An empirical analysis of the factors influencing the data killing behaviour of taxi platforms

Various e-commerce platforms have been exposed to the existence of big data "kill familiar" behaviour, this behaviour is the old customer price deception, this paper is an empirical study of the influence of factors on the taxi platform to kill familiar behaviour. The establishment of regression models to put forward research hypotheses, the distribution of questionnaires to collect data, to verify the influence of factors on the taxi platform big data kill familiar behaviour. It is found that big data kill familiarisation has a negative impact on the conversion cost, and the quality of IWOM of the taxi platform can weaken the negative impact of "kill familiarisation behaviour" on the customer's willingness to consume. Accordingly, we should improve the market regulation mechanism, optimally adjust the pricing strategy of goods, and improve the enthusiasm of consumers to protect their rights, so as to eliminate the negative effect of "familiarity killing".