基于Fuzzy-ISM的生产安全大数据共享行为模型构建
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摘要
[目的/意义]分析生产安全大数据共享行为,识别其影响因素并建构因素间的交互关系,优化和促进生产安全大数据共享行为,为生产安全大数据共享能力建设提供理论指导和参考依据。[方法/过程]首先,借鉴制度理论和计划行为理论,结合生产安全大数据及其共享特点分析生产安全大数据共享行为;然后,运用三角模糊数对生产安全大数据共享行为影响因素间交互关系进行表征,并引入解释结构模型对影响因素之间的层级关系进行解析,从而形成生产安全大数据共享行为多层递阶模型。[结果/结论]生产安全大数据共享行为模型是以资助政策为根本因素层,以数据时效性、数据维度、数据层次、感知收益和感知风险为直接因素层的6层递阶结构模型。
[Purpose/Significance]The purpose of this paper is to optimize and promote the production safety big data sharing behavior and provide theoretical guidance and reference basis for the construction of production safety big data sharing capacity by analyzing the production safety big data sharing behavior. During the analysis,we also identify the interactions among influencing factors.[Method/Process]First,the production safety sharing behavior is analyzed based on the institutional theory and the theory of planned behavior.Next,applying the triangular fuzzy number to depict the interaction relationships among influencing factors of production safety big data sharing behavior. Then,the ISMmethod is introduced to construct the hierarchy structure model of these influencing factors.[Result/Conclusion]Production safety big data sharing behavior model consists of six levels. The basic factor level includes aid policy factors,and the direct factors level includes data timeliness,data dimension,data hierarchy,perceived benefits and perceived risk.
[Purpose/Significance]The purpose of this paper is to optimize and promote the production safety big data sharing behavior and provide theoretical guidance and reference basis for the construction of production safety big data sharing capacity by analyzing the production safety big data sharing behavior. During the analysis,we also identify the interactions among influencing factors.[Method/Process]First,the production safety sharing behavior is analyzed based on the institutional theory and the theory of planned behavior.Next,applying the triangular fuzzy number to depict the interaction relationships among influencing factors of production safety big data sharing behavior. Then,the ISMmethod is introduced to construct the hierarchy structure model of these influencing factors.[Result/Conclusion]Production safety big data sharing behavior model consists of six levels. The basic factor level includes aid policy factors,and the direct factors level includes data timeliness,data dimension,data hierarchy,perceived benefits and perceived risk.
引文
[1]欧阳秋梅,吴超.安全大数据共享影响因素分析及其模型构建[J].中国安全生产科学技术,2017(2):27-32.
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[8]李小涛,胡晓惠,郭晓利,等.基于元数据的复杂信息共享技术[J].系统工程与电子技术,2015,37(3):700-706.
[9]Shi W,Shambare N,Wang J.The adoption of internet banking:An institutional theory perspective[J].Journal of Financial Services Marketing,2008,12(4):272-286.
[10]Lu A B,Lcük L G.Development of a two-phase structural model for evaluating ERP critical success factors along with a case study[J].Computers&Industrial Engineering,2017,106(2):256-274.
[11]Agi MA N,Nishant R.Understanding influential factors on implementing green supply chain management practices:An interpretive structural modelling analysis[J].Journal of Environmental Management,2017,188:351-363.
[12]程聪慧.基于ISM的应急指挥信息沟通多层递阶影响因素研究[J].情报科学,2015,33(12):56-61.
[13]Chang A,Hu K,Hong Y.An ISM-ANP approach to identifying key agile factors in launching a newproduct into mass production[J].International Journal of Production Research,2013,51(2):582-597.
[14]Parameshwaran R,Baskar C,Karthik T.An integrated framework for mechatronics based product development in a fuzzy environment[J].Applied Soft Computing,2015,27(60):376-390.
[15]Mehregan MR,Hashemi S H,Karimi A,et al.Analysis of interactions among sustainability supplier selection criteria using ISMand fuzzy DEMATEL[J].International Journal of Applied Decision Sciences,2014,7(3):271-293.
[2]孙晓燕.科学数据共享行为的理论模型构建及测度实证研究[J].情报学报,2016,35(10):1062-1071.
[3]李明.大数据技术与公共安全信息共享能力[J].电子政务,2014(6):10-19.
[4]Welch E W,Feeney MK,Park C H.Determinants of data sharing in U.S.city governments[J].Government Information Quarterly,2016,33(3):393-403.
[5]曾胜.重大危险源动态智能监测监控大数据平台框架设计[J].中国安全科学学报,2014,24(11):166-171.
[6]黄如花,王春迎.我国政府数据开放平台现状调查与分析[J].情报理论与实践,2016,39(7):50-55.
[7]Gibbon D C,Liu Z,Basso A,et al.Automated content metadata extraction services based on MPEG standards[J].Computer Journal,2013,56(5):628-645.
[8]李小涛,胡晓惠,郭晓利,等.基于元数据的复杂信息共享技术[J].系统工程与电子技术,2015,37(3):700-706.
[9]Shi W,Shambare N,Wang J.The adoption of internet banking:An institutional theory perspective[J].Journal of Financial Services Marketing,2008,12(4):272-286.
[10]Lu A B,Lcük L G.Development of a two-phase structural model for evaluating ERP critical success factors along with a case study[J].Computers&Industrial Engineering,2017,106(2):256-274.
[11]Agi MA N,Nishant R.Understanding influential factors on implementing green supply chain management practices:An interpretive structural modelling analysis[J].Journal of Environmental Management,2017,188:351-363.
[12]程聪慧.基于ISM的应急指挥信息沟通多层递阶影响因素研究[J].情报科学,2015,33(12):56-61.
[13]Chang A,Hu K,Hong Y.An ISM-ANP approach to identifying key agile factors in launching a newproduct into mass production[J].International Journal of Production Research,2013,51(2):582-597.
[14]Parameshwaran R,Baskar C,Karthik T.An integrated framework for mechatronics based product development in a fuzzy environment[J].Applied Soft Computing,2015,27(60):376-390.
[15]Mehregan MR,Hashemi S H,Karimi A,et al.Analysis of interactions among sustainability supplier selection criteria using ISMand fuzzy DEMATEL[J].International Journal of Applied Decision Sciences,2014,7(3):271-293.