The Relationship between Job Satisfaction and Retention Intention of Cabin Crews in Taiwan

全文

(1)The Relationship between Job Satisfaction and Retention Intention of Cabin Crews in Taiwan. by Yi-Li Chen. A Thesis Submitted to the Graduate Faculty in Partial Fulfillment of the Requirements for the Degree of MASTER OF BUSINESS ADMINISTRATION Major: International Human Resources Development. Advisor: Chih-Chien Steven Lai, Ph.D.. National Taiwan Normal University Taipei, Taiwan February 2018.

(2) ACKNOWLEDGEMENT There are too many people to express my appreciation one by one. It is not possible to face all challenges without everyone’s assistance. Writing the thesis is like a long-term journey. The traveler would confront unexpected accidents and must try to figure out how to solve the problems. In this long-term trip, I would like to firstly thank Dr. Lai, my considerate advisor of Graduate Institute of International Human Resource Development, for his inspiring guidance and instruction throughout my research. For the reminding, helpful suggestions and other supports, I want to thank my committees, Dr. Chang and Dr. Tsai. In addition, my gratitude is extended to my classmates for their encouragement and friendly aid during my study. Furthermore, I also greatly appreciate data collection from those who did not know me but help to fill and transfer the questionnaires without any rewards. The last but not the least, I would like to extend my heartfelt thanks to my family, especially my mom. With their support and supervision, I am willing to encounter these tough difficulties. Thank you all to let me complete this impossible mission..

(3) ABSTRACT Retention intention is a long-term discussing issue for human resources to innovate strategies for better organizations’ development and working environment. Nowadays, due to arising turnover rate, especially in aviation industry, what kind of factor affecting employees to retain the most was discussed. By literature review, job satisfaction was one of the major factors to impact on retention intention, including nine dimensions, pay, promotion, supervision, fringe benefits, contingent rewards, operating procedures, coworkers, nature of work, and communication. To explore (1) current condition of overall job satisfaction for cabin crews in Taiwan airlines, (2) the relationship between each dimension of job satisfaction and retention intention, and (3) the interaction effect between each demographic variable and job satisfaction on retention intention, a questionnaire was developed and employed to collect the data from 226 respondents who have worked in Taiwan airlines as cabin crews. The SPSS Statistics Desktop version 22.0 were employed for data analysis after data collection and coding. The results indicate that (1) cabin crews have ambivalent perception of overall job satisfaction, (2) except promotion, other dimensions of job satisfaction have significant correlation with retention intention; among them, fringe benefits, coworkers, nature of work have significant relationship with retention intention, (3) there is no interaction effect between each demographic variable and job satisfaction on retention intention. Based on the results, recommendations are provided to future research and human resources development practical field in Taiwan airlines. Keywords: job satisfaction, retention intention, cabin crew. I.

(4) TABLE OF CONTENTS ACKNOWLEDGEMENT ABSTRACT .......................................................................................................... I TABLE OF CONTENTS ..................................................................................... II LIST OF TABLES ..............................................................................................IV LIST OF FIGURES ............................................................................................. V CHAPTER I INTRODUCTION ........................................................................ 1 Background and Motivation of the Research......................................................................... 1 Statement of the Research Problem ....................................................................................... 2 Significance of the Research .................................................................................................. 2 Research Purposes ................................................................................................................. 2 Research Questions ................................................................................................................ 3 Delimitation of the Research ................................................................................................. 3 Definitions of Key Terms ....................................................................................................... 3. CHAPTER II LITERATURE REVIEW ............................................................ 5 Retention Intention................................................................................................................. 5 Job Satisfaction ...................................................................................................................... 8 Relationship between Job Satisfaction and Retention Intention .......................................... 10. CHAPTER III RESEARCH DESIGN ............................................................. 15 Research Framework ........................................................................................................... 15 Research Method ................................................................................................................. 16 Measurement Design ........................................................................................................... 16 Research Samples ................................................................................................................ 18 Data Collection .................................................................................................................... 19 Data Analysis ....................................................................................................................... 19 Validity and Reliability of the Study .................................................................................... 20 Research Procedure .............................................................................................................. 23. CHAPTER IV RESULTS AND DISCUSSIONS ............................................ 25 Descriptive Analysis ............................................................................................................ 25 Relationship of JS and RI .................................................................................................... 27 Interaction Effects of Demographic Variables between JS and RI...................................... 31 Summary of Findings and Discussions ................................................................................ 34 II.

(5) CHAPTER V CONCLUSIONS AND RECOMMENDATIONS.................... 37 Conclusions .......................................................................................................................... 37 Limitations ........................................................................................................................... 37 Recommendations ................................................................................................................ 38. REFERENCES ................................................................................................... 40 APPENDIX QUESTIONNAIRE ....................................................................... 48. III.

(6) LIST OF TABLES Table 2.1. Factors Affecting Retention/Turnover Intention……………………………….……6 Table 2.2. The Reliability of JSS……………………………………………..……………….10 Table 3.1. Item Directions of JSS…………………………………………….……………….18 Table 3.2. Model Fit Indices Criteria and Results of 47 items………………………………..21 Table 3.3. The Description and Cronbach’s Alpha Value of Each Dimension of JSS……….23 Table 4.1. Descriptive Statistics on Sample Characteristics (N=226) …………….………….26 Table 4.2. Descriptive Statistics on Each Dimension of JS and RI (N=226) ….….………….27 Table 4.3. Correlation Matrix of Job Satisfaction and Retention Intention……………….….29 Table 4.4. Linear Regression for Each Dimension of JS and RI………………….….............30 Table 4.5. Result of Hierarchical Regression Analysis for JS on RI……….…….…...............31 Table 4.6. Result of Hierarchical Regression Analysis for Interaction between Age and JS on RI………………………………………………………...……………………......32 Table 4.7. Result of Hierarchical Regression Analysis for Interaction between EL and JS on RI…………………………………………………………...……………………..32 Table 4.8. Result of Hierarchical Regression Analysis for Interaction between Position and JS on RI………………………………………………….….......................................33 Table 4.9. Result of Hierarchical Regression Analysis for Interaction between Tenure and JS on RI…………………………………………………….………...........................33 Table 4.10. Hypotheses Testing Results Summary……………………...…………………...35. IV.

(7) LIST OF FIGURES Figure 3.1. Research framework………………………………………………………………........15 Figure 3.2. Research procedure……………………………………………………………………..24. V.

(8) CHAPTER I. INTRODUCTION. This chapter consists of background and motivation of the research, statement of the research problem, significance, purposes, questions, delimitation of the research, and definition of key terms.. Background and Motivation of the Research As developing vigorously in aviation industry, the needs of flight attendants increased, showing the significance of manpower distribution and efficient flight attendants’ management (Ching, 2014). However, based on the corporate social responsibility reports from Taiwan airlines, the data showed that turnover rate increased in recent years. According to Fang (2008), to work at airlines, cabin crews must accept high-pressured training and own considerably strong physical fitness. In addition, although both working time and rest time for cabin crews were made by express statutory provision, cabin crews could not be entitled to national holidays or take leaves freely. Owing to the nature of work, the pressure of physical health, interpersonal relationship, family and work in terms of female cabin crews are usually higher than usual (Association of Wage-Earners, 2000; Fang, 2008). In this circumstance, it enhances the uncertainty to keep working and possibility of resignation. On Jane 24th 2016, it was the first time in the history of Taiwan that flight attendants had taken industrial action. According to Shan (2016, June 24), the Taipei News reported that China Airlines (CAL) flight attendants went on strike at midnight due to low allowances and long working hours. This event showed conspicuous dissatisfaction of work toward cabin crews and aroused the acquisitiveness to probe into main factors affecting retention intention. Through reviewing qualitative and quantitative researches, various scholars focusing on different industries (include academia, aviation, construction, finance, hospitality, manufacture and technology) indicated that numerous factors would influence retention intention or turnover intention. Some factors are related to personal background, such as gender, age and marital status, others are personal perception in terms of different items, e.g., organizational commitment, nature of work, pay/salary, promotion, job satisfaction, work-life balance and employee motivation et cetera. Among factors above, as a result of multiple aspects of job satisfaction, it was regarded as a crucial factor affecting retention intention. On the other hand, although gender was viewed as one of the affecting factors in previous researches, it was seldom to be examined the relationship with job satisfaction or retention intention due to uneven gender distribution of cabin crews. Moreover, since demographic factors were infrequently utilized to test the interaction effect with job satisfaction on retention 1.

(9) intention in aviation industry, this would be the motivation to explore the consequence.. Statement of the Research Problem A number of factors would impact employees to stay or leave, especially job satisfaction (Cotton & Tuttle, 1986; Hundera, 2014; Khan & Aleem, 2014; Rizwan et al., 2011; Shakeel & Butt, 2015; Stanz, 2009). Job satisfaction and retention intention respectively play a vital role in diverse organizations. Besides, an organization can predict and perceive how employees tend to retain through job satisfaction (Medina, 2012; Mitchell & Albright, 1972). When employees are dissatisfied with their jobs, environment or other reasons, it is easy to let them feel upset or intent to leave (HR Council for the nonprofit sector, 2011). Hence, job satisfaction can be one of the important indicators to observe employees’ tendency of intention to leave or stay and looked upon as a tool to examine turnover rate (Mudor & Tooksoon, 2011; Ronra & Chaisawat, 2011). Working in each airline, cabin crews tend to work day and night due to the nature of work, and this would increase their dissatisfaction with job and turnover intention. Kraut (1975) pointed out that retention intention could be deemed as an important indicator to predict resignation. Therefore, this study examined the relationship between each dimension of job satisfaction and retention intention of Taiwan airlines. Moreover, with the increasing turnover rate in Taiwan airlines (EVA Airways Corporation, 2016; China Airlines, 2016), what would be the current situation of job satisfaction for cabin crews? In addition, age, education level, position and tenure would be regarded as demographic variables and test the interaction effect with job satisfaction on retention intention.. Significance of the Research First, it is beneficial for airlines to realize overall job satisfaction and retention intention nowadays. Second, after receiving the results from this study, human resources department of airlines could discuss future plan or development through setting the guidelines or strategies for maintaining potential employees and decreasing turnover rate (Ronra & Chaisawat, 2011). Therefore, it contributed to airlines to building an improved environment or plans for cabin crews. The last, since several scholars researched on Taiwan airlines, this study would be an exploration to know the relationship between nine dimensions of job satisfaction and retention intention towards cabin crews. Also, the demographic variables’ interaction effect between job satisfaction and retention intention.. Research Purposes Based on the background and motivation of this study, the main purpose is to have further 2.

(10) understanding of the relationship between each dimension of job satisfaction and retention intention for cabin crews in Taiwan airlines. In addition, the author also investigated whether the interaction effect existed among demographic variables (e.g., age, education level, position and tenure) and overall job satisfaction on retention intention respectively or not. The purposes of the research listed as follows: 1.. To explore current condition of overall job satisfaction for cabin crews in Taiwan airlines.. 2.. To discover the relationship between each dimension of job satisfaction and retention intention.. 3.. To analyze the relationship between overall job satisfaction and retention intention by controlling demographic variables (age, education level, position and tenure).. 4.. To examine the interaction effect of each demographic variable on the relationship between job satisfaction and retention intention.. Research Questions Based on the research purposes, the problems were aroused as below: 1.. What is the current condition of overall job satisfaction for cabin crews in Taiwan airlines?. 2.. Is there significant relationship between each dimension of job satisfaction and retention intention?. 3.. If controlling demographic variables, including age, education level, position and tenure, is there significant relationship between job satisfaction and retention intention?. 4.. Is there significant interaction effect among demographic variables, age, education level, position and tenure, on the relationship between job satisfaction and retention intention?. Delimitation of the Research On account of diverse staff in airlines, let alone multitudinous positions in different industries, the researcher narrowed down the scope of this study. First, according to the research topic, this research only focused on cabin crews of Taiwan airlines. The samples from other positions, international airlines or industries, were excluded from the research. Second, there is no limitation in demographic information, such as gender, age, education level, position, tenure, and so on, that is, as long as cabin crews have been working in Taiwan airlines, they would be the respondents of the research.. Definitions of Key Terms According to the research purposes, the key terms would be defined as follows and used in further processes of the research.. 3.

(11) Job Satisfaction Since job satisfaction is a popular term in countless organizations, the concept of job satisfaction has been developed in several ways by different researchers. In this study, the definition of job satisfaction is the degree of overall satisfaction toward jobs in terms of cabin crews’ perception, including nine dimensions, communication, contingent rewards, coworkers, fringe benefits, operating procedures, nature of work, pay, promotion, and supervision.. Retention Intention Retention is a critical element of an organization for sustainable development. In this study, the definition of retention intention is the degree of intention to stay at current company for cabin crews.. Cabin Crews Cabin crews, equivalent to flight attendant, are qualified to perform not only safety duties in the passenger cabin based on the requirements of the operator and the authority but also cabin functions in emergency situations (International Air Transport Association, 2013). In this study, cabin crews are defined as people engaging in passenger-related service and safety during the flight at Taiwan airlines.. 4.

(12) CHAPTER II. LITERATURE REVIEW. According to research purposes, this section would describe factors affecting retention intention. Also, the definitions and relevant literatures of job satisfaction and retention intention were clarified separately. In addition, the relationship between each dimension of job satisfaction and retention intention, and the interaction effect of demographic variables between job satisfaction and retention intention were reviewed as well.. Retention Intention In this section, factors affecting retention intention, the definition and instrument of retention intention were described.. Factors Affecting Retention Intention The concept of retention could be viewed as logical inverse of turnover (Hausknecht, Rodda, & Howard, 2009). Although the reason causing employees to stay was not completely the same as to leave (Flowers & Hughes, 1973; Steel, 2002), some overlapped reasons still existed. Through reviewing qualitative and quantitative researches, various scholars focusing on different industries indicated that numerous factors would influence intention to retain or resign (see table 2.1). Several industries include academia (Choong, Keh, Tan, & Tan, 2013; Hundera, 2014; Ng’ethe, Iravo, & Namusonge, 2012), aviation (Baloch, Zaman, & Jamshed, 2014; Gultekin, Abdan, & Kilic, 2012; Mokaya & Kittony, 2008), construction (Huang, Lin, & Chuang, 2006), finance (Enu-Kwesi, Koomson, Segbenya, & Annan-Prah, 2014; Salman, Nawaz, & Matin, 2014), hospitality (Arshad & Puteh, 2015; Emiroğlu, Akova, & Tanrıverdi, 2015; Hausknecht et al., 2009; Khan & Aleem, 2014; Ronra & Chaisawat, 2011), manufacture (Patgar & Vijayakumar, 2015) and technology (Cave, Chung, & Choi, 2013; Liang, 2013; Sinha & Sinha, 2012; Stanz, 2009).. 5.

(13) Table 2.1. Factors Affecting Retention/Turnover Intention Industry. Factors. Authors Choong et al. (2013). Age, gender, marital Status. Academia. Aviation. Construction. Finance. Hospitality. Manufacturing. Technology. Overall job satisfaction, commitment, role conflict. organizational. Hundera (2014). Autonomy, distributive justice, leadership, Ng’ethe et al. promotional opportunities, salary, training and (2012) development, recognition, work environment Co-workers, extended flight hours, family work Baloch et al. conflict, pay, promotion, supervision (2014) Benefit, decreased chances for advanced education, family, inadequate career counseling, inflexible assignment, not enough chances for Gultekin et al. further specialization, overall career (2012) dissatisfaction, unattractiveness of duties, pay, promotion policies, retirement uncertainties Competition and poaching, industry dynamics, Mokaya & Kittony leadership, non-responsive management, (2008) remuneration Effect of economic cycles, gender, honored employee status, marriage, promotion speed, wage Huang et al. (2006) effects Salman et al. Employees motivation (2014) Egocentric reasons, growth and development Stanz (2009) opportunities, kob satisfaction Age, education, gender, marital status, position, Emiroğlu et al. tenure, wage, working department (2015) Job satisfaction, nature of the work, pay, Khan & Aleem promotion, working conditions (2014) Attitude towards job, attitude towards company, employee retention importance, service conditions, Patgar & trade union, working conditions, welfare measures, Vijayakumar wage and salary administration, worker's (2015) participation in management Attitude of job-hopping, nature of work, Cave et al. (2013) organizational commitment, payment Employee motivation, organizational culture, Liang (2013) work-life balance. As table 2.1, it shows that a variety of factors would impact on intention to leave or stay. As for several duplicate factors, some of the factors are demographic-related (gender, age and marital status), others are self-perception oriented (organizational commitment, nature of work, 6.

(14) pay/salary, promotion, job satisfaction, work-life balance and employee motivation). Among above factors, since job satisfaction could be measured by different facets (Vroom, 1964) and was deemed to be the predictor or indicator of turnover intention for younger workers (Medina, 2012) or retention (Mitchell & Albright, 1972), it can infer that job satisfaction is a crucial factor to affect retention intention.. Definition of Retention Intention As for the definition of retention intention, it was a positive perspective to observe employees’ maintenance possibility and willingness in organizations (Tett & Meyer, 1993), and regarded as an opposite notion of turnover intention (Black & Stevens, 1989; Johnston, 1995). In general, retention intention was considered as a degree of staying in the same organization after cautious self-evaluation (Tett & Meyer, 1993; Thoresen, Kaplan, Barsky, Warren, & de Chermont, 2003). Arnold and Feldman (1982) asserted that retention intention was a tendency of remaining in current organization due to obtaining a sense of belonging and positive affirmation towards job and organization after joining in the organization. If focusing the definition on aviation industry, retention intention was looked upon as an attitude and behavioral tendency for airline employees to stay in the current company (Huang, 2008). To integrate and merge previous definition, retention intention was defined as a degree of intention to stay at current company for cabin crews in this study.. Instrument of Retention Intention Several instruments can measure retention intention, showing as follows: Intent to stay. “Intent to stay” was adapted from “intent to leave” developed by Hunt, Osborn and Martin (1981). The measurement with 4 items used 5-point scale to examine respondents’ intention tendency by several statements. For instance, “which of the following statements most clearly reflects your feelings about your future with this organization in the next year?”, five means “I definitely will not leave this organization in the next year.” whereas one means “I will definitely leave this organization in the next year”. As the total score is higher, the tendency of retention intention is higher. Intent to stay can be considered as a predictable indicator to test respondents’ intention to stay or leave. Intention to stay instrument (ISI). Through qualitative research method, Kumar and Govindarajo (2014) interviewed employees in manufacturing sector about the causative factors of “member’s intention to stay”, especially focused on individual and organizational factors. Intention to stay instrument was finalized with 76 items under 21 sub factors, including career advancement, reward management, training and development, management style, insufficient 7.

(15) challenge, terms and conditions, working hours/shift, work condition, health facilities, nature of work, heavy workload, relationship with co-workers, relationship with supervisors, achievement recognition, supportive management, socialization, employment confirmation, location, target orientation, safety, and ergonomics. The Cronbach’s alpha value of each sub scale was over .7 with 10-point interval scale (Kumar & Govindarajo, 2014). Employee retention. Employee retention questionnaire with 11 items was constructed based on previous literatures and researches on the motivation of employees regarding to their jobs. (Kyndt, Dochy, Michielsen, & Moeyaert, 2009). To measure intention to stay, Kyndt et al. (2009) adjusted three items subject to Egan, Yang and Bartlett’s questionnaire (2004). For instance, “I intend to change job within this firm in the foreseeable future” was adjusted to “If I wanted to do another job or function, I would look first at the possibilities within this company.” The questionnaire examined not only retention intention but also personal future prospects towards jobs. Among instruments of measuring retention intention above, employee retention questionnaire was chosen because of several reasons. Firstly, the reliablity of measurement is considerably high (α=.91), which means the questionnaire is reliable. Secondly, the number of scale item is not too few as “intent to stay” adapted from Hunt et al. (1981) and not too many as intention to stay instrument developed by Kumar and Govindarajo (2014). The last, the point of scale is also a concerned point to select appropriate measurement. 5-point Likert scale has been well adopted in numerous studies. Although “intent to stay” measured by 5 points, each point represents different meaning based on the questions. Additionally, since it is not meaningful to divide into too many points, intention to stay instrument, a 10-point scale, is not suitable to use. Based on reasons above, employee retention questionnaire develooped by Kyndt et al. (2009) was employed in this study.. Job Satisfaction The definition and instrument of job satisfaction were described in this section.. Definition of Job Satisfaction Owing to the popularity of job satisfaction within multiple filed of organizations, various researchers had their own opinion and definition about job satisfaction. As for the definition development of job satisfaction, the perspective changed single, affection, between 1930s and 1970s (Fisher & Hanna, 1931; Locke, 1976) into multiple, affection and cognition, from 1980s to now (Cranny, Smith, & Stone, 1992; Greenberg & Baron, 1997; Moorman, 1993; Organ & 8.

(16) Near, 1985). Affection-oriented job satisfaction is an overall affective evaluation towards job, whereas cognition-oriented job satisfaction is a logic and rational comparison between individuals’ expectation and self-evaluation on different facets of job, containing working conditions, nature of job, development opportunities, as well as working output (Zhu, 2013). Referring to previous researches, job satisfaction in this study is to know how people feel about distinct aspects of jobs (Spector, 1997). In hence, the definition tended to multiple definitions as the degree of overall satisfaction toward different facets of jobs in terms of cabin crews’ perception.. Instrument of Job Satisfaction Several approaches can be used to measure job satisfaction, showing as follows: Job descriptive index (JDI). Job Descriptive Index includes five major dimensions associated with job satisfaction: work itself, pay, promotion opportunities, co-workers, and supervision. The JDI was first introduced by Smith, Kendall and Hulin (1969), and has been widely used in different industries since then (Ramayah, Jantan, & Tadisina, 2001). It consists of 72 items: 18 items for the facets of work itself, co-workers, and supervision, 9 items for the facets of pay, promotion (Suma & Lesha, 2013). Job in general scale (JIG). Job in General Scale is similar to JDI, but is viewed as a global scale to measure job satisfaction. The JIG was constructed by Ironson, Smith, Brannick, Gibson and Paul (1989), consisting of 18 global evaluative items. Minnesota satisfaction questionnaire (MSQ). Weiss, Dawis, England and Lofquist (1967) developed the manual for the Minnesota satisfaction questionnaire that includes descriptions of the development and scoring of the two long-form MSQs (1977 and 1967 version), short-form MSQ, reliability and validity data, and normative data on specific occupations. While the long-form MSQ makes up 20 subscales with 100 items, short-form MSQ consists of 3 facets with 20 items: intrinsic (10 items), extrinsic (8 items) and general (2 items). Job satisfaction survey (JSS). By collecting data from human service, public and nonprofit sector organizations, Spector (1985) developed the Job Satisfaction Survey with a nine-subscale measure of employee job satisfaction, including communication, contingent rewards, coworkers, fringe benefits, operating procedures, nature of work, pay, promotion, and supervision. Each subscale is composed of four items. In a variety of job satisfaction scales, JSS was chosen due to several reasons. First, although more than fifty percent of published articles used JDI to measure job satisfaction 9.

(17) (Ramayah et al., 2001) and the reliability of JDI is quite high, there are merely five facets of JDI, which cannot cover other factors. In addition, the description of JDI with single words or phrases focuses more on the tangible satisfaction instead of intangible. Furthermore, the responses are “Y” (Yes), “N” (No), or “?” that represent “satisfied” or “unsatisfied” rather than the degree of satisfaction (Tsai, 2006; Wang, 2010). Second, the reasons not to choose JIG are nearly the same as JDI. Although the reliability of JIG is high as well (Ironson et al., 1989), it only uses 18 single words or phrases to test job satisfaction. Besides, the responses use two directions (yes or no) to describe satisfaction in place of the degree as well (Tsai, 2006; Wang, 2010). Additionally, both long-form and short-form MSQ are reliable, but still exist some not applicable reasons. As for the long-form MSQ, it is too long to make respondents keep concentration on the scales. On the other hand, the integrity of short-form MSQ is not enough as long version due to decrease facets from twenty to three (Tsai, 2006). The last, the reliability of JSS is higher than 0.7 (see table 2.2) which means data is reliable (Ghozali, 2013).. Table 2.2. The Reliability of JSS Cronbach’s alpha value Pilot test Present study. Author (year) Gholami Fesharaki, Talebiyan, Aghamiri, Mohammadian (2012) Hussain & Soroya (2017) Tam & Zeng (2014) Ibrahim, Ohtsuka, Dagang, & Bakar (2014). &. -. 0.86. 0.917 0.76. 0.886 0.84. According to above reasons, JSS was selected to be the instrument of job satisfaction in this study.. Relationship between Job Satisfaction and Retention Intention In this section, the relationship between each dimension of job satisfaction and retention intention, and the interaction effect of demographic variables between job satisfaction and retention intention were reviewed.. Relationship between Each Dimension of Job Satisfaction and Retention Intention Based on plentiful literatures, some researchers studied about the relationship between 10.

(18) each dimension of job satisfaction and employee retention or retention intention, while others discussed the relationship between sub-dimension of job satisfaction and employee turnover or intention to leave. The following context was described in detail for each relationship. Job satisfaction and retention intention. Job satisfaction has been viewed as an important prediction tool for both employee retention (Enu-Kwesi et al., 2014; Mitchell & Albright, 1972) and turnover intention (Medina, 2012; Mudor & Tooksoon, 2011). Through evaluating job satisfaction, an organization can probably increase positive outcomes, such as performance as well as decreasing absenteeism and turnover (Ronra & Chaisawat, 2011). Therefore, it could be seen that job satisfaction had an inverse relationship with turnover intention (Medina, 2012; Price, 1977; Rizwan et al., 2011). The more employees were dissatisfied with their jobs, the higher turnover would happen (Cotton & Tuttle, 1986; Hausknecht et al., 2009). On the contrary, there was a significant relationship between job satisfaction and employee retention (Enu-Kwesi et al., 2014; Kavitha, Geetha, & Arunachalam, 2011). According to above researches, the author proposed: H1: Job satisfaction has positive influence on retention intention. Pay and retention intention. Since money is a survival instrument to fulfill physiological needs in daily life, it has been highly discussed with both retention intention and turnover intention in all sorts of professional fields, such as the industry of technology (Cave et al., 2013), academia (Ng’ethe et al., 2012), hospitality (Emiroğlu et al., 2015), medical (Chou, 2005; Khan & Aleem, 2014), and aviation (Baloch et al., 2014; Gultekin et al., 2012; Mokaya & Kittony, 2008) and so on. Based on previous research results of the relationship between pay and retention, most researchers asserted that pay is negatively related to turnover (Cave et al., 2013; Cotton & Tuttle, 1986; Khan & Aleem, 2014) or highly affect retention rate (Dutta & Banerjee, 2014). Moreover, focusing on aviation industry, the results were consistent with most researches, that is, pay would highly affect separation decision (Gultekin et al., 2012) or turnover intention (Baloch et al., 2014). Subject to former findings, hypothesis 1-1 was proposed that: H1-1: Pay has positive influence on retention intention. Promotion and retention intention. To fulfill Maslow’s self-actualization or the sense of achievement, talented employees would have propensity to the expectation of being promoted (Ng’ethe et al., 2012; Prince, 2005). Promotion opportunities would be regarded as a significant factor for employees to make decision of resignation or retention (Prince, 2005). However, the relationship between promotion and retention or turnover intention is 11.

(19) controversial. As some researchers (Cotton & Tuttle, 1986; Khan & Aleem, 2014; Lazear, 1998) asserted that promotion would be negatively related to turnover, others (Baloch et al., 2014; Huang et al., 2006) argued that promotion would inversely enlarge turnover intention. To explore more in the case of cabin crews in Taiwan, the hypothesis was proposed as below: H1-2: Promotion has positive influence on retention intention. Supervision and retention intention. To develop the desire to stay, any organizations or effective programs requires supportive supervisors or managers to supervise or interact with subordinates positively (Freyermuth, 2007; Zenger, Ulrich, & Smallwood, 2000). Immediate supervisors’ support is an essential factor to alternative employees’ propensity to leave and increase job involvement (Greenhaus, 1987), resulting in following hypothesis: H1-3: Supervision has positive influence on retention intention. Fringe benefits and retention intention. According to Spector (1985), the description of fringe benefits included two forms, monetary and non-monetary. Both forms of fringe benefits could not be ignored since it could enhance employees’ loyalty and motivated them to work productively, especially towards sales (Malik & Naeem, 2009), and make them stay in the organization (Dutta & Banerjee, 2014; Sinha & Sinha, 2012). As the previous finding, the hypothesis was proposed: H1-4: Fringe benefits have positive influence on retention intention. Contingent rewards and retention intention. Any forms of rewards, bonus, certificate, recognition, awards, free trips and so on, would be a satisfactory incentive or response for employees’ contribution offered by organizations (Irshad, 2011). Rewards is so important as to enhance the willing to work and the perception of self-worth towards employees (Silbert, 2005) and result in stop thinking job opportunities from other organizations (Tan, 2008). Some studies highlighted the linkage between rewards and employee retention (Towers Perrin, 2003; Watson Wyatt Worldwide, 1999), and revealed that rewards would enhance the possibility of intention to retain. Based on above researches, the hypothesis was proposed as follows: H1-5: Contingent rewards have positive influence on retention intention. Operating procedures and retention intention. To make prime retention management, Dutta and Banerjee (2014) illustrated that understanding retaining employees demands for suitable policies and procedures. As for the relationship between operating procedures and retention intention, it would be an exploration to probe in the case of Taiwan cabin crews and hypothesize that: H1-6: Operating procedures has positive influence on retention intention. Coworkers and retention intention. The existence of supportive coworkers would be a 12.

(20) strength to motivate employees to enhance work efficiency and satisfaction towards job. Steijn and Leisink (2006) pointed out that support by colleagues showed a positive influence on the intention to remain, leading to following hypothesis: H1-7: Coworkers have positive influence on retention intention. Nature of work and retention intention. As flight attendants, the nature of work is different from office workers, especially on flexible working time and various job content. Due to the unique work characteristics in airline, nature of work would be one of the factor affecting employee retention (Chen & Lai, 2017). On the other hand, nature of work or work itself would be negatively related to turnover intention (Cave et al., 2013) or employee turnover (Khan & Aleem, 2014); or influence on employee intentions (Gaiduk & Gaiduk, 2009). In light of above researches, the hypothesis was proposed as follows: H1-8: Nature of work has positive influence on retention intention. Communication and retention intention. Communication is viewed as a component of organizational factors (Enu-Kwesi et al., 2014) to deliver organizational goals, policies, job requirements to employees, which assists to enhance employees’ participation, identification and trust (Becker & Gopinath, 2000). For retention management, communication was the key factor to build the bridge between employees and employers, leading to retain employees (Gaiduk & Gaiduk, 2009; Kavitha et al., 2011; Sinha & Sinha, 2012). As previous finding, the hypothesis was proposed as: H1-9: Communication has positive influence on retention intention.. The Interaction Effect of Demographic Variables between Job Satisfaction and Retention Intention Through literatures review, the major discussed issues are the relationship between each demographic variable, such as age, education level, position and tenure and retention/turnover intention. In hence, the research would mainly describe the relationship between (1) age and retention/turnover,. (2). education. level. and. retention/turnover,. (3). position. and. retention/turnover, and (4) tenure and retention/turnover separately, and hypothesized the interaction effect of demographic variables on the relationship between job satisfaction and retention intention in this section. Age, job satisfaction and retention intention. Age would be one of personal characteristics influencing employees’ intention to quit (Choong et al., 2013; Kipkebut, 2010) or to remain (Gaiduk & Gaiduk, 2009; Govaerts, Kyndt, Dochy, & Baert, 2011). Choong et al. (2013) claimed that there is a significant difference between age and turnover intention and age 13.

(21) would be considered as a determinant on turnover intention (Emiroğlu et al., 2015). Additionally, several studies concluded that elders would have more potential to retain in their respective organizations than youngers (Choong et al., 2013; Cotton & Tuttle, 1986; Govaerts et al., 2011). As there exists the relationship between age and retention, and job satisfaction and retention, the hypothesize was proposed that: H2: Age has a significant interaction effect on the relationship between job satisfaction and retention intention. Education level, job satisfaction and retention intention. Education level, a personal factor, would be great relevance to employee retention (Kyndt et al., 2009). Regarding to the relationship between education level and retention, there existed inconsistent results. While one asserted that there is a significant negative relationship between education level and retention (Kyndt et al., 2009; Mitchell, MacKenzie, Styve, & Gover, 2000), others stood for no significant influence (Govaerts et al., 2011; Huang et al., 2006). As a result, probing into the relationship between education level and retention intention and the interaction effect of education level between job satisfaction and retention intention would be an exploration in the case of Taiwan cabin crews. The hypothesis was proposed as follows: H3: Education level has a significant interaction effect on the relationship between job satisfaction and retention intention. Position, job satisfaction and retention intention. Employees with higher position requires more responsibilities towards organizations, resulting in higher organizational commitment and lower turnover intention (Salami, 2008). In hence, position has negative relationship with turnover intention (Emiroğlu et al., 2015), that is, employees with higher position tend to retain at organizations. Based on this result and significant relationship between job satisfaction and retention intention, the hypothesis was proposed that: H4: Position has a significant interaction effect on the relationship between job satisfaction and retention intention. Tenure, job satisfaction and retention intention. Tenure was found as one of the major determinant factors related to turnover intention (Brodie, 1995; Emiroğlu et al., 2015). Additionally, there is a significant difference between tenure and turnover intention. In other words, employees with high tenure would have the inclination to remain at the organizations (Emiroğlu et al., 2015). In the event that existing the relationship between job satisfaction and retention intention and tenure and retention respectively leads to following hypothesis: H5: Tenure has a significant interaction effect on the relationship between job satisfaction and retention intention. 14.

(22) CHAPTER III. RESEARCH DESIGN. In this chapter, research framework, research method, research measurement, research sample, data collection, data analysis, validity and reliability of the study, and research procedure would be discussed.. Research Framework Based on previous literature review, the framework aligns with the purposes of this study was constructed as figure 3.1. Job satisfaction was selected as independent variable, while retention intention was the dependent variable. In addition, age, education level, position and tenure were viewed as demographic variables in this study.. Job Satisfaction • Pay • Promotion • Supervision • Fringe benefits • Contingent rewards • Operating procedures • Coworkers • •. Retention Intention. Demographic Variables • Age • Education level • Position • Tenure. Nature of work Communication. Figure 3.1. Research framework. Hypotheses Based on literature review, the hypotheses of this study were proposed as below: Hypothesis 1. Job satisfaction has positive influence on retention intention. Hypothesis 1-1. Pay has positive influence on retention intention. Hypothesis 1-2. Promotion has positive influence on retention intention. Hypothesis 1-3. Supervision has positive influence on retention intention. Hypothesis 1-4. Fringe benefits have positive influence on retention intention. Hypothesis 1-5. Contingent rewards have positive influence on retention intention. 15.

(23) Hypothesis 1-6. Operating procedures have positive influence on retention intention. Hypothesis 1-7. Coworkers have positive influence on retention intention. Hypothesis 1-8. Nature of work has positive influence on retention intention. Hypothesis 1-9. Communication has positive influence on retention intention. Hypothesis 2. Age has a significant interaction effect on the relationship between job satisfaction and retention intention. Hypothesis 3. Education level has a significant interaction effect on the relationship between job satisfaction and retention intention. Hypothesis 4. Position has a significant interaction effect on the relationship between job satisfaction and retention intention. Hypothesis 5. Tenure has a significant interaction effect on the relationship between job satisfaction and retention intention.. Research Method This study conducted a quantitative approach to measure the relationship between job satisfaction and employee retention based on the research method of previous researchers (EnuKwesi et al., 2014; Kyndt et al., 2009; Medina, 2012; Mitchell & Albright, 1972; Ronra & Chaisawat, 2011), since using quantitative method would test hypotheses and be more structured, reliable and objective. The method of this study used two versions of questionnaires (paper and online) to collect data. The author employed Google form to create online questionnaire.. Measurement Design The measurements were designed separately in this research as below. The integrated questionnaire includes 47 items which consists of 11 questions of employee retention and 36 questions of job satisfaction and demographic information (see appendix). In addition, to avoid the inappropriate targets, there is a filter showed as “Are you a cabin crew on active duty in Taiwan airlines?” on first page.. Demographic Information Demographic information includes five items: Gender. Gender was separated into two sexes: male and female. Because of the nature of work in Taiwan airlines, there was a wide gap between male and female, approximately one to nine (Association of Wage-Earners, 2000). In hence, gender was merely conducted to analyze the frequency in this study.. 16.

(24) Age. A column was blank for respondents to fill out their born year. By calculation of qualities, the age would be divided into 4 ranges, the age of 23 to 25, 26 to 28, 29 to 31 and above 32. Education level. Education level consisted of five levels: high school or below, associate, bachelor, master and doctor. Position. Position represented respondents’ current position in the company, including two categories: management and non-management. Tenure. To identify the precise tenure, respondents must fill in the specific numerals of working length in current company. By calculation of qualities, the tenure was composed of four ranges, below 1 year, 1 to below 3 years, 3 to below 7 years and above 7 years.. Job Satisfaction Job satisfaction was an independent variable in this study. The instrument of job satisfaction was Job Satisfaction Survey which was developed by Spector in 1985. The Job Satisfaction Survey (JSS) was a 36-item questionnaire consisting of ninedimension scales to assess employees’ attitudes about the job and aspects of the job (Spector, 1985). Each scale comprised four items written in positive and negative direction (see table 3.1). Different from Spector (1985), The scoring of each item employed 5-point Likert scale, ranging from 1 (very dissatisfied) to 5 (very satisfied). For the 4-item subscales with a range from 4 to 20, scores of 4 to 10 are dissatisfied, 14 to 20 are satisfied, and between 10 and 14 are ambivalent. For the 36-item total where possible scores range from 36 to 180, the ranges are 36 to 90 for dissatisfaction, 120 to 180 for satisfaction, and between 90 and 120 for ambivalent.. 17.

(25) Table 3.1. Item Directions of JSS Item numbers. Subscale. Positive. Negative. Pay 12, 39 21, 30 Promotion 22, 31, 44 13 Supervision 14, 41 23, 32 Fringe benefits 24, 33 15, 40 Contingent rewards 16 25, 34, 43 Operating procedures 26 17, 35, 42 Coworkers 18, 36 27, 45 Nature of work 28, 38, 46 19 Communication 20 29, 37, 47 Note. Job Satisfaction Survey. Adapted from “Measurement of human service staff satisfaction: Development of the Job Satisfaction Survey,” by Spector, P. E., 1985, American Journal of Community Psychology, 13(6), 693-713.. Retention Intention The instrument of retention intention used Kyndt et al.’s questionnaire (2009). Eleven items stated including whether the respondents would like to keep working on their current jobs, whether they wanted to change jobs or functions and whether they had future prospects. For instacne, “I’m planning on working for another company within a period of three years.” and “I see a future for myself within this company.” The total items used 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The total scoring of all items ranges from 5 to 55. The higher score represented higher employee retention.. Research Samples This study focuses on all cabin crews in Taiwan airlines. To approach appropriate targets, the samples should be a current cabin crew working at Taiwan airline, excluding foreign airlines. Before conducting the formal questionnaire, the pilot test must be executed since this would manifest some particular problems or conceal issues that should be considered in future research (Connelly, 2008). According to annual report of Civil Aeronautics Administration (CAA) in 2016, the total number of cabin crews in different airlines was 7,183. As for the sample size of pilot test, there were several distinct discussions. Connelly (2008) declared that the sample size of pilot test should be around 10 percent of the population size, that is, approximately 720 respondents. In addition, Herzberg (2008) mentioned that sample size from 18.

(26) 10 to 40 per group is adequacy of evaluating and estimating a variety of possible aims. Furthermore, Gay and Diehl (1992) asserted that at least 30 samples are required to build a relationship in correlational research. On the other hand, to analyze sample size requirements for structural equation models, Boomsma (1982) declared that a minimum sample size was 100. Moreover, 5 or 10 observations per estimated parameter was necessary (Bentler & Chou, 1987; Bollen, 1989; Hair, Anderson, Tatham, & Black, 1998) as Thompson (2000) affirmed that sample size were at least 10 or 15 times observation items. In accordance with previous studies about sample size of pilot test (Bentler & Chou, 1987; Bollen, 1989; Boomsma,1982; Connelly, 2008; Gay & Diehl, 1992; Hair et al., 1998; Herzberg, 2008; Thompson, 2000), the sample size of the pilot test was 10 times observation of retention items, that is, 110 in this study. As for the sample size of official questionnaire, this study collected 283 questionnaires in total; however, 57 questionnaires were considered as invalid since respondents did not match the criteria or provide complete information. In hence, 226 samples were employed to be analyzed.. Data Collection Data collection was conducted from May to July in 2017. Through convenient sampling technique, the online questionnaire was delivered via social software, such as Facebook and Line to request people to assist to complete the survey if they fit the criteria of the research samples. Moreover, by snowball sampling, if respondents were willing to share online or paper questionnaires, they would get the link or paper to forward or deliver to their personal network who fits the qualification. As for collected samples, since paper questionnaires were delivered by a cabin crews of a local airline and the samples were limited by convenient and snowball sampling, the result of samples mainly sourced from two major local airlines and most of the respondents are female.. Data Analysis To analyze the data, the statistic software of IBM Statistical Product and Service Solutions (SPSS) 22 for Win 7 were used in this study. The analysis method of each variable included as below.. Descriptive Statistics To recognize the basic features of the data, descriptive statistics was used to measure in the study and present quantitative descriptions in a manageable form or graphics. It provides simple summaries about frequency distribution of samples and measures, such as, mean, standard deviation and so on. 19.

(27) Pearson Correlation Correlation is a technique for probing into the relationship between two quantitative, continuous variables. The most common measure method is Pearson product moment correlation (PPMC), called Person Correlation for short. The value of correlation coefficient shows the strength of a linear association between two variables, varying between plus one (namely perfect degree of positive correlation) and minus one (namely perfect degree of negative correlation). As the correlation coefficient value is zero, it represents there is no correlation between two variables. The direction of the relationship between the variables is either positive or negative correlation. In this study, each dimension of job satisfaction was analyzed to test the correlation with retention intention separately.. Linear Regression Linear regression is the most basic type of regression, attempting to explain the relationship between one dependent variable and one or more independent variables by fitting a linear equation to observed data. The direction of coefficient value and significance determine positive or negative relationship between the variables. In this study, the relationship between each dimension of job satisfaction and retention intention were analyzed.. Hierarchical Regression Hierarchical regression is an approach to compare several regression models and explain a statistically significant amount of variance in one dependent variable after all other variables. The improvement in R2 shows the proportion of explained variance in dependent variable by the model. The result determines whether adding newly variables increase or decrease the variance of R2. In this study, age, education level, position, and tenure were considered as control variables to analyze the relationship between job satisfaction and retention intention. In addition, the interaction effect of each demographic variable on the relationship between job satisfaction and retention intention was examined through hierarchical regression as well.. Validity and Reliability of the Study To test the validity and reliability of the study, the process includes experts review, confirmatory factor analysis (CFA) and Cronbach’s alpha which respectively examine content validity, construct validity and reliability. The information described in detail as follows.. Validity of the Study Validity refers to the credibility or believability of an instrument, implying precise and accurate results acquired from the data collected. There are four typical types of validity: face validity, content validity, criterion validity (includes concurrent and predictive) and construct 20.

(28) validity (includes convergent and discriminant). To confirm the validity of the study, content validity and construct validity were employed. Content validity. Content validity, named as logical or rational validity as well, refers to the measurement representing each aspect of a construct. In this study, five experts from several professional field reviewed and assisted to check the translation between English and Mandarin. Construct validity. Construct validity refers to the degree to which an instrument measures its construct by using multiple indicators and has two subtypes: how well the indicators of one construct converge (namely convergent validity) and how well the indictors of different constructs diverge (namely discriminant validity). In this study, analysis of moment structure (AMOS) was employed to conduct confirmatory factor analysis. The criteria and result of confirmatory factor analysis showed as table 3.2. Table 3.2. Model Fit Indices Criteria and Results of 47 items. Acceptable fit Employee Retention (11) Pay (4). χ2/df <5 1.774 2.715. RMSEA < .08 0.84 .125. GFI > 0.8 .892 .978. AGFI > 0.8 .839 .888. Promotion (4) .215 .000 .998 .990 Supervision (4) 1.871 .089 .984 .919 Fringe Benefit (4) 1.814 .086 .984 .918 Contingent Rewards (4) .082 .000 .999 .996 Operating Conditions (4) 3.348 .147 .970 .848 Coworkers (4) 1.709 .081 .985 .923 Nature of Work (4) .473 .000 .996 .978 Communication (4) 1.345 .056 .988 .940 Note. RMSEA= Root Mean Square Error of Approximation; GFI=. CFI > 0.9 .917 .940 1.000 .975 .0984 1.000 .895 .984 1.000 .982 Goodness. CR > 0.7 .986 .873. AVE > 0.5 .862 .651. .769 .490 .861 .627 .934 .781 .917 .735 .867 .674 .901 .719 .933 .801 .819 .555 of Fit Index;. AGFI= Adjusted Goodness of Fit Index; CFI= Comparative Fit Index; CR= Composite Reliability; AVE= Average Variance Extracted As for the criteria of internal model fit, the value of CR should be larger than 0.7, whereas the value of AVE should be larger than 0.5 (Hair et al., 1998). The result showed that most value of CR and AVE reached the criteria of acceptable range, which represented the construct of the instrument is reliable and valid. On the other hand, as for the whole model fit, although the value of RMSEA of pay and operating conditions subscales was not fit for the acceptable 21.

(29) criteria, the value of GFI (> .09) showed good model fit (Hu & Bentler, 1999). Several scholars explained that if the number of samples was less than 200, the value of RMSEA would be high (Bentler & Yuan, 1999; Boomsma, 1982; Marsh, Hau, Balla, & Grayson, 1998). On the whole, the value of each criterion item was acceptable, and the instrument of each subscale was valid to measure.. Reliability of the Study Reliability refers to the degree to which an instrument produces stable and consistent quality of results. There are four general types of reliability, each of which measures reliability in a different approach, including inter-rater or inter-observer reliability, test-retest reliability, parallel-forms reliability and internal consistency reliability (Phelan & Wren, 2005). Internal consistency reliability, a common way to test reliability, were employed in this study. Internal consistency. Internal consistency reliability is a measure of reliability used to evaluate the consistency of results across items within a test. On purpose of examining the internal consistency of the questionnaire, Cronbach’s alpha was conducted to show the results. According to several researchers, if the Cronbach’s alpha value is below .4, the items should be deleted (Leech, Barrett, & Morgan, 2005). The Cronbach’s alpha value below .6 should not be acceptable (DeVellis, 1991; Leech et al., 2005). Data is reliable, as the Cronbach’s Alpha value is equal or more than .6 (Ghozali, 2013), or should be at least above .7 (DeVellis, 1991; Leech et al., 2005; Nunnally, 1978). As for the reliabilty analysis in the pilot test, the Cronbach’s alpha value of employee retention is .818, whereas total job satisfaction is .904, showing the instrument of this study is reliable. The Cronbach’s alpha value and description of each subscale showed as table 3.3.. 22.

(30) Table 3.3 The Description and Cronbach’s Alpha Value of Each Dimension of JSS Scale Pay Promotion Supervision Fringe Benefits Contingent Rewards Operating Procedures Coworkers Nature of Work Communication Total Note. N=110. Alpha .63 .45 .66 .76 .73 .56 .67 .77 .58 .90. Description Pay and remuneration Promotion opportunities Immediate supervisor Monetary and nonmonetary fringe benefits Appreciation, recognition, and rewards for good work Operating policies and procedures People you work with Job tasks themselves Communication within the organization Total of all facet. In accordance with previous results of validity and reliability of this study, each item of the questionnaire was keep to become the official questionnaire after pilot test.. Research Procedure Due to the violent strike of CAL in 2016, this aroused author’s motivation to explore what factors affecting cabin crews to stay or to leave in Taiwan airlines. Through reviewing relevant literatures and studies, the research topic, the definition of key terms, research background and son on gradually emerged from plenty of factors and industries. Since a small number of researchers probed into aviation industry, especially on cabin crews, it showed the importance to research and to develop further discussion. After reviewing literatures, the author developed research questions and hypotheses in accordance with research purposes and framework. To measure specific variables in this research, instruments were developed and chosen subject to the reliability and validity. Before delivering the official questionnaire, the experts should inspect the quality of the study to confirm the content and measurement of the research could be conducted and pilot test was employed in the continued step. Going through above steps, the samples could be collected and analyzed. The last but not the least, the research results were described in the conclusion, providing discussion and concrete suggestions for future research. The research procedure was illustrated as figure 3.2.. 23.

(31) Motivation development. Literatures review. Research topic dertermination. Research questions and framework development. Research instruments development. Experts review. Pilot test and adjustment. Data collection and analysis. Research finding conclusion and suggestions. Figure 3.2. Research procedure. 24.

(32) CHAPTER IV. RESULTS AND DISCUSSIONS. The chapter revealed the result of data analysis, the finding of each hypothesis and discussion in this study. Descriptive statistics analysis showed the demographic information of respondents and the current condition of cabin crews’ job satisfaction and retention, afterward, the result of correlation analysis, linear regression between each dimension of job satisfaction and retention intention would be presented as well. Finally, hierarchical regression revealed the result of the relationship of job satisfaction and retention intention and the interaction effect of demographic variables (age, education level, position and tenure) between job satisfaction and retention intention.. Descriptive Analysis The result of sample distribution, and job satisfaction and retention intention would be discussed in this section.. Sample Distribution The demographic information in descriptive statistics was collected from 226 cabin crews, showing the distribution of gender, age, education level, position and tenure. The frequency and percentage of the demographic information were summarized in table 4.1. As for the gender, the percentage of female (95.1%) was extremely higher than male (4.9%). Due to the nature of work at the airlines, the ratio between male and female was 1 to 9. In terms of age, since most female cabin crews would confront marriage pressure, health problem, family issue and so on, the result showed 170 respondents (75.2%) were below 32 years old and the age of 56 respondents (24.8%) were above 32. In the case of education level, 184 respondents (81.4%) owned bachelor degree while the percentage of associate (8.4%) and master (10.2%) was quite close. About the position, the ratio of management (35.4%) and nonmanagement (64.6%) was almost one to two. The last but not the least, the tenure below 1 year of respondents was 65 (28.8%) while 58 respondents (25.7%) has worked for 1 year to below 3 years. 37 respondents (16.4%) has worked for 3 to below 7 years, as 66 respondents (29.2%) has worked for more than 7 years. To sum up, the ratio of male and female was almost the same as previous distribution, approximately one to nine (Association of Wage-Earners, 2000) as a result of the characteristic of cabin crews. In hence, due to limited convenient and snowball sampling, major respondents are young female cabin crews, less than 32 years old with bachelor degree and entry level.. 25.

(33) Table 4.1. Descriptive Statistics on Sample Characteristics (N=226) Demographic variables Gender. Age. Education level Position. Tenure. Category Male Female 23-25 26-28 29-31 Above 32 Associate Bachelor Master Management Non-management Below 1 year 1-below 3 years 3-below 7 years Above 7 years. Frequency 11 215 57 71 42 56 19 184 23 80 146 65 58 49 54. Percentage 4.9 95.1 25.2 31.4 18.6 24.8 8.4 81.4 10.2 35.4 64.6 28.8 25.7 21.7 23.9. Job Satisfaction and Retention Intention After conducting descriptive statistics on pay, promotion, supervision, fringe benefits, contingent rewards, operating procedures, coworkers, nature of work, communication, total job satisfaction and retention, the result presented as the table 4.2 below. Compared with different dimensions of job satisfaction, the scoring of minimum, maximum and standard deviation is quite the same. However, the percentage of minimum scoring is not identical. For instance, fringe benefits are much higher than other dimensions of job satisfaction, inferring that respondents are less satisfied with fringe benefits than the others. On the other hand, although the maximum scoring of each dimension of job satisfaction is extremely high, quite few respondents satisfied with these sub-variables indeed. As for the total job satisfaction, the scoring shows that each respondent has different perception about it; therefore, the standard deviation is little bit large (SD =18.051). Furthermore, the qualities of total job satisfaction scoring are 86, 100.5, 112 respectively, meaning that the thought of overall job satisfaction for most respondents are neutral, even partial to negative. About retention intention, even though the scoring is not much high, it represents that most respondents tends to retain in the same company. To explore the current condition of overall job satisfaction for cabin crews in Taiwan airlines, the finding manifests ambivalent perception about job satisfaction. Additionally, even 26.

(34) if over half of cabin crews are not really satisfied with sub-variables, their overall retention intention exceeds half scoring. To explain this result, the author infers that there are other workrelated or personal-related factors leading to resign or retain, or respondents are inclined to stay by comparing with other industries.. Table 4.2. Descriptive Statistics on Each Dimension of JS and RI (N=226) Pay Promotion Supervision Fringe Benefits Contingent Rewards Operating Procedures Coworkers Nature of Work Communication Total Job Satisfaction Retention Intention. Min 4 4 4 4 4 5 5 4 4 47 11. Max 20 18 19 17 19 18 20 20 19 149 51. Median 10 12 11 9 11 11 12 14 11.5 100.5 33. Mean 9.95 11.28 10.37 9.05 10.74 11.03 12.15 13.30 11.19 90.06 32.69. SD 3.172 3.124 2.906 3.103 3.171 2.395 2.701 2.953 2.851 18.051 7.328. Relationship of JS and RI Pearson correlation and regression analysis was performed in order to determine the relationship between each dimension of job satisfaction and retention intention. The correlation finding (see table 4.3) showed that pay [r (224) = .396, p < .01], supervision [r (224) = .380, p < .01], fringe benefit [r (224) = .394, p < .001], contingent rewards [r (224) = .376, p < .01], operating procedures [r (224) = .332, p < .01], coworkers [r (224) = .472, p < .01], nature of work [r (224) = .615, p < .01], communication [r (224) = .383, p < .01] and total job satisfaction [r (224) = .557, p < .01] have significant positive correlation with retention intention. Among them, pay, supervision, fringe benefits, contingent rewards, operation conditions and communication are modestly correlated with retention intention, whereas coworkers, nature of work and total job satisfaction showed moderate correlation with retention intention. On the other hand, there is no significant correlation between promotion [r (224) = .096, p = .149] and retention intention, which means no linear relationship between them. To interpret reasonable possibility resulting in this consequence, the promotion system would be one of the affecting factors. Since the promotion system is diverse from different airlines, the perception of being promoted would be distinct from cabin crews. Therefore, it is 27.

(35) hard to be consistent with thought in terms of promotion to build the correlation between promotion and retention intention.. 28.

(36) Table 4.3. Correlation Matrix of Job Satisfaction and Retention Intention 1 2 3 4 5 6 7 8 9 10 1. Pay 2. Promotion .316*** 3. Supervision .547*** .339*** 4. Fringe Benefits .684*** .248*** .495*** 5. CR .686*** .416*** .669*** .625*** 6. OP .355*** .026 .430*** .421*** .450*** 7. Coworkers .269*** -.027 .511*** .248*** .342*** .335*** 8. NW .343*** .164** .430*** .315*** .418*** .339*** .479*** 9. Communication .411*** .258*** .530*** .431*** .558*** .453*** .375*** .406*** 10. TJS .765*** .466*** .806*** .737*** .851*** .597*** .559*** .630*** .715*** 11. RI .396*** .096 .380*** .394*** .376*** .332*** .472*** .615*** .383*** .557*** Note. ** p < .01, *** p < .001; CR= Contingent Rewards; OP= Operating Procedures; NW= Nature of Work; TJS= Total Job Satisfaction; RI= Retention Intention.. 29.

(37) The result of regression model, there is a significantly positive relationship between fringe benefit (β = .145, p < .05), coworkers (β = .203, p < .01), nature of work (β = .444, p < .001) and retention intention separately, representing that fringe benefit, coworkers, and nature of work could predict or explain retention intention towards cabin crews. On the contrary, there is no significant relationship between pay (β = .136, p = .079), promotion (β = -.021, p =.715), supervision (β = -.059, p = .446), contingent rewards (β = -.066, p = .439), operating procedures (β = .029, p = .637), communication (β = .069, p = .291) and retention intention respectively.. Table 4.4. Linear Regression for Each Dimension of JS and RI Retention Intention β .136 -.021 -.059 .145 -.066 .029 .203 .444 .069 .467 .445 21.018***. Pay Promotion Supervision Fringe Benefits Contingent Rewards Operating Procedures Coworkers Nature of Work Communication R2 Adj R2 F Note. *** p < .001.. p .079 .715 .446 .047 .439 .637 .002 .000 .291. On the other hand, to analyze the relationship between job satisfaction and retention intention by controlling demographic variables (age, education level, position and tenure) based on the research question, hierarchical regression analysis was employed and the result presented as table 4.5. The consequence displayed that age, education level, position and tenure could explain the variance of retention intention for 16.4% (F = 10.847, p < .001) whereas controlling the demographic variables, job satisfaction could increase 32.1% variance of retention intention (F = 41.431; p < .001). With controlling the demographic variables, there is a significant relationship between job satisfaction and retention intention (β = .567; p < .001), that is, the scoring of job satisfaction is higher, the possibility of intention to retain is much higher.. 30.

(38) Table 4.5. Result of Hierarchical Regression Analysis for JS on RI Retention Intention Model 1 (β) Model 2 (β) Step 1 Age Education Level Position Tenure Step 2 Job Satisfaction R2 Adj R2 △R2 F △F Note. * p < .05. *** p < .001.. .167* -.039 -.005 .247*. .210* -.051 -.008 .214*. .164 .149 .164 10.847*** 10.847***. .567*** .485 .473 .321 41.431*** 137.060***. Interaction Effects of Demographic Variables between JS and RI Based on the research purpose, hierarchical regression analysis was performed to answer the research question, “is there significant interaction effect of demographic variables, age, education level, position and tenure, on the relationship between job satisfaction and retention intention?”. The following sections would describe the result of interaction effect of each demographic variable in detail.. Age, Job Satisfaction and Retention Intention Table 4.6 showed that the main effect of age and job satisfaction can explain 46.3% variance of retention intention (F(2, 223) = 96.293, p < .001), whereas after controlling main effect, the interaction between age and job satisfaction can increase 0.4% variance of retention intention (F(1, 222) = 1.838, p = .177). However, there is no significant interaction effect between age and job satisfaction on retention intention.. 31.

(39) Table 4.6. Result of Hierarchical Regression Analysis for Interaction between Age and JS on RI Retention Intention 2. △R .463***. Step 1 Age Job Satisfaction Step 2 Age Job Satisfaction Age x Job Satisfaction. β .391*** .570***. .004 .397*** .718*** -.162 Total R2. .468***. Note. *** p < .001.. Education Level, Job Satisfaction and Retention Intention Table 4.7 showed that there is no significant interaction effect between education level and job satisfaction on retention intention (F(1, 222) = .075, p = .784). However, the main effect of education level and job satisfaction can explain 32.3% variance of retention intention (F(2, 223) = 53.117, p < .001).. Table 4.7. Result of Hierarchical Regression Analysis for Interaction between EL and JS on RI Retention Intention 2 β △R Step 1 .323*** Education Level -.111* Job Satisfaction .559*** Step 2 .000 Education Level -.112* Job Satisfaction .475 Education Level x Job Satisfaction .086 2 Total R .323*** Note. * p < .05. *** p < .001.. Position, Job Satisfaction and Retention Intention To measure the effect of position and job satisfaction on retention intention, table 4.8 presented that there is no significant interaction effect between position and job satisfaction on retention intention (F(1, 222) = .171, p = .679). Nevertheless, the main effect of position and 32.