Pub Date : 2023-11-27DOI: 10.1080/1463922x.2023.2284295
D. Restuputri, Fita Amalia, I. Masudin, Widayat
{"title":"The influence of industry 4.0, internet of things, and physical-cyber systems on human factors: a case study of workers in Indonesian oil and gas refineries","authors":"D. Restuputri, Fita Amalia, I. Masudin, Widayat","doi":"10.1080/1463922x.2023.2284295","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2284295","url":null,"abstract":"","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139230287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-14DOI: 10.1080/1463922x.2023.2281004
Hamad S. J. Rashid
AbstractHumans strive to understand and respond to abnormal changes that occur within their surrounding contexts. Current literature is yet to discuss the process of triggering an enquiring process within the human cognition after the occurrence of an unforeseen change event or an accident, to explain what behavioral response can follow, and to recognize what factors shape such a response. This article presents a new theoretical model – tagged as the ‘Slammed Adjacent Door (SAD)’ model that addresses the behaviour of an individual responder to a simple change event, which is expanded to discuss the wider social and organizational behaviour relevant to an accident. The model establishes the link between the preliminary cognition of potential investigators and their following practical response to an accident, by discussing the dynamic interactions of various endogenous and exogenous factors that trigger and control their post-event investigative actions. According to the SAD model, an industrial accident investigation is a six-phased sequence of mental manipulations, decisions, and physical actions that are initiated, motivated, and sustained by complex mutually-influencing personal, organizational, and wider set of input factors. The model has consequential set of theoretical and practical implications relating to organizational or other incidents and accidents investigations.Keywords: Accidents investigationstheoretical modellinghuman cognition and behavioursafetyorganizational behaviour Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"A theoretical model of industrial accidents investigations: a conceptualization of the mental processes that trigger and control investigative activities","authors":"Hamad S. J. Rashid","doi":"10.1080/1463922x.2023.2281004","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2281004","url":null,"abstract":"AbstractHumans strive to understand and respond to abnormal changes that occur within their surrounding contexts. Current literature is yet to discuss the process of triggering an enquiring process within the human cognition after the occurrence of an unforeseen change event or an accident, to explain what behavioral response can follow, and to recognize what factors shape such a response. This article presents a new theoretical model – tagged as the ‘Slammed Adjacent Door (SAD)’ model that addresses the behaviour of an individual responder to a simple change event, which is expanded to discuss the wider social and organizational behaviour relevant to an accident. The model establishes the link between the preliminary cognition of potential investigators and their following practical response to an accident, by discussing the dynamic interactions of various endogenous and exogenous factors that trigger and control their post-event investigative actions. According to the SAD model, an industrial accident investigation is a six-phased sequence of mental manipulations, decisions, and physical actions that are initiated, motivated, and sustained by complex mutually-influencing personal, organizational, and wider set of input factors. The model has consequential set of theoretical and practical implications relating to organizational or other incidents and accidents investigations.Keywords: Accidents investigationstheoretical modellinghuman cognition and behavioursafetyorganizational behaviour Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134991333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.1080/1463922x.2023.2261995
Markus Hartono, Dina Natalia Prayogo, I. Made Ronyastra, Abdullah Baredwan
AbstractKansei Engineering (KE) has shown its prominent applicability in service design and development, focusing on translating and interpreting customers’ emotional needs (Kansei) into service characteristics. It is critical and promising as the services sector has grown faster than the manufacturing sector in developing economies in the past three decades. It accounted for an average of 55% of GDP in some developing economies. KE’s flexibility in collaborating with other methods and covering various service settings shows its unique superiority. However, there is criticism of the collected Kansei’s validity and the proposed solution’s robustness. It might be potentially caused by the dynamics of customer emotional needs and various service settings. As a result, Kansei is found to be somewhat fuzzy, unclear, and ambiguous. Hence, a more structured KE methodology incorporating the Kansei text mining process for robust service design is proposed. Kansei text mining approach will extract and summarize service attributes and their corresponding affective responses based on the online product descriptions and customer reviews. The Taguchi method will support the robustness of the proposed improvement strategy. An empirical study of a zoo as a tourism attraction service and its practical implication is discussed and validated in the proposed integrative framework.Keywords: Kansei engineeringrobust designmining methodologyservice innovation Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis study was supported by the Department of Industrial Engineering University of Surabaya and the research grant by the Ministry of Education, Culture, Research, and Technology Republic of Indonesia under a research scheme of Excellent Basic Research of Higher Education (PDUPT) with a contract number 003/SP2H/LT-MULTI-PDPK/LL7/2021.
{"title":"Kansei engineering with online review mining methodology for robust service design","authors":"Markus Hartono, Dina Natalia Prayogo, I. Made Ronyastra, Abdullah Baredwan","doi":"10.1080/1463922x.2023.2261995","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2261995","url":null,"abstract":"AbstractKansei Engineering (KE) has shown its prominent applicability in service design and development, focusing on translating and interpreting customers’ emotional needs (Kansei) into service characteristics. It is critical and promising as the services sector has grown faster than the manufacturing sector in developing economies in the past three decades. It accounted for an average of 55% of GDP in some developing economies. KE’s flexibility in collaborating with other methods and covering various service settings shows its unique superiority. However, there is criticism of the collected Kansei’s validity and the proposed solution’s robustness. It might be potentially caused by the dynamics of customer emotional needs and various service settings. As a result, Kansei is found to be somewhat fuzzy, unclear, and ambiguous. Hence, a more structured KE methodology incorporating the Kansei text mining process for robust service design is proposed. Kansei text mining approach will extract and summarize service attributes and their corresponding affective responses based on the online product descriptions and customer reviews. The Taguchi method will support the robustness of the proposed improvement strategy. An empirical study of a zoo as a tourism attraction service and its practical implication is discussed and validated in the proposed integrative framework.Keywords: Kansei engineeringrobust designmining methodologyservice innovation Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis study was supported by the Department of Industrial Engineering University of Surabaya and the research grant by the Ministry of Education, Culture, Research, and Technology Republic of Indonesia under a research scheme of Excellent Basic Research of Higher Education (PDUPT) with a contract number 003/SP2H/LT-MULTI-PDPK/LL7/2021.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135344326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1080/1463922x.2023.2250406
Jose Luis Vilchez, Mauricio Esteban Reyes Guaranda, Miguel Francisco Moreno Polo, María Cristina Ávila Martínez, Camila Inés Campos Castro, Mateo Sebastián Montesdeoca Andrade, Wilson Xavier Tigre Atiencia, Danny Ordóñez Alberca, Wendy Lizbeth Michay Valarezo
{"title":"Cognitive psychology in traffic safety","authors":"Jose Luis Vilchez, Mauricio Esteban Reyes Guaranda, Miguel Francisco Moreno Polo, María Cristina Ávila Martínez, Camila Inés Campos Castro, Mateo Sebastián Montesdeoca Andrade, Wilson Xavier Tigre Atiencia, Danny Ordóñez Alberca, Wendy Lizbeth Michay Valarezo","doi":"10.1080/1463922x.2023.2250406","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2250406","url":null,"abstract":"","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46915018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-25DOI: 10.1080/1463922x.2023.2250424
R. Pak, E. Rovira
{"title":"A theoretical model to explain mixed effects of trust repair strategies in autonomous systems","authors":"R. Pak, E. Rovira","doi":"10.1080/1463922x.2023.2250424","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2250424","url":null,"abstract":"","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45801130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-13DOI: 10.1080/1463922x.2023.2233591
Mehdi Poornikoo, Kjell Ivar Øvergård
{"title":"Model evaluation in human factors and ergonomics (HFE) sciences; case of trust in automation","authors":"Mehdi Poornikoo, Kjell Ivar Øvergård","doi":"10.1080/1463922x.2023.2233591","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2233591","url":null,"abstract":"","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41943173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents a holistic model based on Fuzzy Bayesian Network-Human Factor Analysis and Classification System (FBN-HFACS) to analyze contributing factors in the pandemic, Covid 19, risk management under uncertainty. The model contains three main phases include employing a) HFACS to systematically identify influencing factors based on validation using content validity indicators, b) Fuzzy Set Theory to obtain the prior probability distribution of contributing factors in pandemic risk and address the epistemic uncertainty and subjectivity, and finally, c) Bayesian network to develop causality model of the risk, probabilistic inferences and handle parameter and model uncertainties. The Ratio of Variation (RoV), as BN-driven importance measures, is utilized to conduct sensitivity analysis and explore the most critical factors that yield effective safety countermeasures. The model is tested to investigate four large manufacturing industries in South Khorasan (Iran). It provided a deep understanding of influencing human and organizational factors and captured dependencies among those factors, while quantitative finding paves a way to efficiently make risk-based decisions to deal with the pandemic risks under uncertainty.
提出基于模糊贝叶斯网络-人因分析与分类系统(FBN-HFACS)的整体模型，分析不确定条件下新冠肺炎风险管理的影响因素。该模型包括三个主要阶段:a) HFACS基于内容效度指标的验证，系统识别影响因素;b)模糊集理论，获得大流行风险影响因素的先验概率分布，解决认知不确定性和主观性;c)贝叶斯网络，建立风险因果关系模型，进行概率推理，处理参数和模型的不确定性。变化率(Ratio of Variation, RoV)作为bn驱动的重要性度量，用于进行敏感性分析，探索产生有效安全对策的最关键因素。通过对南呼罗珊(伊朗)四个大型制造业的调查，对该模型进行了检验。它提供了对影响人类和组织因素的深刻理解，并捕获了这些因素之间的依赖关系，而定量发现为有效地做出基于风险的决策，以应对不确定情况下的大流行风险铺平了道路。
{"title":"A model to analyze human and organizational factors contributing to pandemic risk assessment in manufacturing industries: FBN-HFACS modelling","authors":"Amirhossein Khoshakhlagh, Saber Moradi Hanifi, Fereydoon Laal, Esmaeil Zarei, Fatemeh Dalakeh, Hamid Safarpour, Rohollah Fallah Madvari","doi":"10.1080/1463922x.2023.2223254","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2223254","url":null,"abstract":"This study presents a holistic model based on Fuzzy Bayesian Network-Human Factor Analysis and Classification System (FBN-HFACS) to analyze contributing factors in the pandemic, Covid 19, risk management under uncertainty. The model contains three main phases include employing a) HFACS to systematically identify influencing factors based on validation using content validity indicators, b) Fuzzy Set Theory to obtain the prior probability distribution of contributing factors in pandemic risk and address the epistemic uncertainty and subjectivity, and finally, c) Bayesian network to develop causality model of the risk, probabilistic inferences and handle parameter and model uncertainties. The Ratio of Variation (RoV), as BN-driven importance measures, is utilized to conduct sensitivity analysis and explore the most critical factors that yield effective safety countermeasures. The model is tested to investigate four large manufacturing industries in South Khorasan (Iran). It provided a deep understanding of influencing human and organizational factors and captured dependencies among those factors, while quantitative finding paves a way to efficiently make risk-based decisions to deal with the pandemic risks under uncertainty.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135399627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.21203/rs.3.rs-2358971/v1
A. Khoshakhlagh, Saber Moradi Hanifi, F. Laal, E. Zarei, Fatemeh Dalakeh, H. Safarpour, Rohollah Fallah Madvari
This study presents a holistic model based on Fuzzy Bayesian Network-Human Factor Analysis and System Classification (FBN-HFACS) to analyze contributing factors in the pandemic, Covid 19, risk management under uncertainty. The model contains three main phases include employing a) HFACS to systematically identify influencing factors based on validation using content validity indicators, b) Fuzzy Set Theory to obtain the prior probability distribution of contributing factors in pandemic risk and address the epistemic uncertainty and subjectivity, and finally, c) Bayesian network to develop causality model of the risk, probabilistic inferences and handle parameter and model uncertainties. The Ratio of Variation (RoV), as BN-driven importance measures, is utilized to conduct sensitivity analysis and explore the most critical factors that yield effective safety countermeasures. The model is tested to investigate four large manufacturing industries in South Khorasan (Iran). It provided a deep understanding of influencing human and organizational factors and captured dependencies among those factors, while quantitative finding paves a way to efficiently make risk-based decisions to deal with the pandemic risks under uncertainty.
提出基于模糊贝叶斯网络-人因分析与系统分类(FBN-HFACS)的整体模型，分析不确定条件下新冠肺炎风险管理的影响因素。该模型包括三个主要阶段:a) HFACS基于内容效度指标的验证，系统识别影响因素;b)模糊集理论，获得大流行风险影响因素的先验概率分布，解决认知不确定性和主观性;c)贝叶斯网络，建立风险因果关系模型，进行概率推理，处理参数和模型的不确定性。变化率(Ratio of Variation, RoV)作为bn驱动的重要性度量，用于进行敏感性分析，探索产生有效安全对策的最关键因素。通过对南呼罗珊(伊朗)四个大型制造业的调查，对该模型进行了检验。它提供了对影响人类和组织因素的深刻理解，并捕获了这些因素之间的依赖关系，而定量发现为有效地做出基于风险的决策，以应对不确定情况下的大流行风险铺平了道路。
{"title":"A model to analyze human and organizational factors contributing to pandemic risk assessment in manufacturing industries: FBN-HFACS modelling","authors":"A. Khoshakhlagh, Saber Moradi Hanifi, F. Laal, E. Zarei, Fatemeh Dalakeh, H. Safarpour, Rohollah Fallah Madvari","doi":"10.21203/rs.3.rs-2358971/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-2358971/v1","url":null,"abstract":"This study presents a holistic model based on Fuzzy Bayesian Network-Human Factor Analysis and System Classification (FBN-HFACS) to analyze contributing factors in the pandemic, Covid 19, risk management under uncertainty. The model contains three main phases include employing a) HFACS to systematically identify influencing factors based on validation using content validity indicators, b) Fuzzy Set Theory to obtain the prior probability distribution of contributing factors in pandemic risk and address the epistemic uncertainty and subjectivity, and finally, c) Bayesian network to develop causality model of the risk, probabilistic inferences and handle parameter and model uncertainties. The Ratio of Variation (RoV), as BN-driven importance measures, is utilized to conduct sensitivity analysis and explore the most critical factors that yield effective safety countermeasures. The model is tested to investigate four large manufacturing industries in South Khorasan (Iran). It provided a deep understanding of influencing human and organizational factors and captured dependencies among those factors, while quantitative finding paves a way to efficiently make risk-based decisions to deal with the pandemic risks under uncertainty.","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46617461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1080/1463922x.2023.2223251
A. Atchley, Hannah M. Barr, Emily H. O’Hear, Kristin Weger, Bryan L. Mesmer, Sampson Gholston, N. Tenhundfeld
{"title":"Trust in systems: identification of 17 unresolved research questions and the highlighting of inconsistencies","authors":"A. Atchley, Hannah M. Barr, Emily H. O’Hear, Kristin Weger, Bryan L. Mesmer, Sampson Gholston, N. Tenhundfeld","doi":"10.1080/1463922x.2023.2223251","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2223251","url":null,"abstract":"","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43422452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-05DOI: 10.1080/1463922x.2023.2219297
S. Talapatra, M. Parvez, P. Saha, M. Kibria
{"title":"Assessing the impact of critical risk factors on the development of musculoskeletal disorders: a structural equation modelling approach","authors":"S. Talapatra, M. Parvez, P. Saha, M. Kibria","doi":"10.1080/1463922x.2023.2219297","DOIUrl":"https://doi.org/10.1080/1463922x.2023.2219297","url":null,"abstract":"","PeriodicalId":22852,"journal":{"name":"Theoretical Issues in Ergonomics Science","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48619001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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