Elsevier

Decision Support Systems

Volume 56, December 2013, Pages 259-269
Decision Support Systems

Improving RFID adoption in Taiwan's healthcare industry based on a DEMATEL technique with a hybrid MCDM model

https://doi.org/10.1016/j.dss.2013.06.006Get rights and content

Highlights

  • RFID adoption is a problem requiring a multi-criteria decision analysis.

  • This study is presented to demonstrate the effectiveness of hybrid MCDM model.

  • DEMATEL for solving the problems of interdependence and feedback problem.

  • DANP and VIKOR for identify influential weights and gaps base on TOEC framework.

  • The results can provide the best way to improve existing RFID adoption processes.

Abstract

The use of radio frequency identification (RFID) technology has progressed tremendously in recent years. In the healthcare industry, the decision to adopt RFID technology is a problem requiring a multi-criteria decision analysis that involves both qualitative and quantitative factors. The evaluation of this decision may be based on imprecise information or uncertain data. Furthermore, there can be significant dependence and feedbacks between the different criteria and alternatives. However, most conventional decision models cannot capture these complex interrelationships. As a result, in this study we develop a general evaluation framework for industry evaluation, improvement and adoption of RFID. We use a hybrid Multiple Criteria Decision Making (MCDM) method known as DDANPV that combines DEMATEL (decision making trial and evaluation laboratory), DANP (DEMATEL-based ANP), and VIKOR to evaluate the factors that influence the adoption of RFID. Specifically, we study the adoption of RFID in Taiwan's healthcare industry. We find that technology integration is the most influential criterion and the strongest driver in the adoption of RFID of Taiwan's healthcare industry.

Introduction

Radio frequency identification (RFID) is a communication technology that uses radio waves to exchange data. RFID has three components: (1) an antenna for transmitting and receiving signals; (2) a transponder programmed with the identification information; and (3) an RF module (reader) with a decoder or transceiver. RFID has many applications and is an increasingly valuable tool for enabling automatic identification and management. For many industries, RFID is not only a new alternative to existing tracking methods but is also a solution for a range of previously cost-prohibitive innovations in internal control and supply chain coordination [34], [46].

RFID has existed for decades. This technology was originally used to identify and track flying aircrafts during the Second World War. Until recently, RFID was deemed to be too expensive and limited in functionality for many commercial applications. As the prices of RFID equipment and RFID tags have dropped in recent years, RFID applications have become increasingly prevalent. Cost is no longer a barrier. However, RFID has not been extensively adopted by the healthcare industry. The relatively conservative attitudes of healthcare providers have prevented hospitals from using the latest information technologies. Furthermore, technology adoption often depends on a critical mass being reached; a manager's decision to adopt a new technology often depends on the technology's diffusion rate, which, in turn, depends on the decisions made by other managers. Furthermore, even if a hospital decides to evaluate the relative costs and benefits of implementing RFID technology, no comprehensive evaluation and adoption model exists that can be used as a reference for the adoption of RFID in the healthcare industry. Thus, it is inappropriate to focus only on the cost of a new IT technology as the primary factor in its adoption [4], [7], [9], [50].

Most of the conventional multi-criteria decision analysis (MCDA) models cannot handle the analysis of complex relationships among different hierarchical levels of criteria. However, the decision to adopt RFID requires a decision model that performs just that analysis. In this paper, we develop a hybrid MCDM model called DDANPV that combines DEMATEL, DANP, and VIKOR. DDANPV overcomes the limitations of existing decision models and can be used to help us analyze the factors that influence industry adoption of RFID technology. In particular, we use Taiwan's healthcare industry as an example to study the interdependence of the factors that influence the adoption of RFID in the healthcare industry, as well as to evaluate alternative RFID adoption processes to achieve the desired levels of performance from RFID technology.

This paper is organized into five sections. Section 2 reviews the literature on the implementation of RFID in the healthcare industry. We will discuss the advances in evaluating the RFID adoption process, the selection criteria for adopting RFID technology, the decision models currently being used to determine whether RFID technology should be adopted, and the specific problems related to evaluating the RFID adoption process. Section 3 introduces the hybrid MCDM method called DDANPV. In Section 4, we use Taiwan's healthcare industry as an empirical example to illustrate how DDANPV could help select the best RFID adoption method and discuss the results. In Section 5, we draw conclusions.

Section snippets

The effects of evaluating the RFID adoption model in the healthcare industry

The purpose of this section is to survey the relevant studies in the RFID adoption process, to investigate and compare various evaluation frameworks, and to identify possible factors that influence the RFID adoption process in the healthcare industry. Due to the lack of previous research on the criteria used in evaluating RFID for adoption, this study expands upon a general evaluation framework used in other industries and compiles four primary factors—technology, organization, environment and

DDANPV — A hybrid MCDM model for evaluating and improving RFID adoption

DDANPV is comprised of three stages. First, we use the DEMATEL method to uncover the relationship between the criteria and their network structure in the presence of interdependence and feedback among criteria. DEMATEL is more suitable in real-world applications than traditional methods, which assume independence among criteria [8], [14], [15], [23], [24], [33], [43]. Second, we combine DEMATEL with the ANP method to form DANP (DEMATEL-based ANP) to obtain influential weights for each dimension

An empirical case study on RFID adoption in Taiwan's healthcare industry

In this section, we present an empirical study using the proposed DDANPV model to evaluate, select, and improve upon the best alternative for RFID adoption in Taiwan's healthcare industry.

Conclusions

The dimensions and criteria outlined in this study serve as bridging mechanisms for the evaluation of RFID adoption processes. Prior literature has identified the dimensions and criteria that influence the evaluation of adopting RFID. The main contributions of this study are twofold. First, the evaluation of technology adoption is a decision-making problem that is composed of complex dependences and interactions. In this paper we used previous studies to develop a TOEC framework to evaluate

Ming-Tsang Lu is a Ph.D. student in the graduate institute of management science, National Chiao Tung University, Taiwan. His research interests include Multiple Criteria Decision Making, application of fuzzy theory to information systems, and information technology.

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    Ming-Tsang Lu is a Ph.D. student in the graduate institute of management science, National Chiao Tung University, Taiwan. His research interests include Multiple Criteria Decision Making, application of fuzzy theory to information systems, and information technology.

    Shi-Woei Lin is a risk and decision analyst. His current research interests include the application of game theory to risk-informed regulation and the use of mathematical models to aggregate experts' uncertainty judgments. Other interests include decision biases and methods for effective risk communication, both to decision makers and to the general public.

    Gwo-Hshiung Tzeng was born in 1943 in Taiwan. In 1967, he received a bachelor's degree in business management from the Tatung Institute of Technology (now Tatung University), Taiwan. In 1971, he received a master's degree in urban planning from Chung Hsing University (Now Taipei University), Taiwan. In 1977, he received a Ph.D. in management science from Osaka University, Osaka, Japan.

    Gwo-Hshiung Tzeng was an Associate Professor at Chiao Tung University, Taiwan, from 1977 to 1981, a Research Associate at Argonne National Laboratory from July 1981 to January 1982, a Visiting Professor in the Department of Civil Engineering at the University of Maryland, College Park, MD, from August 1989 to August 1990, a Visiting Professor in the Department of Engineering and Economic System, Energy Modeling Forum at Stanford University, from August 1997 to August 1998, a professor at Chaio Tung University from 1981 to 2003, and a Chair Professor at Chiao Tung University. He was named a National Distinguished Chair Professor (Highest Honor offered by the Ministry of Education Affairs, Taiwan) and Distinguished Research Fellow (Highest Honor Offered by NSC, Taiwan) in 2000. His current research interests include statistics, multivariate analysis, networks, routing and scheduling, multiple criteria decision making, fuzzy theory, application of hierarchical structure analysis to technology management, energy, the environment, transportation systems, transportation investment, logistics, locations, urban planning, tourism, technology management, electronic commerce, global supply chain, etc. He was awarded a Highly Cited Paper (March 13, 2009) ESI “Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS” as published in the “EUROPEAN JOURNAL OF OPERATIONAL RESEARCH” on July 16th, 156(2), 445–455, 2004, which has recently been identified by Thomson Reuters' Essential Science Indicators SM as one of the most cited papers in the field of Economics and Business.

    He received the MCDM Edgeworth-Pareto Award from the International Society on Multiple Criteria Decision Making (June 2009), the world Pinnacle of Achievement Award in 2005, and the National Distinguished Chair Professor Award (highest honor offered) of the Ministry of Education Affairs of Taiwan; additionally, he is a three time recipient of a distinguished research award and was twice named a distinguished research fellow (highest honor offered) of the National Science Council of Taiwan. He is also a Fellow IEEE Member (since September 30, 2002). He organized a Taiwan affiliate chapter of the International Association of Energy Economics in 1984 and he was the Chairman of the Tenth International Conference on Multiple Criteria Decision Making, July 19–24, 1992, in Taipei, the Co-Chairman of the 36th International Conference on Computers and Industrial Engineering, June 20-23, 2006, Taipei, Taiwan, and the Chairman of the International Summer School on Multiple Criteria Decision Making 2006, July 2–14, Kainan University, Taiwan. He is a member of IEEE, IAEE, ISMCDM, World Transport, the Operations Research Society of Japan, the Society of Instrument and Control Engineers Society of Japan, the City Planning Institute of Japan, the Behavior Metric Society of Japan, and the Japan Society for Fuzzy Theory and Systems and participates in many societies of Taiwan. He is an editor-in-chief of the International Journal of Information Systems for Logistics and Management.

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