Title: Modelling mobile technology growth using diffusion models and Neural Networks

Authors: Somnath Mukhopadhyay, Kallol Bagchi, Godwin J. Udo

Addresses: Department of Information and Decision Sciences, College of Business, The University of Texas at El Paso, 500 West University Drive, Suite #205, El Paso, Texas 79968-0544, USA. ' Department of Information and Decision Sciences, College of Business, The University of Texas at El Paso, 500 West University Drive, Suite #205, El Paso, Texas 79968-0544, USA. ' Department of Information and Decision Sciences, College of Business, The University of Texas at El Paso, 500 West University Drive, Suite #205, El Paso, Texas 79968-0544, USA

Abstract: It is important for market planners and managers of Multi-National Enterprises (MNEs) to forecast global adoption of information technology for efficient market planning. This study builds two pure diffusion models, two popular time-series forecasting models, and one simple Neural Network (NN) model to predict mobile technology growth in 30 Organisation of European Council for Development (OECD) countries, the European Economic and Monetary Union (EMU) of the European Union (EU), and four non-OECD emerging nations. We compare the performances of all models on new samples. The results show that the NN model is superior to all other models.

Keywords: mobile technology; technology adoption; external influence; diffusion models; neural networks; multinational enterprises; MNEs; information technology; time-series forecasting; mobile communications; market planning.

DOI: 10.1504/IJEB.2009.029047

International Journal of Electronic Business, 2009 Vol.7 No.6, pp.553 - 580

Published online: 29 Oct 2009 *

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