A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents

Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaste...
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Gespeichert in:

Autor*in:	Zhu, Tiantian [verfasserIn] Yang, Xue [verfasserIn] Haugen, Stein [verfasserIn] Liu, Yiliu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach

Übergeordnetes Werk:	Enthalten in: Journal of loss prevention in the process industries - Amsterdam [u.a.] : Elsevier Science, 1988, 87
Übergeordnetes Werk:	volume:87

DOI / URN:	10.1016/j.jlp.2023.105235

Katalog-ID:	ELV066816815

Internformat


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520			\|a Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements.
650		4	\|a Problem feature
650		4	\|a Risk-related decision problem
650		4	\|a Decision-making process
650		4	\|a Decision problem analysis
650		4	\|a Accident prevention
650		4	\|a Multi-dimensional approach
700	1		\|a Yang, Xue \|e verfasserin \|0 (orcid)0000-0002-7552-0495 \|4 aut
700	1		\|a Haugen, Stein \|e verfasserin \|4 aut
700	1		\|a Liu, Yiliu \|e verfasserin \|0 (orcid)0000-0002-0612-2231 \|4 aut
773	0	8	\|i Enthalten in \|t Journal of loss prevention in the process industries \|d Amsterdam [u.a.] : Elsevier Science, 1988 \|g 87 \|h Online-Ressource \|w (DE-627)320605469 \|w (DE-600)2020695-1 \|w (DE-576)271585269 \|x 0950-4230 \|7 nnns
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912			\|a GBV_ILN_32
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2190
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912			\|a GBV_ILN_2507
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
936	b	k	\|a 58.18 \|j Chemische Betriebstechnik \|q VZ
951			\|a AR
952			\|d 87

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matchkey_str	article:09504230:2023----::mliiesoaapocfrnlznrsrltdeiinrbesonacdcs
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publishDate	2023
allfields	10.1016/j.jlp.2023.105235 doi (DE-627)ELV066816815 (ELSEVIER)S0950-4230(23)00265-6 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Zhu, Tiantian verfasserin (orcid)0000-0002-3401-8482 aut A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements. Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach Yang, Xue verfasserin (orcid)0000-0002-7552-0495 aut Haugen, Stein verfasserin aut Liu, Yiliu verfasserin (orcid)0000-0002-0612-2231 aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 87 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:87 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.18 Chemische Betriebstechnik VZ AR 87
spelling	10.1016/j.jlp.2023.105235 doi (DE-627)ELV066816815 (ELSEVIER)S0950-4230(23)00265-6 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Zhu, Tiantian verfasserin (orcid)0000-0002-3401-8482 aut A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements. Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach Yang, Xue verfasserin (orcid)0000-0002-7552-0495 aut Haugen, Stein verfasserin aut Liu, Yiliu verfasserin (orcid)0000-0002-0612-2231 aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 87 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:87 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.18 Chemische Betriebstechnik VZ AR 87
allfields_unstemmed	10.1016/j.jlp.2023.105235 doi (DE-627)ELV066816815 (ELSEVIER)S0950-4230(23)00265-6 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Zhu, Tiantian verfasserin (orcid)0000-0002-3401-8482 aut A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements. Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach Yang, Xue verfasserin (orcid)0000-0002-7552-0495 aut Haugen, Stein verfasserin aut Liu, Yiliu verfasserin (orcid)0000-0002-0612-2231 aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 87 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:87 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.18 Chemische Betriebstechnik VZ AR 87
allfieldsGer	10.1016/j.jlp.2023.105235 doi (DE-627)ELV066816815 (ELSEVIER)S0950-4230(23)00265-6 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Zhu, Tiantian verfasserin (orcid)0000-0002-3401-8482 aut A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements. Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach Yang, Xue verfasserin (orcid)0000-0002-7552-0495 aut Haugen, Stein verfasserin aut Liu, Yiliu verfasserin (orcid)0000-0002-0612-2231 aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 87 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:87 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.18 Chemische Betriebstechnik VZ AR 87
allfieldsSound	10.1016/j.jlp.2023.105235 doi (DE-627)ELV066816815 (ELSEVIER)S0950-4230(23)00265-6 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Zhu, Tiantian verfasserin (orcid)0000-0002-3401-8482 aut A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements. Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach Yang, Xue verfasserin (orcid)0000-0002-7552-0495 aut Haugen, Stein verfasserin aut Liu, Yiliu verfasserin (orcid)0000-0002-0612-2231 aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 87 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:87 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.18 Chemische Betriebstechnik VZ AR 87
language	English
source	Enthalten in Journal of loss prevention in the process industries 87 volume:87
sourceStr	Enthalten in Journal of loss prevention in the process industries 87 volume:87
format_phy_str_mv	Article
bklname	Chemische Betriebstechnik
institution	findex.gbv.de
topic_facet	Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach
dewey-raw	670
isfreeaccess_bool	false
container_title	Journal of loss prevention in the process industries
authorswithroles_txt_mv	Zhu, Tiantian @@aut@@ Yang, Xue @@aut@@ Haugen, Stein @@aut@@ Liu, Yiliu @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320605469
dewey-sort	3670
id	ELV066816815
language_de	englisch
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author	Zhu, Tiantian
spellingShingle	Zhu, Tiantian ddc 670 bkl 58.18 misc Problem feature misc Risk-related decision problem misc Decision-making process misc Decision problem analysis misc Accident prevention misc Multi-dimensional approach A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents
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topic_title	670 VZ 58.18 bkl A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents Problem feature Risk-related decision problem Decision-making process Decision problem analysis Accident prevention Multi-dimensional approach
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title	A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents
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title_full	A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents
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title_sort	a multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents
title_auth	A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents
abstract	Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements.
abstractGer	Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements.
abstract_unstemmed	Risk-related decision problems are the problems that influence the risk of accidents. In most cases, the probability of major accidents is very low, but their consequences can be extreme, resulting in numerous fatalities and extensive environmental damage. An example is the Deepwater Horizon disaster in the Gulf of Mexico in 2010. Decision making under such circumstances (i.e., under high stake and complexity) is challenging, where expected utility calculations typically are not sufficient to provide a robust foundation. This article focuses on this specific category of risk-related decision problems, aiming to develop a decision analysis approach to enhance decision makers’ understanding on the features of their decision problems. This can in turn form the basis for tailoring the information needed for decision making. The proposed approach is a multi-dimensional approach, which includes seven dimensions: criticality, uniqueness, structuredness, complicatedness, dynamic, residual uncertainty, and problem trigger. Real-life examples are analyzed to illustrate and assess the proposed multi-dimensional approach. Overall, an improved understanding of risk-related decisions problem can be aided by the proposed approach, which indirectly helps to prevent accidents and maintain safety by predicting the human decision-making process, potential decision-making errors, and identifying decision support requirements.
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title_short	A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents
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