A Relational Perspective on Turnover: Examining Affective, Continuance, and Normative Predictors Bambang Setiono1, Christian Haposan Pangaribuan2, Rith Analin Osok3 Faculty of Business, Sampoerna University, Jalan Raya Pasar Minggu 16, Jakarta, Indonesia 1
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Abstract High rate for employee turnover intention may lead to significant expenses to an organization, including direct costs of replacing an employee and indirect cost related to loss of experience and lowered productivity. This study investigates the influence of organizational commitment toward the employee turnover. Method used in this research is quantitative approach. Primary data were obtained by distributing questionnaires to 100 employees of a state-owned electricity corporation in Jakarta, Indonesia. Multiple linear regression shows that all three components of organizational commitment, i.e. affective, normative and continuance, are having a significant influence towards employee turnover intention. Keywords: organizational commitment, affective commitment, continuance commitment, normative commitment, job satisfaction, turnover intention
1. INTRODUCTION High employee turnover rate has increasingly been an issue, not just in developed countries but also in developing countries. According to International Labour Organization (2016), the youth unemployment rate in Indonesia stood at 17.8%, while the average youth unemployment rate for South-Eastern Asia was 13.1%. Therefore, unemployment in Indonesia was considerably higher than the regional average. The youth-to-adult unemployment ratio for Eastern Asia was 3.2, while for South-Eastern Asia it was 5.1 (International Labour Organization, 2016). Additionally, according to the Indonesia economic forecast, employee turnover in Indonesia in 2017 approximately reached 8.4 percent. This problem could raise a question why this situation could occur (Prahadi, 2015). Egan, Yang, and Bartlett, (2004) noted decreases in turnover led to increases in organizational performance and a reduction in costs associated with losses of firm and job-specific knowledge, hiring, and retraining of replacement employees. Consistent with a study written by Mitchell, Holtom, & Lee (2001), when employees leave the organization, it costs the organization time and money to replace them, the total cost of which sometimes range from 90% to 200% of the annual salary for the position advertised. According to Harrie (2002), the costs of employee turnover involve advertising expenses, headhunting fees, resource management expenses, loss of time and efficiency, work imbalance, and employee training and development expenses for new joiners. Previous study found that organizational commitment were studied as they have been the most influential predictors of employee turnover (Harun, Salleh, Memon, Baharom & Abdullah, 2014). In determining the organizational commitment, there are three
indicators that can be tested, i.e. affective commitment, normative commitment, and continue commitment. For this reason, this study would like to analyze the influence of organizational commitment towards employee turnover intention in one company. The reason why the company has been selected to be the sample of researcher study is because as discovered in the Table 1 that the employee turnover intention was exceptionally high and should have been a serious concern for the company. In January, employee turnover rate reached 2.5% and in March, employee turnover rate decreased to 1.05%. However, the situation changed in May, June and July because of the increase to 3.66%, 6.35% and 6.52%, respectively. Table 1. Employee Turnover Data (2018) Month
Total # of Employees
Employee Turnover
Percentage of Turnover (%)
New Hire
Jan Feb Mar Apr
200 195 190 189
5 7 2 5
2.50 3.59 1.05 2.64
0 2 1 7
1.03 0.53 3.70
May Jun
191 189
7 12
3.66 6.35
5 7
2.62 3.70
10
5.43
Jul 184 12 6.52 Source: Data from State-Owned Electricity Corp. 2018
Percentage of New Hire (%)
According to Table 1, the researchers argued that there is a problem with high employee turnover intention in the state-owned electricity company which may negatively influenced to the employee productivity. Turnover intention may lead to loss of experienced and trained employees. Possible causes of this problem are lack of organizational commitment. Thus, referring to this problem, a study that investigates the influence of organizational commitment towards employee turnover intention by quantitative method is highly needed to test the factors used. 2. LITERATURE REVIEW 2.1. Organizational Commitment Organizational commitment is an important research topic and has both practical and theoretical implications Levy (2003) defined organizational commitment as the strength of an individual’s identification with, and involvement in the organization. Furthermore, Luthans (2008) stated organizational commitment is a strong desire to stay afloat as a member of the organization, the desire to try according to the wishes of the organization, certain beliefs and acceptance of the values and goals of the organization. Meyer, Allen and Smith (1993) initially viewed organizational commitment as twodimensional, i.e. affective and continuance. First, they defined affective commitment as “positive feelings of identification with, attachment to and involvement in the work organization.” Affective commitment comes from the emotional attachment from employees to the organization (Luthans,
2008). So, employees with strong affective commitment will be actively involved in the organization and enjoys their belongingness in the organization. Continuance commitment was viewed as “the extent which employees feel committed to their organization by virtue of the costs that they feel are associated with leaving” (Allen & Meyer, 1990). Employees who have high normative commitment will stay in an organization because they are supposed to do that (ought to). The third dimension, normative commitment, was defined as “the employee’s feelings of obligation to remain with the organization” (Meyer, Allen & Smith, 1993). Rational commitments relating to commitment based on the perceptions of employees for losses will be obtained if he does not continue his job in the organization (Luthans, 2008). Therefore, highly-committed employees will opt to stay in an organization because they do require (need to). Consequently, the concept organizational commitment is described as a tri-dimensional concept, characterized by the affective, continuance and normative dimensions (Meyer, Allen & Smith, 1991). Company or organization in competitive environment often expected to have better performance to achieve organization goal, often disturbed by employees’ turnover intention. High turnover intention in one company will give negative impact on the company by creating unstable working condition and increase the cost of recruiting new employee. In this case, organization have to have good commitment to increase employees work motivation. Good organizational commitment will decrease turnover intention in a company or organization (Nawab and Bhatti, 2011). As such, organizational commitment is considered an important employee quality for organizations as it is indicative of a more stable, engaged and higher performing employee (Perryer, Jordan, Firns & Travaglione, 2010). 2.2. Turnover Intention Turnover intent has been defined as an individual’s voluntary or involuntary withdrawal to depart from an organization (Robbins & Judge, 2007). According to the first type, employees might quit the organization intentionally because of the difficult work environment or they may have some other job offers. On the other hand in involuntary turnover organization terminates the individual because of his inability. Employee voluntary turnover remains a critical issue for managements because of its negative implications for organizations. Intention to leave is referred to as a worker’s intention to leave the present organization (Cho, Johanson & Guchait, 2009). This terminology is identical with the term turnover intention. Intention to leave is considered a conscious and deliberate desire to leave an organization within the near future and considered the last part of a sequence in the withdrawal cognition process (Mobley et al., 1978). Previously it has been found that turnover intention is the stronger and immediate predictor of actual turnover (Jang and George, 2012). Thus, it is important to investigate the triggering factors that lead the employees to make attempt to quit the company. The following model depicts the relationship among the independent and dependent variables to form the theoretical framework (Figure 1).
Figure 1. Research Framework
2.3. Hypothesis Development Structural model in Figure 1 proposes that affective commitment is negatively related to turnover intention. Previous research has shown that commitment is negatively related to turnover. Mehmood et al. (2016) studied that affective commitment is negatively related to turnover intention among front desk staff in banking organizations of Pakistan. According to Tarigan and Ariani (2015), affective commitment has negative impact on intention to leave in manufacturing companies. The findings by Kalidass and Bahron (2015) prove that affective commitment is negatively related to turnover intention in three-star hotels in Malaysia. This is similar to the result of the research by Mardiana et al. (2012) on nurses at private hospitals in Indonesia. However, Saporna and Claveria (2013) found that there is no relationship between affective commitment and turnover intentions of low-cost hotel employees in the Philippines. Similarly, a research done by Tnay et al. (2013) indicated that affective commitment has no significant relationship with turnover of the employees. Given the literature reviewed, it can be hypothesized that: H1: Affective commitment is negatively related to turnover intention. Structural model in Figure 1 proposes that continuance commitment is negatively related to turnover intention. According to Tarigan and Ariani (2015), continuance commitment has negative impact on intention to leave in manufacturing companies. The findings by Kalidass and Bahron (2015) prove that continuance commitment is negatively related to turnover intention in three-star hotels in Malaysia. This is similar to the result of the research by Mardiana et al. (2012) on nurses at private hospitals in Indonesia. Mensah & Kosi (2016) observed that continuance commitment had significant contributions to the prediction of turnover intentions on lab scientists in Ghana. Yet, Saporna and Claveria (2013) discovered that there is no association between continuance commitment and turnover intentions of low-cost hotel employees in the Philippines. Likewise, Tnay et al.’s (2013) study found that there is no relationship between continuance commitment and employee turnover. Based on the discussions above, we can hypothesize: H2: Continuance commitment is negatively related to turnover intention. Structural model in Figure 1 proposes that normative commitment is negatively related to turnover intention. According to Tarigan and Ariani (2015), normative commitment has negative impact on intention to leave in manufacturing companies. The findings by Kalidass and Bahron (2015) prove that normative commitment is negatively related to turnover intention in three-star
hotels in Malaysia. This is similar to the result of the research by Mardiana et al. (2012) on nurses at private hospitals in Indonesia. Mensah and Kosi (2016) also found a significant negative relationship between normative commitment and turnover intentions on lab scientists in Ghana implying that high normative commitment leads to less turnover intentions. Still, Saporna and Claveria (2013) found that normative commitment does not affect turnover intentions of low-cost hotel employees in the Philippines. Also, Tnay et al. (2013) concluded in their study that normative commitment does not contribute to turnover intention in organization. Considering the previous research evidence, we can hypothesize that: H3: Normative commitment is negatively related to turnover intention. 3. RESEARCH METHODS In this research, a survey questionnaire was designed according to the objective of the study, and it was used to gather accurate and less bias data. The questionnaire involved comprised of 3 sections whereby it contained the demographic characteristics of the respondents on the first section, factors of organizational commitment on the second, and factors of turnover on the last. The last two sections were measured using a four-level Likert-scale, ranging from (1) “strongly disagree” to (4) “strongly agree.” The test of validity uses Pearson correlation. The value of the correlation is then compared to the critical value. The instruments are valid when the value of the correlation from the research is bigger than the critical value. Result of validity test of the instrument consisting 14 items exceeded the lower limit of correlation coefficient of 0.6. Because the instruments have high validity, it proves that the data collected are valid. The test of reliability was done using Cronbach’s alpha. The conclusion is that all item explaining organizational commitment (such as affective, continuance and normative) is reliable because all alpha of the variables exceeded the lower limit of Cronbach’s alpha standard of > 0.60. The alpha coefficient for affective commitment sample item shows Cronbach’s Alpha of 0.68, continuance commitment with 0.82, normative commitment is 0.62, and employee turnover intention with 0.72. This means that each of the variables exceeded the minimum standard of reliability and hence, can be relied on. After conducting validity and reliability test among the items of the questionnaires, we conducted a test of multicollinearity and the value shows through variance inflation factors (VIF). So, if VIF value < 10 with coefficient of tolerance > 0.1 or on the contrary, it means that there is no multicollinearity between independent variables (Hair et al., 2010). Table 2 shows that all coefficient of VIF is smaller than 10 and all coefficient of tolerance is bigger than 0.1. This means that there is no multicollinearity between all independent variables.
Table 2. The Result of Multicollinearity Test Independent Variable
Collinearity Tolerance
Collinearity VIF
Affective Commitment Continuance Commitment Normative Commitment
0.93 0.94 0.92
1.07 1.06 1.08
A total of 100 questionnaires were distributed among the management and nonmanagement employees, and 100% of them were successfully collected from the studied organization. This research took place at the state-owned electricity company from June until July 2018, including the research preparation, data collection, data processing and data analysis. The company strictly allowed the researchers to distribute the exact aforementioned number of questionnaires. Employees were not asked to provide their names nor employee identification numbers. Participants were informed that their responses were known only by the researchers and would be kept confidential. In analyzing the available data, descriptive and inferential statistics were used by utilizing the Statistical Package for Social Science (SPSS) version 23.0. As mentioned earlier, descriptive statistics were used to analyze the respondents’ demographic data, i.e. gender, age, educational level, job department/division at work, and years of service working in the organization. The data was presented via frequency and percentage. On the other hand, inferential statistics were used to determine the relationship between the independent and dependent variables. The research hypotheses were analyzed using Pearson’s Correlation Coefficient, and the signs indicate the strength of the relationship or the degree of association between the two variables. The independent variables for this study include organizational commitment, which consisted of affective commitment, continuance commitment, and normative commitment. On the other hand, the dependent variable was the employees’ turnover intention. 4. RESULTS AND DISCUSSION Table 3 shows the descriptive statistics of the respondents’ demographic characteristics stated on the first section of the questionnaire. From the total number of the 100 respondents, 86% respondents are male and 14% are female. As for the frequency and percentage of the respondents’ age, most of the respondents fall in the age category of 18 to 24 years old (72%). For education background, total number of respondents with a college degree is 62.4%. The length of service of all the respondents, mostly had served the company for 1 to 2 years (69%), while the second highest is 3 to 5 years (25%). Finally, in the job division category, most respondents were in the distribution & service division (37%), and technical operation came second highest (28%). Table 3. Respondents’ Demographic Characteristics Demographic Factor Gender
Age
Education
Job Division
Characteristic
Percentage (%)
Male
86
Female
14
18-24
72
25-34
26
35 or older
2
College
83
Undergrad
16
Grad School
1
Distribution & Service
37
Technical Operations
28
Information Technology
12
Tenure
Human Resources
10
Sales & Marketing
7
Finance/Accounting
6
Less than 1 year
2
1-2 years
69
3-5 years
25
More than 5 years
4
The result of the influence of affective, continuance and normative commitments on turnover intentions of state-owned electricity corporation employees is summarized in Table 4. The data analysis shows that all the hypotheses are accepted. Turnover intention has a negative significant relationship with affective, continuance and normative commitments (r=0.50, p
