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Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP)
The Hospital Information System (HIS) is a computer system aimed at providing a paperless environment that covers all aspects of the hospital's operation such as clinical, administrative, and financial systems. The aim of this study is to provide more insight within the context of Malaysia to u...
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Published in: | Technological forecasting & social change 2016-10, Vol.111, p.244-264 |
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description | The Hospital Information System (HIS) is a computer system aimed at providing a paperless environment that covers all aspects of the hospital's operation such as clinical, administrative, and financial systems. The aim of this study is to provide more insight within the context of Malaysia to understand the potential factors that importantly driving or inhibiting the decision of HIS adoption from non-adopters' perspective. This study mainly integrates the diffusion of innovation theory, technology-organization-environment framework, institutional theory along with human-organization-technology fit model that can be tailored in understanding of the HIS adoption by Malaysian public hospitals. In this regard, the initial model is designed by considering four main dimensions (Technology, Environment, Human, Organization) with seventeen variables based on reviewing of the existing extensive literature of information system in particular information technology adoption in line with prior HIS adoption studies. Accordingly, a Fuzzy Analytic Network Process (ANP), one of the Multi-Criteria Decision Making (MCDM) techniques, model is developed to determine the most important factors among the four categories for the HIS adoption in the context of Malaysian public hospitals. These factors are identified and compared by 20 hospital experts and decision makers, who are fully familiar of HIS technology with also professional management and decision-making experience in hospitals. Then fuzzy ANP is applied to compute the weights of incorporated factors in the HIS adoption. The results reveal that hospitals with compatibility, complexity, mimetic pressure and vendor support are more likely to adopt HIS. Hence, the decision to adopt HIS is mainly determined by technological and environmental context. The study and its findings have resulted in theoretical contributions and research implications where the integrated theoretical model serves as a tool for healthcare industry to gain insight into the process of HIS adoption.
•HIS adoption from non-adopters' perspective is investigated.•A MCDM model is developed using Fuzzy ANP for HIS adoption.•Technology, Environment, Human and Organization are considered in MCDM model.•The findings show that technological factor is more important for HIS adoption. |
doi_str_mv | 10.1016/j.techfore.2016.07.008 |
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•HIS adoption from non-adopters' perspective is investigated.•A MCDM model is developed using Fuzzy ANP for HIS adoption.•Technology, Environment, Human and Organization are considered in MCDM model.•The findings show that technological factor is more important for HIS adoption.</description><identifier>ISSN: 0040-1625</identifier><identifier>EISSN: 1873-5509</identifier><identifier>DOI: 10.1016/j.techfore.2016.07.008</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Adoption of innovations ; Categories ; Decision analysis ; Decision making ; Diffusion ; DOI theory ; Fuzzy ; Fuzzy ANP ; Fuzzy logic ; Fuzzy systems ; Health care management ; Health services ; HIS adoption ; Hospitals ; HOT-fit model ; Information dissemination ; Information systems ; Information technology ; Innovations ; Institutional theory ; Mathematical analysis ; Mathematical models ; Multiple criteria decision making ; Multiple criterion ; Networks ; Studies ; Technology adoption ; Technology utilization ; TOE framework</subject><ispartof>Technological forecasting & social change, 2016-10, Vol.111, p.244-264</ispartof><rights>2016</rights><rights>Copyright Elsevier Science Ltd. Oct 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c404t-cd29987eaa9dc49ad657184878620d46d770028b35cd735afa31b05d3d4eace33</citedby><cites>FETCH-LOGICAL-c404t-cd29987eaa9dc49ad657184878620d46d770028b35cd735afa31b05d3d4eace33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902,33751</link.rule.ids></links><search><creatorcontrib>Nilashi, Mehrbakhsh</creatorcontrib><creatorcontrib>Ahmadi, Hossein</creatorcontrib><creatorcontrib>Ahani, Ali</creatorcontrib><creatorcontrib>Ravangard, Ramin</creatorcontrib><creatorcontrib>Ibrahim, Othman bin</creatorcontrib><title>Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP)</title><title>Technological forecasting & social change</title><description>The Hospital Information System (HIS) is a computer system aimed at providing a paperless environment that covers all aspects of the hospital's operation such as clinical, administrative, and financial systems. The aim of this study is to provide more insight within the context of Malaysia to understand the potential factors that importantly driving or inhibiting the decision of HIS adoption from non-adopters' perspective. This study mainly integrates the diffusion of innovation theory, technology-organization-environment framework, institutional theory along with human-organization-technology fit model that can be tailored in understanding of the HIS adoption by Malaysian public hospitals. In this regard, the initial model is designed by considering four main dimensions (Technology, Environment, Human, Organization) with seventeen variables based on reviewing of the existing extensive literature of information system in particular information technology adoption in line with prior HIS adoption studies. Accordingly, a Fuzzy Analytic Network Process (ANP), one of the Multi-Criteria Decision Making (MCDM) techniques, model is developed to determine the most important factors among the four categories for the HIS adoption in the context of Malaysian public hospitals. These factors are identified and compared by 20 hospital experts and decision makers, who are fully familiar of HIS technology with also professional management and decision-making experience in hospitals. Then fuzzy ANP is applied to compute the weights of incorporated factors in the HIS adoption. The results reveal that hospitals with compatibility, complexity, mimetic pressure and vendor support are more likely to adopt HIS. Hence, the decision to adopt HIS is mainly determined by technological and environmental context. The study and its findings have resulted in theoretical contributions and research implications where the integrated theoretical model serves as a tool for healthcare industry to gain insight into the process of HIS adoption.
•HIS adoption from non-adopters' perspective is investigated.•A MCDM model is developed using Fuzzy ANP for HIS adoption.•Technology, Environment, Human and Organization are considered in MCDM model.•The findings show that technological factor is more important for HIS adoption.</description><subject>Adoption of innovations</subject><subject>Categories</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Diffusion</subject><subject>DOI theory</subject><subject>Fuzzy</subject><subject>Fuzzy ANP</subject><subject>Fuzzy logic</subject><subject>Fuzzy systems</subject><subject>Health care management</subject><subject>Health services</subject><subject>HIS adoption</subject><subject>Hospitals</subject><subject>HOT-fit model</subject><subject>Information dissemination</subject><subject>Information systems</subject><subject>Information technology</subject><subject>Innovations</subject><subject>Institutional theory</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Multiple criteria decision making</subject><subject>Multiple criterion</subject><subject>Networks</subject><subject>Studies</subject><subject>Technology adoption</subject><subject>Technology utilization</subject><subject>TOE framework</subject><issn>0040-1625</issn><issn>1873-5509</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>BHHNA</sourceid><recordid>eNqFkU9v1DAQxSMEEkvhKyBLXMoh6TiO_-TGqlBaqSqVgLPl2hPqJYmD7YC2nx5vFy5cOI2e9HtvNPOq6jWFhgIVZ7smo70fQsSmLboB2QCoJ9WGKslqzqF_Wm0AOqipaPnz6kVKOwCQTIlNtb7HjHHys5-_kXyPxE9LiNnMFkkYyGVIi89mJFdzWTCZ7MNMPu9TxokYF5ZHPRibQ0xkTYeQi_XhYU-2sxn32Vtyg_lXiN_JbQwWUyKn25vbty-rZ4MZE776M0-qrxcfvpxf1tefPl6db69r20GXa-vavlcSjemd7XrjBJdUdUoq0YLrhJMSoFV3jFsnGTeDYfQOuGOuQ2ORsZPq9Ji7xPBjxZT15JPFcTQzhjXpEsYVA6BtQd_8g-7CGssVB6oVHRUSeKHEkbIxpBRx0Ev0k4l7TUEf2tA7_bcNfWhDg9SljWJ8dzRiOfenx6iT9Vi-7HxEm7UL_n8RvwG885eg</recordid><startdate>20161001</startdate><enddate>20161001</enddate><creator>Nilashi, Mehrbakhsh</creator><creator>Ahmadi, Hossein</creator><creator>Ahani, Ali</creator><creator>Ravangard, Ramin</creator><creator>Ibrahim, Othman bin</creator><general>Elsevier Inc</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>7U4</scope><scope>8FD</scope><scope>BHHNA</scope><scope>DWI</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>WZK</scope></search><sort><creationdate>20161001</creationdate><title>Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP)</title><author>Nilashi, Mehrbakhsh ; Ahmadi, Hossein ; Ahani, Ali ; Ravangard, Ramin ; Ibrahim, Othman bin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c404t-cd29987eaa9dc49ad657184878620d46d770028b35cd735afa31b05d3d4eace33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adoption of innovations</topic><topic>Categories</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Diffusion</topic><topic>DOI theory</topic><topic>Fuzzy</topic><topic>Fuzzy ANP</topic><topic>Fuzzy logic</topic><topic>Fuzzy systems</topic><topic>Health care management</topic><topic>Health services</topic><topic>HIS adoption</topic><topic>Hospitals</topic><topic>HOT-fit model</topic><topic>Information dissemination</topic><topic>Information systems</topic><topic>Information technology</topic><topic>Innovations</topic><topic>Institutional theory</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Multiple criteria decision making</topic><topic>Multiple criterion</topic><topic>Networks</topic><topic>Studies</topic><topic>Technology adoption</topic><topic>Technology utilization</topic><topic>TOE framework</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nilashi, Mehrbakhsh</creatorcontrib><creatorcontrib>Ahmadi, Hossein</creatorcontrib><creatorcontrib>Ahani, Ali</creatorcontrib><creatorcontrib>Ravangard, Ramin</creatorcontrib><creatorcontrib>Ibrahim, Othman bin</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>Technology Research Database</collection><collection>Sociological Abstracts</collection><collection>Sociological Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>Technological forecasting & social change</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nilashi, Mehrbakhsh</au><au>Ahmadi, Hossein</au><au>Ahani, Ali</au><au>Ravangard, Ramin</au><au>Ibrahim, Othman bin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP)</atitle><jtitle>Technological forecasting & social change</jtitle><date>2016-10-01</date><risdate>2016</risdate><volume>111</volume><spage>244</spage><epage>264</epage><pages>244-264</pages><issn>0040-1625</issn><eissn>1873-5509</eissn><abstract>The Hospital Information System (HIS) is a computer system aimed at providing a paperless environment that covers all aspects of the hospital's operation such as clinical, administrative, and financial systems. The aim of this study is to provide more insight within the context of Malaysia to understand the potential factors that importantly driving or inhibiting the decision of HIS adoption from non-adopters' perspective. This study mainly integrates the diffusion of innovation theory, technology-organization-environment framework, institutional theory along with human-organization-technology fit model that can be tailored in understanding of the HIS adoption by Malaysian public hospitals. In this regard, the initial model is designed by considering four main dimensions (Technology, Environment, Human, Organization) with seventeen variables based on reviewing of the existing extensive literature of information system in particular information technology adoption in line with prior HIS adoption studies. Accordingly, a Fuzzy Analytic Network Process (ANP), one of the Multi-Criteria Decision Making (MCDM) techniques, model is developed to determine the most important factors among the four categories for the HIS adoption in the context of Malaysian public hospitals. These factors are identified and compared by 20 hospital experts and decision makers, who are fully familiar of HIS technology with also professional management and decision-making experience in hospitals. Then fuzzy ANP is applied to compute the weights of incorporated factors in the HIS adoption. The results reveal that hospitals with compatibility, complexity, mimetic pressure and vendor support are more likely to adopt HIS. Hence, the decision to adopt HIS is mainly determined by technological and environmental context. The study and its findings have resulted in theoretical contributions and research implications where the integrated theoretical model serves as a tool for healthcare industry to gain insight into the process of HIS adoption.
•HIS adoption from non-adopters' perspective is investigated.•A MCDM model is developed using Fuzzy ANP for HIS adoption.•Technology, Environment, Human and Organization are considered in MCDM model.•The findings show that technological factor is more important for HIS adoption.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.techfore.2016.07.008</doi><tpages>21</tpages></addata></record> |
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subjects | Adoption of innovations Categories Decision analysis Decision making Diffusion DOI theory Fuzzy Fuzzy ANP Fuzzy logic Fuzzy systems Health care management Health services HIS adoption Hospitals HOT-fit model Information dissemination Information systems Information technology Innovations Institutional theory Mathematical analysis Mathematical models Multiple criteria decision making Multiple criterion Networks Studies Technology adoption Technology utilization TOE framework |
title | Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP) |
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