Lin Liu, Fang Wang, Jinnan Wu, Wenpei Zhang, Lixin Jiang, Gang Chen
{"title":"无法遵守法规:威慑和社会学习因素如何导致违反工作场所安全规定的行为。","authors":"Lin Liu, Fang Wang, Jinnan Wu, Wenpei Zhang, Lixin Jiang, Gang Chen","doi":"10.3233/WOR-240213","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Workplace safety violation is a significant challenge for global enterprises. However, prior studies have generated inconsistent findings, which calls for a holistic framework to reveal the complex causality between antecedent conditions and workplace safety violations in high-risk industries.</p><p><strong>Objective: </strong>By embracing deterrence theory and social learning theory, this study aimed to examine how punishment (i.e., perceived punishment certainty and perceived punishment severity), shame (i.e., perceived shame certainty and perceived shame severity) and coworker safety violations (CSV) combine into configurational causes of employee safety violations (ESV).</p><p><strong>Methods: </strong>A two-wave sampling approach was used to obtain 370 usable samples from various high-risk industries in China. The confirmatory factor analysis was performed to test construct validity, and an emerging fuzzy set qualitative comparative analysis (fsQCA) was conducted to explore the complex causality between ESV and its multiple antecedents.</p><p><strong>Results: </strong>The fsQCA results indicate that no single antecedent condition is necessary for predicting high ESV, but three distinct configurations of multiple antecedents equivalently lead to high ESV. Among all configurations, a lack of perceived punishment severity, a lack of perceived shame certainty and severity, and high CSV play important roles in explaining ESV.</p><p><strong>Conclusions: </strong>This study represents a pioneering endeavor utilizing fsQCA to explore how different combinations of punishment, shame and social learning antecedents contribute to high ESV, which goes beyond previous research focusing on antecedents independently and offers new insights into interconnected antecedents of ESV and their complex causality.</p>","PeriodicalId":51373,"journal":{"name":"Work-A Journal of Prevention Assessment & Rehabilitation","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unable to comply with regulations: How deterrent and social learning factors contribute to workplace safety violation.\",\"authors\":\"Lin Liu, Fang Wang, Jinnan Wu, Wenpei Zhang, Lixin Jiang, Gang Chen\",\"doi\":\"10.3233/WOR-240213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Workplace safety violation is a significant challenge for global enterprises. However, prior studies have generated inconsistent findings, which calls for a holistic framework to reveal the complex causality between antecedent conditions and workplace safety violations in high-risk industries.</p><p><strong>Objective: </strong>By embracing deterrence theory and social learning theory, this study aimed to examine how punishment (i.e., perceived punishment certainty and perceived punishment severity), shame (i.e., perceived shame certainty and perceived shame severity) and coworker safety violations (CSV) combine into configurational causes of employee safety violations (ESV).</p><p><strong>Methods: </strong>A two-wave sampling approach was used to obtain 370 usable samples from various high-risk industries in China. The confirmatory factor analysis was performed to test construct validity, and an emerging fuzzy set qualitative comparative analysis (fsQCA) was conducted to explore the complex causality between ESV and its multiple antecedents.</p><p><strong>Results: </strong>The fsQCA results indicate that no single antecedent condition is necessary for predicting high ESV, but three distinct configurations of multiple antecedents equivalently lead to high ESV. Among all configurations, a lack of perceived punishment severity, a lack of perceived shame certainty and severity, and high CSV play important roles in explaining ESV.</p><p><strong>Conclusions: </strong>This study represents a pioneering endeavor utilizing fsQCA to explore how different combinations of punishment, shame and social learning antecedents contribute to high ESV, which goes beyond previous research focusing on antecedents independently and offers new insights into interconnected antecedents of ESV and their complex causality.</p>\",\"PeriodicalId\":51373,\"journal\":{\"name\":\"Work-A Journal of Prevention Assessment & Rehabilitation\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Work-A Journal of Prevention Assessment & Rehabilitation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3233/WOR-240213\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Work-A Journal of Prevention Assessment & Rehabilitation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3233/WOR-240213","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Unable to comply with regulations: How deterrent and social learning factors contribute to workplace safety violation.
Background: Workplace safety violation is a significant challenge for global enterprises. However, prior studies have generated inconsistent findings, which calls for a holistic framework to reveal the complex causality between antecedent conditions and workplace safety violations in high-risk industries.
Objective: By embracing deterrence theory and social learning theory, this study aimed to examine how punishment (i.e., perceived punishment certainty and perceived punishment severity), shame (i.e., perceived shame certainty and perceived shame severity) and coworker safety violations (CSV) combine into configurational causes of employee safety violations (ESV).
Methods: A two-wave sampling approach was used to obtain 370 usable samples from various high-risk industries in China. The confirmatory factor analysis was performed to test construct validity, and an emerging fuzzy set qualitative comparative analysis (fsQCA) was conducted to explore the complex causality between ESV and its multiple antecedents.
Results: The fsQCA results indicate that no single antecedent condition is necessary for predicting high ESV, but three distinct configurations of multiple antecedents equivalently lead to high ESV. Among all configurations, a lack of perceived punishment severity, a lack of perceived shame certainty and severity, and high CSV play important roles in explaining ESV.
Conclusions: This study represents a pioneering endeavor utilizing fsQCA to explore how different combinations of punishment, shame and social learning antecedents contribute to high ESV, which goes beyond previous research focusing on antecedents independently and offers new insights into interconnected antecedents of ESV and their complex causality.
期刊介绍:
WORK: A Journal of Prevention, Assessment & Rehabilitation is an interdisciplinary, international journal which publishes high quality peer-reviewed manuscripts covering the entire scope of the occupation of work. The journal''s subtitle has been deliberately laid out: The first goal is the prevention of illness, injury, and disability. When this goal is not achievable, the attention focuses on assessment to design client-centered intervention, rehabilitation, treatment, or controls that use scientific evidence to support best practice.