This chapter is divided into the research framework, research hypotheses, sample, data collection, pilot test, measurement, control variables and data analysis.
Research Framework
Based on the research purposes, and after reviewing the relevant literature, this study explored the relationship between career plateau and organizational commitment, as well as the moderating effects of transactional and transformational leaderships on the above relationship. As a result, the research framework in Figure 3.1. was created.
Figure 3.1. Research framework
Research Hypotheses
Based on the framework presented in Figure 3.1., the following hypotheses are proposed:
Hypothesis 1a: Career plateau has a negative relationship with affective commitment.
Career Plateau
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Hypothesis 1b: Career plateau has a negative relationship with normative commitment.
Hypothesis 1c: Career plateau has a positive relationship with continuance commitment.
Hypothesis 2a: Transformational leadership will weaken the negative relationship between career plateau and affective commitment. Specifically, transformational leadership has a stronger moderating effect on career plateau – affective commitment than transactional leadership.
Hypothesis 2b: Transformational leadership will weaken the negative relationship between career plateau and normative commitment. Specifically, transformational leadership has a stronger moderating effect on career plateau – normative commitment than transactional leadership.
Hypothesis 2c: Transformational leadership will strengthen the positive relationship between career plateau and continuance commitment. Specifically, transformational leadership has a stronger moderating effect on career plateau – continuance commitment than transactional leadership.
Sample
The target sample in this study consisted of full-time employees Belize. Belize currently faces economic challenges; therefore, this population was chosen because of interest to examine a population that is threatened with changes in their career and/or organization. The sample had to be full time employees, working for at least one year with their organization. An equal sample was obtained from both public and private sectors.
However, only public servants working within the ministries and departments under the management of the Ministry of Labor, Local Government and Rural Development, Public Service, Energy and Public Utilities were considered. For the private sector, employees from all the different industries within Belize were considered.
Pilot Test
A pilot test was conducted prior to the data collection. The purpose was to determine the effectiveness and suitability of the terms and structure of the questions for full-time employees in Belize. 40 responses were used for the pilot test. As well, the pilot test was to determine the reliability and validity of the instrument. The acceptable Cronbach’s alpha for reliability analysis is ≥0.7 (Nunnally, 1978). For the pilot test, Cronbach’s alpha for career plateau was 0.80, for transformational leadership was 0.96, while transactional leadership had
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0.69. The Cronbach’s alpha for affective commitment was 0.90, for normative commitment was 0.77 and continuance commitment was 0.77.
After the pilot study, no changes were made or errors corrected. Therefore, the results of the pilot study were included in the final data analysis.
Data Collection Process
Belize’s labor force totaled 164, 935 by April 2017 (Statistical Institute of Belize, 2017b). Due to the distribution of the labor force throughout the country, and the difficulty in personally accessing a representative sample from each district, convenient and snowball sampling were used. A quantitative research approach was adopted for this study; therefore, data was gathered using online questionnaire. The main approach for conducting data collection was personally contacting individuals who meet the sample criteria, by sending them an email with the link to the online questionnaire. They were then asked to distribute the questionnaire to their friends, family and co-workers who also met the criteria. In addition, the online questionnaire was posted on social media, such as Facebook. The questionnaire had a cover letter, indicating the purpose of the research, reassuring confidentiality and the researcher’s contact information in case of any questions. A total of 247 valid questionnaires were filled. The questionnaire consisted of 66 variable related items, and 10 personal and demographic items.
Measurement
The measurement in this study comprised of three parts: career plateau, organizational commitment, leadership and demographical information. These measures are described below:
Career Plateau
The instrument for this variable was adopted from Milliman (1992). It measures the two constructs of career plateau: structural and job content plateau. The measurement consisted of 12 items (6 for each construct). A seven-point Likert scale, ranging from 1 = Strongly Disagree to 7 = Strongly Agree, response format was used for this variable. In his study, Milliman (1992) reported a Cronbach’s Alpha of 0.87 for career plateau. The Cronbach’s alpha for this study was 0.78, as shown in Table 4.2.
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Sample items for structural plateau included: “My job tasks and activities have become routine for me”; and “My job requires me to continually extend my abilities and knowledge.” As for job content plateau, items include: “I am unlikely to obtain a much higher job title”; and, “I expect to be promoted frequently in the future.”
Organizational Commitment
Because this study focused on the three dimensions of organizational commitment, the instrument adopted for measuring this variable was adopted from Meyer, Allen, and Smith (1993). This measurement included three dimensions: affective, normative and continuance commitment. It contains a total of 18 items with 6 items for each dimension.
These were measured on a five-point Likert scale (1 = Strongly Disagree; 5 = Strongly Agree). The reported Cronbach’s alpha in Meyer et al. (1993) for affective commitment was 0.85, normative commitment was 0.76 and continuance commitment was 0.74. In this study, the Cronbach’s alpha for affective commitment was 0.89, normative commitment was 0.84 and continuance commitment was 0.69.
Sample questions were: “This organization has a great deal of personal meaning to me”; “I owe a great deal to my organization”; and “I feel that I have few little options to consider leaving this organization” for affective, normative and continuance commitment, respectively.
Transactional Leadership
This variable will be measured using the Multifactor Leadership Questionnaire (MLQ-5X) proposed by Bass and Avolio (1990). The instrument consisted of 16-items for transactional leadership, with 4-items for each dimension. Responses were collected using a five-point Likert scale ranging from 1 = Strongly Disagree to 5 = Strongly Agree. Some of the items included were: (contingent reward) “My direct supervisor provides me with assistance in exchange for my efforts”; (active management-by-exception) “My direct supervisor keeps track of all mistakes”; (laissez-faire) “My direct supervisor is absent when needed”; (passive management-by-exception) “My direct supervisor fails to interfere until problems become serious.”
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Transformational Leadership
This variable was also measured using the MLQ-5X questionnaire by Bass and Avolio (1990). The instrument consisted of 20-items for this variable, with 4-items for each of the dimensions. Responses to the items were measured on a seven-point Likert scale ranging from 1 = Strongly Disagree to 7 = Strongly Agree. The cumulative Cronbach’s alpha reported for this measurement was 0.85. This study had a cumulative Cronbach’s alpha of 0.83.
Examples of items included: (individualized consideration) “My supervisor spends time teaching and coaching me”; (intellectual stimulation) “My supervisor seeks differing perspectives when solving problems”; (inspirational motivation) “My direct supervisor speaks enthusiastically about what needs to be accomplished”; (idealized influence attributes)
“My supervisor acts in ways that builds his/her respect”; (idealized influence behaviors) “My supervisor talks about his/her most important values and beliefs.”
Control Variables
Some of the control variables which might have influenced organizational commitment were identified. These are listed and described below:
Gender
A study by Khan, Ziauddin, and Ramay (2010) showed that the female participants were more committed than the male participants. As well, Jung and Tak (2008), in their study of career plateau and organizational commitment identified gender as a control variable.
Age
Khan et al. (2010) also indicated that participants aged 25 years have relatively low organizational commitment while those between 35 and 46 portrayed a relatively higher commitment. Moreover, Meyer et al. (2002) showed a positive correlation between the employees’ age and all three dimensions of organizational commitment. Hunt, Chonko, and Wood (1985) also supported that characteristics such as age have influence on organizational commitment.
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Tenure
Mathieu and Zajac (1990) have demonstrated that tenure is a potential predictor of organizational commitment. Other studies on career plateau and organizational commitment also demonstrated that job tenure positively correlates with organizational commitment (Chay et al., 1995; Jung & Tak, 2008).
Data Analysis
The responses collected from the online questionnaire were analyzed by IBM SPSS version 22.0. Other statistical techniques used to analyze the data collected included descriptive statistics, Pearson’s correlation analysis, confirmatory factor analysis and hierarchical regression analysis.
Descriptive Statistics
This type of analysis provided an overview of the characteristics of the participants in terms of frequency and percentages. Descriptive statistics in this study included background information such as gender, age, education level, job tenure, public/private sector and organizational structure position (hierarchical position). It also provided an idea of the respondents’ profile through the distribution pattern and percentage of demographic information. The frequency and percentage of these demographics are shown in Table 3.1.
Most of the participants were females (54.3%). As well, most of the sample were single (43.3%), and were aged between 26 to 30 years (39.7%). Almost 86% of participants had been working in their organization between 1 to 10 years. The Belize private sector employs 52.6% of them, while the public sector employs 47.4%. In addition, 54.3% of the population considered themselves as “professional staff” in the hierarchical structure of their organization.
25 Table 3.1.
Descriptive Statistics (n=247)
Item Frequency Percentage Item Frequency Percentage
Gender 26 – 30 1 0.4%
Female 134 54.3% More than 30 1 1.2%
Male 113 45.7%
Public Service
Age Agriculture, Fisheries… 13 5.3%
16 – 20 1 0.4% Economic Development 1 0.0%
Education Agriculture, Forestry… 11 4.5%
Ph.D. 0 0.0% Arts, Entertainment… 4 1.6%
Tenure Financial & Insurance 15 6.1%
1 – 5 103 41.7% Food Services 2 0.8%
26 Table 3.1. (continued)
Item Frequency Percentage Item Frequency Percentage
Mass Media 1 0.4% Hierarchical Position
Professional 11 4.5% Professional Staff 134 54.3%
Real Estate 0 0.0% Supervisory Level 72 29.1%
Transportation 3 1.2% Middle-Management 37 15.0%
Water 1 0.4% Top-Management 4 1.6%
Wholesale & Retail 9 3.6%
Other Industry 10 4.0%
Correlation and Reliability Analysis
The reliability and Pearson correlation analyses were conducted to ensure the reliability of the measurements and to examine the correlations among the variables. Table 3.2 presents the mean, standard deviation, and reliability for each variable and Pearson correlation coefficient among each variable. The acceptable Cronbach’s alpha is ≤ 0.7 (Nunally, 1978). The results show career plateau had a Cronbach’s alpha of 0.78, transactional leadership had a 0.72, transformational leadership had a 0.93, affective commitment had a 0.89, continuance commitment had a 0.69 and normative commitment had a 0.84.
The Pearson coefficient was used to examine the correlations on career plateau, organizational commitment and transactional and transformational leaderships. The Pearson correlation (r) was used to describe the strength and direction of the relationship between career plateau and organizational commitment as well as the moderating relationship of transactional and transformational leaderships. A high correlation meant there was a strong relationship between variables. The coefficient value ranges from -1.0 to +1.0. Should the coefficient value be greater than 0, it is indication that there is a positive relationship.
Otherwise, it indicates a negative relationship. When analyzing relationships, two variables are said to be correlated if change in one variable causes change in the other; the change can be in the same direction or reverse. As well, coefficient values r < 0.4 were considered low correlation. Also, coefficient values between r > 0.4 and r < 0.7 were considered medium, while high correlation are r > 0.7. The correlation values are what indicated the strength of the relationship between variables.
The results of the Pearson correlation analysis (Table 3.2.) showed that most of the major variables in this study had significant correlation coefficients. Career plateau had a
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negative, low correlation to affective (r = -.26, p < .001) and normative commitment (r = -.27, p < .001), while it had a low, positive correlation to continuance commitment (r = .34, p
< .001). At the same time, transformational leadership had a medium, positive correlation with affective and normative commitments (r = .49, r = .45, p < .001), while it had a low, negative correlation with continuance commitment (r = -.13, p < .05). As for transactional leadership, this variable had a low, negative correlation with affective (r = -.20, p < .01) and normative commitments (r = -.13, p < .05), while it had no significant relationship to continuance commitment.
28 Table 3.2.
Mean, Standard Deviations, Correlations, and Reliability (n=247)
Note. Cronbach’s Alpha are in boldface.
*p < .05, **p < .01, ***p < .001.
Mean S.D. 1 2 3 4 5 6 7 8 9
1 Gender .46 .50 1.00
2 Age 33.05 7.62 -.12 1.00
3 Tenure 7.20 5.04 .03 .52*** 1.00
4 Career Plateau 4.30 .84 -.13* .03 -.03 (.78)
5 Transformational Leadership 3.31 .59 .06 -.03 -.01 -.51*** (.93)
6 Transactional Leadership 2.74 .42 .17** -.09 .03 .07 -.24*** (.72)
7 Affective Commitment 3.40 .88 .01 .29*** .33*** -.26*** .49*** -.20** (.89)
8 Continuance Commitment 3.41 .70 -.04 .00 -.07 .34*** -.13* .05 -.11 (.69)
9 Normative Commitment 3.22 .76 .06 .17** .26*** -.27*** .45*** -.13* .71*** .07 (.84)
29 measurements using AMOS 22.0. The study had a total of 247 respondents. The number of observed variables for career plateau was 12, transactional leadership had 16, transformational leadership had 20, and organizational commitment had 12. To confirm the adequacy, three categories of fit indices of the CFA model were analyzed (Hair, Black, Babin, Anderson, & Tatham, 2010). These are the absolute fit indices, incremental fit indices, and parsimony fit indices.
According to Hair et al. (2010), three to four indices are enough to indicate “adequate evidence” in evaluating a good fit. These must include one absolute index, one incremental index, the chi-square (x2) value, and the associated degrees of freedom. The acceptable range for the incremental index (Bollen’s IFI) is < .90. The same applies for the non-normed fit index (TLI). The other index, chi-square, is the result of chi-square divided by degrees of freedom. This index is used to investigate whether distributions of categorical variables differ from one another (Marsh & Hocevar, 1985). The result of chi-square confirms the model fit.
The root mean square error of approximation (RMSEA) then indicates how well a model fits a population. The standardized root mean square residual (SRMR) indicates the average discrepancy between the correlations in the input matrix and the correlations which is predicted by the model. Lastly, the comparative fit index (CFI) assesses how well the estimated model fits relative to some alternative baseline model. A good model fit, therefore, will have a chi-square (x2) value of p < .05, CFI > .95, SRMR < .09, and SRMEA < .08 (Hair et al., 2010).
The results of the CFA for this study are displayed in Table 4.1. Examining the 12-item model of measurement for career plateau suggest that the model did not provide an adequate model fit. The CFA analysis produced a relative chi-square (x2) of 654.05 and a ratio of chi-square to degrees of freedom (x2/df) of 12.11, well above the acceptable range of a good model fit (Carmines & McIver, 1981). Other fit indices, as well, were significantly below the acceptable range; the RMSEA was 0.21; the CFI was 0.54; the NFI was 0.52; IFI