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The airline industry has been severely impacted by COVID-19 due to widespread travel restrictions. Its current response is crucial to ensure continued operations after the global pandemic is resolved. One resource the airlines are leveraging is loyalty programs. This study aims to examine the viability of leveraging loyalty programs in times of crisis.

This study employs a case study methodology to examine how one company, American Airlines, has used its loyalty program to survive a pandemic and alleviate the financial costs associated with limited and restricted travel.

American Airlines' AAdvantage loyalty program structure may be used as a benchmark to understand how airlines can anchor their loyalty base to reinvigorate travel interest and use these programs as safeguards in critical instances that may arise in the future.

The case was bound by the fact that the pandemic was still a threat during the time of analysis. The findings of this case study go beyond the airline industry and may inform other hospitality and tourism organizations on the benefits of loyalty programs in times of financial distress.

This is the first known case study examining the strengths and opportunities of the structure of the American Airlines' AAdvantage program as a means for surviving in a time of crisis. Moreover, understanding how to mitigate the long-term effects of crises may help to inform future short-term strategies of airlines and other hospitality and tourism organizations for navigating unexpected shocks to their ecosystem.

Health risks associated with coronavirus disease 2019 (COVID-19) have severely affected the financial stability of airline companies globally. Recapturing financial stability following this crisis depends heavily on these companies’ ability to attain efficient and productive operations. This study uses several empirical approaches to examine key factors contributing to carriers sustaining high productivity prior to, during and after a major recession. Findings suggest, regardless of economic conditions, that social distancing which requires airline companies in the Asia Pacific region to fly with a significant percentage of unfilled seats weakens the performance of those companies. Furthermore, efficient operations do not guarantee the avoidance of productivity declines, especially during a recession.

Aerospace is a demanding technological and industrial sector. Several regulations and policies via innovative digital transformation have been integrated to impact production systems and supply chains, including safety measures. Studies demonstrated that the Fourth Industrial Revolution (4IR) technologies could enhance productivity growth and safety measures. The 4IR role in influencing airlines’ growth is yet to receive in-depth studies in South Africa. Thus, this study aims to investigate the role of 4IR technologies in influencing airlines’ growth in South Africa.

This research used a qualitative research method. Primary data were compiled via 56 face-to-face semi-structured interviews with major stakeholders. The study achieved saturation. A thematic method was used to analyse the collected data.

Findings reveal the nine major factors influencing South African airlines’ growth in the 4IR era. This includes investment in ergonomics applications and research, governance is driven by 4IR, collaboration and incorporation of 4IR concepts, partnership with drone technology and high precision and efficiency with 4IR. Others are reskilling and upskilling, investment in 4IR software, policies to promote 4IR usage in the industry and policies to reduce human interface.

Understanding the relative significance of 4IR technologies’ role in airlines’ growth can assist critical stakeholders in promoting innovative policies and regulations tailored towards digitalised aerospace. Thus, the study contributes to strategies to improve digital innovation, airline growth and safety as components of the air travel demands in South Africa.

The static world of flight scheduling where schedules rarely change once published is becoming more responsive with schedule change updates leading up to the departure date due to demand volatility and unpredictable demand patterns. Innovation in cash flow generation will take center stage to operate the business in these uncertain times. Forecasting demand for future flights is a challenge since historical demand patterns are not meaningful which requires a new adaptive robust revenue management approach that monitors key metrics, detects anomalies and quickly takes corrective action when performance targets cannot be achieved.

The novel COVID-19 pandemic decimated the travel industry in 2020 and continues to plague us with no end in sight. With the steep drop in revenues, airlines need to adapt to a new marketing planning process of scheduling, pricing and revenue management that is more nimble to adapt quickly to changing market conditions. This new approach will continue to be relevant in a post-COVID-19 world during and after economic recovery.

A methodology for airline revenue planning: scheduling, airline pricing and revenue management, has been proposed that will also work in a post-COVID-19 era.

The limitation of the proposed model is that it needs to be applied in practice to determine the true benefits of this novel approach to airline revenue planning.

Flight scheduling will rely more on clean sheet scheduling, schedule revisions and close in refleeting to better match demand to supply. The office of the chief financial officer will have a permanent task force to monitor cash flow and come up with innovative solutions to generate cash flow for liquidity. Adaptive robust revenue management workflows will be integrated into traditional revenue management workflows in the future for competitive advantage.

In a post-COVID-19 world it is anticipated that airline business processes will transform to be nimbler and more proactive in making timely decisions at a greater velocity.

The approach to airline revenue planning for scheduling, pricing and revenue management is a new business process that does not exist today at scale in the airline industry.

The purpose of this paper is to explore the effective taxonomies of airline green operations strategy.

To this end, a sample of 23 airlines from five regions (North America, South America, Europe, Asia and the Middle East) was surveyed. The annual sustainability reports of the surveyed airlines for the period 2013‒2016 were retrieved from the Global Reporting Initiatives website. K-means clustering analysis was used to generate taxonomic clusters of airline green operations strategy. A special data analysis technique, called rank analysis, was also adopted to identify the significant green actions and develop indicative models.

This study revealed that three effective taxonomies were adopted by airlines: a low-effect strategic pattern, a low-to-moderate effect strategic pattern and a high-effect strategic pattern. A different combination of green operation actions characterized each strategic pattern.

The research contribution of taxonomies of green operations strategy has so far been limited, country focused and concentrated on the manufacturing sector. This study reported the taxonomies and performed an in-depth analysis of the categories of effective actions taken to promote green performance. Moreover, this study developed indicative models for the relationship between categories of action and green performance for each strategic pattern, an action that has seldom been reported by previous studies of green operations strategies for airlines.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

The International Air Transport Association (IATA) New Distribution Capability (NDC) standard aims at modernising the airline distribution landscape. It has supported the spread of Direct Connects by providing a common standard for linking airlines to travel agencies. The purpose of this paper is to analyse the historical development of airline distribution and to derive implications for the future.

This paper follows the approach of Yeoman and McMahon-Beattie (2017) in providing a chronological account based on published research.

Direct Connects are discussed to be a step back in the evolution of the distribution landscape because they foster disaggregation. An analysis of the history of distribution finds that a comparison of Direct Connects to the early stages of computer reservation system technology falls short to recognise the tremendous technological and market changes connected to the internet, cloud computing and the rise of low-cost carriers. Moreover, drawing on the seminal article by Anderson and Tushman (1990) on technical discontinuities and dominant designs, the current state of the distribution landscape is characterised to be an era of ferment that is driven by design competition and that might end up in a new dominant design.

The originality of this paper lies in a critical review of the turning points of distribution. By reviewing the past developments, the paper sheds light on the contribution that IATA NDC and Direct Connect technology might deliver to the field of airline distribution.

This paper uses various Data Envelopment Analysis (SBM-DEA) approaches to study the efficiency of major airlines in Asia-Pacific region. To evaluate the operation efficiency of fourteen major airlines in Asia-Pacific region from 2003-2011, Available Seat Kilometers(ASK), Available Ton Kilometers(ATK), the number of employees are used as input factors, Revenue Passenger Kilometers(RPK), Revenue Ton Kilometers(RTK), the amount of Sales are used as output factors.

The non-radial SBM-DEA (Slacks-based Measure of Efficiency) model was able to provide a more comprehensive efficiency of combining economic performance and regional difference. And it was also able to capture slack values in input excess and output shortage.

The results demonstrate that Korea and Japan airlines are operated efficiently and could be regarded as the benchmarking airlines. On the other hand, most of the China and ASEAN airlines are deemed to be inefficient. Also analyzing slacks may be more suitable way for the evaluation or suggestion of an improvement scheme for the inefficient airlines. The excess of labor is the major cause of the airlines’ inefficiency.

As the wave of liberalization and deregulation have accelerated to relieve rigid controls over airline routes, capacity, and fare setting regimes, Low Cost Carriers (LCCs) have emerged especially in local aviation markets since the 1970s.

This paper has studied the effects of LCC's entry into the domestic aviation market which was pre-occupied by two major carriers, Korean Air (KAL) and Asiana Airlines. Through a simple model describing two situations, prior and post to LCC's entry, we analyzed changes and trends of each airline's output and profit based on the Cournot and two-stage Stackelberg game equilibrium.

In summary, our conclusion consists of five points: (1) Even though JIN Air's entry reduced KAL's respective output and profit, the more JIN Air produces, the higher the joint-profit of KAL and JIN Air is, (2) From the joint-profit aspect, increasing KAL's output to a level than JIN Air's is more profitable on the Gimpo-Jeju route, on the other hand, increasing JIN Air's output higher than KAL's is more profitable on the Jeju-Busan route, (3) Even though JIN Air's entry increase Asiana Airline's output, the more JIN Air produces, the less Asiana Airlines's profit is, (4) Total output in markets as well as total profits of firms will increase under certain conditions, (5) KAL and JIN Air tend to get caught in an unresolved conflict on level of LCC cost.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.