Consumer satisfaction versus churn in the case of upgrades of 3G to 4G cell networks
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Consumer satisfaction versus churn in the case of upgrades of 3G to 4G cell networks Steven D’Alessandro & Lester Johnson & David Gray & Leanne Carter
# Springer Science+Business Media New York 2014
Abstract The current use of 3G technologies has created significant demands for capacity, such as cell TV, and this needs to be balanced with the capital constraints of many firms. Providers face price pressures on margins and the need to update cell networks to 4G in the post-GFC era where capital is scarce. Understanding consumer behavior in this area by use of simulations may be a time- and cost-efficient method, but how accurate is it? This study demonstrates that the use of a simple, agent-based model can lead to accurate initial prediction of parameters of satisfaction with a cell phone provider, and provides a basis of understanding factors of cell phone subscriber choice in the context of the introduction of new technology. Keywords Simulations . Netlogo . Mobile phone networks . 3G versus 4G choice . Provider choice models . Triangulation of models
1 Introduction Simulation in marketing is an innovative and cost-effective means to understand complex, time-dependent consumer behavior, by simplifying decision rules of actors S. D’Alessandro (*) : L. Johnson School of Management and Marketing, Charles Sturt University, Panorama Avenue, Bathurst, NSW 2795, Australia e-mail: [email protected] L. Johnson e-mail: [email protected] L. Johnson Melbourne Business School, Charles Sturt University, Panorama Avenue, Bathurst, NSW 2795, Australia D. Gray : L. Carter Department of Marketing and Management, Macquarie University, North Ryde, NSW 2109, Australia D. Gray e-mail: [email protected] L. Carter e-mail: [email protected]
Mark Lett
and allowing for interactions which mimic marketplace phenomena (Ma and Büschken 2011; McIntyre and Miller 1992; Neslin and Schneider Stone 1996; Ross et al. 2000). Compared to survey, experimental, and test market research, simulations have the potential to provide much quicker insights into marketplace behavior at significantly lower costs. One popular and easy to program simulation is Agent-Based Modeling (ABM). ABM as one type of simulation in marketing has been shown to be useful in showing the dynamics and complexity of markets and networks. Rand and Rust (2011, p185) list application areas suitable for ABM as consisting of diffusion of information and innovations, retail location decisions, inter-firm relationships, strategy and competition, marketing mix models and retail, and servicescape design. ABM simulations can also simplify what appears to be multifaceted and novel consumer behavior. Goldenberg et al. (1999) note that many new innovations and product choices in markets can be modeled accurately with as few as six parameters. Yet the acceptance of ABM in published marketing research has been lacking. As Rand and Rust (2011, p182) note: Critiques of agent-based modeling often come from two points of view: one viewpoint is that ABM does not deal with real
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