Plane Ticket Research Articles

Airline Price prediction using ExtraTrees Regressor

Airlines employ dynamic pricing strategies, which are based on demand estimation models, to set ticket prices. Airlines often set the price of their seats based on the necessary demand because they can only sell a certain number of seats on each journey. Airlines typically raise travel costs during times of strong demand, which slows down the rate at which seats are filled. When demand declines and seats become unsold, airlines typically lower their ticket prices to draw in new passengers. It will be more beneficial to sell those seats for more than the cost of service per passenger because unsold seats result in a loss of revenue. In order to forecast airline ticket prices, the primary objective of this study was to determine the factors influencing airline ticket costs and look into the relationships between them. Consequently, a model is created to predict the cost of plane tickets, allowing consumers to make better-informed decisions regarding their purchases. The cost of airline tickets in India is then predicted by this study using Four different machine learning algorithms: Extra Trees Regressor, XG Boost Regressor, Random Forest, and Decision Tree. Furthermore, hyperparameter optimization is done to obtain the most accurate and ideal prediction results. The Extrat Trees regressor yielded the greatest results, with the lowest RMSE of about 1807.59 and the highest accuracy of nearly 88%.

Comparison of Air Fare Prediction Using Various Machine Learning Techniques

Due to a rise in air service links globally, air travel is now a popular, significant, and faster form of transportation. Airline rates are thought to be impacted by several factors and are subject to frequent fluctuation, making estimation of these rates a challenging but essential task. The airline uses a pricing structure for the plane ticket. The cost of airline tickets varies based on the time of day, according to the survey. Even the weekends, the tourist season, and the pageant season have an impact on this. An aircraft ticket's price is influenced by several different elements. The buyer only has access to a limited amount of information, which is truly insufficient to estimate flight pricing, but the seller is aware of all the requirements. In this study, we use machine learning regression approaches such as K Nearest Neighbourhood, Decision Tree, and Random Forest to estimate flight fares based on basic data including source, destination, departure time and date, arrival timings, halts, and airline type. The results of the investigation show that the Random Forest Regression Model yields extremely optimal results.

Climate neutrality of the French energy system: overview and impacts of sustainable aviation fuel production

CO2 emission reduction of sectors such as aviation, maritime shipping, road haulage, and chemical production is challenging but necessary. Although these sectors will most likely continue to rely on carbonaceous energy carriers, they are expected to gradually shift away from fossil fuels. In order to do so, the prominent option is to utilize alternative carbon sources—like biomass and CO2 originating from carbon capture—for the production of non-fossil carbonaceous vectors (biofuels and e-fuels). However, the limited availability of biomass and the varying nature of other carbon sources necessitate a comprehensive evaluation of trade-offs between potential carbon uses and existing sources. Then, it is primordial to understand the origin of carbon used in sustainable aviation fuel (SAF) to understand the implications of defossilizing aviation for the energy system. Moreover, the production of SAF implies deep changes to the energy system that are quantified in this work. This study utilizes the linear programming cost optimization tool EnergyScope TD to analyze the holistic French energy system, encompassing transport, industry, electricity, and heat sectors while ensuring net greenhouse gas neutrality. A novel method to model and quantify carbon flows within the system is introduced, enabling a comprehensive assessment of greenhouse gas neutrality. This study highlights the significance of fulfilling clean energy requirements and implementing carbon dioxide removal measures as crucial steps toward achieving climate neutrality. Indeed, to reach climate neutrality, a production of 1,046 TWh of electricity by non-fossil sources is needed. Furthermore, the findings underscore the critical role of efficient carbon and energy valorization from biomass, providing evidence that producing fuels by combining biomass and hydrogen is optimal. The study also offers valuable insights into the future cost and impact of SAF production for air travel originating from France. That is, the European law ReFuelEU would increase the price of plane tickets by +33% and would require 126 TWh of hydrogen and 50 TWh of biomass to produce the necessary 91 TWh of jet fuel. Finally, the implications of the assumption behind the production of SAF are discussed.

How to utilize the information gap for blind box marketing better: evidence from plane tickets

ABSTRACT Blind boxes have swiftly emerged as a prominent marketing strategy in tourism. Based on information gap theory, this research aims to explore how to optimize marketing effectiveness through varying levels of information gap. Findings show that a moderate-level information gap triggers stronger impulsive purchase intention than a high-level information gap, with curiosity and anxiety perception mediating the effect. Moreover, consumers with a low-risk propensity are particularly sensitive to the impact of the information gap level. These findings contribute theoretically and provide practical guidance for optimizing the marketing of plane ticket blind boxes.

Designing an algorithm for predicting plane ticket prices using feedforward neural network modeling

PurposeThis research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.Design/methodology/approachA feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.FindingsThe findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.Practical implicationsBased on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.Originality/valueThe present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.

A Machine Learning Chronicle in Airfares for Pricing the Clouds

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs. The price of a plane ticket is influenced by the length of the trip, the location, the schedule, and several other factors, like holidays or vacations. Therefore, many people will surely save time and effort by having a basic awareness of airline expenses prior to making trip arrangements. The performance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analysed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used to build a system that can predict how much a flight will cost.

Brand awareness and its influence on repeat customers in the airline industry

India’s aviation industry is seeing growth, and the country is host to several domestic airline firms.In India, the domestic aviation industry is predominantly composed of private airlines, accounting for over 75% of the market, making it one of the aviation markets with the highest growth rates globally. Currently, there are 454 functioning airports in the country, out of which 16 are international airports. The aviation sector is projected to have a resurgence with an anticipated compound annual growth rate (CAGR) of 18% in 2011. The Civil Aviation Ministry’s current predictions indicate that increasing traffic movement and revenues—which climbed by about US$ 21.4 million in 2009—will enable India’s Airports Authority to create higher margins in 2009–2010. Acknowledging and. Recognizing and delivering high-quality service begins with knowing exactly what clients want. Service quality is one of the finest measures for assessing the opinions and expectations of clients. Customer performance within an organization determines customers satisfaction with services. Passenger happiness affects customer sovereignty. It is possible for customers to be really satisfied and still not be loyal, or vice versa. Companies need to have a deeper understanding of the relation between online behaviour and contentment in order to divide internet marketing tactics between programs that promote behavioural intention and happiness. The findings will benefit airline managers by enabling them to monitor and improve the quality of their workforce, improve customer service, and increase passenger satisfaction. In India, buying airline tickets again and again is rather usual, particularly for business or frequent visitors. Numerous domestic airlines in India have frequent flyer and loyalty programmes as a means of encouraging consumers to keep using them when making travel reservations. Furthermore, a lot of Indian travellers buy their flights using online travel agents (OTAs), which make it simple for consumers to compare options and costs across several airlines. To entice users to make additional reservations, these OTAs frequently provide cashback or discount incentives for recurring bookings. Furthermore, a lot of Indian airlines entice customers to buy tickets with them again and again by providing a range of promotional deals, discounts, and cashback incentives at different periods of the year. In general, Indians frequently buy plane tickets again and are influenced by loyalty programs, frequent flyer programs, discounts, cashback offers, and the ease of booking through online travel agencies.

Analisis IT Service Management Pada Aplikasi Traveloka Menggunakan Framework ITIL V3

Information technology nowadays is developing very rapidly, especially in the tourism sector. The use of technology in the tourism sector has made Traveloka's services popular because they can be accessed easily, quickly and reliably. The Traveloka service provides a service where users can order plane tickets from various airlines that collaborate with Traveloka with different price variants. This service makes it easier for people to enjoy their holidays and find out plane ticket prices easily. This research used data collection through questionnaires and obtained 30 respondents. Then a validity and reliability test is carried out to measure the quality level of a statement, after which a maturity level calculation will be carried out to analyze whether Traveloka's services are good enough to carry out service operations in the community. This research uses the ITIL V3 framework to analyze Traveloka services, especially in the Service Operation domain, which consists of 5 subdomains, namely the maturity level in the Event Management subdomain gets a value of 4.41, the maturity level in the Incident Management subdomain gets a value of 4.22, then for the Problem subdomain Management got a maturity level of 4.17, then for the Request Fulfillment subdomain the maturity level got a value of 4.21 and finally for the Access Management subdomain it got a maturity level of 4.30. So it can be seen that based on the results of the maturity level calculation it can be stated that all subdomains are at the Managed Level.

Patient brokering in for-profit substance use disorder treatment: a qualitative study with people with opioid use disorder and professionals in the field

BackgroundOpioid use and opioid overdose deaths are at an all-time high and evidence-based treatments for people with opioid use disorder (OUD) are underutilized. Therefore, we sought to understand experiences and perceptions of abuses in the for-profit substance use disorder treatment industry that could potentially put people with OUD at an increased risk for an overdose.MethodsOne-on-one semi-structured interviews were conducted from November 2018 to May 2019 in Southern California with 20 people with OUD and 20 professionals who work in the substance use disorder (SUD) treatment field. A grounded theory approach was conducted to discover emerging patterns from the data.ResultsThree major themes emerged:1) financial and material enticements, 2) encouraging substance use in the for-profit treatment sector, and 3) contributors to overdose risk. Participants reported that patient brokers would pay for plane tickets and offer financial incentives (e.g., money) to attract individuals to SUD treatment, capitalizing on insurance profits despite initial expenses. Participants reported being encouraged to use drugs before treatment to meet insurance conditions, thus jeopardizing genuine recovery efforts and adding to the temptation of drug use. Many participants linked patient brokering to increased overdose deaths, emphasizing the dangerous practices of brokers providing drugs, promoting relapse, and creating a revolving door of treatment, which compounds the overdose risk after periods of abstinence.ConclusionsPatient brokering and unethical abuses in the for-profit treatment industry have caused some people with OUD to seek treatment for money and housing instead of seeking treatment to stop opioid use. The harmful treatment environment was seen as a barrier to care and an unwanted obstacle to overcome on the path to recovery.

I Began to Quiet my Mind….

Three years, nearly to the month of the start of the COVID-19 pandemic, I contracted COVID. I had managed to avoid it during the period when no vaccination was available. But now the pandemic was waning, and I was fully boosted. I had been ready to join the bustling academic environment of the Pediatric Academic Societies (PAS) 2023 Meeting in Washington, DC– my registration, plane ticket, hotel, and dinner ticket to the American Pediatric Society Howland Award Dinner, were all ready. Then I got symptoms -thought they were due to allergies, but with an abundance of caution (and a new 2-month-old grandbaby in the house), I tested myself and that pink line showed up quickly and unequivocally. Plans changed. I started anti-viral medication and an inhaler – and the next two days watched carefully to see if symptoms would worsen.

RANCANG BANGUN SISTEM PEMESANAN TIKET PESAWAT BERBASIS WEB

Indonesia is the largest archipelagic country in the world which has very strategic geography. This can bring many opportunities in exploring natural riches and environmental services. For this reason, the existence of reliable and efficient transportation is very important. One means of transportation that is very popular and widely used by the public is airplanes. In this case, aircraft have made a significant contribution in supporting global connectivity, tourism and economic growth in various sectors. Even though airplane transportation has various advantages, there are still shortcomings in the airplane ticket purchasing process which still relies heavily on travel agents or direct purchases through the destination airline. This often causes problems, such as unstable ticket prices and concerns regarding the security of the ticket purchasing process. One innovation that can be a solution to the problem of purchasing plane tickets is the development of an application that provides a platform for purchasing plane tickets from various airlines. This application will combine various ticket options from various airlines on one platform. Apart from that, the application will also ensure the safety and security of passengers by providing the latest information about the availability of facilities on the plane and payment methods that are familiar to users. Thus, this application will provide convenience, comfort and security for prospective passengers in purchasing airline tickets of their choice.

Flight Price Prediction Using Machine Learning

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs.The price of a plane ticket is influenced by the length of the trip, the location , the schedule, and anumber of other factors, like holidays or vacations. Therefore, many people will surely save timeand effort by having a basic awareness of airline expenses prior to making trip arrangements. Theperformance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analyzed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used tobuild a system that can predict how much a flight will cost.

IMPLEMENTATION OF DIGITAL MARKETING STRATEGY IN THE INNOVATIVE COMPANY UBER

Today's market is characterized by the generally present trend of globalization, and consequently there are also other trends such as internationalization, digitalization, increasing uncertainty. The competitive race is extremely fierce, so much so that those who fail to meet the demands of consumers are quickly out of the game. The life cycle of products is getting shorter and shorter, which means that the distribution channels must also be shorter to reach the end consumers on time. Fewer and fewer people go to travel agencies to inquire about travel arrangements, and fewer people make decisions based on the prospectus viewed in the office. The situation is similar with the purchase of smart devices, home appliances, booking a ride, buying plane tickets, clothing, ordering food. Buyers will increasingly open websites or applications that have the same or similar offer (it is a digital offer of different competitors) to compare prices, benefits, and what that product entails and includes. Information is the number one resource on the demand side, but also on the supply side. Therefore, it is not surprising that companies that do not follow trends and do not implement innovations in their activities easily lose their position on the market in global business conditions. It is necessary to modernize all activities and processes in the company, including the marketing strategy. Before the emergence of digital marketing, marketing activities were quite expensive, so they were a feature of large successful companies that could afford them. On the other hand, digitalization has led to the modernization of activities in the company, and by simply using the Internet and various applications, company managers can achieve the same or even better results, but with less investments. Digital marketing campaigns are more favorable than traditional marketing, which allows companies to carry out marketing activities more than ever and increase their performance based on them. Another reason for implementing a digital marketing strategy in the business of a modern company is the growing number of Internet users. Almost 70% of the world's population uses the Internet every day, while in America that percentage is even higher. A huge number of people who use the Internet use social networks and different applications every day. This means that the number of people following a company's marketing campaigns is increasing day by day, and those campaigns are becoming cheaper considering the increasing number of people using social networks and the Internet. One of the companies that bases its business exclusively on the basics of digitization is Uber. Uber is a company that has been around for 14 years. It was created as a startup company, and today it is present in more than 70 countries of the world and has a huge number of users. The aim of this paper is to point out the importance of implementing a digital marketing strategy in the company's operations, but also to point out all the benefits of its implementation, referring to the business model of the company Uber.

Preparation of Aviation Industry Transition on COVID-19 From Pandemic to Endemic Phase: a Review

Purpose: The aim of this study is to examine the Malaysian government's actions towards the aviation industry to deal with the Covid-19 pandemic and the transition phase from pandemic to endemic. Transition phase refers to a temporary period before the country could fully enter the endemic phase which is subject to an announcement by the World Health Organisation (WHO). Theoretical framework:The study on air transport affected by pandemic and industry action toward the endemic phase. This study refers to the conceptual framework for emergency department design in a pandemic by Aujirapongpan (2023): Relationship between state, hospital and ED in pandemic preparedness planning and response. Design/methodology/approach: The approach used is qualitative research that are observation and literature review. Findings: The results demonstrate the Malaysian government's actions during the transition period from pandemic to endemic. Restrictions on travel between areas cause the public to be unable to move at will, causing passengers to be unable to buy plane tickets. The government's actions have indeed had an impact on the airline company's income. Among the significant effects are the workers who were laid off in the era of the pandemic. At the same time, the government is also trying to help airlines financially to survive while waiting for the endemic period. The Malaysian government does not have a specific framework for the airline industry to face the pandemic, however, the Malaysian government gives a quick reaction to control the situation. Research, Practical & Social implications: The study gives comparative responses on the aviation industry by the government when faced with a pandemic, as well as planning for the transition to the endemic phase. Originality/value: The result indicates the government participation and action changes of the air transport operation on the Covid-19 pandemic to endemic transition phase.

Report of the WFNS Global Relations Committee

Thank you for the opportunity to serve on this committee. It appears the WFNS has assembled an all-star cast of neurosurgeons interested in Global Neurosurgery. I am honored to serve as External Relations Lead. Listed below are a few examples of projects the group is working on that fit with your deliverables (specific, measurable, achievable, relevant, time-based). I look forward to learning of other initiatives from the group as we develop synergies moving forward.
 
 
 It was noted that both the WFNS and the ISPN have Education Committees who produce educational courses either virtually or in person in various LMICs several times per year. I have spoken to President Oyesiku and Kenon Arnautovic, the Chair of Chairs, suggesting that rather than having two parallel processes performing the same task, that we consolidate these committees and have the ISPN serve as the Pediatric Neurosurgery Education Committee for the WFNS hence forth. Typically, in the past, the Committee chairs have been ISPN members. Both Nelson and Kenon have voiced agreement to that arrangement. Since the ISPN is already an international society with 530 members from around the globe, this should be acceptable without the ISPN having to “join” the WFNS. The agreement was that if any course produced a financial profit, those monies would be divided equally between the WFNS and the ISPN. To date, the ISPN has underwritten the costs of plane tickets for the speakers at these meetings, although the courses have all been virtual since the COVID pandemic. The local hosts have covered the costs of hotel, meals, etc. once the speakers are on location. To date I am not aware of any of these courses that have generated a financial profit. Obviously, the marketing and presentations at these teaching courses would be co-branded.
 

Richardson on moral innovation

Richardson on moral innovation

ANALYSIS OF FACTORS INFLUENCING THE PRICING OF AIR TICKETS

The article is devoted to discussing topical issues about the formation of the price of plane tickets. The paper analyzes and evaluates the degree of influence of factors on the pricing process using regression analysis methods. At the first stage, a review of the available research sources of foreign and Russian authors was carried out, according to the results of which the main characteristics determining the price level of air tickets were identified and considered. In the course of studying the issue, the experience and conclusions, based on previously performed studies of foreign segments of air transportation, are extended to the selection and analysis of current data on the Russian market. The assessment of the degree of a possible influence of the considered price-forming indicators on air ticket fares was carried out using four econometric models of the dependence of ticket prices on exchange rates, fare/air route characteristics, socio-economic and secondary factors. They are checked for lowcost and economy segments based on information on 15 thousand of air tickets of Russian air carriers for the period from 19.01.2021 to 12.02.2021, presented in the form of a single data set. The data was collected independently by daily monitoring of information from the official websites of airlines, federal websites of Rosstat, and Rosaviation. As a result of the research conducted within the framework of this article, it was revealed that with an increase in the distance of the flight, the cost of the ticket increases proportionally. The average income of the population negatively affects prices in the economy and budget classes. A similar trend can be traced concerning the cost of jet fuel at the airport of departure and nonstop flights. Reducing the number of days between the dates of ticket purchase and flight departure will also affect the increase in ticket prices. With a decrease in the exchange rate of foreign currency, the cost of economy class air tickets changes significantly compared to the budget. The reverse trend is observed in the case of the IATA exchange rate, where the effect falls on the last group of shipments. The listed characteristics are identified as the most significant relative to the considered classes of tariff groups in the Russian aviation industry. The results of the work can be recommended to air carriers for use in the process of forming the cost of tickets to achieve maximum efficiency and profitability of the business, used by consumers of the airline services as a tool for finding and buying air tickets with the best conditions and offers.

Changing Times

Changing Times

PENGARUH KEMUDAHAN DAN CITRA MEREK TERHADAP KEPUTUSAN PEMBELIAN TIKET PESAWAT SECARA ONLINE MELALUI TRAVELOKA

This research aims to find out how much the ease of use and brand image influence on the decision to purchase plane tickets online through Traveloka. This research was conducted online in April 2021 in Cilacap, Central Java. The research uses a descriptive quantitative approach. The Types of data utilized in this study are primary and secondary data. Data collection is done by online send around questionnaires. The sampling method used is a purposive sampling technique. The amount of samples in this study is 96 respondents. Data analysis used in this research are descriptive analysis, validity test, reliability test, double linear regression analysis, partial test, simultaneous test, classical assumption test, and determination coefficient test. Based on partial test results, ease of use shows the sig > a (0.969 > 0.05) value and the brand image shows the sig < a (0.000 < 0.05). Whereas the simultaneous result shows the sig < a (0.000 < 0.05) value. The result of the coefficient determination test shows that ease of use and brand image influences purchase decisions by 50.8% and the leftovers are influenced by the other factors which are not included in this research. The research shows that in partial, ease of use doesn’t affect significantly on purchasing decision and brand image influences significantly on purchasing decision. Simultaneously, ease of use and brand image influences significantly on purchasing decisions.

ANALISIS E-WALLET BERBASIS TAM (TECHNOLOGY ADOPTION MODEL) DI PT TELKOM INDONESIA TBK

<p align="justify">More and more internet users have made actors in the field of technology to continuously create innovations so that smartphone users can make the best use of technology. One of them is by issuing a product called e-wallet which is a trend in carrying out all payment transaction activities and purchasing items. Likewise with PT Telkom which participated in implementing government policies in reducing the use of cash. By using the e-wallet application owned by PT Telkom, this research is focused on the use of TAM-based e-wallet. In conducting this research, the methodology used is by using a qualitative methodology and through a descriptive approach and using data collection techniques through literature studies. There are many benefits and also the convenience of using Telkom's e-wallet or commonly known as t-money. With various features in the application, users can make bill payment transactions as well as purchase train or plane tickets, merchants, and make purchases of electricity pulses or data packages. To be able to win the competition in the business world, PT Telkom must continue to improve the features available in the e-wallet application. That way users can feel the benefits of using the application. This can be used by Telkom to provide testimonials to other users.</p><p align="justify"><strong><span lang="IN">Keyword</span>s</strong><span lang="IN">: Fintech, E-wallet, TAM</span></p>