Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators

With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Niu, Yi [verfasserIn] Fan, Yunxiao [verfasserIn] Li, Yuanlong [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method

Übergeordnetes Werk:	Enthalten in: Journal of loss prevention in the process industries - Amsterdam [u.a.] : Elsevier Science, 1988, 83
Übergeordnetes Werk:	volume:83

DOI / URN:	10.1016/j.jlp.2023.105090

Katalog-ID:	ELV010325050

Internformat


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245	1	0	\|a Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators
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520			\|a With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained.
650		4	\|a The Chinese oil industry
650		4	\|a Safety performance
650		4	\|a Data envelopment analysis
650		4	\|a Entropy weight method
700	1		\|a Fan, Yunxiao \|e verfasserin \|4 aut
700	1		\|a Li, Yuanlong \|e verfasserin \|4 aut
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allfields	10.1016/j.jlp.2023.105090 doi (DE-627)ELV010325050 (ELSEVIER)S0950-4230(23)00120-1 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Niu, Yi verfasserin aut Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained. The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method Fan, Yunxiao verfasserin aut Li, Yuanlong verfasserin aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 83 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:83 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 83
spelling	10.1016/j.jlp.2023.105090 doi (DE-627)ELV010325050 (ELSEVIER)S0950-4230(23)00120-1 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Niu, Yi verfasserin aut Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained. The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method Fan, Yunxiao verfasserin aut Li, Yuanlong verfasserin aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 83 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:83 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 83
allfields_unstemmed	10.1016/j.jlp.2023.105090 doi (DE-627)ELV010325050 (ELSEVIER)S0950-4230(23)00120-1 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Niu, Yi verfasserin aut Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained. The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method Fan, Yunxiao verfasserin aut Li, Yuanlong verfasserin aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 83 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:83 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 83
allfieldsGer	10.1016/j.jlp.2023.105090 doi (DE-627)ELV010325050 (ELSEVIER)S0950-4230(23)00120-1 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Niu, Yi verfasserin aut Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained. The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method Fan, Yunxiao verfasserin aut Li, Yuanlong verfasserin aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 83 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:83 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 83
allfieldsSound	10.1016/j.jlp.2023.105090 doi (DE-627)ELV010325050 (ELSEVIER)S0950-4230(23)00120-1 DE-627 ger DE-627 rda eng 670 VZ 58.18 bkl Niu, Yi verfasserin aut Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained. The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method Fan, Yunxiao verfasserin aut Li, Yuanlong verfasserin aut Enthalten in Journal of loss prevention in the process industries Amsterdam [u.a.] : Elsevier Science, 1988 83 Online-Ressource (DE-627)320605469 (DE-600)2020695-1 (DE-576)271585269 0950-4230 nnns volume:83 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 83
language	English
source	Enthalten in Journal of loss prevention in the process industries 83 volume:83
sourceStr	Enthalten in Journal of loss prevention in the process industries 83 volume:83
format_phy_str_mv	Article
bklname	Chemische Betriebstechnik
institution	findex.gbv.de
topic_facet	The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method
dewey-raw	670
isfreeaccess_bool	false
container_title	Journal of loss prevention in the process industries
authorswithroles_txt_mv	Niu, Yi @@aut@@ Fan, Yunxiao @@aut@@ Li, Yuanlong @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320605469
dewey-sort	3670
id	ELV010325050
language_de	englisch
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author	Niu, Yi
spellingShingle	Niu, Yi ddc 670 bkl 58.18 misc The Chinese oil industry misc Safety performance misc Data envelopment analysis misc Entropy weight method Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators
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topic_title	670 VZ 58.18 bkl Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators The Chinese oil industry Safety performance Data envelopment analysis Entropy weight method
topic	ddc 670 bkl 58.18 misc The Chinese oil industry misc Safety performance misc Data envelopment analysis misc Entropy weight method
topic_unstemmed	ddc 670 bkl 58.18 misc The Chinese oil industry misc Safety performance misc Data envelopment analysis misc Entropy weight method
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title	Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators
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title_full	Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators
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title_sort	safety performance measurement in collectivized oil companies in china: contribution of leading indicators to lagging indicators
title_auth	Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators
abstract	With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained.
abstractGer	With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained.
abstract_unstemmed	With the collectivization of the Chinese oil industry, oil companies have been expanding in size. However, the intensified differences in the safety performance of subsidiaries have severely hindered the collaborative management of the headquarters. Understanding the safety status of each member is urgent for parent companies and their subsidiaries to identify gaps and make improvements. A unified set of safety performance indicators and a practical measurement tool are essential for the Chinese oil industry. Hence, this study identified a set of safety performance indicators encompassing both leading and lagging indicators using data envelopment analysis (DEA) and entropy weight method (EWM) to reveal the critical factors affecting the safety performance of the oil industry. A total of 300 front-line workers from eight subsidiaries of an oil company participated in the survey. The identified indicators were preliminarily weighted using EWM. Then, DEA was employed to measure the safety performance of the eight subsidiaries, demonstrating that management commitment was the most crucial factor in distinguishing safety performance; safety culture was more differentiated than risk management. Safety performance was not entirely positively correlated with safety investments, but the reasonable allocation of safety resources played a vital role. In addition, the weaknesses in each subsidiary's safety management were identified, and the quantitative effects of each leading indicator on safety performance were obtained.
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title_short	Safety performance measurement in collectivized oil companies in China: Contribution of leading indicators to lagging indicators
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up_date	2024-07-06T17:35:41.201Z
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