Intelligence Group Decision Making via ADCHVAE and Unsupervised Attention

The operation of offline conventional store faces many challenges. We have been commissioned by the operator of a specific brand mobile phone store in China to examine the factors influencing mobile phone sales. The aim is to identify methods to enhance the operation of offline conventional stores. The store operators have provided impact factors determined through consultations with relevant experts and consideration of their experiences. To improve the effectiveness of decision-making, 30 postgraduates were organized to conduct an investigation into the operation of offline stores, with the aim of gaining a deep understanding of their operational processes. Additionally, the postgraduates analyzed the profound significance of the given impact factors and the objectives that offline store operators intend to achieve. Subsequently, these 30 postgraduates were regarded as experts to evaluate the impact factors influencing mobile phone sales. The HLTS was employed to express their uncertain evaluations, thereby reducing information loss. The expert provided data set was saved as, “expert(1).xls” to expert(30).xls” in folder “Expert_data”. Furthermore, we recruited 120 students from a university in China to evaluate the impact factors on the sale of the specific brand mobile phone, from “sale(1).xls” to “sale(101).xls”, in folder “Individual_data”. Each data file corresponds to one evaluator's assessment of the sales factor. In order to facilitate the reading of the data, we saved only the subscripts of the linguistic preference items provided by the evaluators in the data files. For instance, in the file “sale(1).xls”, the first line, “4, 6,7, 6,5,8,5,6”, denote the linguistic terms, “s4, s6, s7, s6, s5, s8, s5, s6”.