expansion of the adoption
theory by the criteria of
perceived risk
Only takes a look at the risk
dimension
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
Service-specific benefit
Adoption
probability
Perceived risk
Social benefit
Service risk
Benefit dimension
Cost risk
Theory of Perceived Risk
The RBA-Model.
The amount of perceived risk will usually decrease during the
adoption process.
Risk
Risk-reduction effect
Perceived part
of the total risk
Perceived risk
Risk-recignition effect
Non-perceived
part of the
total risk
Non-perceived risk
Awareness
stage
Opinion forming
stage
Decreased
risk
Perceived residual
risk
Non-perceived residual
risk
Decision
stage
Time
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
costs) to the adoption probability
-
The service risk determines the cost risk
-0,28
Adoption probability
 The price of a mobile Service does not
influence the adoption probability.
0,29
0,30
0,28
Servicespecific benefit
Economic
benefit
Social benefit
0,37
0,69
0,28
Empirical Examination.
The gap between the benefit and the risk curve illustrates the
market penetration of the different categories in Austria.
The benefit in the
communication
category is obvious
and mainly
responsible for the
adoption
probability.
Einfluss
auf of
dieamount
Adoptionson
Influence
Probability
adoption
wahrscheinlichkeit
(betragsmäßig)
The user of a mobile Service does not think that he has to face any risk in the
information category.
1,20
1,00
0,80
Benefit
Nutzen
0,60
Risiko
Risk
0,40
0,20
0,00
Information
Communication
Kommunikation
Transaction
Transaktion
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!