• DocumentCode
    1110162
  • Title

    Career progression in a Fortune 500 company: examination of the “glass ceiling”

  • Author

    Tokunaga, Howard ; Graham, Tracy

  • Author_Institution
    Dept. of Physchol., San Jose State Univ., CA, USA
  • Volume
    43
  • Issue
    3
  • fYear
    1996
  • fDate
    8/1/1996 12:00:00 AM
  • Firstpage
    262
  • Lastpage
    272
  • Abstract
    This study examines the relationships of gender and race with the career progress of 2508 employees in the technical division of a Fortune 500 company: 1354 employees with bachelor´s degrees (Level One) and 1154 employees with master´s degrees (Level Two) in engineering and computer science. Using company records to measure employee promotions and controlling for level of education, female and nonwhite employees received fewer promotions than males or whites. Hierarchical multiple regression analyses found that gender differences in promotions could be explained by work-related variables, primarily organizational tenure. However, race added significant predictive ability for Level One (not Level Two) employees´ current job level after controlling for work experience, tenure, job performance, and gender. Unexpectedly, marital status predicted the current job level for Level Two employees, with single employees receiving fewer promotions than married employees. These findings are discussed in light of theory and research
  • Keywords
    education; engineering; gender issues; personnel; Fortune 500 company; bachelor´s degrees; career development; career progression; computer science; education level; employee promotions; engineering; female employees; gender; glass ceiling; hierarchical multiple regression analyses; job performance; marital status; master´s degrees; nonwhite employees; organizational tenure; predictive ability; technical division; work experience; work-related variables; Career development; Computer industry; Computer science; Computer science education; Control engineering education; Engineering profession; Glass; Investments; Motion analysis; Regression analysis;
  • fLanguage
    English
  • Journal_Title
    Engineering Management, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9391
  • Type

    jour

  • DOI
    10.1109/17.511837
  • Filename
    511837