Using data-driven safety decision-making to realize smart safety management in the era of big data: A theoretical perspective on basic questions and their answers

被引:40
|
作者
Wang, Bing [1 ,2 ]
Wu, Chao [1 ,2 ]
Huang, Lang [1 ,2 ]
Kang, Liangguo [1 ,2 ]
机构
[1] Cent S Univ, Sch Resources & Safety Engn, Changsha 410083, Hunan, Peoples R China
[2] Cent S Univ, Safety & Secur Theory Innovat & Promot Ctr, Changsha 410083, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Safety management; Safety-Related Data (SRD); Safety Decision-Making (SDM); Data-driven; DATA SCIENCE; INFORMATION; FRAMEWORK; DESIGN; HEALTH;
D O I
10.1016/j.jclepro.2018.11.181
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
How to make an effective safety decision is always a topic of intense interest in the safety management field. Safety-Related Data (SRD) are the most valuable assets for organizations' Safety Decision-Making (SDM), especially in the era of big data. This paper focuses on the potentially important value of SRD in SDM, and aims to systematically answer some fundamental questions concerning a new paradigm for SDM, known as data-driven SDM, from a theoretical perspective. These questions examine (1) what it is, (2) what its benefits are, (3) what its theoretical foundations are, (4) what its fundamental elements consist of, (5) what factors influencing it are, and (6) how the organization should implement it and realize smart safety management by using it. Other theoretical and practical contributions include a discussion of the problems of traditional SDM approaches and how to solve them, a rationale for creating and studying data-driven SDM, and suggestions for future research. This paper is the first to study the basic questions of data-driven SDM specifically, thus its results hold important implications for future research and practice on data-driven SDM and smart safety management. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1595 / 1604
页数:10
相关论文
共 22 条
  • [1] Data literacy for safety professionals in safety management: A theoretical perspective on basic questions and answers
    Wang, Bing
    Wu, Chao
    Huang, Lang
    SAFETY SCIENCE, 2019, 117 : 15 - 22
  • [2] Big data-driven risk decision-making and safety management in agricultural supply chains
    Han, Guanghe
    Pan, Xin
    Zhang, Xin
    QUALITY ASSURANCE AND SAFETY OF CROPS & FOODS, 2024, 16 (01) : 121 - 138
  • [3] Smart Cities and Big Data Analytics: A Data-Driven Decision-Making Use Case
    Osman, Ahmed M. Shahat
    Elragal, Ahmed
    SMART CITIES, 2021, 4 (01): : 286 - 313
  • [4] Big-data-driven safety decision-making: A conceptual framework and its influencing factors
    Huang, Lang
    Wu, Chao
    Wang, Bing
    Ouyang, Qiumei
    SAFETY SCIENCE, 2018, 109 : 46 - 56
  • [5] Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective
    Sarker I.H.
    SN Computer Science, 2021, 2 (5)
  • [6] Data science empowering the public: Data-driven dashboards for transparent and accountable decision-making in smart cities
    Matheus, Ricardo
    Janssen, Marijn
    Maheshwari, Devender
    GOVERNMENT INFORMATION QUARTERLY, 2020, 37 (03)
  • [7] Next-generation data center energy management: a data-driven decision-making framework
    Milic, Vlatko
    FRONTIERS IN ENERGY RESEARCH, 2024, 12
  • [8] Development of a Data-Driven Decision-Making System Using Lean and Smart Manufacturing Concept in Industry 4.0: A Case Study
    Tripathi, Varun
    Chattopadhyaya, Somnath
    Mukhopadhyay, A. K.
    Saraswat, Suvandan
    Sharma, Shubham
    Li, Changhe
    Rajkumar, S.
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [9] Leveraging Frontline Employees' Knowledge for Operational Data-Driven Decision-Making: A Multilevel Perspective
    Colombari, Ruggero
    Neirotti, Paolo
    IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2024, 71 : 13840 - 13851
  • [10] Basin Flood Risk Management: A Territorial Data-Driven Approach to Support Decision-Making
    dos Santos, Pedro Pinto
    Tavares, Alexandre Oliveira
    WATER, 2015, 7 (02): : 480 - 502