| Literature DB >> 35789759 |
R S Weerarathne1, M D C P Walpola1, A D W D Piyasiri1, I A U M Jayamal1, T H P C Wijenayaka1, G Y Pathirana1.
Abstract
This study looks into a predictive model to ascertain the turnover of Generation 'X' and 'Y' employees. Based on Erving Goffman's frame analysis theory, three key factors such as the nature of working styles, social values and the personal values have been identified as influencing 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 differences 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.Entities:
Keywords: Comparison; Generation ‘X’; Generation ‘Y’; Predictive analysis; Workplace
Year: 2022 PMID: 35789759 PMCID: PMC9244235 DOI: 10.1007/s11135-022-01456-z
Source DB: PubMed Journal: Qual Quant ISSN: 0033-5177
Characteristics of Generations ‘X’ and ‘Y’
| Characteristic | Generation X | Generation Y |
|---|---|---|
| Loyalty | More loyal to the profession (Sayers | Less loyal to the profession (Smola & Sutton |
| Orientation | Result oriented; Glass ( | Achievement oriented (Han & Su |
| Preference | More independent at workplace (Cole et al. | Most of the times, engaged in teams at workplace (Howe & Strauss |
| Discipline | Maintain discipline at workplace Tayyab & Tariq ( | Aggressive at workplace (Zemke et al. |
| Technology savvy | Technologically skilled but not getting updates about it (Kupperschmidt | More technologically skilled and are always updated about the technological advancements (Han & Su, |
| Decision making | Takes decisions in order to fulfill their own goals as well as to fulfill the corporate goals (Cole et al., | Takes short term decisions and expect the results to be higher Leo ( |
| Nature of interrogation | Less interrogating at workplace (Bova & Kroth, | More interrogating at workplace Martin ( |
(Source: Author’s Own)
Common Characteristics of Generations ‘x’ and ‘y’. (
Source: Author’s Own)
| Findings | Author |
|---|---|
| Generations ‘x’ and ‘y’ seek comfort and have more respect for those who share their own values | Kipnis & Childs ( |
| Generation ‘x’ and ‘y’ motivated by maintaining a personal life and need constant feedback and a mentor | Ritter ( |
| Generations ‘x’ and ‘y’ are more comfortable using technology and prefer communication digitally than face-to-face or personal interactions | Hannay ( |
| Do not expect or show loyalty in the workplace which shows some of the unique features of these generations | Park & Gursoy ( |
Fig. 1Conceptual model. (
Source: Author’s Own)
Predictive analysis of generations X and Y using descriptive analysis
| Frequency | Percentage | |
|---|---|---|
| 0 = Retain | 149 | 50.2 |
| 1 = Leave | 148 | 49.8 |
| Total | 297 | 100.0 |
Predictive analysis of generations X and Y using Binary Logistic Regression. (
Source: SPSS Binary Logistic Regression Test Output)
| Leave or retention | Percentage correct | ||
|---|---|---|---|
| Leave | Retention | ||
| Leave retention | 86 | 63 | 57.7 |
| Overall percentage | 48 | 100 | 67.6 |
| 62.6 | |||
aThe cut value is .500
Predictive analysis of generations X and Y using neural network analysis. (
Source: SPSS Neural Network Test Output)
| Training | Cross Entropy Error | 51.033 |
|---|---|---|
| Percent Incorrect Predictions | 8.4% | |
| Stopping Rule Used | 1 consecutive step(s) with no decrease in errora | |
| Training Time | 0:00:00.22 | |
| Testing | Cross entropy error | 22.167 |
| Percent incorrect predictions | 8.8% |
Dependent variable: Leave_or_Retention
aError computations are based on the testing sample
Predictive analysis of generations X and Y using neural network analysis. (
Source: SPSS Neural Network Test Output)
| Sample | Observed | Predicted | ||
|---|---|---|---|---|
| .00 | 1.00 | Percent correct | ||
| Training | .00 | 84 | 15 | 84.8% |
| 1.00 | 2 | 102 | 98.1% | |
| Overall Percentage | 42.4% | 57.6% | 91.6% | |
| Testing | .00 | 36 | 6 | 85.7% |
| 1.00 | 1 | 37 | 97.4% | |
| Overall Percentage | 46.3% | 53.8% | 91.3% | |
Dependent variable: Leave_or_Retention