Disruptive Passenger Behavior Impact on Overall Service Experience: An Appraisal Theory Perspective

Abstract

The aim of this research is to examine the impact of bystander appraisal components, specifically congruence and relevance, on the intention to share negative experiences resulting from disruptive passengers on a flight. The investigation focuses on the mediating factors of negative emotions, satisfaction with service recovery, and trust in the airline. Employing a scenario-based approach, the detailed perceptions of passengers who may not have directly encountered disruptive behavior were explored. A total of 368 questionnaires were collected, and a structural equation model (SEM) was utilized to assess the relationship between bystanders’ appraisal and their intention to share. The results revealed that relevance positively correlated with negative emotions, and congruence significantly affected negative emotions. Moreover, negative emotions had a negative impact on both satisfaction with service recovery (SSR) and airline trust. Both SSR and airline trust, influenced by negative emotions, were found to negatively affect the intention to share. The results will help inform strategies to manage and mitigate in-flight disturbances, so that a high-quality cabin service can be maintained and the overall airline reputation does not suffer.

1. Introduction

The aviation industry, marked by a unique shared-service environment inside aircraft cabins, faces challenges associated with in-flight disruptive behavior. A recent analysis by the International Air Transport Association (IATA) revealed a concerning surge in disruptive passenger incidents in 2022 compared to the previous year. According to the 2022 figures, an unruly incident happened once every 568 flights, which marks a considerable increase from once every 835 flights in 2021 [1]. Unruly passenger behaviors involved various issues, such as being drunk, making noise, initiating violence against other passengers, or sexually harassing others [2]. Physical assault incidents remain very rare, but there was an astonishing increase of 61% over the course of 2021 [1]. From minor disruptions to more severe incidents, these disturbances significantly impact passenger experience and their perception of the overall quality of service.

Furthermore, an escalation in disruptive behavior within the cabin is linked to heightened negative emotions among passengers. Recognizing the crucial role negative emotions can play in the airline service industry is essential, given that these emotions can evoke various coping behaviors, impact customer loyalty, and contribute to shaping the reputation and image of airline service providers [3]. Negative emotions resulting from such events further impact customers in an airline and diminish a company’s overall value.

To the best of these authors’ knowledge, no previous studies have evaluated disruptive behavior, negative emotions, and behavioral intention from other passengers’ perspectives. To fill this research gap, this paper analyzes the increasingly prevalent in-flight disturbances from the viewpoint of other passengers. Passengers who are innocent bystanders, sharing a common negative experience due to disruptive events, are likely to harbor negative attitudes that affect behavior and intention toward the airline as a whole [4,5].

More specifically, this study aims to bridge the research gap by delving into the interplay between bystander appraisal, negative emotions, satisfaction from service recovery, trust, and intention to share negative experiences that result from in-flight disturbances. This investigation aligns with the current discourse in the airline industry, emphasizing the need for a thorough understanding of passengers’ reactions in shared-service environments. Given the complexity of reactions within this unique environment, exploring bystander appraisal and subsequent intentions to share negative experiences contributes not only to academic understanding but also offers practical insights for airlines to enhance their service recovery strategies, maintain high-quality cabin service, and ensure the sustainability of service excellence. This research endeavors to shed light on the critical role played by bystanders in the aftermath of in-flight disturbances, aiming to contribute to improved strategies for managing and mitigating disruptions that deter from sustained cabin service quality and tarnish the overall airline reputation.

2. Theoretical Background

2.1. Disruptive Passenger Behaviors

Over the past decade, there has been a notable increase in reports of in-flight disturbances [1]. As defined by the International Air Transport Association [1], an in-flight disturbance refers to disruptive behavior exhibited by passengers aboard an aircraft during a flight [6]. Such incidents pose potential risks to the safety of both passengers and flight crew members. When these disturbances occur mid-flight, neither passengers nor crew can easily escape the enclosed environment or seek immediate external aid [7]. Though in-flight disturbances theoretically encompass actions from check-in to baggage retrieval, they are commonly linked to disruptions during the flight itself [8]. Different organizations have diverse definitions of terms like air rage, unruly passengers, and disruptive behavior. The United Kingdom’s Sussex Police defines a disruptive passenger as someone who engages in actions aboard an aircraft that contravene UK criminal legislation or could constitute an offense under the Air Navigation Order [9]. Another definition emphasizes in-flight disorder as any behavior that disrupts the safe and orderly operation of the aircraft or jeopardizes the well-being of its occupants or property. While it may not be immediately violent, it is disruptive, threatening, or offensive [10]. Alternatively, the UK defines disruptive behavior in line with the Tokyo Convention, addressing it as actions that are criminal offenses, jeopardize aircraft safety or the safety of passengers or property, or disrupt good order and discipline onboard [11]. According to the International Transport Workers’ Federation (ITF), disruptive passenger behavior refers to any behavior on an aircraft that hampers cabin crew duties, disrupts safe operations, or risks the safety of occupants, excluding more potentially catastrophic behaviors such as premeditated sabotage or terrorism [8].

Research on disruptive passenger behavior primarily appears in aviation industry periodicals, with limited academic papers available [12]. DeCelles and Norton [13] have also noted the absence of empirical research exploring the triggers of such in-flight disruptions. For this study, in-flight disorder is defined as “disruptive and aggressive behavior by unruly passengers during a flight” [14].

2.2. Impact of Disruptive Behavior on Other Passengers

Other customers present during service delivery, are perceived as contributors to the service experience, functioning as co-producers or co-creators [15]. They reshape the conventional understanding of customer-to-customer interactions. Consequently, the behaviors of other customers within this service environment inevitably shape the experiences of everyone within the group [16]. Positive interactions among customers can enhance the overall service they encounter [17]. Conversely, negative interactions can evoke a sense of injustice or dissatisfaction [18]. Among these negative impacts, disruptive behavior by other customers stands out as a common issue within service contexts. Such behavior encompasses unproductive actions that detrimentally affect service operations and the experiences of focal customers [19,20]. In shared public settings like theme parks, tourism attractions, hotels, restaurants, and airplanes, customers can directly influence each other’s encounters or indirectly shape the environment itself [16,19,21,22]. These indirect customer-to-customer interactions hold substantial relevance as they significantly mold customers’ assessments of the service provider and influence their future intentions [22]. As a result, service providers cannot overlook negative interactions [23]. Traditionally, research on service failures has centered on situations where service providers directly failed to deliver satisfactory service [24]. Strategies against disruptive customer behavior have often focused on triage or recommended recovery tactics [19,20,25,26].

Miao et al. [4] examined the functions of felt and expressed emotions in both positive and negative interactions among customers. Nevertheless, the existing literature still lacks clarity on how fellow customers may react to misconduct, especially in terms of overt emotional expressions. Consequently, there is a gap in understanding how disruptive passenger behavior affects the service experiences of focal customers beyond conjecture from the service provider’s standpoint.

2.3. Appraisal Theory

This study leverages appraisal theory to investigate how passengers respond behaviorally to other passengers’ misbehavior by studying customers’ perspectives [27,28]. Bagozzi et al. [29] emphasize that an individual assesses whether an encounter with the environment aligns with the current situation. Contrary to popular belief, it is not the specific events themselves that trigger emotions, but rather, it is the individual’s evaluation and interpretation of these events that shape their emotional responses. Appraisal theory, which elucidates the psychological processes individuals undergo when exposed to environmental stimuli, offers two main perspectives. Some scholars focus on the limited dimensions of emotions and relational meanings, while others consider mental processing [27,28]. The evaluation process initiates with primary appraisal, where customers assess the alignment and significance of others’ behaviors with their own goals. If these behaviors are perceived as disruptive and incongruent with customers’ objectives, a secondary appraisal ensues, eliciting thoughts that trigger negative emotions. An individual’s behavioral intentions are influenced by an appraisal process that begins with initial cognition (primary appraisal) and progresses through subsequent cognitive and emotional evaluations (secondary appraisal) [30]. Lazarus’s [27] assessment theory serves the basic structure for this study for four reasons. Firstly, it frames the overall evaluation of environmental stimuli when customers encounter disruptive behavior. Secondly, it elucidates that interactions between customers are dynamic [31,32,33], Thirdly, it permits a deeper exploration of the appraisal processes [34]. Lastly, it shows the complexity of threatening situations caused by disruptive behavior [35].

Lazarus’s [27] model includes a secondary appraisal step, adding depth and complexity to the interpretation of appraisal dimensions [36]. The incorporation of secondary appraisal is crucial as the evaluation process will be different based on the nature of the incident [28]. Some events are cognitively intricate, necessitating a series of secondary evaluations to determine follow-up behaviors [37]. Advancements in evaluation theory and evidence from the recent literature underline the robustness of Lazarus’s [27] two-stage framework. Before Lazarus’s model, Arnold [35] initially proposed appraisal theory to investigate the disparities in emotional reactions to identical events across individuals and situations [36]. Current developments emphasize the complexity of the appraisal process, prompting the amalgamation of cognitive, emotional, motivational, and somatic components [36]. Cognitive appraisal theory has gained prominence in recent decades as it explains emotion formation [38]. According to this theory, emotions are triggered by an initial cognitive judgment of the event, suggesting that emotions emerge rather than being consciously determined [39]. Recent evidence from neuroscience and somatic components suggests that each assessment stage’s outcomes impact behavioral tendencies, preparing individuals for action within Lazarus’s appraisal theory [31,33]. Thus, preliminary appraisal, the initial judgment of the encountered event, influences each component of the appraisal process.

Primary Appraisal

Primary appraisal is the initial assessment when an individual compares environmental stimulus, such as the disruptive behaviors of other customers, to their initial expectations [28]. This process bestows personal relevance to situations, signifying their potential to evoke emotional responses rather than merely a temporal sequence-based response [27]. Consequently, perceptual filters, like beliefs, values, and personal relevance, can significantly shape a person’s evaluations and reactions to events. Through primary appraisal, customers gauge the relevance of an event to their personal beliefs, including perceived fairness and moral values (i.e., equity), determining whether it aligns with their core values [40]. The crucial dimensions of primary assessment are relevance and congruence [41]. Evaluating the match between a goal and a value or belief helps determine the emotional significance of an event [41]. Thus, discrepancies between events and expected goals trigger primary appraisal, leading to robust cognitive and emotional responses when there is low congruence or high relevance [27]. However, emotions can be elicited without necessarily undergoing the entire primary appraisal process [32,42]. In particular, agency concerns whether personal goals can explain outcomes [43]. This study focuses on scenarios of disruptive customers where service providers are held accountable for a customer’s unpleasant experiences. Certainty involves assigning known or definite outcomes [44]. In service environments like hotels, airports, restaurants, and theme parks, disruptive customer behavior generates clearly unfavorable experiences for focal customers. Shared environments successfully operate based on implicit societal rules, where respectful and courteous behavior is expected [45]. Consequently, all involved parties must be clear about appropriate conduct (e.g., check-in procedures in hotels/airlines, acquiring theme park tickets, or restaurant dining) [46]. In the tourism industry, disruptive customer behavior is likely to disrupt the service experience of key customers by violating the norms of pleasant experience. When customers perceive that disruptive behavior is conflicting with their goals and beliefs, negative emotions (e.g., irritation, frustration, or anger) can arise due to the presence of this negative stimulus. Hence, this study proposes the following hypotheses:

H1. 

In the presence of disruptive passenger behavior, perceived congruence influences the negative emotions of passengers.

H2. 

In the presence of disruptive passenger behavior, perceived relevance influences the negative emotions of passengers.

2.4. Negative Emotions

Negative emotions can arise when customers’ experiences are marred by the misbehavior of other customers, leading to feelings of frustration, annoyance, irritation, anger, and outrage [31,47]. While service failures are inevitable in business activities, they often provoke negative emotions in customers [3]. Anger tends to intensify during service failure situations [48,49]. Industries like tourism and hospitality must monitor service attributes, such as ambiance, to minimize disruptive conditions and ensure a comfortable customer stay [50]. The amalgamation of irritation and annoyance can cause anger to manifest in different ways [4,51]. Outrage, more complex than anger, arises when moral norms like fairness and justice are breached. It often revolves around the interests or welfare of an individual, particularly when a service provider’s behavior clashes with the customers’ main goals and values [52]. Expressing negative emotions when others are at fault is a common adaptive strategy [53], and research indicates that the expression of negative emotions can further provoke confrontational or retaliatory behaviors [54]. With this in mind, customers might choose to alleviate additional emotional stress by abstaining from expressing negative feedback directly and instead voice their dissatisfaction to friends, relatives, and on social networks. Anger is a significant emotion in marketing research; it is a strong emotion which leads consumers to complain and share negative experiences [49,55]. Previous studies have shown that negative emotions can drive consumer retaliation [56,57,58]. Bougie et al. [55] highlighted that anger can prompt consumers to voice complaints and share unpleasant experiences with others, while Bonifield and Cole [48] demonstrate that heightened anger levels can result in increased intentions to switch services/providers. Frustration is an emotion that differs from anger as it stems from external situational factors [59,60]. It arises when customers perceive that circumstances beyond their control have led to stressful events. Consequently, when customers feel frustrated, they may be inclined to voice complaints, share negative experiences, or consider switching, as these actions often offer them a sense of relief or comfort [61].

Despite increased attention on emotions in service encounters, there is also a dearth of research on how emotions impact service recovery [62,63]. A recent study has begun to investigate the influence of emotions on trust in service recovery situations [64]. Highly negative emotions, like anger, can notably damage trust in service providers during recovery processes. Mitigating these intense negative emotions can aid in rebuilding trust [64,65]. Emotions also wield significant influence on satisfaction with service recovery [63]. The impact of negative emotions on service recovery satisfaction (SSR) and trust has been demonstrated, and two further hypotheses of this study are as follows:

H3. 

Passengers’ negative emotions affect service recovery satisfaction (SSR).

H4. 

Passengers’ negative emotions affect airline trust.

2.5. SSR (Satisfaction with Service Recovery) and Trust

Customer satisfaction stems from the post-evaluation of service experiences. Prior research has underscored the influence of service recovery assessments on satisfaction. A customer’s evaluation of service recovery can affect whether their satisfaction level is indifferent, positive, or negative [66,67,68,69,70]. Satisfaction occurs when the overall service or product experience exceeds pre-use expectations, leading to a positive confirmation of expectations [71,72]. Service recovery satisfaction (SSR), a form of transaction-specific satisfaction, represents customers’ emotional response to a company’s handling of complaints [73]. In this study, SSR refers to customers’ affective perception of the process and outcomes related to service failure recovery [74]. McCollough et al. [75] conducted an experiment in which they intercepted airline passengers in scenario-based situations to analyze their satisfaction after service failure and recovery. Their findings highlighted distributive and interactional justice as crucial predictors of post-recovery satisfaction.

Trust arises when customers have confidence in the integrity of a company [76,77]. It concerns beliefs regarding the other party’s benevolence, competence, and truthfulness [78]. Trust develops gradually based on perceptions of the provider’s reliability and ethical conduct [76]. Positive service interactions enhance trust levels, influencing long-term relationships [79]. In the context of service recovery, customers’ trust is demonstrated by their willingness to accept vulnerability and their expectations for a positive resolution of service failures [80]. Unsatisfactory complaint resolutions diminish organizational trust [81], while effective resolutions contribute to increased trust. This study proposes the following hypothesis based on the given premises:

H5. 

Passengers’ satisfaction with service recovery (SSR) affects trust in the airline.

2.6. Intention to Share

Katz and Lazarsfeld [82] pioneered word-of-mouth (WOM) research, proving that WOM has a superior influence to actual marketing. Prospective customers often seek information from social media or seek advice from family and friends before deciding on a purchase; the information then significantly impacts their choices. Both offline and online WOM is instrumental when devising or seeking to enhance marketing strategies [83]. Duan et al. [84] defined online word-of-mouth (eWOM) as the use of an online platform where existing and potential customers exchange positive or negative experiences. They emphasize that WOM is a powerful means of sharing opinions and perspectives among individuals [84]. Word-of-mouth (WOM) plays a crucial role in shaping customers’ purchasing decisions [85,86]. This was corroborated by Sotiriadis et al. (2013) [86], where 78% of customers relied on online WOM recommendations for decision-making.

Social media, as elucidated by Kaplan and Haenlein [87], encompass internet-based platforms enabling customers to share opinions, experiences, and perspectives across social networking sites, blogs, and content spaces. They grant customers the ability to publicly express their perceptions regarding products or services. Publicly broadcasted messages on social media platforms also boost market visibility and enhance customers’ negotiation power [88,89]. Poynter [90] underscored the significant influence of information on social networking sites on users. It was discovered that 70% of customers access social media for product-related information, and 49% base purchasing decisions on these platforms [91]. However, it is important to be cognizant that brands who try to leverage social media for promotion can also face issues such as offensive and negative comments or reviews [92]. Xia [93] highlighted those businesses on social media continually facing public complaints, criticism, and adverse incidents from both customers and non-customers [93].

2.7. SSR, Trust, and Intention to Share

Customer satisfaction often leads to increased customer retention rates and positive word-of-mouth (WOM) [94,95,96,97]. Satisfied customers tend to spread positive WOM, contributing to a company’s retention of customers and favorable image [98]. This phenomenon holds true even in potentially adverse service recovery situations where satisfied customers are more inclined to share their experiences through WOM [99,100,101,102]. Positive WOM not only aids in customer retention but also attracts new customers, enhancing the company’s appeal [66]. As trust in a company grows, customers become more apt to engage in positive WOM [74,76,81]. DeWitt et al. [81] conducted scenario-based experiments in restaurant and hotel settings, revealing trust as a key mediator between customer loyalty and perceived justice [69].

The study reveals that trust, developed through fair service recovery, significantly impacts customers’ attitudes and behaviors towards service providers. Similarly, Kim et al. [74] confirmed a positive association between trust and customers’ WOM and intentions. Trust is considered foundational in nurturing successful marketer–customer relationships [76]. Moreover, it influences individuals’ willingness to share information and content [99,100], promoting co-creative behaviors such as information exchange and recommendations among customers [76,100]. The trust dynamic may evolve over time with positive changes in the customer–company relationship. These aspects form the foundation of the following hypotheses:

H6. 

Passengers’ satisfaction with service recovery (SSR) affects their intention to share.

H7. 

Airline trust affects a customer’s intention to share.

3. Methodology

3.1. Research Design

To further explore the limited framework, a scenario-based online survey was conducted. The survey was designed for two primary purposes in this investigation. Firstly, by conducting it within a specific environment, the emotions of respondents were susceptible to the influence of particular co-passengers in the same space, potentially introducing bias to the aggregated results across diverse respondents [101]. Secondly, the survey focused on instances of disruptive passenger behavior within the aircraft setting. Determining preferences posed challenges owing to the ethical concerns and complexities associated with manipulating passengers’ destructive and disruptive actions [4]. In order to enhance the study’s robustness, two distinct scenarios featuring disruptive situations were crafted. Survey respondents were randomly shown one of the two scenarios. The objective of employing a randomized survey design was to ensure significant validity and reliability, while minimizing biases stemming from extraneous variables such as individual differences and demographics. Irrespective of the scenario, all respondents reported encountering instances of misbehavior by fellow passengers during the flight.

The scenarios selected for the study was based on the most prevalent in-flight disorder in Korea, assaults resulting from excessive drinking and failure to comply with flight attendant instructions. The survey presented two scenarios (refer to the Appendix A), wherein respondents played the role of a “bystander” witnessing disruptive behavior from fellow passengers. Both scenarios depicted an otherwise smooth experience for the respondents in terms of services and the physical environment, until the male passenger in the adjacent seat either opened the emergency door upon landing and attempted to escape or assaulted another passenger after consuming alcohol. In the first scenario, the anxious male passenger next to the respondent opened the emergency door and tried to escape, while in the second scenario, he assaulted a fellow passenger seated next to the respondent after drinking. Survey participants were asked various questions to ascertain their exposure to the manipulated stimuli. When the survey was distributed, an explanation of research ethics was included on the front page of the survey, and it was explicitly stated that participants were under no obligation to take part in the survey if they did not wish to do so. Responses that did not accurately address the manipulation and attention-check questions were excluded from the study. To control for potential confounding factors, variables like the respondents’ perceived reality, ease of understanding, mood, familiarity, and severity were included. The research model is shown in Figure 1.

The questionnaires were developed by adapting and supplementing items from previous studies [102], encompassing primary appraisal (congruence, relevance), secondary appraisal (negative emotions), SSR (satisfaction service recovery), airline trust, and intention to share, as detailed in

Table 1. Survey items.

Constructs	Items	Descriptions	Sources
Congruence	CO1	I believe that the passenger behavior described in the box above is acceptable in an on-board environment.	[26,27,31,36]
	CO2	The passenger described in the box above was able to control his behavior to minimize the impact on other passengers in the cabin.
	CO3	The passengers described in the box above behaved politely and constructively.
Relevance	RE1	The behavior of other passengers can influence my trip experience on an airplane.	[27,31,33]
	RE2	Having a good mood is important to me when traveling by air.
	RE3	It is the purser’s duty to ensure that my trip experience is not negatively affected by the behaviors of other passengers.
Negative Emotions	NE1	I feel angry because of the disruptive passenger’s behavior.	[4,31,104]
	NE2	I feel outraged because of the disruptive passenger’s behavior.
	NE3	I feel frustrated by the disruptive passenger’s behavior.
	NE4	I am annoyed by the disruptive passenger’s behavior.
	NE5	The situation feels unpleasant because of the disruptive passenger’s behavior.
Satisfaction Service Recovery (SSR)	SSR1	I am very satisfied with the way the airline handled flight delays.	[104]
	SSR2	The airline provided recovery services that suited my needs.
	SSR3	The airline offered me a favorable solution.
	SSR4	I am very satisfied with the recovery of service provided by the airline.
Airline Trust	AT1	I believe that the airline can effectively resolve problems caused by service failures.	[104]
	AT2	I believe that the airline takes the interests of its customers very seriously.
	AT3	I believe that the airline can keep their promises to their customers.
	AT4	I have great confidence in this airline.
Intention to Share	ITS1	I intention to share X posts on social media in the future.	[105]
	ITS2	I would like to share posts contributed by other users.
	ITS3	I plan to regularly share X posts on social media.

. The questionnaires were adapted to fit the specific objectives of this study, employing a 5-point Likert scale. A convenience sampling method was applied [103]. Three pilot tests were conducted with 14 volunteers in the Korean airline industry, and the questionnaires were subsequently modified to align with the objectives of this research.

3.2. Measures

Measures drawn from the previous literature were incorporated with slight adjustments to align with the unique setting of the aircraft cabin environment (refer to Table 1). The study measured the primary appraisal using six items to reflect perceived relevance and congruence. The measurement scales were used to assess perceived goal relevance and congruence were formulated based on the recommendations of Kähr [31] and Lazarus [27], considering the nature of the passenger goal [36]. The measurement scales are further examined in the data analysis. Negative emotional states were measured using the following five feelings: angry, frustrated, irritated, outraged, and annoyed [4,31]. All items were measured on a 5-point Likert-type scale with “1 = Strongly Disagree” and “5 = Strongly Agree”.

3.3. Data Collection and Analysis

The study focused on South Korean passengers and included a diverse sample. The survey was conducted using a Google survey platform over a two-week period. After screening questions and attention checks, a total of 368 valid responses were retained for data analysis. Of these, 193 participants were given the first scenario, while 175 were presented with the second scenario. Statistical analyses were conducted to assess potential variations in responses between the two scenarios, revealing no significant differences in key demographic measures such as gender, age, marital status, and education.

Table 2. Demographic profile [n: 368].

Constructs		n	%	Constructs		n	%
Gender	Male	174	47.3	Work Experience	None	155	42.1
	Female	194	52.7		3 years or less	19	5.2
Age	18~25	149	40.5		3~5 years	10	2.7
	26~34	37	10.1		5~10 years	33	9.0
	35~44	78	21.2		10 years or more	151	41.0
	45~54	59	16.0	Education	High school graduate	165	44.8
	55 or over	45	12.2		Bachelor’s	122	33.2
Marital status	Single	204	55.4		Master’s	57	15.5
	Married	164	44.6		Doctorate	24	6.5
Presence of children	No children	219	59.5	Number of Boardings per year	None	27	7.3
	With children	149	40.5		3~5	116	31.5
Airline Preference	FSC Airlines (Full-Service Carrier)	198	53.8		6~10	44	12.0
	LCC Airlines (Low-Cost Carrier)	170	46.2		11 or more	30	8.2

provides a summary of the sample characteristics. SPSS version 25 was used for various analyses such as descriptive statistics and internal reliability [106], and AMOS 23 was used for CFA analyses such as convergent reliability, discriminant reliability, model suitability analysis, and SEM path analysis, and for testing the hypotheses [107,108].

4. Empirical Analysis

4.1. Descriptive Statistics

Table 2 illustrates the demographic composition of 368 participants, with a gender distribution of 52.7% female and 47.3% male. The largest age group comprises individuals aged 18–25, constituting 40.5% of the total. The distribution across other age ranges is as follows: 21.2% (35–44), 16.0% (45–54), and 10.1% (26–34). Regarding airline preferences, 53.8% of respondents reported using FSC airlines, while 46.2% opted for LCC airlines. Marital status varied, with 55.4% identifying as single and 44.6% as married. In terms of work experience, 42.1% had no prior experience, while 41.1% possessed over 10 years of work experience. Education levels were diverse, encompassing high school graduates (44.8%), Bachelor’s degree holders (33.2%), Master’s degree holders (15.5%), and Ph.D. holders (8.2%).

4.2. Confirmatory Factor Analysis (CFA)

CFA was conducted to verify the validity and reliability of the measurement items and latent variables. As a result of measurement model analysis, all fit indices were found to be within the acceptable levels (χ² = 445.482, df = 194, χ²/df = 2.296, p < 0.001). To meet other internal consistency issues and maintain reliability, Cronbach’s alpha analysis was performed [106]. As shown in

Table 3. Confirmatory factor analysis (CFA).

Constructs		SE	Cronbach @	SMC	AVE	CR
Congruence	CO1	0.028	0.958	0.829	0.886	0.959
	CO2	0.025		0.891
	CO3	0		0.940
Relevance	RE1	0.087	0.789	0.514	0.560	0.792
	RE2	0.079		0.533
	RE3	0		0.635
Negative Emotions	NE1	0.028	0.902	0.738	0.698	0.920
	NE2	0.033		0.729
	NE3	0		0.766
	NE4	0.025		0.669
	NE5	0.024		0.592
Satisfaction Service Recovery (SSR)	SSR1	0.053	0.914	0.690	0.741	0.919
	SSR2	0.049		0.766
	SSR3	0		0.634
	SSR4	0.047		0.876
Airline Trust	AT1	0.058	0.875	0.526	0.645	0.878
	AT2	0.051		0.628
	AT3	0		0.724
	AT4	0.046		0.702
Intention To Share	ITS1	0.043	0.884	0.628	0.721	0.885
	ITS2	0.04		0.707
	ITS3	0		0.829

, all items exceeded the recommended level of 0.7 [109].

To analyze correlations within the given variables, if it exceeded 0.5 and 07, respectively, average variance extracted (AVE) and composite reliability (CR) tests were performed, as shown in Table 3 [110]. The following pairs of CR and AVE values were calculated: [0.959 (CR), 0.886 (AVE)] for congruence, [0.792 (CR), 0.560 (AVE)] for relevance, [0.920 (CR), 0.698 (AVE)] for negative emotions, [0.919 (CR), 0.741 (AVE)] for satisfaction service recovery (SSR), [0.878 (CR), 0.645 (AVE)] for airline trust, and [0.885 (CR), 0.721 (AVE)] for intention to share.

Table 4. Discriminant validity.

Constructs	A	B	C	D	E	F
A. Congruence	1
B. Relevance	0.179	1
C. Negative Emotions	0.199	0.102	1
D. Satisfaction Service Recovery (SSR)	0.006	0.087	0.016	1
E. Airline Trust	0.009	0.060	0.029	0.535	1
F. Intention to Share	0.013	0.100	0.181	0.139	0.149	1

illustrates the discriminant validity, which indicates that correlations within factors reached acceptable levels.

Fit Indices

As shown in

Table 5. Model fit results.

Division	Result		Good Fit	Acceptable Fit	Sources
Absolute fit index	CMIN/DF	1.864	0$\le x^2/df\le$2	$2\le x^2/df\le$3	[111]
	RMR	0.045	0$\le {\mathrm{S}\mathrm{R}\mathrm{M}\mathrm{R}}^{ }\le 0.05$	$0.05\le {\mathrm{S}\mathrm{R}\mathrm{M}\mathrm{R}}^{ }\le 0.10$
	GFI	0.917	$0.95\le \mathrm{G}\mathrm{F}\mathrm{I}\le 1.00$	$0.90\le \mathrm{G}\mathrm{F}\mathrm{I}\le 0.95$
	AGFI	0.894	$0.90\le \mathrm{A}\mathrm{G}\mathrm{F}\mathrm{I}\le 1.00$	$0.85\le \mathrm{A}\mathrm{G}\mathrm{F}\mathrm{I}\le 0.90$
	RMSEA	0.049	$0\le \mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}\mathrm{A}\le 0.05$	$0.05\le \mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}\mathrm{A}\le 0.08$
Incremental fit index	NFI	0.941	$0.95\le \mathrm{N}\mathrm{F}\mathrm{I}\le 1.00$	$0.90\le \mathrm{N}\mathrm{F}\mathrm{I}\le 0.95$
	CFI	0.972	$0.97\le \mathrm{C}\mathrm{F}\mathrm{I}\le 1.00$	$0.95\le \mathrm{C}\mathrm{F}\mathrm{I}\le 0.97$

, fit indices were calculated to maintain the fit of this model. Most fit indices of this model were found to be acceptable or higher than the standard level. Using CFA, the elements in the absolute fit indices reached and exceeded the recommended thresholds with the following results: $x^2$ = 445.482, CMIN/DF = 1.864, RMR = 0.045, GFI = 0.917, AGFI = 0.894, and RMSEA = 0.049. The elements of the incremental fit index reached almost good levels, with NFI = 0.941 and CFI = 0.972. The goodness-of-fit analysis results by the CFA process were highly accurate and acceptable.

4.3. Path Analysis and Hypothetical Test

Figure 2 and

Table 6. Path coefficients among variables and hypothesis results.

Hypotheses				Coefficient	SE	CR	p	Results
H1	Congruence	→	Negative Emotions	−0.421	0.066	−6.379	***	Supported
H2	Relevance	→	Negative Emotions	0.378	0.155	2.437	0.030 **	Supported
H3	Negative Emotions	→	Satisfaction Service Recovery (SSR)	−0.096	0.043	−2.252	0.048 **	Supported
H4	Negative Emotions	→	Airline Trust	−0.082	0.041	−2.007	0.090 *	Supported
H5	Satisfaction Service Recovery (SSR)	→	Airline Trust	0.888	0.068	12.979	***	Supported
H6	Satisfaction Service Recovery (SSR)	→	Intention to Share	−0.312	0.127	−2.459	0.028 **	Supported
H7	Airline Trust	→	Intention to Share	−0.226	0.106	−2.134	0.066 *	Supported

*** p < 0.001 ** p < 0.05 and * p < 0.10.

summarize the proposed research model and path analysis results. The hypothesis linking congruence to negative emotions (H1), with the values of β = −0.421, SE = 0.066, CR = −6.379, and p = 0.000 (p < 0.001), was supported. The hypothesis connecting relevance to negative emotions (H2), with the values of β = 0.378, SE = 0.155, CR = 2.437, and p = 0.030 (p < 0.05), was supported. The hypothesis connecting to negative emotions to satisfaction service recovery (SSR) (H3), with the values of β = −0.096, SE = 0.043, CR = −2.252, and p = 0.048 (p < 0.05), was supported. The hypothesis connecting negative emotions to airline trust (H4), with the values of β = −0.082, SE = 0.041, CR = −2.007, and p = 0.090 (p < 0.10), was supported. The hypothesis connecting satisfaction service recovery (SSR) to airline trust (H5), with the values of β = 0.888, SE = 0.068, CR = 12.979, and p = 0.000 (p < 0.001), was supported. The hypothesis connecting satisfaction service recovery (SSR) to intention to share (H6), with the values of β = −0.312, SE = 0.127, CR = −2.459, and p = 0.028 (p < 0.05), was supported. Finally, the hypothesis connecting airline trust to intention to share (H7), with the values of β = −0.226, SE = 0.106, CR = −2.134, and p = 0.066 (p < 0.10), was supported. The hypotheses were all supported.

As shown in Figure 2, to examine the elicitation of negative emotions, the two dimensions of evaluation (congruence and relevance) were regressed on the negative emotion factor. The findings indicated that relevance was positively associated with negative emotions. Congruence was found to have a significant effect on negative emotions. While negative emotions negatively affected both SSR and airline trust, SSR was positively associated with airline trust. SSR and airline trust, which was influenced by negative emotions, were found to have a negative effect on intention to share. As with previous study results, it was confirmed that the negative emotions of passengers who experienced in-flight disorder increased as relevance increased and congruence decreased.

5. Conclusions and Implications

5.1. Conclusions

This study aims to explore how bystanders’ intention to share negative experiences is influenced by experiencing the disruptive behavior of other passengers during a flight, considering the mediating factors of negative emotions, satisfaction with service recovery, and trust. The study introduces a scenario-based approach, providing practical insights to enhance the overall airline reputation and image, while emphasizing the importance of achieving sustainable cabin service quality.

The results indicated a positive association between relevance and negative emotions, while congruence significantly influenced negative emotions. Additionally, negative emotions were found to negatively impact both satisfaction with service recovery (SSR) and airline trust. Both SSR and airline trust, influenced by negative emotions, were identified as negatively impacting the intention to share.

In conclusion, this research underscores the pivotal role of bystander appraisal in the unique shared-service environment of an aircraft cabin. It highlights how the appraisal of misbehavior significantly influences the intention to share negative experiences. Understanding bystander appraisal as well as implementing service recovery measures in response to misbehavior have been proven important and can enhance satisfaction with service recovery and foster trust in the airline. This research strongly recommends that airlines respond proactively to misbehavior while being attuned to the negative emotional experiences of passengers who are exposed to the situation. Consequently, this study advocates for airlines to address misbehavior incidents within the cabin and actively manage the negative emotions of other passengers to prevent any indirect impact on the overall reputation and image of the airline.

5.2. Implications

This research carries significant theoretical and managerial implications for the airline industry in the Republic of Korea. Prior studies on disruptive passengers in the aviation industry are scarce because previous studies have investigated customer misbehavior in other service industries such as general tourism and the hotel industry. Consequently, this study contributes to the field by being the first one to look at the repercussions of disruptive behavior exhibited by passengers during flights.

Secondly, this paper delves into the underexamined relationship between bystander appraisal components and the intention to share a negative experience, with a specific focus on the in-flight cabin experience. Previous studies had primarily concentrated on the perspectives of the service provider in cases of unruly behavior in shared-service environments focusing on the stress experienced by employees, intentions to resign [112,113,114], or the causes of disruptive behavior [2]. This research is unique in providing analysis from the viewpoint of customers who are bystanders of an incident. Despite the compromised service experience resulting from other passengers’ misbehaviors, people tend to attribute blame to the airline, even if the disruptive incident was beyond the airline’s control [24]. Consequently, this research suggests that understanding and addressing passengers’ negative emotions are crucial aspects for airlines when responding to in-flight misbehavior. Thirdly, this research highlights the significant correlation between bystander appraisal components and the intention to share, emphasizing the mediating role of satisfaction with service recovery and trust in the airline. This study proposes that variables like satisfaction with service recovery and trust play a crucial role in decreasing passengers’ intention to share a negative experience. Additionally, it underscores how passengers’ appraisal contributes to lowering their intention to share a negative experience when it involves satisfaction with service recovery and trust in the airline. Improved satisfaction and trust serve as key variables for securing the sustainable growth of an airline.

The research findings hold several crucial managerial implications. Firstly, they underscore the importance of understanding passengers’ appraisal and addressing negative emotions. Airlines should work to enhance satisfaction with service recovery and foster passengers’ trust in order to prevent the spread of negative experiences due to in-flight disturbances across social and online networks. The results and findings of this research contribute data that can be helpful to airlines looking to establish sustainable strategies and policies for handling unruly passengers and maintaining high-level cabin service. Specifically, the findings suggest that an airline’s proactive response to misbehavior as a service recovery strategy is highly effective in fostering passenger satisfaction. Hence, it is recommended that airlines include detailed guidelines on how to effectively manage disruptive behaviors as part of service training programs to achieve a higher quality of airline service.

5.3. Limitations and Future Research

While this research provides valuable insights into the relationship between passenger appraisal, negative emotions, satisfaction with service recovery, trust, and the intention to share, it is essential to acknowledge certain limitations. Firstly, the survey questionnaire aimed to capture passengers’ reactions and behavioral intentions in response to in-flight disturbances. However, to achieve a more comprehensive understanding of diverse reactions among passengers, the survey questionnaire concerning behavioral intentions could have included a greater variety of perspectives. The survey term “intention to share” might not fully encompass the varied reactions of bystanders. While the inclusion of two proposed scenarios in the survey questionnaire contributed to the study’s rigor, perceptions based on theoretical scenarios cannot accurately represent a passenger’s real experiences of witnessing unruly behaviors during a flight. Future research could explore the inclusion of diverse media content, such as photos, news articles, or short video clips, to induce clearer reactions regarding in-flight disturbances. This approach would allow for a more nuanced investigation of the diversity of possible perspectives in how passengers appraise disturbances. Therefore, future research endeavors should consider exploring additional variables which might provide deeper insights into how appraisal influences behavioral intentions, mediated by factors such as negative emotions, satisfaction with service recovery, and trust. Since many passengers may not routinely recognize or experience in-flight disturbances firsthand, analyzing survey participants’ reactions with additional variables and utilizing varied media content would likely enhance understanding the full impact of passengers’ appraisal process on their behavioral intentions.