Analyzing the factors affecting the quality of IoT-based smart wearable devices using the DANP method
Journal
Studies in Informatics and Control
Date Issued
2019-12-20
Author(s)
Balog, Alexandru
Băjenaru, Lidia
Cristescu, Irina
DOI
10.24846/v28i4y201907
Abstract
This paper proposes the DANP (DEMATEL-based Analytic Network Process) method so that the factors that
affect the quality of IoT (Internet of Things)-based smart wearable devices can be adequately assessed. The proposed method helps to identify and visualize the importance of certain factors (dimensions and criteria), the causal relationship among the factors, the mutual influence upon each other, and their influential weights. A numerical example was presented to illustrate the feasibility and effectiveness of the proposed method. The results of this study demonstrated that the quality dimensions can be divided into a causal group (the technical and ergonomic dimensions) and an effect group (the functional and symbolic dimensions). The functional dimension proved to be the most important factor and the most important core problem to be solved. The most influential driving factor was the ergonomic dimension. The results of this study provide insights into critical design criteria to better meet the users’ needs and can be used by manufacturers to develop strategies for improving the quality of IoT-based smart wearable devices, in a priority order.
affect the quality of IoT (Internet of Things)-based smart wearable devices can be adequately assessed. The proposed method helps to identify and visualize the importance of certain factors (dimensions and criteria), the causal relationship among the factors, the mutual influence upon each other, and their influential weights. A numerical example was presented to illustrate the feasibility and effectiveness of the proposed method. The results of this study demonstrated that the quality dimensions can be divided into a causal group (the technical and ergonomic dimensions) and an effect group (the functional and symbolic dimensions). The functional dimension proved to be the most important factor and the most important core problem to be solved. The most influential driving factor was the ergonomic dimension. The results of this study provide insights into critical design criteria to better meet the users’ needs and can be used by manufacturers to develop strategies for improving the quality of IoT-based smart wearable devices, in a priority order.