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Fierce competition in the airline industry compels airline companies to offer various services. Yet, while companies strive to become preferable, customers confront numerous airline selection indicators, and as such causes vagueness in human thinking that needs to be systematically and normatively resolved. Accordingly, the purpose of this paper is initially to establish a strategic decision model that incorporates key selection indicators, among hundreds of criteria, through a systematic approach. Subsequently, it also aims to investigate the relative importance of these indicators for passengers.

This research first utilises a comprehensive literature review to uncover key indicators used in airline selection. Afterwards, the outcome obtained from the first phase initiated the phase of determining the prioritisation of these key selection indicators, through the analytic hierarchy process (AHP) method, based on passengers’ judgments.

The outcome of structuring a strategic decision model reveals 32 key selection indicators to be mainly considered by passengers and these indicators are grouped under five dimensions in this paper. Then, the prioritisation results given by the AHP indicate that “price-related factors” and “customer satisfaction-related factors”, respectively, are more important dimensions for passengers while selecting the best airline company.

The proposed approach provides a novel way to identify and prioritise key airline selection indicators for different passengers, through using the AHP, as a response to the need of adopting a systematic and comprehensive manner with the inclusion of general industry norms. Within this scope, the established model and the prioritisation results can be used as a reference by both airline passengers during their decision-making processes and airline companies which aim for becoming more competitive.

The connectivity provided by full-service network carriers under the umbrella of airline alliances is increasingly challenged by the services of Middle Eastern airlines via their own hubs, and the rise of new passenger strategies like self-connectivity. While these two developments can potentially benefit consumers with more services and lower fares, the rise of Middle East carriers has been met with opposition by EU and US airlines that call for increased protectionism. In addition, only a few airports in the world actively support self-connections. In this context, this study aims to investigate (1) the markets in which Middle East carriers exert a stronger dominance in terms of the number of passenger connections, (2) whether EU, US, or Asian hubs provide a competitive quality of connectivity in terms of travel time, and (3) whether a significant potential for self-connections is hidden at major airports worldwide. To that end, several datasets of passenger bookings (MIDT), airline schedules, and minimum connecting times between 2012 and 2015 are combined in a connections-building methodology that delivers six market-specific airport connectivity indicators for our benchmarking exercise. Our findings show that although European and some Asian hubs have lost traffic in global markets, they remain competitive from a quality perspective. US hubs have maintained their market share and competitive position. Finally, we identify the airports and airlines with the highest potential to provide self-connecting travel options, which can become an attractive new source of revenue for the parties involved.

Ground-handling services are important for effective aircraft operations in the air transportation system. Airlines often outsource these services to ground-handling agents through business-to-business (B2B) marketing decisions. Therefore, this paper aims to address the problem of ground-handling agent selection in the airline industry.

A real-world case study was carried out to demonstrate the applicability of the integrated best worst method and fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA) approach to solve ground-handling agent selection problems under uncertainty and imprecision. A two-stage sensitivity analysis was also conducted to ensure the credibility and validity of the application.

In the weighting stage, “Quality” was determined as the most important criterion in terms of supplier performance. With regard to the performance of the ground-handling agents, A2 was found as the optimal supplier in terms of both credibility and validity.

This study enumerated several criteria that ground-handling agents must meet in order to effectively supply services for the airlines. In addition, this study provides a novel framework from which managers can gain additional benefits from their businesses. Finally, it is concluded that this approach will help airline managers quantitatively in choosing the most appropriate ground-handling agent.

The contributions of this study to the existing literature are twofold. First, we propose a novel multiple attribute decision-making approach to address the problem of supplier selection for airlines under uncertainty and imprecision. Second, the selection of ground-handling agents from the B2B perspective is addressed for the first time in literature.

Air cargo was traditionally considered as a by-product of passenger air transport. However, in the last decade a defined strategy for air cargo has gained a key position in the strategies of most combination airlines, contributing largely to the cash and profit levels of these airlines. The global air cargo industry is nowadays a mature industry with over 60 billion USD in direct revenues. The strategic context is, therefore, far beyond the basic entrepreneurial framework in which an emerging and young industry tends to operate. This chapter aims to gain an enhanced insight into the strategies of airlines that transport cargo, either in the bellies of passenger aircraft or in full-freighter aircraft. A Cluster Analysis generates a typology of seven representative clusters of air cargo operators’ strategy models. The typology proposes a spectrum of strategies for air cargo, ranging from the cluster group “Carpet Sellers” up to the “Cargo Stars” cluster. While the former tend to be the small airlines or all-cargo carriers which barely manage to cover their costs with their revenues, the latter are profitable, very large globally operating airlines that focus on both passengers and cargo with passenger and freighter aircraft. Within this spectrum there are five other main strategy groups: the “Basic Cargo Operators,” the “Strong Regionals,” the “Low Cost Low Yielder,” the “Large Passenger Wide-body Operators,” and the “Premium Cargo Operators.” Our findings suggest the existence of superior strategy models that could be defined as “winning strategies” that differ according to airline size.

The purpose of this paper is to evaluate the hotel selection problem of airlines for their hotel and airline alliance (HAA) to develop potential customers of airlines. This paper will propose a hybrid mathematics evaluation model to help airline to select an optimal hotel with both qualitative and quantitative criteria.

To solve the hotel selection problem of airlines for their HAA, this paper focuses on the implementation of the NGT, Fuzzy TOPSIS and MCGP models in the hotel selection process. Initially, the NGT was used to create HAA decision-making criteria based on the literature review and expert opinions, and it was found that scale and scope possibility, brand value, tourism attraction, operating cost and industrial conditions are the most important criteria. Later, the Fuzzy TOPSIS method was used to obtain the general normalized fuzzy preference and to compute the closeness coefficients of each alternative hotel with respect to each criterion. Third, five tangible constraints were incorporated into the Fuzzy TOPSIS-MCGP model to calculate the optimal hotel with LINGO software.

Airline managers can use the proposed model to form a clear view of how to choose the most suitable hotel to cooperate with to outperform their competitors. Having access to this information allows airline managers to take steps to perform better and improve the performance of the partnership, helping them to gain more confidence in their decision-making capabilities while reducing investment risks.

This is the first paper that has adopted Fuzzy TOPSIS-MCGP to select hotel for their HAA from the airline’s point of view. The major contributions of this study are as follows: an efficient and simple evaluation framework is proposed for handling vagueness and uncertainty in real-world hotel selection problems; the advancement of treating uncertainty in the MCDM process; the fuzzy TOPSIS-MCGP method is extended for such problems, taking into account tangible and intangible criteria; airline managers can now make decisions in choosing to select the best hotel for their HAA that meets the airline's business goals and passenger demands; hotel operators are flexible in selecting their airline partnership, thus creating greater profit for both parties.

饭店和航空公司之间横向联盟的选择模型：NGT, fuzzy TOPSIS和MCGP方法的综合应用

本文的主要目的是在协助驾驶评估酒店选择的问题, 并通过由酒店与航空公司的合作联盟HAA, 开发整合的潜在客户。评估模型, 以帮助航空公司选择同时满足定性和定量标准的最佳酒店。

这些研究集中在规模和范围的可能性, 品牌价值, 旅游吸引上力, 运营成本和产业条件上。第二个步骤是日期近似近似最佳解排序技术（fuzzy TOPSIS）计算每家替代酒店与理想解决方案的接近度系数。规划方法（MCGP）选择最佳酒店, 同时选择方法同时考虑酒店的定性和定量标准, 并且从未在酒店选择文献中被采用过。

为了帮助评估评估合适的酒店和建立合作联盟, 因此本文提出了NGT-Fuzzy TOPSIS-MCGP模型, 以帮助决策的决策者实现替代的酒店。在此模型中, 决策者通过最后, 在名目人群技术（NGT）确定客观的酒店选择规范, 然后他们可以根据模糊近似最佳解排序技术（TOPSIS）确定标准权重, 并计算模糊的TOPSIS-MCGP模型中, 决策制定者可以使用多选择目标规划（MCGP）, 通过设定每个目标的期望水准寻找最佳酒店。

这是第一篇以航空的角度, 同时采用模糊TOPSIS-MCGP方法选择合适的酒店的论文。本文最主要的贡献是: 1. 提出了一种有效而简单的评估框架, 用于处理现实世界中酒店选择问题中的模糊性和不确定性。2. 在处理MCDM过程中不确定性方面的进展；模糊TOPSIS-MCGP方法针对此类问题进行了扩展, 同时考虑了有形和无形的标准。3. 航空公司经理现在可以做出决定, 选择适合其HAA的最佳酒店, 借以满足航空公司的业务目标以及乘客的需要。4. 酒店运营商可以灵活选择航空公司合作伙伴关系, 从而为双方创造更大的利润。

饭店, 航空公司, 名目人群技术（NGT）, 最佳解排序技术（TOPSIS）, 多选择目标规划（MCGP）, 横向联盟

El modelo de selección Para alianzas horizontales entre hoteles y aerolíneas (Haa): una aplicación integrada de los métodos NGT, fuzzy TOPSIS y MCGP

El objetivo principal de este documento es evaluar el problema de selección de hoteles de las aerolíneas para su HAA (hotel airline alliance) a fin de desarrollar clientes potenciales para las aerolíneas. Este documento propondrá un modelo híbrido de evaluación matemática para ayudar a la aerolínea a seleccionar un hotel óptimo con criterios cualitativos y cuantitativos.

Para resolver el problema de selección de hoteles de las aerolíneas para su HAA, este documento se centra en la implementación de los modelos NGT, Fuzzy TOPSIS y MCGP en el proceso de selección de hoteles. Inicialmente, el NGT se utilizó para crear criterios de toma de decisiones de HAA basados en la revisión de la literatura y las opiniones de expertos, y se descubrió que la escala y la posibilidad de elección, el valor de la marca, la atracción turística, los costes operativos y las condiciones industriales son los criterios más importantes. Posteriormente, se utilizó el método Fuzzy TOPSIS para obtener la preferencia fuzzy general y normalizada y calcular los coeficientes de cercanía de cada hotel alternativo con respecto a cada criterio. En tercer lugar, se incorporaron cinco restricciones tangibles al modelo Fuzzy TOPSIS-MCGP para calcular el hotel óptimo con el software LINGO.

Los gerentes de aerolíneas pueden usar el modelo propuesto para tener una visión clara de cómo elegir el hotel más adecuado para colaborar con el fin de superar a sus competidores. Tener acceso a esta información permite a los gerentes de las aerolíneas tomar medidas para gestionar mejor y mejorar el resultado de la alianza, lo que les ayuda a ganar más confianza en su capacidad de toma de decisiones y al mismo tiempo reducir los riesgos de inversión.

Este es el primer documento que adopta el modelo Fuzzy TOPSIS-MCGP para seleccionar un hotel para su HAA desde el punto de vista de la aerolínea. Las principales contribuciones de este estudio son las siguientes: 1. Se propone un marco de evaluación eficiente y simple para manejar la imprecisión y la incertidumbre en los problemas de selección de hoteles del mundo real. 2. El avance del tratamiento de la incertidumbre en el proceso MCDM; extiende el método fuzzy TOPSIS-MCGP a tales problemas, teniendo en cuenta criterios tangibles e intangibles. 3. Los gerentes de aerolíneas ahora pueden tomar decisiones al elegir el mejor hotel para su HAA que cumpla con los objetivos comerciales de la aerolínea y las demandas de los pasajeros. 4. Los operadores de hoteles son flexibles en la selección de su asociación de aerolíneas, creando así mayores ganancias para ambas partes.

Hotel, Aerolínea, Técnica de grupo nominal (NGT), Técnica Para el orden de preferencia por similitud a solución real (TOPSIS), Programación de objetivos de opción múltiple (MCGP), Alianza horizontal

Trabajo de investigación

The supply chain (SC) encompasses all actions related to meeting customer requests and transferring materials upstream to meet those demands. Organisations must operate towards increasing SC efficiency and effectiveness to meet SC objectives. Although most businesses expected the coronavirus disease 2019 (COVID-19) pandemic to severely negatively impact their SCs, they did not know how to model disruptions or their effects on performance in the event of a pandemic, leading to delayed responses, an incomplete understanding of the pandemic's effects and late deployment of recovery measures. Therefore, this study aims to consider the impact of implementing Bayesian network (BN) modelling to measure SC performance in the airline catering context.

This study presents a method for modelling and quantifying SC performance assessment for airline catering. In the COVID-19 context, the researchers proposed a BN model to measure SC performance and risk events and quantify the consequences of pandemic disruptions.

The study simulates and measures the impact of different triggers on SC performance and business continuity using forward and backward propagation analysis, among other BN features, enabling us to combine various SC perspectives and explicitly account for pandemic scenarios.

This study's findings offer a fresh theoretical perspective on the use of BNs in pandemic SC disruption modelling. The findings can be used as a decision-making tool to predict and better understand how pandemics affect SC performance.

This paper aims to present the findings of an investigation into environmental reporting practice in the airline sector.

Evidence was gathered from an international survey of 272 IATA Airlines. Responses accounted 65 per cent of the world's scheduled passenger traffic. Reports were assessed against a framework developed by UK's Association of Chartered and Certified Accountants.

The paper demonstrates that, despite an increase in the availability of quantitative data and some consistency in the use of key performance indicators, comparing social and environmental performance across the airline sector is fraught with difficulties. Variations in the exact definitions of the indicators used and the suite of functions embraced by the term “airline” are identified as fundamental obstacles to effective sector benchmarking.

Insight into an understanding of some of the pros and cons of comparisons between airline environmental performance data.

The research highlights the limitations of inter airline comparisons regarding environmental data and confirms the need for environmental and social impacts to be reported in a more standardised manner in order to facilitate meaningful dialogue with stakeholders in communities adjacent to airports.

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.

Scanning both the academic and popular business literature of the last 40 years puzzles the alert reader. The variety of prescriptions of how to be successful (effective, performing, etc.) 1 Organizational performance, organizational success and organizational effectiveness will be used interchangeably throughout this paper.1 in business is hardly comprehensible: “Being close to the customer,” Total Quality Management, corporate social responsibility, shareholder value maximization, efficient consumer response, management reward systems or employee involvement programs are but a few of the slogans introduced as means to increase organizational effectiveness. Management scholars have made little effort to integrate the various performance-enhancing strategies or to assess them in an orderly manner.

This study classifies organizational strategies by the importance each strategy attaches to different constituencies in the firm’s environment. A number of researchers divide an organization’s environment into various constituency groups and argue that these groups constitute – as providers and recipients of resources – the basis for organizational survival and well-being. Some theoretical schools argue for the foremost importance of responsiveness to certain constituencies while stakeholder theory calls for a – situation-contingent – balance in these responsiveness levels. Given that maximum responsiveness levels to different groups may be limited by an organization’s resource endowment or even counterbalanced, the need exists for a concurrent assessment of these competing claims by jointly evaluating the effect of the respective behaviors towards constituencies on performance. Thus, this study investigates the competing merits of implementing alternative business philosophies (e.g. balanced versus focused responsiveness to constituencies). Such a concurrent assessment provides a “critical test” of multiple, opposing theories rather than testing the merits of one theory (Carlsmith, Ellsworth & Aronson, 1976).

In the high tolerance level applied for this study (be among the top 80% of the industry) only a handful of organizations managed to sustain such a balanced strategy over the whole observation period. Continuously monitoring stakeholder demands and crafting suitable responsiveness strategies must therefore be a focus of successful business strategies. While such behavior may not be a sufficient explanation for organizational success, it certainly is a necessary one.