A three-way decision method with pre-order relations

Do backers prefer crowdfunding or pre-order? An empirical study

To advertise or estimate demand, many pre-order items appear on crowdfunding platforms. Few studies have explored backers' preferences between crowdfunding projects and pre-order items. To analyze backers' preferences, 1,800 technology and innovation campaigns were collected from the Indiegogo crowdfunding platform. Using the product stage badge, the campaigns in the concept and prototype stages were treated as crowdfunding projects, while those in the production and shipping stages were labeled pre-order items, resulting in 1,305 crowdfunding projects and 495 pre-order items, respectively. Propensity score matching was leveraged to investigate differences in fundraising outcomes between crowdfunding projects and pre-order items. The results indicate that pre-order items have better fundraising outcomes than crowdfunding projects, suggesting that backers are risk-averse on the crowdfunding platform.

A novel behavioral three-way decision model with application to the treatment of mild symptoms of COVID-19

The Coronavirus Disease 2019 (COVID-19) has popularized since late December 2019. In present, it is still highly transmissible and has severe impact on the public health and global economy. Due to the lack of specific drug and the appearance of different variants, the selection of the antiviral therapy to treat the patients with mild symptom is of vital importance. Hence, in this paper, we propose a novel behavioral Three-Way Decision (3WD) model and apply it to the medicine selection decision. First, a new relative utility function is constructed by considering the risk-aversion behavior and regret-aversion behavior of human beings. Second, based on the relative utility function, some new rules are defined to calculate the thresholds and conditional probabilities in 3WD and some corresponding theorems are explored and proved. Next, a new information fusion mechanism in the framework of evidential reasoning algorithm is developed. Then, the decision results are obtained based on the Bayesian decision procedure and the principle of maximum utility. Finally, an example with large-scale data set and an example about medicine selection for COVID-19 are provided to show the implementation process and effectiveness of the proposed method. Comparative analysis and sensitivity analysis are also performed to illustrate the superiority and the robustness of the current proposal.