This article describes the design of a model to identify the relevant factors in the decision-making process of consumers that adopt technology within a dynamic social network. The proposed model includes specific theories and tools from the psychology of consumer behavior, social networks, and complex dynamical systems. The model has been developed to work with the mobile smartphone market and was able to describe trends similar to those described in the real world market.
This paper describes a model to simulate the decision-making process of consumers that adopts technology within a dynamic social network. The proposed model use theories and tools from the psychology of consumer behavior, social networks and complex dynamical systems like the Consumat framework and fuzzy logic. The model has been adjusted using real data, tested with the automobile market and it can recreate trends like those described in the world market.
In this article we analyze the BSS of the city of Medellin - Colombia called “EnCicla”. The objective is to know the overall behavior of the system to be able to identify the most used hours, the most used stations and the types of behavior that occur. Data on the operation of the system has been collected, with which processing and analysis has been carried out categorized by location and time slots. With the data collected and the statistical analysis performed identified the critical stations within the system, the patterns of behavior of each of them, the peak hours, the maximum, minimum and variability of occupancy on average; which generates the challenge to model, simulate and improve the functioning of the system, as well as evaluating operating policies and its implementation.
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