Exploring smart phone improvements based on a hybrid MCDM model

Hu, Shu-Kung; Lu, Ming‐Tsang; Tzeng, Gwo‐Hshiung

doi:10.1016/j.eswa.2013.12.052

Cited by 94 publications

(60 citation statements)

References 55 publications

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“…This study was designed on the DEMATEL technique which assists in identifying the influence relationship matrix for an INRM and then in determining the influential weights of DANP among dimensions and criteria using basic concepts based on ANP. Finally, practical problems were solved in real-world situations [78]. The DANP method can effectively measure key influential factors for the development of mobile health care.…”

Section: Building a Ddanpmv Model For Evaluating And Improving Mobilementioning

confidence: 99%

“…The DEMATEL technique was first developed by the Battelle Research Center in 1972 to build an interrelationship network and explore complex real-world problems [78]. For the current study, we first identified eight criteria for the evaluation index system of mobile health care through literature analysis, discussion, and summarization.…”

Section: Constructing the Inrm Of Mobile Health Care Based On The Demmentioning

confidence: 99%

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Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Liu¹,

Yang²,

Liu³

et al. 2017

Preprint

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IntroductionMobile health care is an important aspect of electronic medicine that involves using mobile devices (e.g., mobile phones, tablet computers, and personal digital assistants) to provide medical services and health information to patients [1]. Health care faces numerous problems, including high medical costs, restricted coverage, complex medical procedures, and uneven distribution of resources [2]. Mobile health care can help to reduce medical costs and waiting times and improve the efficiency of medical resources use [3]. Mobile health care involves the following categories [4]: (1) Mobile phone applications such as Chun Yu Yi Sheng, which acts as an information exchange platform linking doctors and patients, and comprehensive mobile health care platforms that hospital service providers can apply for appointment registrations, payments, and medical alerts. (2) The collection of users' medical data through wearable devices or mobile intelligent terminals for health monitoring. For example, Kangkang launched a portable intelligent sphygmomanometer that can dynamically monitor blood pressure over a 24-hour period and automatically send data to a corresponding server. Users can view their 24-hour blood pressure analysis report through WeChat. (3) Diagnosis systems that connect with the Internet of Things (IoT). For example, an integrated diagnosis system developed by German researchers can transmit medical data to smart phones through Bluetooth technology. Smartphones applications can then process these data for reference and diagnosis.With the development of mobile networks, many countries have entered the 4G era and benefit from continuously improving mobile communication networks and innovation in software and hardware technology. Abstract: Identifying the key influence factors of mobile health care adoption is a key issue. We established an evaluation index system for consumer adoption and verified the effectiveness of our model by using a DDANPMV model. This model comprises three parts: (1) the decision making trial and evaluation laboratory (DEMATEL) technique, which is used to establish an influence network relationship map at both the "dimensions" and "criteria" levels; (2) a DEMATEL-based analytic network process (ANP; DANP), which determines the interrelationships and influential weights among the criteria; and (3) a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, which applies the influence weights obtained through DANP to performance gaps regarding consumer perception. VIKOR thereby evaluates and improves performance gaps with the aims of satisfying consumer needs, achieving continuous improvement, and enabling sustainable product development. The main innovation of this method is the construction of the DDANPMV model, which integrates the DEMATEL, DANP, and modified VIKOR approaches to examine consumers' adoption of mobile health care. This method was developed to not only help decision-makers evaluate alternative mobile health care and determine the best option b...

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Section: Building a Ddanpmv Model For Evaluating And Improving Mobilementioning

confidence: 99%

Section: Constructing the Inrm Of Mobile Health Care Based On The Demmentioning

confidence: 99%

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Liu¹,

Yang²,

Liu³

et al. 2017

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Chen, Hu, Kuo and Liang 33 proposed recommendation systems for online mobile phone stores by using an AHP-based mechanism. Hu, Lu and Tzeng 27 proposed a hybrid MCDM model for promoting a smart phone's product value by using DEMATEL, ANP and VIKOR. Apart from these MCDM techniques, this study utilized Intuitionistic Fuzzy Sets (IFS) introduced by Atanassov 16,37 .…”

Section: If-topsis With Gdm Environmentmentioning

confidence: 99%

“…Generally, users get satisfied with a particular product when its properties match with their preferences and expectations. In order to develop an effective 27 defined three dimensions which are customer equity, product function and mobile convenience as influencing factors for consumer willingness to purchase a smart phone. Hsiao and Chen 4 came up with three demand dimensions and emphasized their differences.…”

Section: Smart Phone Evaluation Criteriamentioning

confidence: 99%

Multi Criteria Group Decision Making Approach for Smart Phone Selection Using Intuitionistic Fuzzy TOPSIS

Büyüközkan¹,

Güleryüz²

2016

IJCIS

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The objective of this study is to provide an effective multi criteria decision making (MCDM) approach with group decision making to evaluate different smart phone alternatives according to consumer preferences. The choice of the most appropriate phone is a very complex decision, involving several perspectives. In such complex situations intuitionistic fuzzy sets with TOPSIS (IF-TOPSIS) can be utilized to eliminate uncertainty and to better represent decision makers' preferences. The originality of the paper comes from its ability to handle high uncertainty in a smart phone selection and provide a real case study with IFS for the first time.: -d making.

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“…They classify the main functions of smartphones into five categories; according to their results, the most important factor that affects consumers' choice is the hardware and software specifications [10]. Hu et al [11] propose a smartphone improvement for promoting the product value to satisfy the customers' needs with a hybrid MCDM model. They combine a decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) and vise kriterijumska optimizacija i kompromisno resenje (VIKOR) to reduce the gaps corresponding with each criterion in their study [11].…”

Section: Opsommingmentioning

confidence: 99%

A Two-Phased Multi-Criteria Decision-Making Approach for Selecting the Best Smartphone

Yıldız

Ergul

2015

SAJIE

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In the last 20 years, rapid and significant developments have occurred in communication and information technologies. In parallel with these developments, the importance of smartphones has increased. In addition, many smartphone manufacturers have launched and continue to launch a number of new models with many features. People who want to buy a new smartphone have difficulties selecting the best smartphone among the numerous models available on the technology markets. Therefore, smartphone selection has become a complex multi-criteria decision-making (MCDM) problem for people. Hence, decision-making processes will be facilitated by using MCDM methods, and these will provide the most appropriate decision. In this paper, the best smartphone among the 28 alternatives determined by the person who will buy them are selected by using three main criteria and 17 sub-criteria with the help of a two-phased MCDM approach. In the first phase, 28 smartphone alternatives are ranked using the analytic network process (ANP). In the second phase, a model that includes the best four alternatives of ANP is created. Afterwards, the best smartphone is selected using the generalised Choquet integral (GCI) method according to this model. Finally, the findings and the results are given. OPSOMMINGGedurende die afgelope twintig jaar het daar vinnige en noemenswaardige ontwikkeling in die kommunikasie en informasie tegnologie geskied. In parallel hiermee het die belangrikheid van slimtelefone toegeneem. Daarmee saam stel slimtelefoon-vervaardigers gereeld nuwe modelle met nuwe funksies vry. Dit is dus moeilik vir 'n potensiële kliënt om die beste seleksie uit die groot verskeidenheid tot hul beskikking te maak. Slimtelefoonseleksie is 'n ingewikkelde multi-kriteria besluitnemingsprobleem. Die besluitnemingsproses word dus gefasiliteer deur gebruik te maak van multi-kriteria besluitnemingsmetodes. Hierdie artikel bepaal die beste slimtelefoon vanuit agt-en-twintig alternatiewe deur gebruik te maak van drie hoof kriteria en sewentien subkriteria met die hulp van 'n twee-ledige multi-kriteria besluitnemingsbenadering. Eerstens word die agt-entwintig alternatiewe met behulp van die analitiese netwerk proses gerangskik en daaruit word 'n model, wat uit die vier beste alternatiewe bestaan, geskep. Laastens word die beste slimtelefoon gekies deur die veralgemeende Choquet integraal metode op die model toe te pas.

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Exploring smart phone improvements based on a hybrid MCDM model

Cited by 94 publications

References 55 publications

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Multi Criteria Group Decision Making Approach for Smart Phone Selection Using Intuitionistic Fuzzy TOPSIS

A Two-Phased Multi-Criteria Decision-Making Approach for Selecting the Best Smartphone

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