NEW HYBRID FMADM MODEL FOR MOBILE COMMERCE IMPROVEMENT

Abstract

Internet of things (IoT) can provide an extensive scope of services via smart devices to promote the convenience of life. With advances being made in smart phones, enterprises are increasingly considering expanding their customer base through mobile commerce services. To promote m-commerce improvement, enterprises should organize an excellent m-commerce environment and attempt to realize user needs in the era of IoT. In a fuzzy environment of the real world, objective decision-making for m-commerce improvement is usually a FMADM problem involving feedback-effect and interdependence among the dimensions and criteria. But, many traditional decision models cannot conduct the complicated interrelationships among dimensions and criteria. This study proposes an improvement model that can promote m-commerce improvement towards achieving the aspiration level in fuzzy environment. The proposed hybrid model conducts the feedback-effect and dependence among attributes, and it combines the FDEMATEL technique, FDANP, and MFGRA methods. The empirical case study was conducted to prove the utility of the new hybrid FMADM model in evaluating an m-commerce environment. Comparative results exhibited that the proposed approach is superior to the traditional method and that it can obtain most real grey relational degree that can be used for establishing the best performance improvement strategy in reality.