A Pricing Model for Self-Help Investigation Offline Based on Multivariate Linear Regression Analysis

摘要

The self-help market investigation is a new kind of commerce. It encourages the massive registered Internet users to track the goods placement in the market by taking pictures and upload these photos to a platform over the Internet. Nevertheless, we should design a fair price for each task to mobilize the offline users to do it. However, the solutions adapted to the issues are absent. To solve this problem, we proposed a pricing model based on multivariate linear regression analysis. We analyzed the task density, the per capita creditworthiness of the subscribers, and the per capita GDP and proved they were three main factors that affected the tasks' price. As a result, we figured out three variables of the coefficients. Experiments showed that the significance of per capita creditworthiness of the subscribers was greater than the recognized significance threshold 0.05, while the significance of per capita GDP and the task density were both less than the well-known significance level.