Research Background ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 2
Civil aviation plays a crucial role in the economic and technical development of countries, showcasing the application of advanced scientific achievements It is intricately linked to national security, defense, and foreign economic relations Vietnam's civil aviation sector has made significant strides in modernization and reform, demonstrating resilience even during global economic crises The aviation industry has experienced rapid growth, particularly due to the resurgence of emerging economies in the Asia-Pacific region, positioning Vietnam for a positive outlook in aviation sector growth.
Vietnam's aviation sector has expanded significantly, now connecting domestic airports to various continents with modern aircraft Enhanced facilities for passengers, including additional terminals, extended runways, and upgraded aprons, have transformed the travel experience.
The Vietnam aviation market has experienced significant growth over the past five years, with an average annual increase of 15% According to the Civil Aviation Administration of Vietnam, the sector has maintained high growth rates from 2010 to 2014 The International Air Transport Association (IATA) reported that during the period from 2013 to 2017, Vietnam ranked seventh among the fastest-growing aviation markets globally In 2014, the total passenger transport market reached approximately 32 million passengers, reflecting a 10.6% increase from 2013, while the freight market grew by 12.6%, totaling around 706 thousand tons From 2010 to 2014, the average growth rates for passenger and freight transport were 12.4% and 14.6%, respectively.
Vietnam's aviation sector has experienced significant growth in both passenger transport and freight services, driven by strong demand in the Southeast Asian market This development aligns with the objectives outlined in the "Master Plan for Vietnam Tourism Development."
By 2020, Vietnam aimed to attract 10.5 million international and 47.5 million domestic tourists, with projections for 2030 set at 18 million international and 71 million domestic visitors The tourism sector's revenue was expected to reach $18.5 billion in 2020, contributing 7% to GDP, and grow to $35.2 billion by 2030, representing 7.5% of GDP The tourism industry is anticipated to achieve an average growth rate of over 30% in revenue and 20% in passenger traffic.
The advancement of Vietnam's aviation industry hinges on enhancing the management capabilities, professional skills, and service quality of its personnel, including management staff, technicians, air traffic controllers, flight attendants, and ground service staff This development involves both basic and advanced training programs tailored to domestic and international operations As the industry integrates and evolves, it requires the mobilization of all resources, with a particular emphasis on internal factors, where the human element plays a crucial role in achieving sustainable growth and competitiveness Consequently, the industry is prioritizing the planning, training, and retraining of staff to meet international standards In addition to domestic academic programs, airport groups are investing in overseas training for their staff to access advanced technologies and enhance service quality.
As of December 2012, the aviation labor is 32,695 people with the following structure:
Figure 1.1 Vietnam aviation labor structure
(Source: Civil Aviation Authority of Vietnam, 2012)
The average age of employees is from 31 to 33, which under 30 is 37.3%, 30-
40 is 35.2%, 40-50 is 17.9%, and over 50 is 9.6% Educational level of staffs is listed below:
- Primary and technical workers: 9737 people (29.8%)
Administrative and Enterprise Aviation business
Figure 1.2 Vietnam aviation educational labor standards
(Source: Civil Aviation Authority of Vietnam, 2012)
The aviation industry is witnessing a trend of highly qualified university graduates entering the workforce, which bodes well for its future development However, despite the influx of skilled employees, a significant labor shortage persists, presenting a challenge for management To maintain operational stability, civil aviation organizations are hiring thousands of new staff annually Additionally, the turnover rate among aviation workers has been rising at an alarming pace, with an increasing number of employees switching jobs.
The Civil Aviation Authority of Vietnam reports that the turnover rate in the aviation sector has averaged between 20% and 40% annually in recent years, with particularly high rates in air traffic and airport corporation operations Ground service staff, a crucial component of air traffic management, experiences significant turnover, prompting airlines to recruit new employees biannually to address the ongoing shortage.
Unskilled workers5% scale of the civil aviation sector is growing This is really a concern of managers for the stable operation of civil aviation sector.
Research Problem ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 6
The increasing employee turnover rate significantly impacts workplace morale and productivity, leading to higher recruitment and training costs for companies Various factors contribute to employee departures, including low salaries, excessive workloads, lack of motivation, insufficient training, and inadequate recognition Recently, customer verbal aggression has emerged as a critical issue, particularly affecting customer service employees' mental well-being According to Aquino-Nemecek, director of the United Airlines Red Carpet Club in Los Angeles, working in airline customer service is particularly challenging, as employees frequently face complaints and rude behavior from passengers, which can lead to feelings of tension and demotivation.
Ground service staff in the aviation industry face significant challenges due to frequent interactions with passengers from diverse backgrounds, necessitating a high level of knowledge and professional service skills The dual pressures of work demands and customer satisfaction contribute to employee stress and depression, particularly when faced with aggressive or disrespectful behavior from passengers Incidents of verbal and physical abuse towards aviation employees are increasingly reported in the media, highlighting the toll such interactions take on staff morale For instance, a woman was fined 7 million VNĐ for assaulting an aviation worker over a payment dispute, while another incident involved a passenger physically attacking staff for requesting identification According to Mr Lai Xuan Thanh, Director of the Vietnam Civil Aviation Authority, the first half of 2015 saw approximately 30 million air passengers and 41 reported safety incidents, with a notable increase in human-related issues due to passengers ignoring regulations The cumulative stress from job demands and customer hostility often drives employees to seek alternative employment for improved well-being.
Some researches of foreign authors mentioned and studied about the impact of customer verbal aggression to employees, such as:
“Influence of customer verbal aggression to turnover intention” (Xiaoyan Li and Erhua Zhou, 2013)
“The customer is not always right: customer aggression and emotion regulation of service employees” (Grandey et al., 2004)
“Outcomes of customer verbal aggression among hotel employees” (Osman M
Karatepe, Ilkay Yorganci and Mine Haktanir, 2009)
“Frontline service employees’ customer-related social stressors, emotional exhaustion, and service recovery performance: customer orientation as a moderator”
(Taegoo Terry Kim, Soyon Paek, Chang Hwan Choi, and Gyehee Lee, 2012)
Coping with customer aggression is a significant concern for service workers, as highlighted by Dormann and Zapf (2004), who identified customer abusive behavior as a major source of stress Despite this, limited research has explored how organizational or personal resources can buffer the negative effects of frequent customer hostility Most existing studies focus on specific sectors like call centers and hotels, leaving a gap in understanding the impact of verbal aggression on ground service staff in the aviation industry In Vietnam, research predominantly addresses organizational factors influencing employee turnover, with minimal attention given to customer-related issues.
This study investigates the impact of customer verbal aggression on emotional exhaustion and turnover intentions among ground service staff in Vietnam's aviation sector, considering the roles of negative affectivity and stress appraisal The research aims to provide solutions to mitigate these adverse effects.
Research Objective and Research Questions ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 8
This research investigates how customer verbal aggression affects employee emotional exhaustion and turnover intention among ground service staff at Tan Son Nhat International Airport, Da Nang International Airport, and Noi Bai International Airport.
- Is there a significant effect of customer verbal aggression on stress appraisal of customer verbal aggression?
- Is there a significant effect of negative affectivity on customer verbal aggression?
- Is there a significant effect of negative affectivity on stress appraisal of customer verbal aggression?
- Is there a significant effect of customer verbal aggression on employee emotional exhaustion?
- Is there a significant effect of stress appraisal of customer verbal aggression on employee emotional exhaustion?
- Is there a significant effect of customer verbal aggression on turnover intention?
- Is there a significant effect of employee emotional exhaustion on turnover intention?
- Is there a significant effect of stress appraisal of customer verbal aggression on turnover intention?
Research Methodology and Scope ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 9
The research method integrates both qualitative and quantitative approaches to enhance the accuracy and comprehensiveness of the study Qualitative research gathers ideas and opinions, enabling necessary adjustments, while quantitative research ensures a larger sample size for more reliable data analysis Tools like Statistical Package for the Social Science (SPSS) and Analysis of Moment Structure (AMOS) are utilized for data analysis, including testing the reliability of scales using Cronbach’s Alpha, conducting Exploratory Factor Analysis, and validating the findings through Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) to evaluate the hypothesized model.
This study investigates the effects of customer verbal aggression on emotional exhaustion and turnover intention among ground service staff in the aviation industry, specifically targeting check-in and passenger service agents in Vietnam The survey will be conducted via Facebook Messenger, reaching aviation employees primarily in Hanoi, Da Nang, and Ho Chi Minh City Due to time constraints, the research focuses on these two roles In Hanoi and Da Nang, the questionnaire will be distributed digitally, while in Ho Chi Minh City, paper surveys will be directly delivered to staff at Tan Son Nhat International Airport.
Research Significance ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 9
This research aims to shed light on how customer aggression impacts the emotional exhaustion and job turnover decisions of ground service employees The findings offer organizations and managers valuable insights into this prevalent issue in today's workplace.
Understanding the factors associated with customer verbal aggression, such as negative affectivity and stress appraisal, enables managers to develop effective strategies for employee retention and mitigate instances of passenger bullying towards aviation staff.
This research is crucial for effective policy implementation regarding the punishment of cursing, assaulting, and threatening aviation employees By understanding the factors influencing customer verbal aggression on emotional exhaustion and turnover intention, the government can develop policies to protect employees and mitigate the sharply rising turnover rate.
Structure of the research ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 10
The research includes five parts:
This chapter introduces the research background as well as research problems, research objectives and questions, research methodology and scope, and research significance
Chapter 2: Literature Review and Hypotheses
This chapter presents literature reviews of customer verbal aggression, employee turnover intention, stress appraisal, negative affectivity, and employee emotional exhaustion The hypotheses develop from these relationships
Research process, measurement scales, questionnaire design, data collection method, sampling design, and data analysis method are presented more details in this chapter
This chapter presents the comprehensive research findings, highlighting key components such as Sample Descriptive Statistics, Reliability Analysis, Exploratory Factor Analysis, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) Additionally, it includes a discussion of the results obtained from these analyses.
Chapter 5: Conclusions, Implication, and Limitation
The conclusions summarize the study's findings, propose managerial implementations derived from earlier chapters, and outline the limitations affecting these results while also suggesting directions for future research.
This chapter explores various scholarly theories relevant to customer verbal aggression and turnover intention It begins by defining these key concepts, followed by a review of prior research and discussions surrounding them Ultimately, the chapter proposes hypotheses regarding the relationships among these constructs and presents a conceptual model based on the established theories and previous findings.
Review previous study ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 12
Employee turnover refers to the movement of workers within the labor market, encompassing transitions between firms, jobs, and employment statuses, including unemployment (Abassi et al., 2000) According to Price (1977), turnover is calculated as the ratio of employees who leave an organization during a specific period to the average number of employees in that organization during the same timeframe Managers often view turnover as the comprehensive process involved in filling job vacancies.
Sut and Chad (2011) indicated that employee turnover is cause of economic losses of organization It reduces greatly the job efficiency Similarly, Barak et al.,
Employee turnover is a significant concern for organizations, as it can be both detrimental and expensive It negatively impacts overall effectiveness and reduces employee productivity Consequently, managers must invest additional resources and effort into recruiting and training new talent to replace departing employees Therefore, addressing employee turnover is essential for managers to mitigate this hidden burden on their organizations.
Wright and Bonett (2007) categorize employee turnover into two types: voluntary and involuntary Voluntary turnover occurs when employees choose to leave an organization for various reasons, often in pursuit of better opportunities or improved working conditions, which can negatively impact the organization In contrast, involuntary turnover happens when employees are asked to leave due to factors such as layoffs or poor job performance, affecting the company's overall benefit.
Numerous scholars, including Price (1997), have identified a strong correlation between employees' intent to stay and voluntary turnover Most organizational research focuses on voluntary quits, as gathering data on employees who leave voluntarily presents challenges (Currivan, 2000; Price, 1997).
Turnover intention is widely recognized as a strong predictor of actual turnover and a crucial aspect of understanding employee behavior (Lee and Bruvold, 2003) While Van Dick et al (2004) argue that the intention to leave does not equate to actual turnover, it is important to note that a positive turnover intention can indicate an employee's desire to remain with an organization, ultimately influencing voluntary turnover positively (Griffeth et al., 2000) Overall, the concept of turnover intentions is supported by numerous scholars as a significant factor in employee turnover (Lee and Bruvold, as cited in Roberts et al., 1999).
Employee turnover intention refers to the gradual process that begins with contemplating resignation, progresses to the intention of seeking new employment, and culminates in the decision to either leave or remain in a current job (Jacqueline and Milton, 2007).
Verbal aggression in the workplace, as identified by Infante and Gorden (1989, 1991), correlates positively with both dissatisfaction regarding the message source and overall job dissatisfaction Despite service providers training employees to meet service standards, customer perceptions of service value remain crucial The prevalence of unfriendly or aggressive behavior directed at employees in service organizations is an escalating issue (Grandey et al., 2004).
Customer verbal aggression is a significant dimension of customer-related social stressors, as highlighted by Dormann & Zapf (2004) This behavior involves customers intentionally attempting to harm employees through their choice of words, tone, or mannerisms, which can include swearing, yelling, and sarcasm.
Human service employees are generally required to ‘serve with a smile’
Service providers often face a chronic need to regulate their emotions to meet organizational demands, especially when confronted with anger-provoking events that require them to suppress their true feelings (Grandey, 2000) A prevalent source of such anger arises from aggressive customer behavior during service interactions (Grandey et al., 2002) Verbal abuse from customers is a common issue; for example, many airline employees report experiencing verbal abuse at least once a month (Boyd, 2002).
Emotions are defined by Crow LD and Crow A (1991) as an internal state of turmoil that helps individuals adjust to their environment, ultimately promoting well-being and safety These emotions can manifest in various forms, including anger, sadness, fear, pleasure, love, surprise, annoyance, and embarrassment Understanding these emotional states is crucial before delving into the theories of emotional exhaustion.
Emotional exhaustion is a key component of burnout, alongside depersonalization and low self-esteem (Maslach, 1993) Individuals facing emotional exhaustion often feel depleted of emotional resources, leading to frustration, despair, and apathy towards work, which hinders their ability to provide psychological services This condition typically arises from excessive dedication and commitment to work, prioritizing professional responsibilities over personal needs The resulting pressure to perform can stem from internal expectations or demands from colleagues, fostering feelings of guilt that compel individuals to exert even more effort When their reality fails to align with their ideals, they may continue to strive for unattainable goals, ultimately leading to fatigue and frustration due to unmet expectations (Farber, 1991).
Emotional exhaustion, also known as emotional depletion or burnout, is a condition caused by excessive stress, leading individuals to feel drained of their inner resources This state can result in various psychological, physical, and social effects, although it typically does not require medical intervention unless more severe issues arise Recovery is often possible through rest, vacations, or stress reduction However, prolonged stress can lead to emotional depletion, making it difficult for individuals to meet life's demands Common psychological effects include irritability, anxiety, and frustration, alongside fatigue and potential insomnia If left unaddressed, emotional exhaustion may contribute to serious conditions such as depression and gastrointestinal issues.
Emotional exhaustion can be influenced by varying levels of stress tolerance among individuals While there is no precise method to measure the impact of stress on emotional fatigue, it is generally understood that those with strong coping skills are better equipped to handle higher stress levels, making them less susceptible to emotional exhaustion.
Negative affectivity (NA) is a stable, heritable trait characterized by a tendency to experience a wide range of negative emotions, including worry, anxiety, and self-criticism (Keogh & Reidy, 2000) Defined by Watson and Clark (1984) as a higher-order personality variable, NA reflects the frequency and intensity of distressing emotions like anger, hostility, fear, and anxiety Research indicates that individuals with high NA consistently experience negative moods, regardless of the situation, and often focus on the negative aspects of themselves and others, leading to lower life satisfaction (Watson & Pennebaker, 1989) Additionally, those high in NA tend to exhibit more independence and individualism, but are frequently perceived as hostile, demanding, and distant due to their negative emotional states (Watson & Clark, 1984).
Individuals with high negative affectivity (NA) tend to emphasize their own negative traits, dissatisfaction with their jobs, and a pessimistic view of the world (Watson & Clark, 1984) This predisposition makes them more likely to perceive slightly negative or ambiguous social cues as threats As a result, high NA individuals often exhibit heightened sensitivity to perceived threats, leading them to engage in hostile behaviors more frequently than those with low NA This pattern may contribute to their reputation as less likable employees and their struggles in maintaining positive relationships with supervisors.
2.1.1.5 Stress appraisal of customer verbal aggression
Hypotheses and Research Model Development ããããããããããããããããããããããããããããããããããããããããããããããããããããããã 18
2.2.1 Customer verbal aggression and Stress appraisal
Stress appraisal is the individual's perception of a stressor as threatening or stressful, often accompanied by negative emotions such as fear or anger, along with physiological arousal (Lazarus & Folkman, 1984) Richard Lazarus, who researched stress and emotions for over four decades, established a connection between appraisals and stress levels Furthermore, appraisal involves evaluating the significance of interactions between the individual and their environment concerning their overall well-being.
Verbal aggression from customers can create significant stress for employees, as it indicates unmet customer satisfaction (Averill, 1983) The frequency of such aggressive encounters can heighten feelings of arousal and apprehension, leading to increased fear in the workplace While some may argue that repeated exposure could lead to habituation, individuals typically respond strongly to perceived threats Consequently, a higher incidence of verbal aggression is likely to correlate with a heightened perception of threat among employees.
H1: There is a positive impact of Customer verbal aggression on Stress appraisal of customer verbal aggression
2.2.2 The impact of Negative affectivity on Customer verbal aggression and
Stress appraisal of customer verbal aggression
Negative affectivity is defined by feelings of dissatisfaction, pessimism, and a heightened reactivity to everyday stressors, leading individuals to focus on the negative aspects of life (Watson and Clark, 1984) This affective personality type plays a crucial role in how individuals assess stress and choose coping strategies Research indicates that those with high negative affectivity are more likely to react intensely to negative workplace events (Penney and Spector, 2005) and often resort to less effective coping mechanisms such as avoidance, disengagement, and denial (Kluger and DeNisi, 1996).
Research indicates that emotions such as anger, frustration, and distress are often linked to aggressive behaviors Grandey et al (2004), referencing Berkowitz (1989), suggest that all forms of negative affect, not just frustration, should be acknowledged as potential triggers for aggression While not every type of negative emotion has been studied for its potential to heighten aggression, it is evident that certain negative states can significantly escalate aggressive responses.
An individual difference that is likely to contribute to increased frequency and stress appraisal of customer aggression is the negative affectivity of the service provider
Recent research has overlooked the impact of negative affectivity on self-reported work aggression (Schat & Kelloway, 2000) Individuals with high levels of negative affectivity tend to possess a pessimistic worldview, often interpreting ambiguous remarks in a negative light (Spector, Chen, & O’Connell, 2000; Watson & Clark, 1984).
Research indicates that individuals with high negative affectivity are more likely to provoke aggression from customers, as noted by Buss (1987) Such individuals often have limited coping resources, leading them to perceive situations as more threatening (Spector et al., 2000) Consequently, negative affectivity is linked to increased customer verbal aggression and heightened stress in response to such aggression.
H2a: There is a positive impact of Negative affectivity on Customer verbal aggression
H2b: There is a positive impact of Negative affectivity on Stress appraisal of Customer verbal aggression
2.2.3 The impact of Customer verbal aggression and Stress appraisal on Employee emotional exhaustion
Emotional exhaustion is characterized by a significant depletion of energy and emotional resources due to overwhelming psychological demands (Boles et al., 2000) According to the conversation of resources theory, the loss of resources is perceived as more impactful than their gain (Hobfoll and Shirom, 2001) In the service industry, frontline employees expend their limited emotional resources in response to customer demands, hoping for favorable outcomes in return.
Employees often encounter customer aggression, which drains their emotional resources and hinders their ability to participate in activities that replenish their energy and foster positive emotions.
Service employees are particularly vulnerable to emotional exhaustion due to the need to exert additional effort in managing their emotions when facing job-related stressors This emotional regulation is essential for meeting the demands of their roles, as highlighted by Van Jaarsveld et al (2010) and Zohar et al (2003).
Verbal aggression from customers can lead to emotional exhaustion, a key component of burnout characterized by depleted emotional resources and a lack of energy due to overwhelming psychological demands (Grandey et al., 2004).
Stressful emotions significantly impact both health and organizational outcomes, extending beyond mere work aggression frequency This suggests that the nature of these emotions may clarify the connection between the occurrence of stress-related events and their resulting effects.
As customer aggression rises, it leads to increased stress levels, resulting in burnout Grandey et al (2004) highlight that the stress appraisal of such situations triggers significant emotional and physiological responses.
The model focuses on the extent that employees feel threatened by customer verbal aggression (stress appraisal), while emotional exhaustion represented psychological and behavioral forms of strain
H3a: There is a positive impact of Customer verbal aggression on Employee emotional exhaustion
H3b: There is a positive impact of Stress appraisal of Customer verbal aggression on Employee emotional exhaustion
2.2.4 The impact of Customer verbal aggression, Stress appraisal of customer verbal aggression, and Employee emotional exhaustion on Turnover intention
Service workers have limited ways to respond to customer aggression
Quarreling with customers can lead to complaints, poor performance reviews, and management sanctions, prompting service workers to adopt problem-solving, escape-avoidance, and support-seeking strategies to handle customer aggression (Skinner et al., 2003) Escape-avoidance strategies, such as withdrawing from chaotic situations, are common as workers aim to protect themselves from further harm (Cole and Bedeian, 2007; Halbesleben, 2006) The conversation of resources theory suggests that excessive demands or insufficient resources can result in negative emotions and dysfunctional behaviors (Shaffer et al., 2001) Additionally, verbal abuse from customers triggers strong emotional reactions in service employees, leading to quick physiological, cognitive, and behavioral responses (Taylor).
Customer aggression in the workplace often leads to negative outcomes, including job dissatisfaction, turnover intention, and absenteeism (Yagil, 2008; Karatepe et al., 2009) Despite these associations, there is a lack of empirical evidence directly linking customer aggression to increased turnover intention (Karatepe et al., 2009).
Therefore, the following hypothesis is proposed:
H4a: There is a positive impact of Customer verbal aggression on Turnover intention
High emotional exhaustion significantly impacts individual performance by diminishing the resources needed to meet job demands, creating a cycle of increasing exhaustion and declining performance (Baba et al., 2009) This state of emotional fatigue can lead employees to consider turnover as a coping mechanism (Yavas et al., 2008).
Conceptual model ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 23
H1: There is a positive impact of Customer verbal aggression on Stress appraisal of customer verbal aggression H2a: There is a positive impact of Negative affectivity on Customer verbal aggression
H2b: There is a positive impact of Negative affectivity on Stress appraisal of customer verbal aggression
H3a: There is a positive impact of Customer verbal aggression on Employee emotional exhaustion
H3b: There is a positive impact of Stress appraisal of Customer verbal aggression on Employee emotional exhaustion
H4a: There is a positive impact of Customer verbal aggression on Turnover intention
H4b: There is a positive impact of Employee emotional exhaustion on Turnover intention
Stress appraisal of Customer verbal aggression
H4c: There is a positive impact of Stress appraisal if customer verbal aggression on Turnover intention
This chapter reviews literature on customer verbal aggression, emotional exhaustion, and turnover intention, establishing a research model that includes eight hypotheses to demonstrate the effects of customer verbal aggression on employee emotional exhaustion and turnover intention The subsequent chapters will delve into the research methodology and findings.
This chapter outlines all procedures for both qualitative and quantitative research The qualitative study, which includes in-depth interviews, aims to modify and refine the measurement tools To assess the model and hypotheses, a quantitative research approach will be utilized, with data collected through a questionnaire survey.
This chapter describes research process, research design, sampling method, data analysis, measurement scales, and the results.
Research process ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 25
A qualitative study and a quantitative study were undertaken in this research
The draft questionnaire was developed based on prior research and included five key measurement scales: negative affectivity, frequency of customer verbal aggression, stress appraisal of customer verbal aggression, emotional exhaustion, and turnover intention The questions were translated from English to Vietnamese to ensure clarity and relevance The research design comprised two phases: a pilot study followed by a main survey.
A pilot study is a smaller-scale version of a larger research project, designed to test the feasibility of research tools and methods (Zikmund, 2003) It serves as a pretest for new data collection techniques, allowing researchers to evaluate equipment and methodologies before full-scale implementation (Rowan, 2011) In this study, a pilot test was conducted through direct interviews with five individuals working in the aviation industry, providing valuable insights while utilizing fewer participants than would be required for a comprehensive study.
The main survey utilized two methods for data collection: face-to-face and online questionnaires The face-to-face method involved distributing hard copies of the questionnaire to employees at Tan Son Nhat International Airport Due to geographical constraints, the online questionnaire method was employed, with responses collected through Google Surveys.
Literature review Research model and
Testing Cronbach alpha Testing item – total correlation
Analysis Convergent validity Discriminant validity
Testing Structural equation modeling Testing Boostrap
Limitation the link to Facebook friends who are working in Noi Bai International Airport and Da Nang International Airport
The model was tested using SPSS 20 and Amos 20, employing a systematic analysis of the collected data This process included assessing reliability through Cronbach’s Alpha, followed by Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) tests.
Measurement Scale ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 26
In this research, measurement scales were adapted from previous studies, utilizing 08 items from Dorman & Zapf (2004) to assess customer verbal aggression, 04 items from Jaramillo et al (2009) to evaluate turnover intention, and 03 items from Wilk and Moynihan (2005) to measure emotional exhaustion Additionally, stress appraisal was measured using 04 items based on the work of Cohen, S., Kamarck, T., and Mermelstein.
R (1983); and Negative affectivity was measured by 06 items based on Watson and Watson et al., (1988)
To assess customer verbal aggression, the author utilized an eight-item scale adapted from the Customer-Related Social Stressors (CSS) scale created by Dorman and Zapf (2004) This construct employed a five-point Likert scale ranging from "1 = not at all true" to "5 = absolutely true."
CVA1 Customers often shout at us
CVA2 Customers personally attack us verbally
CVA3 Customers are often complaining about us
CVA4 Customers get angry with us even over minor matters
CVA5 Some customers argue all the time
CVA6 Customers vent their bad mood out on us CVA7 The customers often criticize us – they never see what is well done
CVA8 If an error occurs, the customers often blame us - never themselves
The emotional exhaustion scale was adapted from the research conducted by Wilk and Moynihan (2005), utilizing a three-item format To assess responses, a five-point Likert scale ranging from "1 = strongly disagree" to "5 = strongly agree" was employed.
EMO1 I feel burned out from my work
EMO2 I feel fatigued when I get up in the morning and have to face another day on the job
EMO3 I feel frustrated with my job
To assess employee turnover intention, Jaramillo et al (2009) utilized a four-item scale based on a five-point Likert scale, ranging from “1 = strongly disagree” to “5 = strongly agree.” This measurement effectively evaluates the extent of employees' decisions to leave the organization.
TOI1 I do not think I will spend my entire career with this organization
TOI2 I have decided to quit this organization TOI3 I am looking at other jobs now
TOI4 If I do not get promoted soon, I will look for a job elsewhere
Stress appraisal of Customer verbal aggression
The study utilized four modified items from the Perceived Stress Scale (PSS) created by Cohen, Kamarck, and Mermelstein in 1983 to assess stress appraisal A five-point Likert scale ranging from "1 = never" to "5 = very often" was employed to quantify this construct.
STRESS1 How often have you been angered because of things that were outside of your control?
STRESS2 How often have you felt difficulties were piling up so high that you could not overcome them?
STRESS3 How often have you felt confident about your ability to handle your personal problems?
STRESS4 How often have you been able to control irritations in your life?
To measure negative affectivity, the author used PANNAS (positive and negative affect schedule) scale, which was developed by Watson (1988); Watson et al.,
(1988), to measure the employees’ feelings about their job
The Positive and Negative Affect Scale (PANAS, Watson et al 1988) consists of 20-item mood scales and was developed to provide brief measures of PA and NA
However, the survey only choose 6 items from both to positive and negative affectivity to clearly understand the meaning of these characteristics
Participants are requested to evaluate their experiences of specific emotions at work over a designated time frame using a five-point Likert scale, ranging from “1 = very slightly or not at all” to “5 = very much.” To align with the context of this study, the wording of the negative affectivity questions will be modified while maintaining the integrity of the scale.
Watson (1988) and Watson et al.,
NEG2 Enthusiastic NEG3 Inspired NEG4 Distressed NEG5 Irritable NEG6 Upset
The meanings of six items are chosen in the questionnaire:
Interested: wanting to give your attention to something and discover more about it/ relating to a person or group who has a connection with a particular situation, event, business, etc.
Enthusiastic: enthusiastic appreciation for something is more than just liking it – it loves it/ having or showing great excitement and interest.
Inspired: being of such surpassing excellence as to suggest inspiration by the gods
Distressed: describes a general feeling of unhappiness
Irritable: easily irritated or annoyed/ abnormally sensitive to a stimulus/ capable of responding to stimuli
Upset: to be disturbed or very unhappy
Questionnaire Design ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 29
This study utilized a mixed-method approach, combining both quantitative and qualitative techniques to enhance research reliability The qualitative component involved pre-testing a Vietnamese version of the survey questionnaire through in-depth interviews with five ground service staff members These interviews facilitated the refinement of questions for clarity and comprehension, ensuring that the survey effectively measured the intended variables As a result of the respondents' feedback, the final survey questionnaires were more clear and understandable.
The study utilized a Likert scale for all survey items, which was initially prepared in English and subsequently translated into Vietnamese by a bilingual academic A minimum sample size of 125 was necessary for data analysis, leading to the distribution of 200 questionnaires both directly and via Google surveys The questionnaire comprised three sections: the first gathered demographic information such as gender, age, and education level, while the second and third sections explored respondents' perceptions of customer verbal aggression, emotional exhaustion, turnover intention, negative affectivity, and stress appraisal related to customer interactions Multiple-choice answers were accompanied by a Likert scale to facilitate data collection for this research.
This research utilized scales developed by authors from Western countries, noting cultural and economic differences that influenced respondent selection A pilot study was conducted using qualitative research methods to gather insights.
The objective of this research is to collect data and refine variables within the measurement scales A pilot test was conducted at Tan Son Nhat Airport in Ho Chi Minh City, yielding valuable insights and feedback that will inform a larger-scale study The findings and comments from in-depth interviews were instrumental in adjusting the measurement scales, as detailed in Table 3.1.
The author conducted direct interviews with ground service employees in the aviation industry, aged 18 to 25, to verify factors related to six hypotheses in the research This age group, identified as having the highest turnover rate (Report of Civil Aviation Authority of Vietnam, 2012), was selected due to their prevalence in recruitment efforts, as employers value their youth and ability to handle work pressure To ensure accuracy and relevance, the author adjusted and redesigned measurement scales from previous studies to align with the study's objectives.
The author developed an initial questionnaire based on a preliminary scale to conduct in-depth interviews with individuals who interact with customers regularly Five participants were interviewed, and their feedback provided valuable insights that helped refine and enhance the final questionnaire Suggestions included revising certain wording and meanings, as well as replacing some questions with more suitable alternatives According to the author, these recommendations aligned well with the participants' professional experiences and understanding.
The questionnaire was restructured into three sections: the first part gathered demographic information, including gender, age, and education level The second and third parts focused on assessing customer verbal aggression, emotional exhaustion, negative affectivity, stress appraisal, and turnover intention Although the original questionnaire was based on scales developed by Western authors and written in English, it was translated into Vietnamese to ensure comprehension among the respondents in Vietnam.
Table 3.1 In-depth Interview Respondents’ Information
The respondents Draft measurement scales Comments Final measurement scales Customer verbal aggression
Nguyễn Văn Hiên – 21 years old (Jetstar Pacific)
Võ Nghĩa – 25 years old (Jetstar Pacific)
The customers always criticize us
All respondents said that they understood this measurement scale
However, the customers “often” criticized them, not
“always”, and they argue them without seeing their trying better
The customers often criticize us – they never see what is well done
Huỳnh Minh Hải – 24 years old (Vietnam Airlines)
The interviewee recommended the researcher should change the sentence by more details to make this item more understandable
I feel fatigued when I get up in the morning and have to face another day on the job
Trương Trần Ngọc Anh – 25 years old (Vietjet Air)
I intend to leave this organization within a short period of time
Almost the respondents did not understand the meaning of this item
Stress appraisal of customer verbal aggression
Nguyễn Văn Hiên – 21 years old (Vietjet Air)
All respondents indicated that they understood the item; however, the question seemed to focus more on negative emotions rather than stress Consequently, they recommended rephrasing the question to better reflect its intended meaning.
How often have you been angered because of things that were outside of your control?
Huỳnh Minh Hải – 24 years old (Vietnam Airlines)
Trương Trần Ngọc Anh – 25 years old (Vietjet Air)
Võ Nghĩa – 25 years old (Jetstar Pacific)
Interested , Irritable, Distressed , Alert, Excited, Ashamed, Upset, Inspired, Strong, Nervous, Guilty, Determined, Scared , Attentive, Hostile, Jittery, Enthusiast, Active, Proud, Afraid
The respondents recommended that the author identify the key characteristics that impact aviation employees, ensuring that these traits are easily translatable into Vietnamese for better comprehension among all participants.
Interested Distressed Enthusiastic Inspired Irritable Upset
Qualitative research plays a crucial role in generating insights and summarizing knowledge, but involving a larger participant base enhances the generalizability and robustness of the findings Therefore, researchers often complement qualitative studies with quantitative research to achieve more comprehensive results.
The final questionnaire for the study was developed after revising the initial draft based on preliminary qualitative research findings The main survey targeted airport ground service employees, specifically check-in and passenger service agents, who frequently interact with passengers A total of 200 questionnaires were distributed, both in paper form and through a Google survey Paper questionnaires were delivered to colleagues at Tan Son Nhat Airport by the author's friend, while the online survey link was shared via Facebook with friends in Da Nang and Hanoi, who work at Da Nang International Airport and Noi Bai International Airport The author encouraged these friends to share the survey link further to maximize response rates.
The author delivered 200 questionnaires to respondents and collected 192 answers from both paper survey and Google survey after deleting 13 unsuitable items.
Sample size and Sampling method ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 34
According to Hair et al (2009), the minimum sample size for statistical analysis should be at least five times the number of independent variables, ensuring reliable results Specifically, for Exploratory Factor Analysis (EFA), the recommended sampling ratio ranges from 5:1 to 10:1 In this research, with five factors and twenty-five items, the required sample size is calculated as 25 multiplied by 5, resulting in a total of 125 observations.
For conducting Exploratory Factor Analysis (EFA), it is essential to have a minimum sample size that is at least five times the number of variables being analyzed, with a recommended total exceeding 100 observations (Hair et al., 2009) In this study, with 25 variables, the minimum required sample size for EFA is 125 observations, ensuring robust and reliable results.
There were some considerations affecting sample size in structural equation modeling (SEM) First, “estimation technique”’, sample size should be between 150 to
400 responses if using the Maximum Likelihood (ML) method Second, model complexity leads to the need for larger samples
Hair, Anderson, Tatham, and Black (2014) suggests sample sizes in the range of 100 to 150 as follow:
1) Minimum sample size - 100: Models containing five or fewer constructs, each with more than three items (observed variables) and with high item communalities (0.6 or higher)
2) Minimum sample size - 150: Models with seven constructs or less, modest communalities (0.5), and no under-identified constructs (two-item construct)
The study encompassed five constructs, each containing more than three items, ensuring high item communalities of 0.6 or higher Consequently, a sample size of 125 was deemed appropriate for the analysis, as supported by Bollen.
In 1989, a study proposed an empirical ratio of at least five observations for each estimated parameter, which included 25 parameters in total Consequently, the targeted sample size was determined to be 125 respondents to ensure robust results.
This research utilized a convenience sampling method to gather data from ground service employees at airports in three major Vietnamese cities: Ha Noi, Da Nang, and Ho Chi Minh City The study ensured a diverse representation, as respondents were sourced from various provinces and cities across Vietnam However, it is important to note that this survey employed a non-probability sampling approach, which may affect the generalizability of the findings.
Data Analysis Method ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 35
In this research, primary data was analyzed using SPSS version 20.0 and Amos 20.0 The author utilized Amos 20 for Structural Equation Modeling (SEM) to improve the model's effectiveness.
Reliability analysis is essential for assessing the dependability of measurement scales, with Cronbach’s Alpha being a key metric in this evaluation For a scale to demonstrate acceptable internal reliability, Cronbach’s Alpha should be 0.6 or higher Additionally, each item’s correlation with the total score of the other items should exceed 0.3, as indicated by Nunnally.
After assessing scale reliability, the Exploratory Factor Analysis (EFA) method is utilized to uncover the underlying factors that account for the correlations among various variables, while also testing for convergent and discriminant validity Convergent validity indicates the extent to which two measurements of the same concept are correlated (Hair et al., as cited in Nguyen, 2012), whereas discriminant validity asserts that measurement scales for different concepts should remain distinct from one another.
Amos 20 ran for CFA with purpose of testing the reliability and validity of measurement model The CFA results indicated the model fit if Cmin/df was less than
The goodness of fit index (GFI) assesses the alignment between the hypothesized model and the observed covariance matrix The comparative fit index (CFI) evaluates model fit by analyzing discrepancies between the data and the hypothesized model while addressing sample size issues inherent in the chi-squared test A CFI value above 0.95 indicates good fit, above 0.9 is considered acceptable, and above 0.8 may be permissible The root mean square error of approximation (RMSEA) measures discrepancies between the hypothesized models and the population covariance matrix, with a value of 0.1 or less indicating an acceptable model fit The author also assessed the reliability of the measurement scale using composite reliability (CR) Additionally, the average variance extracted (AVE) from confirmatory factor analysis (CFA) was utilized to determine convergent validity, while correlations between items were examined to establish discriminant validity.
Structural equation modeling (SEM) is a robust statistical technique used to test hypotheses about relationships between observed and latent variables It estimates path coefficients for each proposed relationship within a theoretical model, allowing researchers to represent, estimate, and validate a network of mostly linear relationships among variables (Hoyle, 1995; Rigdon, 1998).
Chapter three outlines the design of a questionnaire survey that utilized established measurement scales The customer verbal aggression scale consisted of eight items sourced from Dorman & Zapf (2004), while the emotional exhaustion scale included three items adapted from Wilk and Moynihan (2005).
Scale of turnover intention consisted of four items based on scale of Jaramillo et al
In 2009, a stress appraisal scale was developed consisting of four items based on the research of Nguyen, Cohen, Kamarck, and Mermelstein (1983) Additionally, the scale for negative affectivity included six items adapted from the work of Watson and colleagues (1988).
The Vietnamese and English versions of the questionnaire were modified to enhance accuracy and clarity A total of 25 measurement items were utilized to create the survey, which was distributed to 200 respondents.
Chapter 3 outlines the research methodology and data collection and analysis techniques, while Chapter 4 details the analysis results, including respondent demographics, reliability analysis using Cronbach’s Alpha, Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM), and the bootstrap method The chapter concludes with a discussion of the results pertaining to the tested hypotheses.
Data Collection ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 38
The author distributed 200 questionnaires and received 192 responses through both paper and Google surveys However, 13 responses were discarded due to insufficient answers or selecting only one option for all questions Ultimately, 179 valid responses were retained, exceeding the minimum requirement of 125 for data analysis.
Table 4.1: Source of data collection
Source Distributed Collected Response rate Eliminated Valid
Respondents’ Demographics ããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 38
Table 4.1 reveals that a significant majority of respondents were female, comprising 59.2%, while males accounted for 40.8% Additionally, 62.6% of the participants were aged between 18 and 25 years Notably, 87.7% of respondents held at least a college or university degree.
Summary, majority of aviation employees in ground service were female aged from 18 – 25, and they graduated in college or university.
Demographic profile Category Frequency Percentage (%)
Reliability Analysis ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 39
To ensure the reliability of measurement scales in data analysis, Cronbach’s Alpha was utilized as an internal consistency reliability test for each scale in this research model A Cronbach’s Alpha score of 0.6 or higher indicates acceptable internal reliability, while the correlation of each item with the total of the other items in the scale should exceed 0.3 (Nunnally & Bernstein, cited in Nguyen, 2011).
Table 4.2 in the Appendix summarizes the reliability test results for each construct in the model The item NEG1 showed a corrected item-correlation total value of less than 0.3, necessitating a retest of the negative affectivity table In the initial run, all items had corrected item-correlation total values exceeding 0.3, except for NEG2 After removing NEG2, all remaining values surpassed the 0.3 threshold, ensuring compliance with the required standards.
Table 4.3 Reliability test results after deleted items NEG1 and NEG2
The measurements obtained were utilized to develop the primary survey aimed at testing the research hypotheses Subsequently, the author performed exploratory factor analysis (EFA) to validate the measurement scales effectively.
Exploratory Factor Analysis ãããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããããã 40
Following the assessment of Cronbach’s Alpha coefficient, the study employed Exploratory Factor Analysis (EFA) to examine the relationships among internal variables Factors with loadings below 0.5 were excluded, while components with Eigenvalues exceeding 1.0 were retained The aim of EFA is to group items that exhibit strong correlations and are answered consistently by respondents As noted by Hair et al (1995), a minimum sample size of 100 is recommended, and this study met that criterion with 179 valid observations, detailed in Chapter 3.
The study commenced with 23 variables, and the KMO value was found to be 0.841, exceeding the acceptable threshold of 0.7 (Leech et al., 2005) This KMO test indicates that there are sufficient items predicted by each factor Furthermore, the Chi-squared value of Bartlett's test was 2262.657, with a significance value of 0.000, which is statistically significant at p < 0.05 This suggests a strong correlation among the variables, making them suitable for factor analysis (Hair et al., 1995).
Table 4.4 KMO and Bartlett’s Test
Using a rotated component matrix, exploratory factor analysis (EFA) revealed five factors extracted from 23 items, with each factor having an eigenvalue greater than 1.00 The eigenvalues for the first components were 7.793, 2.343, 1.828, 1.425, and 1.290, as detailed in Table D1 (Appendix D) The total variance explained by these factors was 63.823%, indicating that they account for a significant portion of the data variation.
In the next step, Rotated Factor Matrix displayed the items and factor loading
The analysis revealed that factor loading values below 0.5 were deemed unacceptable, as illustrated in Appendix C, which presented the rotated component matrix Specifically, EMO3 exhibited no value, while EMO2 recorded a factor loading of -0.579, also below the acceptable threshold Consequently, the author decided to remove these variables and re-run the analysis.
The KMO value was measured at 0.825, indicating a good level of sampling adequacy, while the Bartlett's Chi-squared statistic was 2168.642 with a significance value of 0.000, which is well below the threshold of p