Behavioral biases under nonlinear pricing: evidence from industry of mobile broadband services in Ecuador

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2019-11-11

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Pontificia Universidad Católica del Perú

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A fundamental assumption of rational choice model is that customers most of the time choose the best price that minimizes their expenses, but according the Behavioral Economics optimal consumer decision-making can be affected by multiple types of heuristics or behavioral biases. The purpose of this research was to determine and quantify the joint effect of overconfidence bias, framing bias, choice overload bias and smartphone addiction on the optimal usage under nonlinear pricing applied to mobile broadband customers in Ecuador. The analysis was quantitative, using information collected in the field and matched with billing information of 541 mobile customers. The quantitative research design included two steps. First step involved the construction of scales each behavioral bias (independent latent variables) and non-optimal usage (dependent variable); second step involved the estimation of relationship of independent variables with dependent variable. Findings evidenced that 71% mobile broadband customers deviated from the optimal level of use contracted under nonlinear pricing plan (naïve customers). Empirical results found that customers who demonstrated a certain degree of overconfidence bias, framing bias, smartphone addiction, and choice overload bias are more prone to choose wrongly their nonlinear pricing, under/overusing the minimum data allowance including in the plan. The results have important implications for business management, because if mobile firms can identify “naïve consumers” could take advantage from complex nonlinear pricing to maximize profits. For social perspective, the first concern should be the recognition of phenomena of behavioral bias is high enough in customers and can become a market failure under specific conditions, harming customers in particular women and aged users.

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Empresas de servicios, Innovación tecnológica--Ecuador, Investigación cuantitativa

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