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Browsing by Author "Wijenayaka, T. H. P. C"

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    PublicationOpen Access
    ‘Leave or remain’: intentions of Gen X and Y employees
    (Springerlink, 2022-06-28) Weerarathna, R; Walpola, M. D. C. P; Piyasiri, A. D. W. D; Jayamal, I. A. U. M; Wijenayaka, T. H. P. C; Pathirana, G. Y
    This study looks into a predictive model to ascertain the turnover of Generation ‘X’ and ‘Y’ employees. Based on Erving Gofman’s frame analysis theory, three key factors such as the nature of working styles, social values and the personal values have been identifed as infuencing factors. The impact of these factors on workplace behavior in terms of intention to leave or remain with the organization has been tested using responses of 297 employees. The data were collected using a survey questionnaire. Data were analyzed using the Binary Logistic Regression and the Neural Network Analysis to ensure the level of accuracy in Predictive Analysis of Generation X and Y. It was found that diferences in characteristics and behavior between the two Generations lead to a higher turnover rate in Generation ‘Y’ than in Generation ‘X’. Moreover, the researchers predicted data related to retention and intention to leave of the two Generations based on the sample
  • Thumbnail Image
    PublicationOpen Access
    Leave or remain: intentions of Gen X and Y employees
    (Springer, 2022-06) Weerarathna, R; Walpola, M. D. C. P; Piyasiri, A. D. W. D; Jayamal, I. A. U. M; Wijenayaka, T. H. P. C; Pathirana, G. Y
    This study looks into a predictive model to ascertain the turnover of Generation ‘X’ and ‘Y’ employees. Based on Erving Gofman’s frame analysis theory, three key factors such as the nature of working styles, social values and the personal values have been identifed as infuencing factors. The impact of these factors on workplace behavior in terms of intention to leave or remain with the organization has been tested using responses of 297 employees. The data were collected using a survey questionnaire. Data were analyzed using the Binary Logistic Regression and the Neural Network Analysis to ensure the level of accuracy in Predictive Analysis of Generation X and Y. It was found that diferences in characteristics and behavior between the two Generations lead to a higher turnover rate in Generation ‘Y’ than in Generation ‘X’. Moreover, the researchers predicted data related to retention and intention to leave of the two Generations based on the sample.

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