用于分析发展中国家制药 4.0 实施障碍的分层多标准模型

Akib Zaman , Ismat Jerin , Puja Ghosh , Anika Akther , Salma Sultana Shrity , Ferdous Sarwar
{"title":"用于分析发展中国家制药 4.0 实施障碍的分层多标准模型","authors":"Akib Zaman ,&nbsp;Ismat Jerin ,&nbsp;Puja Ghosh ,&nbsp;Anika Akther ,&nbsp;Salma Sultana Shrity ,&nbsp;Ferdous Sarwar","doi":"10.1016/j.health.2024.100334","DOIUrl":null,"url":null,"abstract":"<div><p>Pharmaceutical industries in most developing countries with limited resources are expected to encounter several barriers while incorporating Industry 4.0 to transform into Pharma 4.0. With limited resources, a developing country must prioritize the barriers consider their impacts, and make a resource utilization plan accordingly. In this study, We employed a hierarchical multiple criteria decision analysis (MCDM) technique to identify potential barriers to Pharma 4.0 in developing countries and examine their effects to generate a prioritization inventory. Firstly, we extracted the likely barriers using a systematic literature study and used an expert opinion-based Delphi Method to choose the most pertinent barriers. Subsequently, we analyzed the correlation and influence of the selected barriers on each other by formulating a hierarchical multi-criteria model integrating Interpretive Structural Modelling (ISM) and the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). As an outcome, we found three distinct categories of the selected 12 barriers: Prominent (4 of 12), Influencing (5 of 12), and Resulting (3 of 12). The results of this study are intended to assist the government in developing a solid adoption strategy for Pharma 4.0 and supply chain strategists in ensuring optimum resource utilization by resolving the examined barriers during the deployment of Pharma 4.0. The study is the first of its kind to discover barriers to Pharma 4.0 adoption and create hierarchical correlations within the context of the pharmaceutical sector from the perspective of a developing country.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":"5 ","pages":"Article 100334"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442524000364/pdfft?md5=d9a0ca448b9364d4c911b98bd0600108&pid=1-s2.0-S2772442524000364-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A hierarchical multi-criteria model for analyzing the barriers to Pharma 4.0 implementation in developing countries\",\"authors\":\"Akib Zaman ,&nbsp;Ismat Jerin ,&nbsp;Puja Ghosh ,&nbsp;Anika Akther ,&nbsp;Salma Sultana Shrity ,&nbsp;Ferdous Sarwar\",\"doi\":\"10.1016/j.health.2024.100334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Pharmaceutical industries in most developing countries with limited resources are expected to encounter several barriers while incorporating Industry 4.0 to transform into Pharma 4.0. With limited resources, a developing country must prioritize the barriers consider their impacts, and make a resource utilization plan accordingly. In this study, We employed a hierarchical multiple criteria decision analysis (MCDM) technique to identify potential barriers to Pharma 4.0 in developing countries and examine their effects to generate a prioritization inventory. Firstly, we extracted the likely barriers using a systematic literature study and used an expert opinion-based Delphi Method to choose the most pertinent barriers. Subsequently, we analyzed the correlation and influence of the selected barriers on each other by formulating a hierarchical multi-criteria model integrating Interpretive Structural Modelling (ISM) and the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). As an outcome, we found three distinct categories of the selected 12 barriers: Prominent (4 of 12), Influencing (5 of 12), and Resulting (3 of 12). The results of this study are intended to assist the government in developing a solid adoption strategy for Pharma 4.0 and supply chain strategists in ensuring optimum resource utilization by resolving the examined barriers during the deployment of Pharma 4.0. The study is the first of its kind to discover barriers to Pharma 4.0 adoption and create hierarchical correlations within the context of the pharmaceutical sector from the perspective of a developing country.</p></div>\",\"PeriodicalId\":73222,\"journal\":{\"name\":\"Healthcare analytics (New York, N.Y.)\",\"volume\":\"5 \",\"pages\":\"Article 100334\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772442524000364/pdfft?md5=d9a0ca448b9364d4c911b98bd0600108&pid=1-s2.0-S2772442524000364-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Healthcare analytics (New York, N.Y.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772442524000364\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare analytics (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772442524000364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在大多数资源有限的发展中国家,制药业在融入工业 4.0,向制药 4.0 转型的过程中预计会遇到一些障碍。在资源有限的情况下,发展中国家必须对障碍进行优先排序,考虑其影响,并制定相应的资源利用计划。在本研究中,我们采用了分层多重标准决策分析(MCDM)技术来识别发展中国家制药 4.0 的潜在障碍,并研究其影响,从而生成优先级清单。首先,我们通过系统的文献研究提取了可能存在的障碍,并采用基于专家意见的德尔菲法选出了最相关的障碍。随后,我们结合解释性结构建模(ISM)和交叉影响矩阵乘法分类(MICMAC),建立了一个分层多标准模型,分析了所选障碍之间的相关性和相互影响。结果,我们在选定的 12 个障碍中发现了三个不同的类别:突出障碍(12 个障碍中的 4 个)、影响障碍(12 个障碍中的 5 个)和结果障碍(12 个障碍中的 3 个)。本研究的结果旨在帮助政府制定扎实的医药 4.0 应用战略,并帮助供应链战略家在部署医药 4.0 的过程中解决所研究的障碍,从而确保资源的最佳利用。本研究是首次从发展中国家的视角发现制药 4.0 的应用障碍,并在制药行业的背景下创建分层相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A hierarchical multi-criteria model for analyzing the barriers to Pharma 4.0 implementation in developing countries

Pharmaceutical industries in most developing countries with limited resources are expected to encounter several barriers while incorporating Industry 4.0 to transform into Pharma 4.0. With limited resources, a developing country must prioritize the barriers consider their impacts, and make a resource utilization plan accordingly. In this study, We employed a hierarchical multiple criteria decision analysis (MCDM) technique to identify potential barriers to Pharma 4.0 in developing countries and examine their effects to generate a prioritization inventory. Firstly, we extracted the likely barriers using a systematic literature study and used an expert opinion-based Delphi Method to choose the most pertinent barriers. Subsequently, we analyzed the correlation and influence of the selected barriers on each other by formulating a hierarchical multi-criteria model integrating Interpretive Structural Modelling (ISM) and the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). As an outcome, we found three distinct categories of the selected 12 barriers: Prominent (4 of 12), Influencing (5 of 12), and Resulting (3 of 12). The results of this study are intended to assist the government in developing a solid adoption strategy for Pharma 4.0 and supply chain strategists in ensuring optimum resource utilization by resolving the examined barriers during the deployment of Pharma 4.0. The study is the first of its kind to discover barriers to Pharma 4.0 adoption and create hierarchical correlations within the context of the pharmaceutical sector from the perspective of a developing country.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Healthcare analytics (New York, N.Y.)
Healthcare analytics (New York, N.Y.) Applied Mathematics, Modelling and Simulation, Nursing and Health Professions (General)
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
79 days
期刊最新文献
Optimized early fusion of handcrafted and deep learning descriptors for voice pathology detection and classification A deep neural network model with spectral correlation function for electrocardiogram classification and diagnosis of atrial fibrillation An ensemble convolutional neural network model for brain stroke prediction using brain computed tomography images A hierarchical Bayesian approach for identifying socioeconomic factors influencing self-rated health in Japan An electrocardiogram signal classification using a hybrid machine learning and deep learning approach
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1