Abstract
Crowdsourcing is a business model that relies on computer networks. It was first introduced in 2006 and more and more people began to participate in this business model. At present, how to improve the completion rate of crowdsourcing mode task, while reducing the cost of the publisher has became an urgent problem. Based on the nonstandard form, we implement experiments on the dataset given by CUMCM and propose a time sharing + dynamic pricing model to solve the problem of offline tasks in crowdsourcing. Experiment results show that the model task completion rate improved to 83.5%, 26.6% higher than the traditional mode, the average task publication costs 69 yuan, 4 yuan lower than the traditional. Finally, according to the experiment results, we make some reasonable suggestions to the future crowdsourcing platform design.
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Acknowledgement
Project supported by the National Natural Science Foundation (61502155,61772180); Education cooperation and cooperative education project (201701003076); Research start-up fund of Hubei university of technology (BSQD029); University student innovation and entrepreneurship project of Hubei university of technology (201710500047).
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Yuan, L., Zhou, Y., Fu, Jr., Yan, Ly., Wang, Cz. (2018). Research on Pricing Model of Offline Crowdsourcing Based on Dynamic Quota. In: Zhou, Q., Gan, Y., Jing, W., Song, X., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 901. Springer, Singapore. https://doi.org/10.1007/978-981-13-2203-7_5
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DOI: https://doi.org/10.1007/978-981-13-2203-7_5
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