{"title":"她会留下还是会离开:印度IT行业女性职业坚持与不坚持的决定因素","authors":"S. Alok, Sudatta Banerjee, Navya Kumar","doi":"10.1108/sajbs-08-2020-0276","DOIUrl":null,"url":null,"abstract":"PurposeThis study aims to identify demographic characteristics, personal attributes and attitudes and social support factors that adversely or favourably affect the likelihood of career persistence amongst women workers of the Indian IT sector.Design/methodology/approachThe research, grounded in the social cognitive career theory, analyses primary data collected from 850 women working in IT via a survey. Based on an original definition of career persistence, the sample was segregated into 427 persistent and 423 non-persistent women. Logistic regression was performed to test for the effect of various determinants on the likelihood of women being career persistent versus non-persistent.FindingsBeing married, having children, as well as high levels of belief in gender disadvantage and work–family conflict lowered the likelihood of career persistence amongst women. While being a manager, possessing high career identity, high occupational culture fit, positive psychological capital and family support boost the likelihood.Originality/valueThe study examines women's actual continuance in an IT career vis-à-vis exit from the workforce/IT field, rather than women's stated intent to persist/quit as previously investigated. It uses logistic regression to identify both hurdles and aids on the path of women's career persistence. The findings can help recognize women more likely to struggle, thus be a first step in targeted organizational interventions to plug a leaky talent pipeline.","PeriodicalId":55618,"journal":{"name":"South Asian Journal of Business Studies","volume":" ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Will she stay or will she quit: determinants of career persistence and non-persistence amongst women workers of India's IT sector\",\"authors\":\"S. Alok, Sudatta Banerjee, Navya Kumar\",\"doi\":\"10.1108/sajbs-08-2020-0276\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PurposeThis study aims to identify demographic characteristics, personal attributes and attitudes and social support factors that adversely or favourably affect the likelihood of career persistence amongst women workers of the Indian IT sector.Design/methodology/approachThe research, grounded in the social cognitive career theory, analyses primary data collected from 850 women working in IT via a survey. Based on an original definition of career persistence, the sample was segregated into 427 persistent and 423 non-persistent women. Logistic regression was performed to test for the effect of various determinants on the likelihood of women being career persistent versus non-persistent.FindingsBeing married, having children, as well as high levels of belief in gender disadvantage and work–family conflict lowered the likelihood of career persistence amongst women. While being a manager, possessing high career identity, high occupational culture fit, positive psychological capital and family support boost the likelihood.Originality/valueThe study examines women's actual continuance in an IT career vis-à-vis exit from the workforce/IT field, rather than women's stated intent to persist/quit as previously investigated. It uses logistic regression to identify both hurdles and aids on the path of women's career persistence. The findings can help recognize women more likely to struggle, thus be a first step in targeted organizational interventions to plug a leaky talent pipeline.\",\"PeriodicalId\":55618,\"journal\":{\"name\":\"South Asian Journal of Business Studies\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2021-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South Asian Journal of Business Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/sajbs-08-2020-0276\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South Asian Journal of Business Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/sajbs-08-2020-0276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
Will she stay or will she quit: determinants of career persistence and non-persistence amongst women workers of India's IT sector
PurposeThis study aims to identify demographic characteristics, personal attributes and attitudes and social support factors that adversely or favourably affect the likelihood of career persistence amongst women workers of the Indian IT sector.Design/methodology/approachThe research, grounded in the social cognitive career theory, analyses primary data collected from 850 women working in IT via a survey. Based on an original definition of career persistence, the sample was segregated into 427 persistent and 423 non-persistent women. Logistic regression was performed to test for the effect of various determinants on the likelihood of women being career persistent versus non-persistent.FindingsBeing married, having children, as well as high levels of belief in gender disadvantage and work–family conflict lowered the likelihood of career persistence amongst women. While being a manager, possessing high career identity, high occupational culture fit, positive psychological capital and family support boost the likelihood.Originality/valueThe study examines women's actual continuance in an IT career vis-à-vis exit from the workforce/IT field, rather than women's stated intent to persist/quit as previously investigated. It uses logistic regression to identify both hurdles and aids on the path of women's career persistence. The findings can help recognize women more likely to struggle, thus be a first step in targeted organizational interventions to plug a leaky talent pipeline.