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Research Article

Flying high on low cost: Success in the low-cost airline industry

Roles Data curation, Formal analysis, Methodology, Project administration, Software

Affiliation Faculty of Economics and Administration, Department of Business Management, Masaryk University, Brno, Czech Republic

Roles Conceptualization, Funding acquisition, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

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  • Veronika Majerová, 
  • Michal Jirásek

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  • Published: December 21, 2023
  • https://doi.org/10.1371/journal.pone.0294638
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Table 1

Low-cost airlines have embraced diverse business models, yielding varying degrees of success. In our study, we apply a configurational approach that allows us to evaluate business models not as isolated components but as intricate business configurations. Through this lens, we identify two distinct models that successful low-cost airlines adopt: the pure low-cost model and the hybrid model. Each model has its own specific, often contradictory, attributes. Most significantly, our findings indicate that low-cost airlines must choose between offering a broad spectrum of additional services or focusing on high productivity and on-time performance. Our analyses reveal that low-cost airlines cannot sidestep this trade-off, as a simultaneous offering of both models does not lead to success.

Citation: Majerová V, Jirásek M (2023) Flying high on low cost: Success in the low-cost airline industry. PLoS ONE 18(12): e0294638. https://doi.org/10.1371/journal.pone.0294638

Editor: Baogui Xin, Shandong University of Science and Technology, CHINA

Received: December 8, 2022; Accepted: November 6, 2023; Published: December 21, 2023

Copyright: © 2023 Majerová, Jirásek. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: The research was supported by the Masaryk University research project MUNI/A/1233/2022 Organizations in the era of uncertainty.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Navigating the turbulent skies of the air transportation industry places the business models of airlines under constant pressure [ 1 ]. Therefore, scholars have devoted considerable attention to identifying the critical factors in their success [ 2 , 3 ]. However, such studies often fall into the trap of analyzing success factors in isolation, overlooking the fact that these attributes are interrelated components of more comprehensive business models [ 4 , 5 ]. This underscores the need for a holistic evaluation that takes into account the synergistic effects and relational aspects of the business model attributes–an area in which conventional correlational methods fall short. A more appropriate tool for this task is Qualitative Comparative Analysis (QCA, [ 6 , 7 ]), which allows for a nuanced exploration of the complex interactions within business models ([ 8 ]–and illustrated by, e.g., [ 9 ]).

Our research focuses on a specific category of airlines—low-cost carriers (LCCs). Characterized by their streamlined, all-economy configurations and their use of secondary airports, these airlines offer a narrowed down service at reduced cost [ 10 ]. Despite their potential to disrupt the air transport market [ 11 ], LCCs face their own competitive pressures, prompting the ongoing evolution and diversification of their business models [ 12 ]. In this respect, determining what truly contributes to the success or failure of LCCs is paramount. Moreover, given the recent trend of traditional full-service carriers (FSCs) launching low-cost subsidiaries [ 13 ], understanding the conditions for success has become increasingly important.

This study aims to contribute to this understanding by highlighting the distinguishing features and limitations of successful LCC business models. While there have been many previous studies on airline (and LCC) business models (see below), most have relied on traditional correlation methods that assess the business model attributes in isolation. Although one study [ 9 ] has used configurational methods to look at other aspects of business models (i.e., configurations of different innovative activities), it differs from our research, which is focused on general attributes of LCC business models. Furthermore, by identifying distinct business models–the pure low-cost and hybrid models–and their specific attributes, our research provides invaluable insight into strategic decision-making in existing and emerging LCCs. Our findings thus advance the academic discourse on airlines’ business models and offer practical implications for industry stakeholders seeking to navigate the complexities of the low-cost market.

Theoretical overview

Airline business models.

As in other industries, distinctive business models constitute the basis of competition between individual airlines [ 10 ]. While some scholars have distinguished two [ 14 ] or more [ 10 , 15 , 16 ] categories of airline business models, others have argued for a more fluid understanding, suggesting that there is a spectrum of business models rather than simple categories [ 1 ].

Despite this ongoing debate, classifying business models still facilitates our understanding of airlines’ operations. A standard classification [ 10 , 14 ] divides airlines into low-cost carriers (LCC) and full-service carriers (FSC). The business models of LCCs are characterized by numerous key attributes, including direct sales, significant outsourcing, high-density seating, high public awareness, and a focus on short-haul travel [ 10 , 17 , 18 ].

Moreover, FSCs and LCCs differ significantly in the design of their networks. FSCs often rely on a hub-and-spoke system, considered the most effective logistical system for moving passengers [ 19 ]. The hub is the airline’s main base and is located in its country of origin. The airline operates direct lines from its hub to other destinations (i.e., the spokes). There is no direct connection between the spoke airports, and it is only possible to travel between them by transferring to another flight at the hub [ 20 ]. Thanks to the higher frequency of flights, this system offers economies of scale on connections and at hubs [ 21 ].

In contrast, LCCs typically operate on a point-to-point basis [ 10 ]. This system affords certain advantages, such as direct connections between airports, resulting in potential savings and convenience for passengers [ 14 ]. Nevertheless, it also has drawbacks, such as the low frequency of flights on routes, the need for a higher number of airplanes, low yields per seat, and the need for a high-density market to operate point-to-point flights [ 20 ].

In reality, distinguishing between business models is not black and white. As Lohmann and Koo [ 1 ] suggest, business models can be visualized on a continuum rather than as distinct entities. Today, many airlines adopt attributes from both FSC and LCC business models, creating a hybrid model that better caters to demand and competitive pressures [ 5 , 22 ].

A further convergence in business models can be observed in cases where FSCs establish or acquire low-cost subsidiaries [ 3 , 10 , 23 ]. However, these ventures often fail due to inappropriate role identification for the subsidiary LCC, overlaps in management, inadequate operational knowledge of the low-cost model, and other issues [ 13 ].

Identification of business models

There are several approaches to identifying the business models of airlines [ 5 ]. For instance, Sengur and Sengur [ 24 ] base their conceptualization on multiple general business model frameworks, such as the Business Model Canvas. However, such broad applications may present challenges in subsequent empirical studies. Daft and Albers’ [ 25 ] approach is more tailored to empirical research and provides a comprehensive framework for describing the business models of airlines by means of three main components: corporate logic, value chain structure, and assets.

Yet it is the framework of Mason and Morrison [ 2 ] that seems to have attracted the most attention of researchers [ 5 ]. Their “Product and Organizational Architecture” (POA) offers a standardized method for categorizing key attributes, facilitating differentiation between airline models and their effects on profitability. Nevertheless, the POA framework also has shortcomings, one of which is that it assesses the relationship between components and profitability in isolation. Furthermore, subsequent studies have indicated difficulties in applying this framework due to data unavailability and the need for model adaptation (e.g., [ 1 , 26 ]).

In line with previous literature, we argue that business models are composites of various interrelated attributes that contribute to a complex structure that distinguishes each airline. A piecemeal assessment of the significance of these components (as in [ 2 ]) may mask their actual effects. Therefore, we view business models as exemplifying causal complexity and as defined by three features [ 27 ]: conjunction (the outcomes are not the product of a single cause but combinations of multiple conditions), equifinality (there can be more than one combination that leads to a particular outcome), and asymmetry (the conditions may have varying–or even contradictory–roles in different combinations).

One example of causal complexity is network types. There are successful airlines that operate either hub-and-spoke or point-to-point networks (e.g., Lufthansa and Ryanair), while others using the same network type do not fare as well (e.g., Eurowings and Thomas Cook). Although the network is crucial for success, it works best in conjunction with other conditions. There is also equifinality, as airlines with different network types can both succeed. However, a specific network type that is beneficial to one business model may not work for another, which is an illustration of asymmetry (e.g., an LCC using a hub-and-spoke network while maintaining low prices would not be sustainable due to the added transfer costs).

Methodology

Our study concentrated on European airlines that followed various versions of the low-cost business model. We derived our sample of low-cost European airlines from a list provided by ICAO [ 28 ], subsequently analyzing 21 airlines that met our criteria and had adequate data for 2019. Our primary interest was to identify the business model attributes (conditions) that, when combined, either facilitated the airlines’ success or hindered it.

To scrutinize the complex causality inherent in our case, we deployed a crisp-set Qualitative Comparative Analysis (QCA, e.g., [ 6 ]). Unlike conventional correlational approaches that examine conditions individually, QCA evaluates conditions collectively, highlighting their synergistic effects. This configurational approach embraces the asymmetry of conditions, indicating that the causes for an outcome do not necessarily mirror the causes for the absence of the said outcome [ 29 ]. Therefore, separate analyses need to be done for combinations leading to success and combinations leading to the absence of success among airlines.

A key feature of QCA is that it offers valid results with a moderate number of cases (10–100). Relative to qualitative methods, QCA accommodates more cases while preserving benefits such as in-depth case knowledge. Moreover, its variable-oriented approach promotes the identification of generalized variable relationships [ 6 ]. We used FsQCA 3.0 software for all the calculations.

Qualitative comparative analysis in brief

QCA operates on principles based on Boolean algebra and Mill’s methods [ 7 ]. Firstly, the selection of conditions (independent variables), the outcome (dependent variable), and the cases must be grounded in theoretical understanding. The data used in the analysis may be either qualitative or quantitative, but it must be convertible into binary codes (where 1 signifies the presence of a condition and 0 its absence). This is relevant for crisp-set QCA, which is the form of QCA we employed in our research.

QCA analysis involves multiple stages [ 6 ]. A critical step in the process is the creation of a “data matrix” and, subsequently, a “truth table.” The data matrix is a simplified summary of binary values for each case, from which the truth table is derived. The truth table encompasses all empirically observed combinations of causal conditions. The following step involves the logical minimization of all combinations leading to the presence of the outcome (and, separately, combinations leading to the absence of the outcome). Logical minimization refers to the simplification of complex expressions into “prime implicants” according to Boolean algebra rules, which form the basis for interpreting the results. The findings are presented in three solutions–parsimonious, intermediate, and complex–which differ in the degree of simplification they offer.

Business model attributes

Our study concentrates on the business models of LCCs and their connection to business success. We formulated six conditions (attributes of the business model) that differentiate various business models and might contribute to success or the absence of it: (i) operational size, (ii) membership in an airline group, (iii) breadth of services, (iv) focus on on-time service; (v) productivity, and (vi) provision of long-haul flights. The choice of these conditions was informed by the POA framework [ 2 ], other discussed business model frameworks, and a deep understanding of the individual cases. We focused on conditions that differentiate between the various LCC business models and excluded features which are commonly found in LCC models, such as paid onboard refreshments, the use of secondary airports, tight seat pitches, and limited seat widths. These conditions are common to all LCCs and, therefore, not decisive in distinguishing between successful and not successful ventures. We also did not include conditions (or their indicators) for which there are no openly available data for a sufficient number of airlines or where this data is largely incomplete (e.g., data related to the competition an airline is facing).

It should also be noted that we chose to work with these attributes regardless of whether they were found to be correlated to LCC success or its absence in previous studies. As we argued in the theoretical overview, findings from studies using correlational methods would be misleading, since they do not assess business model attributes as configurations (i.e., they do not assess how they work together and instead focus on their effects “in isolation”).

We chose operational size (i) and airline group membership (ii) due to their potentially significant impact on business models, as they heavily influence management decisions and capital structure. Breadth of services (iii), on-time performance (iv), and productivity (v) are integral to the POA analysis and they are directly adjustable by airlines and leave room for innovation ([ 19 ] also supporting their critical role in LCC business models). We added (vi) the provision of long-haul flights as an additional feature that can distinguish between LCCs.

Table 1 displays the indicators for the individual conditions. The third column presents the criteria used for calibration, with the level of each quantitative condition derived from industry data (values that clearly divide the airlines into two subsets) or from the authors’ knowledge of the industry and individual cases. We used the first approach (values that divide the airlines) where there is no (however abstract) threshold indicating the presence or absence of a condition. The best example for this case is the Size condition that works with airline-specific indicators. With six indicators, all airlines, apart from one, satisfy either a maximum of one criterion or five or six of them (the only exception, Jet2, satisfies two criteria). In most other cases, we combined our knowledge of where the threshold might be with insight into the actual criterion values (case and industry data).

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Where appropriate, we employed several indicators to ensure the condition’s validity and to decrease dependence on individual calibration criteria. Where there were multiple indicators, we marked the condition as present when any majority of the criteria of corresponding indicators was satisfied. We obtained the data for the analysis from various sources, including individual airlines’ websites, other published documents and from industry sources. When data for any indicator was missing, we worked with the remaining indicators, the majority of which decided the presence or absence of a given condition.

Breadth of services includes the offer of through-ticketing (guaranteed compensation for missed connecting flights), a frequent flyer program, and business class quality. Although typically associated with FSCs, some LCCs have recently adopted these attributes. The focus on punctual service can be directly measured by OAG [ 30 ] statistics, with on-time flights defined as those that depart or arrive within 15 minutes of the scheduled time. High on-time performance enhances customer satisfaction while simultaneously improving the utilization of ground staff, aircrews, and aircraft.

We measured fleet and labor productivity by means of five indicators. The fleet is considered uniform if a single type of aircraft comprises over 80% of the fleet, which has a significant impact on operating costs and productivity. The second attribute is maximum seat capacity, which reflects the extent to which an airline utilizes its predominant aircraft type’s maximum seat capacity. For example, the Boeing 737–800 has a maximum certified configuration of 189 seats [ 31 ]. A fleet operating at maximum seat capacity typically provides a single travel class and can sell more tickets per flight. Available seat kilometers per employee and passengers per employee are used interchangeably, given their high correlation in POA analysis [ 2 ].

Table 2 displays the indicators and corresponding criteria for the outcome. We identified seven indicators signifying success. However, we did not include any financial indicators due to the unavailability of data. For many of the observed airlines, financial reports are consolidated and fail to offer detailed information about subsidiaries. Thus, we chose alternative indicators with better availability of data. As before, we set the calibration criteria based on industry data.

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https://doi.org/10.1371/journal.pone.0294638.t002

In QCA analysis, reporting the inputs (the data matrix and the truth table) and outputs (analyses) in a research paper is standard. In the following section, we adopt QCA notation to streamline the textual presentation. More precisely, we use the symbol “~” to signify the absence of a condition or outcome (for example, an airline not offering long-haul flights is denoted as “~Long-haul”) and the symbol “*” to indicate a combination of conditions (e.g., “~Long-haul*Group” signifies an airline that does not offer long-haul flights and which is a subsidiary of another airline).

Data matrix and truth table

Table 3 represents the data matrix that serves as the starting point for QCA. It concisely summarizes the condition and outcome values for the 21 airlines examined. In the table “1” indicates the presence of a condition or outcome, while a “0” signifies its absence (marked as “~” in the text).

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https://doi.org/10.1371/journal.pone.0294638.t003

Table 4 presents the truth table that includes the 14 combinations of causal conditions and outcomes observed in our data. Given that there are six conditions, there are 64 (2 6 ) theoretically possible combinations, for which it is clearly impossible for 21 airlines to represent. However, as Ragin [ 32 ] points out, limited diversity is natural, as the empirical world seldom depicts all logically conceivable combinations.

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Analysis of necessary conditions

In addition to identifying combinations of conditions sufficient for the outcome, QCA also allows for the analysis of the necessary conditions. It is important to understand that the necessary conditions can be sufficient or insufficient for the outcome. The results for both success and its absence are displayed in Table 5 , which are based on two separate analyses. Consistency denotes the ratio of cases that have both the condition and the outcome. According to Ragin [ 32 ], a consistency of 0.9 indicates a necessary condition. Coverage, on the other hand, reveals the empirical relevance of a condition in the sample, computed as the ratio of cases possessing the condition in the total number of cases. None of the conditions in this analysis can be deemed necessary, as they fail to pass the consistency threshold of 0.9. Only the consistencies of the ~Long-haul (outcome: Success) and ~Size (outcome: ~Success) conditions come close to this figure, both of which recorded consistencies of 0.857.

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Analysis of sufficient conditions

To simplify the QCA output, we will now concentrate on the intermediate solutions, which are typically those most frequently interpreted [ 6 ]. The intermediate solutions for the presence and absence of success are presented in Tables 6 and 7 , while the complex and parsimonious solutions can be found in the supporting information section ( S1 – S4 Tables). Each table is divided into four columns: the first outlines the combinations of conditions determined by the analysis; the second presents the raw coverage (the ratio of cases with the outcome possessing this combination); the third presents the unique coverage (the ratio of cases with the outcome possessing this combination and none of the others); and the fourth pertains to consistency (the proportion of cases with a combination that also exhibits the outcome).

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https://doi.org/10.1371/journal.pone.0294638.t006

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Intermediate solutions (Success)

Some unexpected findings were revealed regarding the combinations of conditions linked to success ( Table 6 ). Despite the potential correlational-logic supposition that the On-time condition would be present in the Success outcomes, we identified three combinations where this condition was absent. However, these only accounted for 29% of the Success outcome. By contrast, a single solution featuring the On-time condition covered 43% of the Success outcome. As we will discuss later, this potentially indicates that LCCs face a trade-off. Specifically, maintaining on-time flights appears incompatible with offering a broad range of services (the presence of the Services condition).

Notably, it seems that being a subsidiary does not play a significant role. The combinations that include the presence and absence of this condition (Group) appear equally in combinations leading to success, and the condition is absent in combination with the highest coverage (0.429, ~Services*On-time*Productivity*~Long-haul). Productivity is present in two combinations (~Services*On-time*Productivity*~Long-haul and Size*Group*~Services*Productivity*~Long-haul) covering 50% of cases. Its absence does not feature in any of the combinations. We are cautious when interpreting the role of long-haul flights, given that this condition only appears in four cases. Nevertheless, it seems that successful European LCC airlines tend not to have this condition (and therefore only operate within Europe and its neighboring regions).

Intermediate solutions (~Success)

The combinations of conditions leading to the absence of success ( Table 7 ) support the general trade-off between on-time performance and breadth of services. All of the airlines that were not successful exhibited either both or neither of these two conditions (see all six combinations of conditions in Table 7 ). The airlines that were not successful were typically small (~Size feature in five out of six combinations that are part of the intermediate solution for ~Success), although this may not apply to airlines that are subsidiaries (Group). It could be argued that for airlines that are failing, maintaining their size is challenging unless they have a parent company to provide financial support.

Interpretation of results

Our analysis reveals two distinct business models that contribute to the success of LCCs (see Table 6 ). The first, which we term the “hybrid model”, closely resembles an FSC in its broad range of services. However, this model tends to compromise when it comes to on-time performance (Services*~On-time). In our study, airlines such as easyJet and Norwegian exemplify this model.

The second successful business model, which we term the “pure low-cost model”, is characterized by a limited range of services and the absence of long-haul flights (~Services*~Long-haul). A limited offer of services, such as catering, enabling rapid aircraft turnaround and improved on-time performance facilitates this business model’s efficiency [ 33 ]. The model aligns with Mason and Morrison’s [ 2 ] characterization of a successful LCC. In our sample, Ryanair and WizzAir are examples of this model.

While successful airlines cannot simultaneously offer a broad range of services and maintain a highly productive/on-time business model (see Table 7 and its interpretation above), they must adopt one of these approaches. Either they can copy aspects of the FSC business model or focus on delivering the core product with cost efficiencies. To illustrate the trade-offs airlines face, we have constructed a trade-off triangle, which is depicted in Fig 1 .

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According to the notional trade-off triangle, LCCs cannot afford the absence of productivity (~Productivity; see also the argument by [ 19 ]). As they compete on low prices, they need to maintain business efficiencies, particularly when they do not offer additional services (~Services), as is the case for the pure low-cost model. The hybrid model allows for some flexibility in this area but does so at the expense of on-time performance (~On-time) and, potentially, the core product itself. In both models, LCCs must appeal to customers by offering additional services (Services) or delivering high on-time performance (On-time). However, they cannot provide both without jeopardizing their overall success. Such an offering would essentially mean adopting a traditional FSC model while retaining low prices, which is an untenable strategy in the long term. This is reflected in our analysis of LCCs that were not successful ( Table 7 ).

Finally, being a subsidiary seems to be somewhat of a liability for LCCs (and as Gillen and Gados, [ 19 ], argue, most such ventures have failed). This observation is supported by the frequent exits of LCC subsidiaries from the market segment [ 34 ]. Overlapping management and unclear subsidiary roles may contribute to this issue [ 13 ].

Discussion and conclusion

The configurational logic guiding our research enables us to evaluate LCC business models as complex combinations of diverse attributes [ 8 ]. We argue that this study reflects the three features of causal complexity [ 27 ]. Firstly, our results uphold the conjunction principle–success or failure cannot be traced back to a single attribute. Instead, it results from various business model attributes operating in conjunction. Secondly, we observed equifinality in our findings, having identified two prevalent approaches adopted by successful airlines: the pure low-cost and hybrid business models. Finally, we found asymmetry, which means that the individual attributes exerted different effects when combined with others. We view this last characteristic as the fundamental strength of our approach, contrasting with traditional correlational logic (as adopted in, for instance, [ 2 ]).

To illustrate the asymmetry, consider the attribute of a broad range of services. This feature is common throughout our sample and appears with successful and unsuccessful airlines. Thus, a correlation or regression analysis would likely yield a non-significant or a slightly significant relationship. However, we demonstrated that a broad range of services is a critical element in one business model of successful LCCs: the hybrid model. While this attribute might be overlooked in a correlational analysis, it is crucial to one of the pathways to success.

Hence, we argue that our research sheds additional light not on the attributes of business models, which are widely acknowledged in the industry, but on the relationships between these attributes. The correlational approach calls for the adoption of individual best practices. However, our study suggests that the ill-considered adoption of industry practices could potentially harm an organization if these practices are incompatible with its current business model. This observation probably accounts for why some FSC low-cost subsidiaries have succeeded while others have exited the sector [ 34 ].

Our study employed crisp-set Qualitative Comparative Analysis (QCA), chosen for its straightforward interpretation and communication of results. Nevertheless, this approach is constrained by its binary value system, which acknowledges a condition as either present or absent. Fuzzy set QCA offers a more nuanced approach that accommodates the subtleties observed in real life [ 6 ]. This is a promising avenue for future research that may lead to more robust findings than one which relies on crisp-set QCA.

Our analysis concentrated on attributes that distinguish between alternative LCC business model features. Given that many attributes are incorporated into most LCC models (e.g., paid onboard refreshments, use of secondary airports, small seat pitches and seat width), we argue that they play a minimal role in differentiating between success and failure. Therefore, these attributes were excluded from our analysis, which allowed us to focus on differentiating LCC features. However, this might inadvertently suggest that these attributes are unimportant. While we recognize that some business model attributes might be redundant, many others must be present in every LCC business model. Identifying these conditions would be a suitable task for the related Necessary Condition Analysis method [ 35 ], in the case where it was supplemented with more detailed data on these attributes. Such an analysis could yield important insights for LCCs considering abandoning or limiting these practices.

Finally, our analysis was based on European LCCs. Given the differences in regional air transportation markets (reflected in, e.g., [ 18 ]), our study would require replication in other markets to extend its findings to them.

In conclusion, our research identified two distinct business models adopted by successful LCCs: the pure low-cost model and the hybrid model. Specifically, LCCs must choose between offering a broad range of additional services and focusing on their core product, represented by on-time performance and high productivity. While they must select one of these models to attract customers, they cannot adopt both without rendering their model unworkable. By employing a configurational approach, we examined the fundamental attributes of business models holistically, rather than treating them as separate factors. We believe this approach is particularly beneficial when investigating such complex phenomena.

Supporting information

S1 table. complex solution (success)..

https://doi.org/10.1371/journal.pone.0294638.s001

S2 Table. Parsimonious solution (success).

https://doi.org/10.1371/journal.pone.0294638.s002

S3 Table. Complex solution (~success).

https://doi.org/10.1371/journal.pone.0294638.s003

S4 Table. Parsimonious solution (~success).

https://doi.org/10.1371/journal.pone.0294638.s004

https://doi.org/10.1371/journal.pone.0294638.s005

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Walden Dissertations and Doctoral Studies

Strategies for mitigating low-cost airlines' passenger complaints.

Michael Jay Price , Walden University Follow

Date of Conferral

Doctor of Business Administration (D.B.A.)

Dorothy Hanson

Representatives of the U.S. Department of Transportation's Bureau of Transportation Statistics reported that passenger complaints filed for the first quarter of 2015 were up 14.4% over the same period of the previous year. The purpose of this single case study was to explore strategies for mitigating low-cost airlines' passenger complaints. Porter's generic strategies provided the conceptual framework for this research study. Data were collected from 3 ground service managers employed by a low-cost airline in Florida using semistructured interview questions, direct observation, field notes, and review of the airline's website and public documents filed with the U.S. Securities and Exchange Commission. Member checking and methodological triangulation were used to ensure data saturation. Inductive line-by-line analysis of participant interviews and review of documents and website to identify similar words and phrases resulted in the emergence of 5 themes: complaints, training, customer retention, policies and procedures, and low-cost strategies. The implication for social change exists because airline managers can apply insights gained from this study to mitigate passenger complaints, thereby increasing the number of customers, lowering fares, and maintaining profitability. In this way, the study may support the creation of additional jobs for airlines as well as other industries providing services to an expanded workforce necessary to accommodate more passengers. Further, in supporting better performance for low-cost carriers, this study may help these businesses to offer low fares to customers previously unable to afford travel, enabling them to visit new places and gain a better understanding of other cultures.

Recommended Citation

Price, Michael Jay, "Strategies for Mitigating Low-Cost Airlines' Passenger Complaints" (2017). Walden Dissertations and Doctoral Studies . 4475. https://scholarworks.waldenu.edu/dissertations/4475

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Doctoral Dissertations and Master's Theses

Determination of factors that influence passengers’ airline selection: a study of low cost carriers in thailand.

Thapanat Buaphiban , Embry-Riddle Aeronautical University - Daytona Beach

Date of Award

Access type.

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aviation

Doctoral Studies

Committee Chair

Dothang Truong, Ph.D.

First Committee Member

Frank Richey, DBA.

Second Committee Member

Haydee M. Cuevas, Ph.D.

Third Committee Member

Somchanok Tiamtiabrat, Ph.D.

This research examined the factors that influenced the airline selection of Low Cost Carriers (LCCs) in Thailand. The research was justified based on the rapid growth of LCC travel in Thailand, particularly in domestic and regional travel. There is a relative lack of successful explanation of the choice of LCCs in Thailand, with only a few studies addressing topics like passenger satisfaction and perceptions of service quality. Following an extensive literature review, the author used a theoretical framework based on the Theory of Planned Behavior (TPB) (Ajzen, 1991) in order to explain passenger behavioral intentions. This framework was supplemented by airline operational and marketing factors identified from the literature, including Price, Service Quality, Airline Reputation, Airline Safety, Route Availability and Convenience, and Frequent Flier Programs. A large scaled survey was sent to Thai LCC passengers at major airports in Thailand. The final sample (n = 781) was predominantly working-age, female, highly educated, and with average incomes. In general, they flew frequently (two to three times a year or more). In order to test the relationship among the external factors, TPB factors, behavioral intentions, and actual behavior, Structural Equation Modeling (SEM) was conducted. Results showed that Subjective Norms, Perceived Behavioral Control, Airline Reputation, Price, and Service Quality had a positive impact on Behavioral Intentions, while Behavioral Intentions positively influenced Buying Behavior. This research has important implications both in academia and industry. It indicates that LCC passengers are not merely driven by price as concluded by economic studies in LCC selection. Instead, factors like service quality, airline reputation, and social acceptability implied by subjective norms play a significant role in the choice of LCCs over Full Service Carriers (FSCs). Additionally, the results of this research provide LCCs with useful guidance to form appropriate strategies to attract more passengers: protecting price leadership, improving service quality, enhancing public image, and maintaining route diversity.

Scholarly Commons Citation

Buaphiban, Thapanat, "Determination of Factors That Influence Passengers’ Airline Selection: A Study of Low Cost Carriers in Thailand" (2015). Doctoral Dissertations and Master's Theses . 157. https://commons.erau.edu/edt/157

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Profile image of Muhammad Saeed

How low cost airlines can achieve competitive advantage by adapting innovative marketing strategies? Over the past two decades, the competition between European low cost airlines within the airline industry is becoming fierce and consequently these airlines are facing rigorous criticism in terms of customer service issues. The significance of this study is to demonstrate the situation of low cost airlines by following a marketing point of view and also to inform how low cost airlines can achieve competitive advantage by adapting innovative marketing strategies. For this purpose, five key marketing strategies and tools (i.e. gap analysis model, Porter’s model of competitive advantage, organisational environment, relationship marketing, and marketing mix) will be the part of the discussion throughout the dissertation. A mixture of data collection methods will be used to collect data where the questionnaire method will be employed to conduct primary research. The findings of the paper will suggest which marketing strategies are appropriate for low cost airlines to attain sustainable competitive advantage.

Related Papers

Muhammad Saeed

Over the last few years, the rivalry among low cost airlines in Europe in the aviation sector has become fierce. On a number of occasions, the low cost airlines faced criticism on the basis of their low level of customer services. The scope of this study is to indicate the competitive situations of no-frills using a marketing point and for this purpose, this study intends to inform how low cost airlines can achieve competitive advantage by adapting innovative marketing strategies. A combination of data collection methods is used to gather data where the survey method is employed to conduct primary research. The findings of the paper suggest that a majority of respondents fly with low cost airlines because they are cheaper to fly with but they expect at least fundamental services against low fares. The chief expectations of customers include: safe and sound physical environmental, transparent communication, consistent airline service, and anticipation of basic needs before and after flight starts. The recommendations are made to low cost airlines in the light of four key marketing strategies and tools (i.e. Porter’s models of competitive advantage, relationship marketing, environmental changes, and marketing mix) to achieve sustainable competitive advantage over their rivals.

low cost airline dissertation

Remus Negoi , Daniel Moise

International Business Research

Félix Pereira

David Jarach

Ijetrm Journal

In this world of emerging opportunities, there has been a significance increase in the demand for the low cost carrier airlines in India customers. Customers are preferring to take up flight travels in India rather than the traditional modes of transport. This has only been possible due to launch of Low-cost carrier airlines. It has been able to promote itself very well in the Indian market. With an aim of " Everyone can fly " , Low-cost airlines have been successful over the years in allowing the customers from all the income levels to take an experience in the flights. Providing excellent services with a number of varieties in discounts and offers has allowed the customers to trust on Low-cost carrier airlines. From the Indian customer point of view, it has been able to produce travel with full value for money. This research discusses on the key aspects that are necessary for Low-cost carrier airlines to gain customer satisfaction within the minds of Indian customers. The project was conducted within a target audience of 50 respondents who have already travelled in Low-cost carrier airlines. The research project also reveals the key relationships that exists between the tangible and intangible assets with the satisfaction level of the customers. The research also makes some key findings on the various expectations of customers from Low-cost carrier airlines services. The research also provides necessary recommendations that will be helpful for Low-cost carrier airlines to gain a competitive advantage over its competitors in the coming years. INTRODUCTION The research project exhibits a strategic analysis on the current macro environment of Low-cost carrier airlines in the aviation industry. This study will also help in demonstrating the various business level strategies that will pay a crucial role in making Low-cost carrier airlines become one of the leading low cost carrier (LCC) in India. The research study also reflects an analysis on the service quality and customer satisfaction in Low-cost carrier airlines. It also criticizes on the key determinants that will make the company gain a competitive advantage in the industry. The research on this area will help the company to frame an efficient and effective marketing strategy. Air-Asia airlines is one of the leading low cost carrier that has been able to be sustainable in this competitive industry (Venkatesh, 2013). With the innovative solutions and excellent philosophy of " Now Everyone Can Fly " has brought a huge revolution in the preferences of people is opting to more flights as compared to previous years. The low pricing strategy attracts the customers from major income levels that has been helpful in maximizing the profits for the organization. Low cost-airlines focusses on giving a higher frequency services on short-haul and other point-to-point international and domestic routes. In a developing country like India, People find more options to travel with comfort at cheap rates and Low-cost carrier airlines has been able to fulfill the demands of the target customers. In the aviation industry, deriving strategies by analyzing the environmental challenges and threats still remains as one of the major issues for the organizations.

Vancsisin László

Journal of Spatial and Organizational Dynamics, Vol. III, Issue 4

Journal of Tourism, Sustainability and Well-being (JTSW)

This paper addresses the relationship between the development of the airline industry and tourism. On the one hand, air transport has triggered the growth of tourism throughout the world, while, on the other hand, tourism has acted as a complementary product for developing new flight routes. This process has intensified with the emergence of low-cost carriers. A profound change has been observed in companies' strategy to adapt to the demands of this type of market. To conduct this study, a review of the existing literature related to tourism and low-cost carriers was carried out. To conclude, an analysis of the positioning and price-fixing strategies of low-cost airlines operating on some of the most important tourist routes in Europe was performed. The results indicate different level of fares among the five companies in the sample, especially between Ryanair and easyJet, but similar pricing behaviour on the routes studied.

Anna Pellicelli

Journal of Global Business Insights

FERHAN KUYUCAK SENGUR

This study focused on how airline managers perceive their competitive positions. Based on the perceptions of the airline managers, strengths-weaknesses-opportunities-threats (SWOT) analyses were carried out. All scheduled and unscheduled passenger carriers in Turkey were used as sample for this research. The data were acquired through qualitative research by semi-structured interviews with senior executives of the airlines. This research demonstrated how airline managers assess their competitive positions in the market. The similarities and differences related to each airlines’ strengths, weaknesses, opportunities, and threats were put forward. Interviews among managers of the airline companies operating in Turkey revealed varied perceptions on business models and airline service factors. A criteria framework for the airlines to apply a SWOT analysis was proposed.

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Type: Master's thesis
Year: 2007
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Cheap airlines, through the reduction and control of internal costs. Which is also one of this kind airlines to provide much lower price tickets to the public long-term and regularly than the traditional airlines. This kind of operating mode was firstly created by Southwest Airlines in the 1970s last century, Through the development since the 1990s last century, It has swept across the Americas, Europe, Oceania and Asia, Which is also becoming one of the main trend of the world’s civil aviation industry.Civil aviation transport volume of our country has jumped to second in the world, only next to the United States. But there is only one low-cost airlines in our country-chunqiu airline, which has just started, only a few planes.It is very proportionate with China as a big aviation country . our social economic development needs of low-cost airlines, the ordinary people of china calls for of the benefits of cheap cheap airlines, China’s civil aviation market capacity can support low-cost airlines. To the Chinese market, the rapid growth of the urgent need for low-cost airlines to have a great development. It can be said that China’s low-cost airlines an enormous potential for development and is facing a tremendous historic opportunity for development.The key strategy of cheap airlines has two main points : First, ,second, the . Cheap airlines market is the product of the market division,which is to meet the specific target market of consumer demand. In connection with the character of the General Administration of Civil Aviation of China,the goal of thelow-cost airlines target market is : domestic flight within three hours of the medium-low level business pax, visitors, pax who visits relatives. The newly arisen cheap airline must firmly focus on the target market of customers and introduced corresponding operating mode on the market strategy, should not deviate.On Cost strategy, we must do everything possible to reduce costs and implement cost-leadership strategy. The key to the strategy is : first, choose a single aircraft mode, Boeing 737 series or Airbus 320 series, but only can choose one of them. Second, to establish a direct sales channel,try our best to complete more than 95% ticket sales through the internet and telephone call centers. These are the two concerns can be applied to the leading strategic key strategic decisions which must be firmly grasped.Low-cost is the precondition and the character of the cheap airlines. only doing everything possible to reduce costs ,they can gain the cheap airline market,they can get their own development. With the developing of China’s social economic, the capacity of the civil aviation market is growing, and the low-cost airlines is everywhere.

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Low cost airline - Dissertation Example

Low cost airline

  • Subject: Finance & Accounting
  • Type: Dissertation
  • Level: Masters
  • Pages: 48 (12000 words)
  • Downloads: 5
  • Author: marcos62

Extract of sample "Low cost airline"

udice of people who probably who do not fly a great deal on business themselves and may regard those who do as pampered and privileged minority'' (pp14). According to Knowledgerush website ''A low-cost carrier (also known as a no-frills or discount carrier) is an airline that offers low fares but eliminates all unnecessary services. The typical low-cost'' According to the Statistics and Forecast (STATFOR) Service of Euro control there is no single best definition of a low-cost carrier. It is generally accepted that a low-cost airline, also known as no-frills or discount airline, is such carrier, which offers low fares but eliminates most traditional passenger services.

The 'low-cost carrier' business design is defined by three key elements:- Simple product: catering on demand for extra payment; planes with narrow seating ( but bigger capacity) and only a single class; there is no seat assignment; they don't offer frequent-flyer programs; ticket less travel- positioning : non-business passengers, esp. leisure traffic, and budget priced; they have short-haul point-to-point traffic with high frequencies; they are making an aggressive marketing; they are using secondary airports (e.g. regional airports); they have a strong competition with all transport carriers- low operating costs: low wages, low air fees; low costs for maintenance; reduced employment (with much lower rates of number of passengers per employer); cockpit training and standby crews due to homogeneous fleet; high resource productivity: short ground waits due to simple boarding processes, no air freight, no hub services, short cleaning times (Internet).

There are also other characteristics, which are typical for low-cost airlines. They all have in their fleet a single type of airplane, chosen to reduce. According to the Statistics and Forecast (STRATFOR) Service of Euro control, there is no single best definition of a low-cost carrier. It is generally accepted that a low-cost airline, also known as no-frills or discount airline, is such carrier, which offers low fares but eliminates most traditional passenger services. The ‘low-cost carrier’ business design is defined by three key elements: - Simple product: catering on demand for extra payment; planes with narrow seating and only a single class; there is no seat assignment; they don’t offer frequent-flyer programs; ticketless travel - Positioning: non-business passengers, esp.

leisure traffic, and budget priced; they have short-haul point-to-point traffic with high frequencies; they are making an aggressive marketing; they are using secondary airports (e.g. regional airports); they have a strong competition with all transport carriers - low operating costs: low wages, low air fees; low costs for maintenance; reduced employment (with much lower rates of number of passengers per employee); cockpit training and standby crews due to homogeneous fleet; high resource productivity: short ground waits due to simple boarding processes, no air freight, no hub services, short cleaning times.

There are also other characteristics, which are typical for low-cost airlines. They all have in their fleet a single type of airplane, chosen to reduce training and service costs. Commonly it is the Boeing 737, but it is not always like that, e.g. the Wizzair fleet has only Airbus A320.

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low cost airline dissertation

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    Low-cost airlines have a low fare structure, which is an economic advantage in the marketplace (Chang & Hung, 2013). Low-cost airlines' poor service may be a result of their low-cost strategy (Min & Min, 2013). Identifying customer service requirements may provide low-cost airline managers an opportunity to focus on service failures and

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  5. (PDF) The Development of Low-Cost Airlines and Tourism as a

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  7. Florida State University Libraries

    Electronic Theses, Treatises and Dissertations The Graduate School 2007 Low Cost Carrier Entry, Incumbent Responses and Spatial Competition in the U.S. Airline Industry Ioan Bogdan Daraban Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected]

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  11. Strategies for Mitigating Low-Cost Airlines' Passenger Complaints

    Price, Michael Jay, "Strategies for Mitigating Low-Cost Airlines' Passenger Complaints" (2017). Walden Dissertations and Doctoral Studies. 4475. Representatives of the U.S. Department of Transportation's Bureau of Transportation Statistics reported that passenger complaints filed for the first quarter of 2015 were up 14.4% over the same period ...

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  15. "Determination of Factors That Influence Passengers' Airline Selection

    This research examined the factors that influenced the airline selection of Low Cost Carriers (LCCs) in Thailand. The research was justified based on the rapid growth of LCC travel in Thailand, particularly in domestic and regional travel. There is a relative lack of successful explanation of the choice of LCCs in Thailand, with only a few studies addressing topics like passenger satisfaction ...

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  17. Dissertations / Theses: 'Low-cost airline'

    List of dissertations / theses on the topic 'Low-cost airline'. Scholarly publications with full text pdf download. Related research topic ideas. Bibliography; Subscribe; ... Low-cost airline. Author: Grafiati. Published: 4 June 2021 Last updated: 1 February 2022 Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles.

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    The Southwest Airline was the first low cost airline which started its operations in 1971 and become popular in 1973 due to low fares against low customer quality (Oliveira and Huse, 2008). Nowadays, there are a number of low cost airlines exist that provide services in Europe and the rest of the world.

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    Dissertation > Excellent graduate degree dissertation topics show China 's low-cost airline market and the cost of strategic research Author: LiZhongChao Tutor: ChenYang School: Guizhou University Course: Business Administration Keywords: cheap airlines strategic analysis market strategy cost strategy CLC: F562.6 Type: Master's thesis Year: 2007

  23. Low cost airline

    The following dissertation is focused on the idea of a low-cost airline. As it is stated here, a low-cost airline or carrier (also known as a no-frills or discount airline) is an airline that proposes small costs for that airline and excludes many services made for passengers. …

  24. Airfares are down, but baggage fees are up: Low-cost airlines are

    Low-cost carriers were best positioned to offer no-frills flights and streamlined their offerings to low baseline ticket costs with more complex fee structures. It was a big shift from the golden age of travel that lasted from the 1950s through most of the 1970s and emphasized the luxurious style popular at the time: Think ample legroom ...