SPMS: A Scientific Decision Framework forbSmartphone Manufacturer Selection using Linguistic Preferences

Abstract

The usage of smart phones by Indian students is tremendously growing at faster pace. To cope with the high-end demand, mobile manufacturers have to make rational decisions regarding the market expansion and quality improvement. To critical decision, in this paper, a new scientific decision framework called SPMS is (smart phone manufacturer selector) presented. The SPMS consist of three stages viz., data acquisition and pre-processing stage, data fusion and criteria weighting stage and selection/ranking stage. The data is collected from questionnaires which are completed by students of colleges in and around Thanjavur district. The missing information in the dataset are completed using bin by mean method, followed by feature set reduction is done using Gini index method. In the second stage, linguistic information are aggregated using frequency match aggregation (FMA) operator with unconstrained weight values. Further, criteria weights are determined using standard variance (SV) method under linguistic context. Finally, ranking of smart phone manufacturers is done using VIKOR method under linguistic context. The practicality and usefulness of the proposed framework is demonstrated using a case study for smart phone selection. The strength and weakness of the proposal is also realized by comparison with other state-of-art frameworks.