Determination of effective investment strategies for the airline sector in the context of sustainable economic development

Bu çalışmanın amacı sürdürülebilir ekonomik kalkınma bağlamında havayolu sektörüne yönelik müşteri memnuniyeti bazlı yatırım stratejilerinin belirlenmesidir. Bu amaca yönelik olarak, havacılık sektöründe müşterilerin taleplerini etkileyen faktörlerin tespit edilmesi amaçlanmıştır. Bu bağlamda, 2019 yılında en iyi 75 havayolu şirketi arasına giren şirketler inceleme kapsamına alınmıştır. Bahsi geçen şirketlere yönelik 2011-2020 yılları arasında Skytrax web sitesinden yapılan yorumlar analiz edilmiştir. İlgili müşteri yorumları metin madenciliği yöntemiyle KNIME platformu üzerinde analiz edilmiştir. Bu kapsamda, en fazla geçen tek, ikili ve üçlü kelime grupları belirlenmiştir. Elde edilen analiz sonuçlarına göre, müşterilerin tüm havayolu şirketlerinden genel beklentileri sunulan hizmetin kaliteli olmasıdır. Koltuk rahatlığı, kabin ekibinin kibar ve yardımsever olması ve yemeklerin lezzetli olması gibi hususlar tüm ülkeler için ön plana çıkmıştır. Belirtilen hususlara ek olarak, müşteriler havayolu şirketlerinden genel olarak meydana gelen rötarlara ilişkin şikayetlerde bulunmaktadır. Dolayısıyla, bu problemi yaşayan havayolu şirketlerinin gerekli tedbirleri almadığı durumda diğerlerine kıyasla önemli ölçüde rekabet avantajı kaybedecekleri ortadadır. Öte yandan, Afrika, Kuzey Amerika ve Güney Amerika’lı müşterilerin uçaklardaki temizliğe daha fazla önem gösterdiği sonucuna ulaşılmıştır. Son olarak, Güney Amerika’lı müşterilerin fiyatların yüksek olmasına yönelik bazı rahatsızlıkları bulunduğu belirlenmiştir. Bu bilgiler göz önünde bulundurularak, özellikle bu kıtaya hizmet veren havayolu şirketlerinin düşük fiyat odaklı yatırım stratejisini belirlemeleri yerinde olacaktır. Belirtilen bu öneriler ülkelerin sürdürülebilir kalkınma hedeflerine ulaşabilmelerine yardımcı olacaktır.The aim of this study is to determine customer satisfaction-based investment strategies for the airline industry to achieve sustainable economic development. For this purpose, it is intended to determine the factors affecting the demands of customers in the aviation industry. In this context, the companies that are among the top 75 airline companies in 2019 are included in the review. The comments made on the Skytrax website between the years 2011- 2020 for the aforementioned companies are analyzed. Relevant customer comments are evaluated on the KNIME platform by text mining methodology. In this context, most frequently used single, double and triple word groups are identified. According to the results of the analysis, the general expectations of the customers from all airline companies are the quality of the service provided. Matters such as the comfort of the seats, the polite and helpfulness of the cabin crew and the deliciousness of the food have come to the forefront for all countries. In addition, customers complain of general delays from airlines. Therefore, it is obvious that airline companies experiencing this problem will lose a significant competitive advantage compared to others if they do not take the necessary precautions. On the other hand, it is concluded that customers from Africa, North America and South America attach more importance to the cleanliness of their aircraft. Finally, it is determined that South American customers had some discomfort with the high prices. Considering this information, it would be appropriate for airline companies serving this continent to determine their investment strategy focused on low prices. These recommendations will help countries achieve their sustainable development goals

Spatial competition and efficiency : an investigation in the airport sector

This paper analyses the potential impact of airport competition on technical efficiency by applying the spatial stochastic frontier approach (SSFA) rather than traditional model (SFA). The SSFA allows to isolate the cross-sectional spatial dependence and to evaluate the role of intangible factors in influencing the airport economic performance, through the inclusion of the distance matrix and the shared destinations matrix, calibrated for different distances. By analysing statistical differences between the traditional and the spatial model, it is possible to identify the competition effects. This study includes 206 airports at worldwide level. First, the results show the existence of the spatial component, that could not be otherwise captured by the traditional SFA. Moreover, airport competition is found to affect the efficiency level with either a positive or a negative effect, depending on the distance considered in the spatial model

Road-Rail Intermodal Hubs Site Selection Based on Road Freight Demand Mining – A Case from Beijing-Tianjin-Hebei Region

This study introduces a holistic framework for optimising road-rail intermodal hub locations based on real regional freight data and railway station information. The primary objective is to enhance railway transportation capacity, thereby facilitating the development of a low-carbon transport system. Research begins by scrutinising the freight landscape in the region, focusing on transport volume, freight intensity, goods types and average delivery distances. Subsequently, data mining techniques, including DBSCAN clustering and frequent itemset mining, are employed to uncover freight demand hotspots across both spatial and temporal dimensions. Based on these findings, a mathematical model for hub location selection is constructed, along with criteria for goods categories suitable for rail transportation. Ultimately, using the Beijing-Tianjin-Hebei region as a case study, 12 road-rail intermodal hubs are identified, along with the main cargo types best suited for rail transport within their respective service areas. This transition is expected to result in an annual reduction of 470,000 tons of regional carbon emissions. The proposed method framework provides valuable guidance and practical insights for the optimisation of freight structures in various regions. Furthermore, it aligns with contemporary environmental and sustainability objectives, contributing to the broader goal of establishing low-carbon transport systems

A multiobjective hub-airport location problem for an airline network design

This paper presents a biobjective multiple allocation p-hub median problem, discusses the properties of the Pareto frontier and proposes exact and heuristic algorithms for finding the Pareto frontier. Our motivation emanates from airline networks and their new hub investment strategies. The first objective minimizes the total transportation cost of the network, while the second one minimizes 2-stop journeys in order to improve customer satisfaction, which is negatively affected by the multiple-transit routes of airlines. Although using hubs reduces operating costs in networks, a cost-effective hub network may not imply minimum individual travel times for passengers, or happy passengers. It is well-known that airline customers prefer flights with fewer stops. However, reducing 2-stop routes increases the number of arcs, non-stop and 1-stop routes, and thus the total cost in the network. We analyzed the tradeoff between these objective functions. We performed experiments on well-Known data sets from the literature. We were able to find the Pareto frontier exactly for small/medium size instances. A variable neighborhood search (VNS) heuristic is presented to approximate the Pareto frontier of large size instances. We also performed an application on the current Turkish aeronautics network. The results are presented and discussed. (C) 2019 Elsevier B.V. All rights reserved