The chapter presented data analysis and revealed the finding of each hypothesis in this study. First, descriptive statistics analysis showed the demographic information of respondents, afterward, the result of correlation analysis among learning intention (LI), career adaptability (CA) and employee retention (ER). Structure Equation Modeling (SEM) is employed to test hypothesizes by path analysis.
Results of Demographic Analysis
The demographic information in descriptive statistics was collected from 349 workers of Gen Y. The descriptive statistics was divided into 9 questions including gender, born year, position, employment, education level, industry of current company, tenure in the current, total working experience and the amount of companies that respondents have work for. The frequency and percentage of the demographic information are summarized in Table 4.1.
Gender
Among the 349 participants, there were 136 male respondents (39%) and 213 female respondents (61%). In this study, most of the respondents were female.
Born Year
Among the 349 participants, 132 respondents (37.8%) were born between 1990~1993, 136 respondents (39%) were born between 1985~1989, 81 respondents (23.2%) respondents were born between 1980~1984.
Position
Among the 349 respondents, 63 respondents (18.1%) are management position, 286 respondents (81.9%) are non-management.
Employment
Among the 349 participants, 330 respondents (94.6%) employed as permanent, 19 respondents (5.4%) employed as contingent.
Educational Level
Among the 349 participants, 7 respondents (2%) have graduated from high school or below, 253 respondents (72.5%) have bachelor or college level, 89 respondents (25.5%) have masters degree or above.
Industry
Among 349 participants, 28 respondents (8%) worked in education field, 25 respondents (7.2%) worked in finance and insurance field, 68 respondents (19.5%) worked in manufacture field, 32 respondents (9.2%) worked in public administration field, 135 respondents (38.7) worked in service field, 56 respondents (16%) worked in technology field, others industry were occupy 1.4% of respondents.
Discussion
Based on the descriptive analysis, most of the respondents are female, aged 22-31 and have a bachelor degree. Besides, the majority of employment and position is permanent and non-management. The profile of Gen Y in workplace did represent the characteristics of the age group.
Table 4.1.
Descriptive Statistics on Sample Characteristics
Item Frequency Percentage Item Frequency Percentage
1. Gender 5. Educational Level
Male 136 39%
One-Way ANOVA
Regarding to the educational level of learning intention of Gen Y, this paper performed one-way ANOVA to answer the third research question, “Are there significant differences between educational level on the learning intention of Gen Y? ”
As the descriptive information stated as Table 4.2, the mean and standard deviation of each educational level on learning intention, high school or below (M=4.14, S.D=.445), bachelor or college level (M=3.9, S.D=.595) and masters degree or above (M=3.97, S.D=.607) is insignificant. In conclusion, no matter what educational level does, Gen Y’s learning intention has no discrepancy (Table 4.3.) The result is unexpected because according Kyndt et al. (2009), the level of education, seniority are of great relevance in employee retention.
The current did prove that there is no difference on the level of employee retention toward educational level.
Table 4.2.
Descriptive of Educational Level of Learning Intention
N Mean Std. Deviation
High School or below 7 4.14 .445
Bachelor or College level 253 3.90 .595
Masters Degree or above 89 3.97 .607
Total 349 3.93 .596
T-Test
The t-test is preformed to answer the second research question, “Are there significant differences between male and female on learning intention and employee retention of Gen Y?”
According the statistical finding (Table 4.4.), the value of significant in Levene’s Test for Equality of learning intention and employee retention are all above .05, then viewing equal variances assumed of learning intention, and employee retention, the value of significant all above .05, means male or female have no difference between each other toward learning intention and employee retention.
Recall the finding of Sanders et al. (2011), female had higher learning intentions than male. Elman and O’Rand (2002) further investigate the willingness to retrain in order to increase job insecurity. They found that female have more willingness to retrain because they are the group that have more risky of losing its job. On the contrary, Greenhalgh & Mavrotas (1994) and Zoogah (2010) did not find gender differences of learning intention. Based on the finding of current research, it’s clear that gender has no significance discrepancy on learning intention, research presume the reason is because cohort effect expose Gen Y at a same Table 4.3.
One-Way ANOVA Analysis of Educational Level on Learning Intention
Sum of Squares df Mean Square F Sig.
Between Groups .612 2 .306 .861 .424
Within Groups 122.843 346 .355
Total 123.455 348
external environment which have speedy information, thus the difference between male and female on learning intention is not obvious, only depends on individual case.
Regarding the gender differences of employee retention, the current research have a same result with Kyndt et al. (2009), the gender have no significant differences on employee retention. Researcher presumes the reason is because respondent belongs to kinds of industry that have various job characteristics, the level of employee retention have no direct influence on Gen Y.
Table 4.4.
Summery of t-Test
Levene's Test for Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Learning Intention
Equal variances
assumed .46 .49 -.88 347 .377
Equal variances
not assumed -.88 282 .38
Employee Retention
Equal variances
assumed .057 .81 1.28 347 .201
Equal variances
not assumed 1.28 286 .201
Relationships of LI, ER and CA Correlation Analysis
Correlation analysis was conducted to understand the relationship between two variables.
Table 4.5. present means, standard deviations, and correlation among learning intention, career adaptability, and employee retention. The major variables in the current study showed significant correlations.
Through correlation analysis, the results showed the finding both expected and unexpected result. In the finding, it is expected to found out that learning intention is positive correlated to employee retention. (r=.258, p<.01), which means those with higher learning intention have higher employee retention, in other words, people who are willing and ready to undertake a concrete action in training or education, have higher intention to stay in an organization.
In addition, correlation between learning intention and career adaptability represent people who are more willing to devote themselves in training or education physically, the more tactful to construct their career.
According to the finding, learning intention is positive correlated to career adaptability (r=.449, p<.01), which means people who are proactive to participant in learning activities or training, the more possibility to be tactful to build their career path. Furthermore, within the four dimensions of career adaptability, the finding (Table 4.3.) revealed that career curiosity have highest correlated to learning intention (r=.453, p<.01), meaning people who are initially exploring information and proactive to take part in training courses, the more motivation to experience different role by seeking alternative possible selves and scenarios, thus, the strong interest in learning enable people to browse the environment and learn solid
knowledge in certain situation.
Regarding the relationship between career adaptability and employee retention, the finding revealed the CA is positive correlated to ER (r=.139, *p<.01), especially on career confidence (r=.162, p<.01). Which means that if people possess certain ability and confident to fulfill task or assignment, they have higher intention to stay longer in an organization.
An unexpected result is given by the insignificant relationships among demographics and variables. As the finding, gender, position, educational level, and employment of Gen Y have weak correlation among variables, which means there is no difference between male and female on LI, CA and ER, as well as position, employment, educational level, and industry. To denote this finding, researcher presumed it’s because Gen Y have diverse concept toward LI, CA and ER. Compare to the previous generation, Yers, break the concept boundary on gender difference. Furthermore, the answer of each category on employment, educational level and industry is not equally distributed, it might cause the result insignificant.
This research adopts this situation into a limitation.
Table 4.5.
Mean, Standard Deviations and Correlations of LI, ER, CA
Mean S.D 1 2 3
1. LI 3.93 .596 1
2. ER 3.05 .895 .258** 1
3. CA 3.58 .745 .449** .139** 1
**p<.01.
LI= Learning Intention; ER= Employee Retention; CA= Career Adaptability.
Structural Equation Model (SEM)
Structural Equation Model is employed to test the established hypothesis in this research.
All items in SEM were underwent CFA respectively. The modified items for the research was performed to AMOS, afterward, the path diagram was produced.
As Table 4.6. presented, the model fit is considered acceptable (X2/df=2.47<3, RMSEA=.065<.08). Furthermore, according to Doll, Xia, Torkzadeh (1994) suggested, if the estimated parameters of the model are complex, GFI and AGFI can relaxed to 0.8, thus, these two indexes are acceptable (GFI=.849>.8, AGFI=.0822>.8)
Table 4.6.
Model Fit Summary of Structural Equation Model
Model X2 df p X2/df RMR GFI AGFI RMSEA
Default Model 849.65 344 .000 2.470 .103 .849 .822 .065
From SEM, standardized regression weight (beta coefficient) was examined to reveal the path analysis. As Table 4.7. depicted, the beta coefficient of hypothesis were examined.
The relationship between learning intention and career adaptability (β=.476, p<.001), learning intention to employee retention (β=.622, p<.001) are all positively significant.
However, the beta coefficient showed that career adaptability is negative influence to employee retention (β=-.178, p<.001).
Table 4.7.
Standard Coefficients of Structural Equation Modeling
Path Standardized Coefficients
LI → CA .476 ***
LI → ER .622 ***
CA → ER -.178***
Notes. ***p<.001.
Afterward, since Table 4.7. only describe the direct effects among variables, Table 4.8.
detailed both direct and indirect path analysis. It depicted standardized direct, indirect, and total effect of learning intention, career adaptability and employee retention.
Table 4.8.
Result from Structural Equation Modeling
Model
β
Learning Intention Career Adaptability Direct
Career Adaptability .476
Employee Retention .622 -.178
Indirect
Career Adaptability .476
Employee Retention -.085
Total
Career Adaptability .476
Employee Retention .537 -.178
Discussion
Based on the result of the statistics, we can learn that the learning intention and career adaptability is surely influence to the level of employee retention. In other words, individual who are more willing to take action of learning activities, the more possibility that have higher competency of career adaptability; in the same way, the level of employee retention increased by learning intention increased, employee who participates learning activities continually, means they believe the training can benefit to their career path in the current, thus, learning intention can considered as a predictor of employee retention.
However, the negative influence on career adaptability and employee retention provides an unexpected result in this research. According to Fleisher (2014), career adaptability can be denoted to the concept of career competency that make people knowing-why, knowing how, and knowing-whom to developing one’s career, thus, an individual who have higher competency of career adaptability may lead to a lower employee retention because of constructing a broader career path outside the current company. That is to say, employee retention decreased because of people have a high learning intention plus higher career, concern about their career path, exploring career information, seeking alternative possible selves and alternative scenarios, controlling and shaping themselves in performing vocational tasks, and last, and feel confidence in performing tasks successfully.
According to the result, when count in career adaptability into consideration, the mediating effect makes learning intention weaken the influences on employee retention. In other words, it’s clearly that learning intention is a factor that enables people to have higher level of retention but the higher competency of career adaptability also eliminates the strength of the influences on learning intention and employee retention. In conclusion, career
adaptability served as a two-edged sword. On the one hand, it enhanced career develop competency, but on the other hand it decreased employee retention, both positive and negative influence.
Summary of Analysis Result
In the previous section, T-test, One-Way ANOVA, Person Correlation Analysis and SEM were performed and answer all of the research question and hypothesis. From T-test and One-Way ANOVA can learn that there is no difference between gender and educational level among learning intention and employee retention (research question 2 and 3). Afterward, Person Correlation Analysis revealed learning intention has highly correlated to employee retention and career adaptability of Gen Y. However, career adaptability and employee retention is less significant. Furthermore, after conducting the path analysis and observed the beta coefficient in SEM, learning intention is positive influences career adaptability and employee retention, but career adaptability is negative influences employee retention.
Hypothesis testing resulting summary listed as Table 4.10.
Table 4.10.
Hypothesis Testing Result Summary
Hypothesis Result
H1
Learning intention positive influences career adaptability of Gen Y.
Supported
H2
Learning intention positive influences employee retention of Gen Y.
Supported
H3
Career Adaptability positive influences employee retention of Gen Y.
Not supported