Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/123456789/10753
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dc.contributor.advisorDe, Rahul
dc.contributor.authorPai, Ratnakar
dc.date.accessioned2017-10-04T10:07:38Z
dc.date.accessioned2019-03-18T10:29:26Z-
dc.date.available2017-10-04T10:07:38Z
dc.date.available2019-03-18T10:29:26Z-
dc.date.issued2008
dc.identifier.urihttp://repository.iimb.ac.in/handle/123456789/10753
dc.description.abstractData from the Indian Mobile market 2006 statistical handbook reveals that the mobile ownership will pass 100 million in 2007 as the largest middle class in the world takes up ownership. Indian mobile owners are becoming more connected as a result of cheaper calls, subsidized handsets and widespread availability of prepaid cards lowering the barriers to ownership. With availability of such a prolific customer base, services based on the existing mobile phone infrastructure would be essential to improving the return on investment of operators and improve operating efficiencies. For anyone developing a business model for mobile services, it would be essential to predict the adoption of the service(using Bass Models and other such models based on diffusion of innovations). The adoption can also be modelled using an agent based model. An Agent-Based Model (ABM) is a computational model for simulating the actions and interactions of autonomous individuals in a network, with a view to assessing their effects on the system as a whole. The project attempts to develop a simple multi-agent model to simulate adoption of mobile services. This involves developing an adoption model and analyzing it to learn about large-scale effects.
dc.language.isoen_US
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGSEM-PR-P8-070-
dc.subjectMobile services
dc.subjectCommunication technology
dc.titleA model for prediction of mobile services adoption using multi-agent modelling
dc.typeProject Report-PGSEM
dc.pages49p.
dc.identifier.accessionE32120-
Appears in Collections:2008
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