Assessing the Quality of Sustainable Airline Services Utilizing the Multicriteria Decision-Making Approach

Abstract

Monitoring customer satisfaction in the airline service industry is critical for improving service quality and meeting consumer expectations. Modern and comprehensive quality of service measurement tools offer firms critical information about how consumers perceive quality and their service quality expectations. It is vital to assess service quality in airline transportation, which is becoming more popular in comparison to other modes of transportation, resulting in increased competition. Businesses should know their clients well and make adjustments by properly analyzing their expectations if they want to compete in the market and enhance the quality of their services. As a consequence of this, we decided to utilize a model called the analytical hierarchy process (AHP) in order to determine how passengers in Saudi Arabia evaluate the level of service that is offered by airlines. Using the analytic hierarchy process (AHP) approach to model the five SERVQUAL dimensions and 22 sub-criteria, the purpose of the study effort was to determine the criteria for improving airline services. For the purpose of the study, the service from three different airlines was chosen and assessed based on their overall quality performance. Systematically, the AHP-based approach is presented for rating the airlines according to the Saudi aviation services. According to the observations, airlines should focus more on reliability, assurance, responsiveness, and empathy and less on tangibles. The sub-criteria also state that the airlines’ top aim should be to deliver accurate services on the first try. According to the AHP analysis, Saudi Airlines ranked first, followed by flynas and then flydeal. The findings of this study have consequences for decisions about the effective monitoring of the total airline system in order to enhance the delivery of high-quality services that would increase customers’ pleasure, which is the aim of airline services.

1. Introduction

The aviation industry is one of the biggest service industries in the world. In 2018, 4.3 billion people flew on 46.1 million flights, and at the beginning of 2019, revenue passenger kilometers (RPKs) were 5.3% higher than in 2018 [1]. As the number of people who want to fly keeps increasing, so has the competition between airlines. This is because passengers have become more thoughtful about looking for alternatives that give them more for their money [2]. Service quality is one of the many marketing criteria that has been shown to increase airlines’ competitive advantage [3,4]. Quality customer service is essential for any airline looking to attract and keep customers [5,6]. This is because happy consumers are more inclined to tell others about the airline and keep utilizing its services. Thus, the focus of the airlines these days is often on how to raise the level of service. Today’s airlines are primarily focused on understanding, maintaining, and enhancing service quality.

To guarantee appropriate quality standards for users and enhance the services provided to travelers and visitors, it is essential to evaluate the quality of air transport services. There are many studies about how to assess the quality of public transportation services based on the opinions of passengers in the literature on transportation, but more recently, it has become important to assess the quality of air transportation services. Given the complexity of the air transportation system compared to other systems, evaluating service quality in this industry presents a more interesting challenge. In fact, air transportation services are characterized by a wide range of service aspects relating to services offered by the airlines and provided by the companies managing airports. Due to the intricacy of such a service, a thorough analysis of the techniques used to gather and analyze information on passengers’ views is necessary. Recently, literature reviews based on the service quality of airlines have been performed [7,8] showing customer perceptions. From the literature review, there are many different approaches to data collection and analysis, making it challenging to determine which approaches are most effective for assessing the quality of air transportation services. As a growing area in the realm of public transport service quality analysis, it is crucial to delve further into the literature of the aviation industry. With the ultimate goal of improving the services and offering high levels of service quality to the users, this research ought to serve as a first step in providing a systematic analysis of airline services that can be useful for both researchers and practitioners in order to identify the most-suitable services offered by airlines to the passengers and for determining the most-critical or most-important service aspects for the passengers.

Based on the assessment of quality data from thorough explanatory research, Parasuraman et al. [9] established a service quality model and identified five quality attributes, namely tangible, empathy, responsiveness, reliability, and assurance. Airline customers frequently have what Babbar et al. [10] refer to as “moments of truth” with internal staff members such as cabin crew. Surprisingly, because it is more obvious and pleasurable, travelers may use service quality as a benchmark for evaluating an airline’s overall quality [11]. Because clients are now generally exposed to a range of information regarding competitors’ services, it is crucial to please them. This is because they are more knowledgeable about current trends, particularly those in technology, well educated about service quality, and highly interested in goods and services [12,13]. The airline sector does not fit into the five dimensions of the 22-item SERVQUAL scale, according to Nadiri et al. [13], since it lacks distinct service quality elements. The higher the employee comprehension of the workplace environment and the company’s ability to accomplish its goals, the more the topic of service quality is discussed within the organization.

1.1. Problem Statement

In today’s competitive aviation sector, passenger pleasure is key. The customer’s onboard experience is still unique, and if he/she is unhappy with the service, he/she may not book future trips or transfer airlines [14]. Airlines must provide high-quality service to survive and compete; thus, research on service quality and consumer happiness has increased [14]. According to Archana and Subha [14], Huang [15], and Munusamy et al. [16], the link between airline service quality and passenger satisfaction in different countries has been examined. This study was motivated by the fact that Saudi Arabia’s airline business has never been studied.

1.2. Objective of Study

One of the objectives of quality improvement is to satisfy client demands and keep them as customers. According to research in the past, providing clients with high-quality service helps keep them satisfied and ensures their loyalty [17,18]. Providing better quality is also a big part of making an airline more competitive. High service quality was also shown to lead to a better corporate image. A positive brand image helps customers understand products better and feel less uncertain when making a choice [19]. People used to think that a company’s reputation was its most valuable non-tangible asset for keeping a competitive edge [20,21]. A positive company reputation can result in positive outcomes such as increased cash flow and profitability [20,21]. However, a company’s reputation takes a long time to build up because it is made up of the opinions of many different people [22]. A business establishes its reputation by acting in a trustworthy manner [23].

The main goal of the current study was to use SERVQUAL to ascertain the impact of airline service quality.

The current study sought to fill this gap. In this regard, the primary goals of this research were as follows:

• Analyze the service quality literature and lay the groundwork for future research.
• Show the importance of selected aspects and dimensions in assessing airline service excellence.
• Construct an AHP-based model to prioritize the SERVQUAL dimensions and sub-criteria.
• Using the AHP to choose the airlines with the best overall value.

The paper continues as follows: Section 2 presents an in-depth literature assessment on service quality and airline service quality. Section 3 discusses the study design. Section 4 explains the AHP approach and model development. Section 4.7 prioritizes the SERVQUAL criteria and dimensions. Section 5 gives a full analysis and discussion of the findings. Section 6 analyzes reliability, and Section 7 and Section 8 provide the conclusions and future service quality evaluation scope.

2. Theoretical Concepts

This section includes a literature overview on service quality. The literature was divided into three primary categories: service quality, airline quality, dimensions, and sub-criteria of service quality.

2.1. Service Quality

Customers’ assessment of any business’s product or service distinctiveness and dominance, on the whole, is indicated by the level of service that the firm gives, according to [24,25]. He defines service quality as the customer’s evaluation of the services provided by the organization’s service processes. Therefore, businesses need to show concern for the level of service they provide to their clients since clients give feedback to the company by demonstrating their faith in and behavioral intentions toward the organization’s goods and services. Customers express their behavioral intentions based on their trust in an organization and its services or products when they feel that the company’s goods and services live up to their expectations. According to Bateson and Hoffman [26], the cognitive creation of service quality is “the customer’s overall judgment of the performance of the service provider.” According to different research, customers’ trust in a company is determined by its service quality [9,27], which also confirms the consumer’s behavioral intention.

2.2. Service Quality in the Airline Industry

Parasuraman, Zeithaml, and Berry deserve praise for establishing the idea of service quality and its assessment [3,9]. “SERVQUAL”, a measure of service quality based on factors such as tangibles, dependability, responsiveness, assurance, and empathy, was introduced by Parasuraman et al. [3] in their empirical research in 1988. This strategy attempted to assess customer satisfaction by measuring consumer expectations and perceptions. SERVQUAL was used in the research by [28] to gauge the airline industry’s level of customer service from the standpoint of travelers from outside.

In the airline sector, a “competitive marketing strategy” comprises customer attention, service inventiveness, innovation, and the desire to achieve “service excellence”. For decades, company management has continued to be interested in service quality [29]. Service quality is viewed as a continuous and reliable construct comprising performance quality in organizational operations undertaken by workers and management [30].

Customers view clean and comfortable seats as key services that the airline business can provide [31,32]. They also support the idea that the airline sector should offer customers a “complaint handling service”. Despite their history and place of birth, Park [33] also claimed that passengers have their own perceptions of seats, classes, and usage frequency. Additionally, consumers in the aviation business place value on “safety-related services” [34].

In a highly competitive climate, Jou et al. [35] stressed that businesses must offer their customers high-quality services to establish a competitive edge and generate large profits over the long term.

Airlines should be able to consistently provide their customers with high-quality service in order to maintain their sustainability in the challenging global competitive environment of today. Since its relationship with customer happiness and productivity was discovered, the number of studies on airline service quality has significantly expanded [36]. Service quality is a result of several interactions between passenger and airline staff, as well as any other factors, including an airline’s reputation, that could affect consumers’ perceptions [37]. Basfirinci and Mitra [38] assessed the impact of several airline service quality factors on customer satisfaction across cultural boundaries. According to a different research work by Elliott and Roach [39], travelers see timely luggage delivery, top-notch food services, plush seats, a simple check-in procedure, and in-flight service elements as essential. Service quality was characterized in one study by Truitt and Haynes [40] in terms of the check-in process, transportation suitability, luggage handling, promptness, seat hygiene, catering quality, and customer complaint behavior. For full-service airlines, Koklic et al. [41] discovered a significant positive correlation between customer happiness and airline tangibles (seat comfort, legroom, and additional offers).

In their research, Park et al. [42] showed that the aviation business has a number of service quality traits that are exclusive to the service sector and cannot be measured using the SERVQUAL scale, including ticketing, baggage allowance, and onboard amenities. The Service Performance (SERVPERF) scale was created by Cronin and Taylor [43] to measure service quality in the aviation industry more effectively, but it has also drawn criticism from a number of studies [44].

3. Research Design

Considering the rising relevance of service quality, Abha International Airport airlines were evaluated. The survey ought to determine airline passengers’ views on service quality. The research will advise airline service providers on how to improve their products, which will help them gain or retain customers.

Numerous authors have credited Parasuraman et al. [9], including [45,46,47,48,49,50,51,52,53,54,55,56]. When asked how they would define service quality, they stated it was the discrepancy between what clients believed a business offered and what they really experienced [57]. The degree to which the service, the service process, and the service organization match the user’s expectations is how Kasper et al. [58] defined service quality. We refer to “service quality” as the way a consumer views a business and its offerings as a whole (Park et. al. [59]). In agreement, Cronin and Taylor [60] defined service quality as an attitude since it entails a comprehensive evaluation of the service’s perfection.

In 1985, Parasuraman et al. [9] looked into the idea of service quality in four service sectors: retail banking, credit cards, securities brokerage, and product repair and maintenance. They found ten parts of service quality (tangibles, reliability, responsiveness, understanding the customers, access, communication, credibility, security, competence, and courtesy). To establish what is now known as the SERVQUAL instrument, they ultimately restricted the focus to just five variables: tangibles, reliability, responsiveness, assurance, and empathy. Previous studies [17,61] have employed the SERVQUAL metric to examine airline companies [17]. However, there has been much criticism on this level. It is challenging to adapt the five dimensions and 22-item scale to the airline industry, according to Park et al. [59], since it does not cover other crucial elements of airline service quality such as in-flight meals, seating comfort, and seat space. Similar to this, Cronin and Taylor [60,62] suggested a new SERVPERF scale to measure customer satisfaction since they thought it was unnecessary to evaluate customers’ expectations. They contended that it was acceptable to only measure how people felt about the performance. In comparison to SERVQUAL’s 44 components, this scale only includes 22. A performance-based scale was used to assess the levels of service provided by the examined airlines because SERVPERF is vastly superior to earlier service quality models. Domestic passengers at Abha International Airport were utilized to evaluate a modified SERVPERF instrument designed specifically for airline settings.

Many real-world studies have tried to measure the quality of service in different ways. Gourdin [62] put the quality of airlines into three groups: price, safety, and on-time arrival. Ostroowski, O’Brien, and Gordon [63] looked at how on-time the service was, how good the food and drinks were, and how comfortable the seats were. In contrast, Truitt and Hayynes [63] used the check-in process, how on-time the service was, how clean the seats were, how good the food and drinks were, and how the service handled customer complaints as their standards for measuring service quality. Other scholars, such as Tsaur, Chang, and Yen [64] and Gilbert and Wong [61] changed and adopted Parasuraman, Ziethaml, and Berry’s [3,9] five-aspect model of service quality. This model includes tangibility, reliability, responsiveness, assurance, and empathy. Our study investigated five criteria of service quality, namely: tangibility, reliability, responsiveness, assurance, and empathy.

4. Methodology

4.1. Preliminary Steps

The study’s criteria for measuring service quality were drawn from previous research, focus groups with experts in airline service quality, and some preliminary passenger interviews. The airlines’ management was invited to a preliminary meeting. At this conference, there were six aviation industry specialists in attendance. More than ten years of experience in the area of airline service quality were held by these professionals. A list of the characteristics of a high-quality service was compiled during a brainstorming session that was held three weeks later. First, a list of characteristics was developed based on a careful analysis of the literature on airline service quality. Prior to the brainstorming session, interviews were conducted with randomly selected domestic travelers at the Abha International Airport (AHB). This was done in order to comprehend the customer’s viewpoint and include it in the service design aspects. These unstructured direct interviews were conducted without the use of any properly designed questionnaires. These interviews led to the investigation of several criteria, which were then added to the list and updated. Finally, the service quality dimensions and the characteristics of service quality based on passenger interviews were incorporated.

However, SERVQUAL was developed as a key tactic [3]. Even though many industries have used SERVQUAL to evaluate service quality, no two service providers are the same. According to the focus group’s findings, SERVQUAL has to be improved and should serve as the foundation for service quality. The instrument was seen as a basic framework that needs to be modified and improved with elements relevant to airlines and their situations. SERVQUAL is built on the five service quality pillars of tangibility, dependability, responsiveness, assurance, and empathy [3]. Based on how the dimensions have traditionally been utilized, the focus group decided on a definition for them, as shown in Figure 1. The following are the working definitions of the five dimensions that apply to the airline industry:

Tangibility: Look at physical facilities, employees, communication material, and equipment. This dimension comprises check-in and boarding services, luggage handling services, waiting time, contemporary aircraft, clean facilities, and a wide range of in-flight entertainment and dining options.

Reliability: Dependable and accurate service delivery. This includes on-time departures/arrivals and efficient service.

Responsiveness: The willingness to help customers and provide quick services. It also means keeping passengers up-to-date on service times and responding quickly to complaints and requests.

Assurance: Employees’ expertise, civility, and capacity to instill trust and confidence. It also involves safety considerations, safe planes and facilities, and personnel competencies.

Empathy: Giving passengers compassionate, personalized care. It also features easy travel scheduling and awareness of each passenger’s unique needs.

Finally, a list of 22 qualities was produced by the focus group. Based on the working definitions and the “try and error” clustering method, these qualities were grouped into five service quality dimensions [45]. The five service quality dimensions and the items adapted for the context of the aviation business are shown in

Table 1. Airlines’ service quality evaluation criteria and sub-criteria.

Criteria	Sub-Code	Sub-Criteria
Tangibles	TN1	Nicely dressed, attractive personnel.
	TN2	Entertainment options on board.
	TN3	Effective baggage-handling service (reasonable baggage wait times).
	TN4	Modern aircraft and clean facilities.
	TN5	Check-in and boarding are hassle-free (waiting time and queue).
Responsiveness	RS1	Quick passenger service.
	RS2	Helpful to travelers.
	RS3	Informing passengers of the timing of service.
	RS4	Prompt reaction to passengers’ requests or concerns.
	RS5	The behavior and attitude of employees inspire confidence.
Reliability	RL1	Providing accurate services on the initial attempt.
	RL2	On-time flights (on-time performance).
	RL3	Check-in efficiency.
	RL4	Missing or delayed baggage remedy.
Assurance	AS1	Flights and facilities are safe (safer airline).
	AS2	Always-friendly staff.
	AS3	The capability to answer passengers’ questions.
	AS4	Personalized care for each passenger.
Empathy	EP1	Passengers receive personal care.
	EP2	Keeping the interests of the passengers in heart.
	EP3	Know passenger needs.
	EP4	Flight schedules are convenient.

. The final list of service quality characteristics showed face validity, and the conceptual meanings agreed with the attribute wordings. Furthermore, three impartial airline industry experts matched the characteristics to the service quality criteria in a short pretest. No expert struggled to connect the characteristics to the service aspects, further supporting the face validity.

The five aspects of airline service excellence are examined along with the sub-criteria. Table 1 lists the five dimensions of service quality and the definitions of the sub-criteria for each dimension that was taken into consideration.

4.2. Analytic Hierarchy Process

There are several decisions and applications where the Saaty [46] technique, a multi-criteria decision-making methodology, is often applied [46,47]. Strategy is advantageous since it is straightforward to use and incorporates the views of several specialists and decision-makers [48,49]. Theoretically, bias in the evaluation experts’ consensus may be supported by AHP quantification [50]. It is recognized that the AHP technique can evaluate solutions based on a wide variety of skewed criteria, both statistically and qualitatively. Additionally, it is a startlingly symmetrical strategy that may make specific challenges such as project screening complex by transforming complex problems into hierarchical structures. The AHP is used in different phases [51,52]. Included is the development of a hierarchy model, the construction of a pairwise comparison matrix, the determination of the priority and eigenvalue, and the confirmation of the consistency of the pairwise comparison.

4.3. Development of the Hierarchy Model

Before gathering data for a decision problem, a conceptual model must be developed. It is said that a system is hierarchical when entities are categorized into separate groups and entities in one group influence entities in other groups [45]. When reviewing airline services, a hierarchical structure must be built to highlight the practical features of applying the AHP. Figure 2 depicts how the AHP’s major qualitative component drives the global objective requirements. The earliest and most-significant step is determining service quality elements that serve as selection criteria (Table 2) and are necessary for decision-making (goal). The main goal is first listed, followed by the decision criteria, sub-criteria, and options. This is done after determining the decision criteria and options [46]. The hierarchy is not ordered systematically; instead, it is mostly governed by the intricacy of the choice problem and the decision-maker’s preferences [53]. The objects on the same level, however, must be of identical size and relate to some or all of the components on the level above them [53,54]. The AHP for the benchmarking issue is shown in Figure 2.

The five service quality dimensions (the core criterion) and the accompanying characteristics (the sub-criteria) that affect airline service quality are shown in Table 1. Figure 1 illustrates how the AHP is structured with 5 main criteria, 22 sub-criteria, and 3 choice possibilities. The process has four levels. The purpose of the task is at the first level. The following are the primary requirements at the second level: tangibility, reliability, responsiveness, confidence, and empathy. The fourth level consists of three alternatives: Saudi Airlines, “Flynas”, and Flyadeal.

4.4. Matrix for Pairwise Comparison and Priority Weights in the Hierarchy

When establishing a matrix for pairwise comparisons using a relative relevance scale, the primary diagonal components of the pairwise comparison matrix are all set to 1, since a characteristic compared to itself is consistently assigned the value 1. Then, 2, 4, 6, and 8 are in between 3, 5, 7, and 9, while 3, 5, 7, and 9 are markers of significance that are moderate, strong, “very important”, and “very vital”, respectively [45,46].

We normalized the pairwise comparison matrix next. Each criterion in the matrix’s columns was normalized by dividing it by the total number in that column. The arithmetic mean of each row was then used to calculate the relative weights of the various criteria. This was performed by dividing the total numbers in each matrix row by the sum of those numbers. Finally, the predicted relative weights of the criteria and the options were added together. When the criteria and alternatives were multiplied, the results were ranked in increasing order of importance, with the choices having the highest priority being considered.

4.5. Consistency Index and Consistency Ratio

The AHP may use the consistency index (CI), random consistency index (RI), and consistency ratio (CR) to assess the comparability’s consistency; for further information, see Equations (1) and (2). The authorized CR is 10% (CR 0.1), indicating that the subjective evaluation is acceptable, while total consistency is indicated by a zero value of the CI (CI = 0) [56].

CI = (λmax − n)/ (n − 1)

(1)

where CI represents the consistency index, max represents the largest eigenvalue, and n represents the size of the measured matrix.

CR = CI/RI

(2)

where CR is the consistency ratio, CI is the consistency index, and RI is the random consistency index.

4.6. Data Collection

The general questionnaire and the AHP questionnaire were used in this research. The former was first used to figure out the most-important selection criteria and choose experts with the right credentials and skills to take part in the AHP survey. Then, prior to the general survey, a preliminary investigation was carried out to assess the suitability of the introduced criteria summary gathered from prior publications and to assess the questionnaire’s readability before it was distributed. The total survey findings were eventually refined and enhanced by performing the AHP survey and carefully considering the perceived criteria.

The data processing and immediate result interpretation were the only research aspects impeded by the small sample size. However, the AHP offers advantages over other MCDM techniques, namely the ability to provide broad conclusions that are statistically robust without the need for a large sample size [65].

4.7. Prioritization of Dimensions and Sub-Criteria

In order to assess the level of service quality offered by the airlines, all five dimensions of the service quality were compared to one another. Two dimensions were compared to indicate how crucial each is to achieving the model’s objective. Numerous paired comparisons were conducted, and the matrices of each pairwise comparison were examined by computing the consistency ratio (CR), the consistency index (CI), and the maximum (max) (CR). All tables were deemed to comply with the consistency check’s requirement. The local weight of each component was determined by calculating the overall preferences of the five service quality dimensions—reliability, responsiveness, tangibles, assurance, and empathy. The five sub-criteria for the tangibles were: contemporary aircraft and clean facilities (MA); onboard entertainment (EO); efficient baggage handling service (acceptable luggage wait times) (EB); well-dressed, attractive staff (ND); check-in and boarding hassle-free (waiting time and line) (CI) (MA). Quick passenger service (QS), helpfulness to travelers (HT), notifying passengers of the timeliness of service (IP), rapid response to passengers’ requests or concerns (PR), and the behavior and attitude of workers inspire confidence (BE) were the five sub-criteria assessed for responsiveness. Providing correct services on the first try (PA), on-time flights (on-time performance) (TF), check-in effectiveness (CE), and lost or delayed luggage remedies (MB) were the four sub-criteria taken into consideration for dependability. The four sub-criteria that were taken into account for assurance were the following: customized service for each customer, always-friendly employees, safe flights and facilities (safer airline) (PC). Last but not least, the four sub-criteria for empathy were that passengers receive personal attention (PR), that passengers’ interests are kept in mind (KI), that passengers’ requirements are recognized (PN), and that flight schedules are convenient (SC). All of the sub-local criteria’s weights were calculated, much like the local dimension weight. The product of the various measurements and their sub-criteria were used to calculate the overall weight. In Table 2, one can see the pairwise comparison matrices for the five dimensions, and in Table 3, Table 4, Table 5, Table 6 and Table 7, one can see the pairwise comparisons for the sub-criteria. Table 8 displays the pairwise evaluation of three solutions for the three sub-criteria to improve the security criteria/dimensions.

Additionally, for each of the five dimension for service quality, Saudi Airlines (SA), flynas (FLN), and flyadeal (FLD) were compared. The airlines’ services were then evaluated using the findings of their calculations. The global weight of the three options was then calculated by multiplying the local weights of the three alternatives by the global weight of the sub-criterion. The total of the three different global weights was then calculated. The best option was the one with a greater summation value, while the worst alternative was the one with the lowest. Table 8 displays the synthesized comparison matrix.

Table 2. Pairwise comparison of service quality dimensions.

Dimensions	Tangibles	Reliability	Responsiveness	Assurance	Empathy	E-Vector
Tangibles	1	1/5	1/3	1/7	1/2	0.048758
Reliability	5	1	2	1/2	4	0.436025
Responsiveness	3	1/2	1	1/3	2	0.151855
Assurance	7	2	3	1	4	0.270878
Empathy	2	1/4	1/2	1/4	1	0.092484
λ max = 5.05102; CR = 0.011, CI = 0.0128

Table 2. Pairwise comparison of service quality dimensions.

Dimensions	Tangibles	Reliability	Responsiveness	Assurance	Empathy	E-Vector
Tangibles	1	1/5	1/3	1/7	1/2	0.048758
Reliability	5	1	2	1/2	4	0.436025
Responsiveness	3	1/2	1	1/3	2	0.151855
Assurance	7	2	3	1	4	0.270878
Empathy	2	1/4	1/2	1/4	1	0.092484
λ max = 5.05102; CR = 0.011, CI = 0.0128

Table 3. Pairwise comparison of five sub-criteria/factors for tangible criteria/dimensions.

	TN1	TN2	TN3	TN4	TN5	E-Vector
TN1	1	4	1/2	2	1/2	0.185619
TN2	1/4	1	1/5	1/3	1/7	0.047588
TN3	2	5	1	2	1/2	0.25694
TN4	1/2	3	1/2	1	1/3	0.121247
TN5	2	7	2	3	1	0.388607
λ max = 5.070869, CR = 0.015755, CI = 0.017717

Table 3. Pairwise comparison of five sub-criteria/factors for tangible criteria/dimensions.

	TN1	TN2	TN3	TN4	TN5	E-Vector
TN1	1	4	1/2	2	1/2	0.185619
TN2	1/4	1	1/5	1/3	1/7	0.047588
TN3	2	5	1	2	1/2	0.25694
TN4	1/2	3	1/2	1	1/3	0.121247
TN5	2	7	2	3	1	0.388607
λ max = 5.070869, CR = 0.015755, CI = 0.017717

Table 4. Pairwise comparison of three sub-criteria/factors for responsiveness criteria/dimensions.

	RS1	RS2	RS3	RS4	RS5	E-Vector
RS1	1	2	2	6	3	0.385976
RS2	1/2	1	2	4	2	0.251833
RS3	1/2	1/2	1	3	2	0.180577
RS4	1/6	1/4	1/3	1	1/3	0.056093
RS5	1/3	1/2	1/2	3	1	0.125521
λ max = 5.08819 CR = 0.019606, CI = 0.022048

Table 4. Pairwise comparison of three sub-criteria/factors for responsiveness criteria/dimensions.

	RS1	RS2	RS3	RS4	RS5	E-Vector
RS1	1	2	2	6	3	0.385976
RS2	1/2	1	2	4	2	0.251833
RS3	1/2	1/2	1	3	2	0.180577
RS4	1/6	1/4	1/3	1	1/3	0.056093
RS5	1/3	1/2	1/2	3	1	0.125521
λ max = 5.08819 CR = 0.019606, CI = 0.022048

Table 5. Pairwise comparison of three sub-criteria/factors for reliability criteria/dimensions.

	RL1	RL2	RL3	RL4	E-Vector
RL1	1	1/4	1/3	1/2	0.096899
RL2	4	1	2	2	0.434773
RL3	3	1/2	1	2	0.286325
RL4	2	1/2	1/2	1	0.182003
λ max = 4.045822, CR = 0.016795, CI = 0.015274

Table 5. Pairwise comparison of three sub-criteria/factors for reliability criteria/dimensions.

	RL1	RL2	RL3	RL4	E-Vector
RL1	1	1/4	1/3	1/2	0.096899
RL2	4	1	2	2	0.434773
RL3	3	1/2	1	2	0.286325
RL4	2	1/2	1/2	1	0.182003
λ max = 4.045822, CR = 0.016795, CI = 0.015274

Table 6. Pairwise comparison of four sub-criteria/factors for assurance criteria/dimensions.

	AS1	AS2	AS3	AS4
AS1	1	4	2	2	0.427903
AS2	1/4	1	1/3	1/3	0.087176
AS3	1/2	3	1	1/2	0.200479
AS4	1/2	3	2	1	0.284441
λ max = 4.081301, CR = 0.029799, CI = 0.0271

Table 6. Pairwise comparison of four sub-criteria/factors for assurance criteria/dimensions.

	AS1	AS2	AS3	AS4
AS1	1	4	2	2	0.427903
AS2	1/4	1	1/3	1/3	0.087176
AS3	1/2	3	1	1/2	0.200479
AS4	1/2	3	2	1	0.284441
λ max = 4.081301, CR = 0.029799, CI = 0.0271

Table 7. Pairwise comparison of four sub-criteria/factors for empathy criteria/dimensions.

	EP1	EP2	EP3	EP4
EP1	1	1/2	1/4	1/5	0.08089
EP2	2	1	1/2	1/3	0.153867
EP3	4	2	1	1/2	0.287953
EP4	5	3	2	1	0.47729
λ max = 4.021131, CR = 0.007745, CI = 0.007044

Table 7. Pairwise comparison of four sub-criteria/factors for empathy criteria/dimensions.

	EP1	EP2	EP3	EP4
EP1	1	1/2	1/4	1/5	0.08089
EP2	2	1	1/2	1/3	0.153867
EP3	4	2	1	1/2	0.287953
EP4	5	3	2	1	0.47729
λ max = 4.021131, CR = 0.007745, CI = 0.007044

Table 8. Composite priority weights for criteria and sub-criteria to establish best airline services.

Main Criteria	Local Weight	Sub-Criteria	Local Weight	Global Weight	Airline “SA” Local Weight	Airline “FLN” Local Weight	Airline “FLD” Local Weight	Airline “SA” Global Weight	Airline “FLN” Global Weight	Airline “FLD” Global Weight
Tangibles	0.049	TN1	0.1856	0.0091	0.5396	0.2970	0.1634	0.0049	0.0027	0.0015
		TN2	0.0476	0.0023	0.7153	0.1870	0.0977	0.0017	0.0004	0.0002
		TN3	0.2569	0.0125	0.6483	0.2297	0.1220	0.0081	0.0029	0.0015
		TN4	0.1212	0.0059	0.7010	0.1929	0.1061	0.0041	0.0011	0.0006
		TN5	0.3886	0.0189	0.6250	0.2385	0.1365	0.0118	0.0045	0.0026
Reliability	0.436	RL1	0.0969	0.0423	0.5396	0.2970	0.1634	0.0228	0.0125	0.0069
		RL2	0.4348	0.1896	0.6483	0.2297	0.1220	0.1229	0.0435	0.0231
		RL3	0.2863	0.1248	0.6483	0.2297	0.1220	0.0809	0.0287	0.0152
		RL4	0.1820	0.0794	0.5584	0.3196	0.1220	0.0443	0.0254	0.0097
Responsiveness	0.152	RS1	0.3860	0.0586	0.1365	0.6250	0.2385	0.0080	0.0366	0.0140
		RS2	0.2518	0.0382	0.1220	0.5584	0.3196	0.0047	0.0214	0.0122
		RS3	0.1806	0.0274	0.1958	0.4934	0.3108	0.0054	0.0135	0.0085
		RS4	0.0561	0.0085	0.6250	0.1365	0.2385	0.0053	0.0012	0.0020
		RS5	0.1255	0.0191	0.1220	0.5584	0.3196	0.0023	0.0106	0.0061
Assurance	0.271	AS1	0.4279	0.1159	0.5816	0.3090	0.1095	0.0674	0.0358	0.0127
		AS2	0.0872	0.0236	0.1958	0.4934	0.3108	0.0046	0.0117	0.0073
		AS3	0.2005	0.0543	0.1958	0.4934	0.3108	0.0106	0.0268	0.0169
		AS4	0.2844	0.0770	0.1634	0.5396	0.2970	0.0126	0.0416	0.0229
Empathy	0.092	EP1	0.0809	0.0075	0.1958	0.4934	0.3108	0.0015	0.0037	0.0023
		E2	0.1539	0.0142	0.1958	0.3108	0.4934	0.0028	0.0044	0.0070
		EM3	0.2880	0.0266	0.5584	0.3196	0.1220	0.0149	0.0085	0.0032
		EM4	0.4773	0.0441	0.1396	0.5278	0.3325	0.0062	0.0233	0.0147
Overall Priority								0.4478	0.3609	0.1913
Rank								1	2	3

Table 8. Composite priority weights for criteria and sub-criteria to establish best airline services.

Main Criteria	Local Weight	Sub-Criteria	Local Weight	Global Weight	Airline “SA” Local Weight	Airline “FLN” Local Weight	Airline “FLD” Local Weight	Airline “SA” Global Weight	Airline “FLN” Global Weight	Airline “FLD” Global Weight
Tangibles	0.049	TN1	0.1856	0.0091	0.5396	0.2970	0.1634	0.0049	0.0027	0.0015
		TN2	0.0476	0.0023	0.7153	0.1870	0.0977	0.0017	0.0004	0.0002
		TN3	0.2569	0.0125	0.6483	0.2297	0.1220	0.0081	0.0029	0.0015
		TN4	0.1212	0.0059	0.7010	0.1929	0.1061	0.0041	0.0011	0.0006
		TN5	0.3886	0.0189	0.6250	0.2385	0.1365	0.0118	0.0045	0.0026
Reliability	0.436	RL1	0.0969	0.0423	0.5396	0.2970	0.1634	0.0228	0.0125	0.0069
		RL2	0.4348	0.1896	0.6483	0.2297	0.1220	0.1229	0.0435	0.0231
		RL3	0.2863	0.1248	0.6483	0.2297	0.1220	0.0809	0.0287	0.0152
		RL4	0.1820	0.0794	0.5584	0.3196	0.1220	0.0443	0.0254	0.0097
Responsiveness	0.152	RS1	0.3860	0.0586	0.1365	0.6250	0.2385	0.0080	0.0366	0.0140
		RS2	0.2518	0.0382	0.1220	0.5584	0.3196	0.0047	0.0214	0.0122
		RS3	0.1806	0.0274	0.1958	0.4934	0.3108	0.0054	0.0135	0.0085
		RS4	0.0561	0.0085	0.6250	0.1365	0.2385	0.0053	0.0012	0.0020
		RS5	0.1255	0.0191	0.1220	0.5584	0.3196	0.0023	0.0106	0.0061
Assurance	0.271	AS1	0.4279	0.1159	0.5816	0.3090	0.1095	0.0674	0.0358	0.0127
		AS2	0.0872	0.0236	0.1958	0.4934	0.3108	0.0046	0.0117	0.0073
		AS3	0.2005	0.0543	0.1958	0.4934	0.3108	0.0106	0.0268	0.0169
		AS4	0.2844	0.0770	0.1634	0.5396	0.2970	0.0126	0.0416	0.0229
Empathy	0.092	EP1	0.0809	0.0075	0.1958	0.4934	0.3108	0.0015	0.0037	0.0023
		E2	0.1539	0.0142	0.1958	0.3108	0.4934	0.0028	0.0044	0.0070
		EM3	0.2880	0.0266	0.5584	0.3196	0.1220	0.0149	0.0085	0.0032
		EM4	0.4773	0.0441	0.1396	0.5278	0.3325	0.0062	0.0233	0.0147
Overall Priority								0.4478	0.3609	0.1913
Rank								1	2	3

5. Findings and Discussion

The summary of the study results is given in Table 8. The rankings of the decision alternatives (airlines) with respect to the sub-criteria, the service dimensions (Level 2), the sub-criteria (Level 3), and the main criteria are all shown in order of priority. Moreover, Figure 3 shows the weight of the dimensions, and Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8 represent the weight of the sub-criteria. Figure 9 represents the global weight of the sub-criteria, and Figure 10 presents the ranking of the airlines based on the AHP analysis. In order to understand how passengers prioritize the service quality elements they consider important, the respondents’ assessments of the primary criterion, the sub-criteria, and the relative preferences of three air carriers with respect to each sub-criteria were evaluated.

As shown in Table 2, the results showed that, with a weight of 43%, air passengers consider “reliability” to be the most-critical factor when evaluating the caliber of the services provided by the airline business. It is clear from this that airlines should stress the dependability of service components by improving the timeliness and efficient check-in and baggage-handling operations. As shown in Table 5, the results showed that, of the four sub-criteria (Level 3), air travelers ranked on-time performance (RL2) as the most-important service sub-criteria with a weight of 43%. Next in importance were providing services correctly the first time (RL3), remedial procedures for lost and delayed baggage (RL4), and check-in process efficiency (RL1), the latter two of which had weights of 28% and 9%, respectively. As a result, airlines must prioritize punctuality (on-time performance) and improve their operations (processes) to improve both on-time performance and the prompt delivery of baggage.

The “assurance” service dimension was ranked by air passengers as the second-most important component of service quality, with a weight of 27%, as shown in Table 2. Another element of the assurance service is ensuring that passengers feel secure while they are traveling (safety aspects). As a result, an airline must provide both safety and a secure journey. According to air passengers, the three most-essential service characteristics are safety, knowledge, and friendliness. According to the findings, out of the four sub-criteria (Level 4), travelers assigned safe planes and facilities (safety during the journey) (AS1) as the most-significant service sub-criteria with a weight of 42%, followed by individualized attention to passengers (AS4) with 28%, knowledge to answer passengers’ questions (AS3) with 20%, and consistently polite staff (AS2) with 8%. Airlines must, thus, focus on providing customers with safe flights, as seen in Table 6. These results are consistent with a prior study conducted by Gilbert and Wong [61], which found that assurance was the customer service attribute most appreciated.

According to Table 2, responsiveness was rated as the third-most important aspect of the service quality dimension in the aviation industry, with a weight of 15%. Travelers anticipate quick service, enthusiastic staff members, and a swift resolution of their complaints. According to the findings, out of the five sub-criteria (Level 3), air travelers gave prompt service to passengers (RS1) the most weight (38%), followed by a willingness to help passengers (RS2), a prompt response to passenger requests or complaints (RS4), informing passengers of the time of service (RS3), and employee behavior and attitude instill confidence (RS5). As a consequence, airlines need to stress offering prompt service to passengers.

Empathy, which acquired a weight of 9%, was placed fourth in the airline industry’s service quality dimension, as shown in Table 2. Travelers ranked the most-convenient flight schedule (EM4), which weighted 47 percent, as the most important of the four service sub-criteria (Level 3), followed by understanding individual passenger needs (EM3), which had a weight of 28 percent, keeping the passenger’s best interests in mind (EM2), which had a weight of 15 percent, and receiving personalized service (EMP1) (with a weight of 8 percent). As a result, airlines must spend much time and effort developing adequate flight schedules for their network.

As stated in Table 2, tangibility received a weight of 6%, placing it last among the service quality standards for the aviation industry. Easy check-in and boarding (TN5), efficient luggage handling (TN3), modern aircraft and spotless facilities (TN1), neat, well-dressed, and aesthetically pleasing crew (TN4) with 12 percent for each of the five sub-criteria was awarded by air passengers (level3). Last but not least, 4% was the weight of in-flight entertainment services being varied and available. Therefore, airlines must place a strong emphasis on improving boarding and check-in processes, as well as the quality of onboard food.

Additionally, it was evident from the final weights of the sub-criteria that passengers rated safe planes and facilities (AS1) (safety) as the most-critical sub-criterion with a weight of 25.7 percent, followed by the on-time performance (RL1) with a weight of 14.9 percent, providing services correctly the first time (RL2) with 6.4 percent, and the remedial procedure for delayed or missing baggage (RL4) with 6.3 percent.

6. Reliability Analysis

Cronbach’s alpha test is the most-often used to assess internal consistency and dependability. Cronbach’s alpha prediction runs from 0 (indicating no internal reliability) to 1 (indicating good internal reliability), with a projected value of 0.73 or higher [66]. We assessed the reliability of each component using Cronbach’s alpha. Regarding assurance, responsiveness, and reliability, Cronbach’s alpha values are 0.82, 0.84, and 0.80, respectively. Tangibles scored 0.84. Tangible customer satisfaction was 0.83. Empathy scored 0.814. The scale was shown to be internally consistent and mostly error-free in measurement since Cronbach’s alpha for these constructs was more than 0.80.

7. Conclusions

This study offered a framework for comparing the level of service provided by full-service domestic airlines in Saudi Arabia. It began with identifying the service quality features for Saudi Arabia’s domestic airline sector. The goal of this study was to develop a model that could be used to evaluate the effectiveness of various airline services offered by the Kingdom of Saudi Arabia and the standard of such services using the AHP approach. To achieve the objective, information from experts in the aviation service quality sector was gathered and used in the model to assess the relative effectiveness of various customer satisfaction airline choices. Based on the results of the survey and the AHP analysis, reliability received the highest weight (0.436), followed by assurance, responsiveness, empathy, and the least weight by tangible (0.048). Furthermore, based on global weight analysis of sub-criteria using AHP, RL2 (on time flight) the highest weight followed by RL3 (check-in efficiency) and AS1 (flight and facilities are safe). Based on the overall analysis of the dimensions and their sub-criteria, Saudi Airlines was the best airline followed by Flynas and Flydeal. The study results have implications for judgments about how to efficiently monitor the whole airline system to improve quality service delivery and further the goal of providing airline services—improving customer satisfaction. The policy implication of such a study includes initiatives that encourage the expansion of the sector, such as spending money on infrastructure and providing tax breaks. The Saudi Arabian government can put rules in place to ensure airline safety. The government may boost competition by abolishing airline route limits and boosting the number of carriers. The government can lessen the aviation industry’s environmental effect. Sustainable aviation fuel and carbon offset schemes are examples. The government may safeguard airline passengers by mandating flight delay and cancellation compensation and safety requirements.

8. Limitations and Recommendation for Future Research

Even though this research added to what is already known about the quality of aviation service, it had some limitations. In this research, only people who had flown on all three of the airlines under study were asked about their experiences. This is a requirement of the AHP framework method. The current research did not look into how often air travelers switch airlines or how other marketing factors such as brand image, customer loyalty, perceived value, etc., affect the service quality dimensions. This is something that could be looked into in future research. This research only looked at full-service domestic airlines in Saudi Arabia. More research can be performed to look at international and low-cost airlines in Saudi Arabia or anywhere else. This research paper talked about a framework that helps find service quality gaps between the domestic airlines. However, the current approach did not talk about “how” to fill these gaps and what needs to be done in the future to fix these problems. Another problem with this research is that the SERVQUAL service quality dimensions were changed to fit the AHP framework. In future research, the framework proposed here could be expanded to include other dimensions or could be used with other service dimensions as well. The proposed AHP framework methodology can also be used in other service sector industries, not just the airline industry.

The main advantage of the AHP is that it allows the panelists to interact with one another and, so, share ideas and information. The AHP can improve the accuracy of economic studies of innovative airline services. Although the AHP was initially developed to aid management decision-making, it may have a function in (1) prioritizing different customer-related outcomes in airline choice and (2) measuring the net benefit of airlines’ services. Creating a tree-like structure of the outcome measures considered makes it possible to assign weights to specific customers and groups of endpoints that are important to those customers. Ideally, this might happen before the benefits’ analysis with a sizable group of well-informed clients. Since the AHP has not been extensively employed for this specific purpose, more research is required to evaluate if it can be utilized in surveys and how it compares to utility-based customer-reported outcome measures.