College of Management and Economics

About: College of Management and Economics is a based out in . It is known for research contribution in the topics: Supply chain & Stock market. The organization has 2184 authors who have published 2193 publications receiving 28830 citations.

Self-driving vehicles: Are people willing to trade risks for environmental benefits?

Abstract: Mass adoption of self-driving vehicles (SDVs) is predicted to have a profound effect on the environment. Here, we present three studies (N = 1258) that examine the impact of the environmental benefits (EB) of SDVs on individuals’ acceptance of their risks, and their willingness to ride (WTR) in them. Two types of SDVs were presented: SDVs with a clear mention of positive EB information (“EB-enhanced SDVs”) and SDVs without the mention of positive EB information (“normal SDVs”). Study 1 and Study 2 found that participants expressed higher risk acceptance and WTR regarding EB-enhanced SDVs. Further, Study 2 reported that higher trust in EB-enhanced SDVs, rather than lower negative affect associated with EB-enhanced SDVs, accounted for the participants’ higher risk acceptance and WTR. Study 3 observed that the participants’ acceptable risk of EB-enhanced SDVs was greater than that of normal SDVs in magnitude, although not significant. If SDVs can achieve the purported EB, the public may be willing to tolerate their risks more. Highlighting the environmental advantages of SDVs and increasing public trust in them are likely to be useful strategies for increasing societal acceptance of SDVs.

A complex multi-attribute large-group decision making method based on the interval-valued intuitionistic fuzzy principal component analysis model

Abstract: In the complex multi-attribute large-group decision making (CMALGDM) problems where attribute values are interval-valued intuitionistic fuzzy numbers (IVIFNs), the number of decision attributes is often large and their correlation degrees are high, which increase the difficulty of decision making and thus influence the accuracy of the result. To solve this problem, this paper proposes the interval-valued intuitionistic fuzzy principal component analysis (IVIF-PCA) model. This model represents major information of original attributes, effectively reduces dimensions of attribute space, and synthesizes original attributes into several relatively independent principal components (PCs). The basic thought of this model is as follows: first, we use thoughts of `equivalency' and `order invariance' to transform IVIFN samples into interval number samples; subsequently, we use the `error theory' to replace interval numbers with their middle points, and combine the middle points with the traditional PCA to obtain the PC scores of interval number samples; finally, we adopt the thought of `equivalency' to obtain the PC scores of IVIFN samples. Moreover, based on the IVIF-PCA model, we give a decision making method for the CMALGDM problem. The feasibility and validity of the decision making method is investigated through a numerical example.