{"title":"理解智能技术、人工智能、机器人和自动化带来的工作不安全感的出现和发展轨迹","authors":"Marvin Walczok, Tanja Bipp","doi":"10.1002/hfm.70000","DOIUrl":null,"url":null,"abstract":"<p>Smart technologies, artificial intelligence, robotics, and automation (STARA) can revolutionize the labor market by substituting human labor. STARA Awareness has been introduced to capture employees' appraisal of the impact of STARA on their employment without a thorough validation and overarching theoretical framework. Therefore, we contributed a content validation of STARA Awareness and examined the internal structure of the suggested measurement instrument, the differentiation from cognitive and affective job insecurity (JI), potential antecedents, and its 1-year trend. We conducted two cross-sectional (<i>N</i><sub><i>1</i></sub> = 215, <i>N</i><sub><i>2</i></sub> = 224) and one longitudinal study (<i>N</i><sub><i>3</i></sub> = 233) with German employees from various branches. We adapted the questionnaire and redefined the construct as affective automation-related job insecurity (AAJI) based on content criticism. Our results indicate that AAJI is weakly positively related to cognitive and affective JI but empirically different. We identified the substitution potential of occupation, the use of STARA as positive predictors, and core self-evaluations as a negative predictor of AAJI. Latent growth curve models reveal no linear change of AAJI over 1 year but different trajectories as a function of the use of STARA. Thus, AAJI represents a digitalization-specific form of job insecurity with its distinct nomological net and high temporal stability.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 3","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hfm.70000","citationCount":"0","resultStr":"{\"title\":\"Understanding the Emergence and Trajectory of Job Insecurity Due to Smart Technology, Artificial Intelligence, Robotics, and Automation\",\"authors\":\"Marvin Walczok, Tanja Bipp\",\"doi\":\"10.1002/hfm.70000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Smart technologies, artificial intelligence, robotics, and automation (STARA) can revolutionize the labor market by substituting human labor. STARA Awareness has been introduced to capture employees' appraisal of the impact of STARA on their employment without a thorough validation and overarching theoretical framework. Therefore, we contributed a content validation of STARA Awareness and examined the internal structure of the suggested measurement instrument, the differentiation from cognitive and affective job insecurity (JI), potential antecedents, and its 1-year trend. We conducted two cross-sectional (<i>N</i><sub><i>1</i></sub> = 215, <i>N</i><sub><i>2</i></sub> = 224) and one longitudinal study (<i>N</i><sub><i>3</i></sub> = 233) with German employees from various branches. We adapted the questionnaire and redefined the construct as affective automation-related job insecurity (AAJI) based on content criticism. Our results indicate that AAJI is weakly positively related to cognitive and affective JI but empirically different. We identified the substitution potential of occupation, the use of STARA as positive predictors, and core self-evaluations as a negative predictor of AAJI. Latent growth curve models reveal no linear change of AAJI over 1 year but different trajectories as a function of the use of STARA. Thus, AAJI represents a digitalization-specific form of job insecurity with its distinct nomological net and high temporal stability.</p>\",\"PeriodicalId\":55048,\"journal\":{\"name\":\"Human Factors and Ergonomics in Manufacturing & Service Industries\",\"volume\":\"35 3\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hfm.70000\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Factors and Ergonomics in Manufacturing & Service Industries\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/hfm.70000\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Factors and Ergonomics in Manufacturing & Service Industries","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hfm.70000","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Understanding the Emergence and Trajectory of Job Insecurity Due to Smart Technology, Artificial Intelligence, Robotics, and Automation
Smart technologies, artificial intelligence, robotics, and automation (STARA) can revolutionize the labor market by substituting human labor. STARA Awareness has been introduced to capture employees' appraisal of the impact of STARA on their employment without a thorough validation and overarching theoretical framework. Therefore, we contributed a content validation of STARA Awareness and examined the internal structure of the suggested measurement instrument, the differentiation from cognitive and affective job insecurity (JI), potential antecedents, and its 1-year trend. We conducted two cross-sectional (N1 = 215, N2 = 224) and one longitudinal study (N3 = 233) with German employees from various branches. We adapted the questionnaire and redefined the construct as affective automation-related job insecurity (AAJI) based on content criticism. Our results indicate that AAJI is weakly positively related to cognitive and affective JI but empirically different. We identified the substitution potential of occupation, the use of STARA as positive predictors, and core self-evaluations as a negative predictor of AAJI. Latent growth curve models reveal no linear change of AAJI over 1 year but different trajectories as a function of the use of STARA. Thus, AAJI represents a digitalization-specific form of job insecurity with its distinct nomological net and high temporal stability.
期刊介绍：
The purpose of Human Factors and Ergonomics in Manufacturing & Service Industries is to facilitate discovery, integration, and application of scientific knowledge about human aspects of manufacturing, and to provide a forum for worldwide dissemination of such knowledge for its application and benefit to manufacturing industries. The journal covers a broad spectrum of ergonomics and human factors issues with a focus on the design, operation and management of contemporary manufacturing systems, both in the shop floor and office environments, in the quest for manufacturing agility, i.e. enhancement and integration of human skills with hardware performance for improved market competitiveness, management of change, product and process quality, and human-system reliability. The inter- and cross-disciplinary nature of the journal allows for a wide scope of issues relevant to manufacturing system design and engineering, human resource management, social, organizational, safety, and health issues. Examples of specific subject areas of interest include: implementation of advanced manufacturing technology, human aspects of computer-aided design and engineering, work design, compensation and appraisal, selection training and education, labor-management relations, agile manufacturing and virtual companies, human factors in total quality management, prevention of work-related musculoskeletal disorders, ergonomics of workplace, equipment and tool design, ergonomics programs, guides and standards for industry, automation safety and robot systems, human skills development and knowledge enhancing technologies, reliability, and safety and worker health issues.
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