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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.

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.

The Korean airline industry continues to change in 20-year cycles structurally. The major changes are in their market through deregulation and liberalization resulting in adding more carriers, especially low-cost carriers (LCCs) from 2006. The authors categorize three types of LCCs in Korea: (1) independent LCCs, (2) LCCs subsidized by existing airlines as airlines-within-airlines (AwAs), and (3) LCCs supported by conglomerates and local governments. Independent LCCs have suffered financially during the research period from 2009 to 2013, especially from the impaired capital, even though these LCCs are growing rapidly and expanding their markets in domestic and international routes. AwAs’ efficiency is higher than that of independent LCCs, the roles in the market are limited because of cannibalization by their mother company.

This paper aims to investigate the combined effect of airline service quality (ASQ), loyalty programme and perceived value (PV) on word-of-mouth (WOM) behavior of passengers’ traveling to domestic and international destinations from India.

Passenger’s perception on service quality, loyalty programme and PV varies with flight type, which can affect WOM. This study was designed to know whether destination based difference in passengers’ perception on airline services affects their WOM. Hence, a sample of 554 frequent passengers was taken, which includes 358 domestic and 196 international passengers. The responses were collected using well-structured questionnaire. The hypothetical model was developed and tested using structural equation modeling using analysis of a moment structures (AMOS).

Travel destination (flight) type moderates significantly the effect of ASQ on WOM behavior. ASQ affects WOM behavior more in domestic passengers. PV and loyalty programme do not moderate significantly with respect to destination type. PV was found to have significant influence on international passengers. However, loyalty programme was significant among domestic passengers.

Airline managers can develop appropriate marketing strategies targeting the passenger influencing attributes. ASQ is the most significant attribute applicable to both flight types. The airlines can focus on attractive ticket fares for international passengers and more loyalty programme benefits for domestic passengers.

This study examined the combined effect of ASQ, loyalty programme and PV on WOM behavior of passengers traveling in domestic and international sectors, which has not been researched yet.

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.

With an increasing air cargo demand in the global air cargo transport industry, not only domestic airlines but also foreign carriers are actively investing in the air cargo service sector and trying to provide a differentiated service in order to gain a competitive advantage. There are a variety of service quality models available but most research to date has not found an optimal model for the air cargo service sector.

Using questionnaire data collected from air freight forwarders in Korea with respect to the air cargo service provided by Korean Air, Asiana Airlines, and foreign carriers(JAL or China Eastern), this paper compares four models in measuring the service quality in the air cargo sector and identifies the best model. We then analyze the weakness of each airline’s service operation and make suggestions for improvement.

For demonstration analysis, the survey of domestic air cargo forwarders revealed that Reliability>Responsiveness> Supply ability>Security in important order in air cargo service quality dimension. In the context of this paper, we considered four models-unweighted SERVQUAL, unweighted SERVPERF, weighted SERVQUAL, and weighted SERVPERF–for our investigation into which is the most suitable model in the air cargo service sector with testing of goodness of fit by three criteria. Our results indicate that the most suitable model for the air cargo service sector is the weighted SERVPERF model.

The primary aim of revenue management (RM) is to sell the right product to the right customer at the right time for the right price. Ever since the deregulation of US airline industry, and the emergence of the internet as a distribution channel, RM has come of age. The purpose of this paper is to map out ten turning points in the evolution of Revenue Management taking an historical perspective.

The paper is a chronological account based upon published research and literature fundamentally drawn from the Journal of Revenue and Pricing Management.

The significance and success to RM is attributed to the following turning points: Littlewood’s rule, Expected Marginal Seat Revenue, deregulation of the US air industry, single leg to origin and destination RM, the use of family fares, technological advancement, low-cost carriers, dynamic pricing, consumer and price transparency and pricing capabilities in organizations.

The originality of the paper lies in identifying the core trends or turning points that have shaped the development of RM thus assisting futurists or forecasters to shape the future.

The manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.

The barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.

The impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”

The ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.

This study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.

Focusing on two beer festivals held in Nottingham, England, this study aims to evaluate their indirect impact on the performance of city hotels. This study builds on theoretical insights from the revenue management literature to shed empirical light on the potentially beneficial effects of events on the hotels’ performance. This study investigates the impact of the differential support offered by the destination management organisation (DMO) over two years.

Using online prices posted in advance of the events on an online travel agent, the authors assess hotel performance for each day of the events relative to the same day of the week in a week with no event. A similar comparison is made to assess the impact across two different years. In both cases, an ordinary least squares methodology was used.

Both events appear not to have had a strong impact on hotel prices and occupancy in 2016, i.e. when the DMO’s promotional effort was more proactive. Instead, in 2017, one event registered higher hotel prices and occupancy both relative to the year before and to the “business as usual” week.

The study identifies the existence of an indirect positive economic impact of the events on the hospitality sector.

The investigation adopts a more naturalistic experimental design to collect the data, which allows the authors to control for both the impact on prices and occupancy at the level of the single hotel. The evidence is therefore micro-founded. Moreover, results shed light on the role played by the DMO.

The purpose of this paper is to review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.