About Dataset:

This dataset provides detailed information on airline flight routes, fares, and passenger volumes within the United States from 1993 to 2024.

Data Features:

1. tbl: Table identifier 2. Year: Year of the data record 3. quarter: Quarter of the year (1-4) 4. citymarketid_1: Origin city market ID 5. citymarketid_2: Destination city market ID 6. city1: Origin city name 7. city2: Destination city name 8. airportid_1: Origin airport ID 9. airportid_2: Destination airport ID 10. airport_1: Origin airport code 11. airport_2: Destination airport code 12. nsmiles: Distance between airports in miles 13. passengers: Number of passengers 14. fare: Average fare 15. carrier_lg: Code for the largest carrier by passengers 16. large_ms: Market share of the largest carrier 17. fare_lg: Average fare of the largest carrier 18. carrier_low: Code for the lowest fare carrier 19. lf_ms: Market share of the lowest fare carrier 20. fare_low: Lowest fare 21. Geocoded_City1: Geocoded coordinates for the origin city 22. Geocoded_City2: Geocoded coordinates for the destination city 23. tbl1apk: Unique identifier for the route

Potential Uses: 1. Market Analysis: Assess trends in air travel demand, fare changes, and market share of airlines over time. 2. Price Optimization: Develop models to predict optimal pricing strategies for airlines. 3. Route Planning: Identify profitable routes and underserved markets for new route planning. 4. Economic Studies: Analyze the economic impact of air travel on different cities and regions. 5. Travel Behavior Research: Study changes in passenger preferences and travel behavior over the years. 6. Competitor Analysis: Evaluate the performance of different airlines on various routes.

United States - Consumer Price Index for All Urban Consumers: Airline Fares in U.S. City Average was 270.33600 Index 1982-84=100 in September of 2025, according to the United States Federal Reserve. Historically, United States - Consumer Price Index for All Urban Consumers: Airline Fares in U.S. City Average reached a record high of 322.64500 in March of 2013 and a record low of 128.00000 in January of 1989. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Consumer Price Index for All Urban Consumers: Airline Fares in U.S. City Average - last updated from the United States Federal Reserve on December of 2025.

In 2024, the consumer price index (CPI) of airplane fares in Japan reached ***** points, increasing by **** points compared to the base year in 2020. This was a significant increase and the highest index during the surveyed period.

Quarterly domestic (short and long haul) and international air fares, by fare type group (business class, economy, discounted and other).

Airfare Price Drop Protection Market Outlook

According to our latest research, the global airfare price drop protection market size in 2024 stands at USD 1.17 billion, reflecting robust demand for travel cost optimization solutions across the globe. The market is expected to expand at a CAGR of 18.2% from 2025 to 2033, reaching a projected value of USD 5.16 billion by 2033. This remarkable growth is primarily fueled by increasing consumer awareness of dynamic airfare pricing, the proliferation of digital travel platforms, and a heightened focus on user-centric travel experiences.

One of the primary growth drivers for the airfare price drop protection market is the growing volatility and unpredictability of airline ticket prices. As airlines increasingly adopt dynamic pricing algorithms, travelers often face substantial price fluctuations between the time they search for and book tickets. This uncertainty has led to a surge in demand for solutions that can offer financial protection against post-purchase price drops. The integration of advanced analytics and artificial intelligence in travel platforms has further facilitated the development of automated price monitoring and refund mechanisms, making these services more accessible and user-friendly for a broad spectrum of travelers.

The rapid digital transformation of the travel industry has also been a significant catalyst for market expansion. The widespread adoption of online travel agencies (OTAs), mobile travel apps, and meta-search engines has made it easier for consumers to compare prices and access ancillary services, including price drop protection. These platforms have leveraged big data and machine learning to enhance their offerings, providing real-time notifications and seamless refund processes. Additionally, the increasing penetration of smartphones and high-speed internet in emerging economies has expanded the addressable market, enabling even budget-conscious travelers to benefit from airfare price drop protection services.

Another crucial factor propelling the market is the changing expectations of both individual and corporate travelers. With business travel rebounding post-pandemic and leisure travelers seeking greater value for money, there is a heightened emphasis on risk mitigation and cost savings. Corporate travel managers are increasingly integrating airfare price drop protection into their travel policies to optimize budgets and improve employee satisfaction. Simultaneously, leisure travelers, empowered by technology, are demanding more transparent and flexible booking options. This evolving consumer mindset is pushing airlines, OTAs, and travel agencies to differentiate themselves by offering innovative price assurance features.

From a regional perspective, North America remains the largest contributor to the airfare price drop protection market, owing to high digital adoption rates and a mature travel ecosystem. However, Asia Pacific is emerging as the fastest-growing region, driven by a burgeoning middle class, increased international travel, and rapid technological advancements. Europe also holds a significant share, supported by a well-established airline network and a strong culture of travel insurance adoption. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, bolstered by the expansion of low-cost carriers and increased online travel bookings.

Product Type Analysis

The product type segment of the airfare price drop protection market is broadly categorized into Automatic Refund, Manual Claim, Subscription-Based, and Pay-Per-Use models. Automatic refund solutions have gained significant traction due to their seamless, user-friendly experience. These services automatically monitor ticket prices after purchase and initiate refunds or credits if a lower fare becomes available, eliminating the need for customer intervention. The integration of real-time fare tracking algorithms and secure payment gateways has made automatic refund offerings highly attractive to both individual and corporate travelers, driving their adoption across major online travel agencies and airline platforms.

Manual claim models, while less automated, remain relevant, particularly among traditional travel agencies and consumers who prefer a more hands-on approach. In this model, travelers must

China Air: Transport Index: Ticket Price: Domestic Line data was reported at 129.600 Jan2004=100 in Jun 2019. This records an increase from the previous number of 127.500 Jan2004=100 for May 2019. China Air: Transport Index: Ticket Price: Domestic Line data is updated monthly, averaging 109.600 Jan2004=100 from Jan 2007 (Median) to Jun 2019, with 149 observations. The data reached an all-time high of 136.800 Jan2004=100 in Aug 2018 and a record low of 78.500 Jan2004=100 in Dec 2008. China Air: Transport Index: Ticket Price: Domestic Line data remains active status in CEIC and is reported by Civil Aviation Administration of China. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TI: Air: Transport Index.

This statistic shows the change in domestic corporate ticket prices in the United States from the first quarter of 2015 through the first quarter of 2020, with a breakdown by number of days the ticket was purchased in advance. In the first quarter of 2020, for a ticket purchased between zero and *** days in advance, the U.S. average domestic corporate air fare stood at *** U.S. dollars.

The "flights.csv" dataset contains information about the flights of an airport. This dataset includes information such as departure and arrival time, delays, flight company, flight number, flight origin and destination, flight duration, distance, hour and minute of flight, and exact date and time of flight. This data can be used in management analysis and strategies and provide useful information about the performance of flights and placement companies. The analysis of the data in this dataset can be used as a basis for the following activities: - Analysis of time patterns and trends: by examining the departure and arrival time of the aircraft, changes and time changes, patterns and trends in flight behavior can be identified. - Analysis of American companies: By viewing information about airlines such as the number of flights, the impact and overall performance, you can compare and analyze the performance of each company. - Analysis of delays and service quality: By examining delays and arrival time, I can collect and analyze information about the quality of services provided by the airport and companies. - Analysis of flight routes: by checking the origin and destination of flights, distances and flight duration, popular routes and people's choices can be identified and analyzed. - Analysis of airport performance: by observing the characteristics of flights and airport performance, it is possible to identify and analyze the strengths and weaknesses of the airport and suggest improvements.

It provides various tools for data analysis and visualization and can be used as a basis for managerial decisions in the field of aviation industry.

Airline Company Codes (in order of frequency for this dataset)

WN -- Southwest Airlines Co.

DL -- Delta Air Lines Inc.

AA -- American Airlines Inc.

UA -- United Air Lines Inc.

B6 -- JetBlue Airways

AS -- Alaska Airlines Inc.

NK -- Spirit Air Lines

G4 -- Allegiant Air

F9 -- Frontier Airlines Inc.

HA -- Hawaiian Airlines Inc.

SY -- Sun Country Airlines d/b/a MN Airlines

VX -- Virgin America

This statistic shows the price per route of low cost airlines in Europe in 2013 and 2014. The average cost per route of budget airline Ryanair was 65.67 euros in 2014, up from 58.45 euros the previous year.

The statistic illustrates the results of a 2018 survey among U.S. air travelers based on their preferences for booking channels in 2017, with a breakdown by type of travel. For domestic flights, some ** percent of the respondents used the airline's website to book their tickets for personal flying purposes, while on international flights ** percent of them said they book travel from an online travel agency.

https://www.hackerearth.com/challenges/hackathon/enter-the-travel-verse/

Identify trends with Airline ticketing data

The past few years represent the best and worst in air travel in decades. 2019 saw the best year for air travel this century while the pandemic brought long periods of extreme swings in demand. ARC’s data is the world’s largest single source of airline ticketing data.

The goal is to identify a trend that leads to a new prediction using ARC’s data to incorporate it into a marketable data product within the B2B or B2B2C space.

Your task is to find creative ways to apply the vast data store from historical trends mapped into predictive analytics to specific recommendations for consumers and suppliers of air travel — the potential has no limit.

The Challenge - Review the provided airline ticketing dataset below Identify a problem in the travel and tourism industry where advanced awareness of current and future trends using airline ticketing data will solve. - Identify the audience in the B2B or B2B2C space that would find value in the solution. - Using Machine learning, data science technologies and/or advanced analytics to develop a solution that solves the problem that you have identified and defined. (For example, recommender systems, predictive analytics, etc.) - Create an application prototype (program, website, API etc.) and/or visual aid (such as a dashboard or video presentation) to demonstrate the business value of the proposed solution.

Price-To-Tangible-Book-Ratio Time Series for Southwest Airlines Company. Southwest Airlines Co. operates as a passenger airline company that provides scheduled air transportation services in the United States and near-international markets. As of December 31, 2024, the company operated a total fleet of 803 Boeing 737 aircraft; and served 117 destinations in 42 states, the District of Columbia, and the Commonwealth of Puerto Rico, as well as ten near-international countries, including Mexico, Jamaica, the Bahamas, Aruba, the Dominican Republic, Costa Rica, Belize, Cuba, the Cayman Islands, and Turks and Caicos. It also provides inflight entertainment and connectivity services; and Rapid Rewards loyalty program that enables program members to earn points for dollars spent on Southwest base fares. In addition, the company offers a suite of digital platforms to support customers' travel needs, including websites and apps; and SWABIZ, an online booking tool. Further, it provides ancillary services, such as Southwest's EarlyBird Check-In, upgraded boarding, and transportation of pets and unaccompanied minors. Southwest Airlines Co. was incorporated in 1967 and is headquartered in Dallas, Texas.

Flight Search Market Outlook

According to our latest research, the global Flight Search market size reached USD 4.2 billion in 2024, reflecting robust expansion driven by increasing digitalization in the travel sector. The market is projected to grow at a CAGR of 9.7% from 2025 to 2033, reaching an estimated USD 9.7 billion by 2033. This growth is primarily attributed to the rapid adoption of advanced search technologies, the proliferation of mobile platforms, and the rising demand for personalized travel experiences. As per our latest research findings, the market is poised for significant transformation, with technology innovation and shifting consumer preferences acting as pivotal growth factors.

One of the most significant growth drivers in the Flight Search market is the increasing penetration of internet connectivity and mobile devices across both developed and emerging economies. With the proliferation of smartphones and the widespread availability of high-speed internet, consumers now have seamless access to flight search platforms, enabling them to compare prices, check real-time availability, and make informed travel decisions. This digital transformation has not only simplified the process of booking flights but has also empowered consumers to seek out the best deals and personalized travel options. Additionally, the integration of artificial intelligence and machine learning into flight search algorithms has enabled platforms to provide more accurate, relevant, and dynamic search results, further enhancing user satisfaction and driving market growth.

Another critical factor contributing to the expansion of the Flight Search market is the growing emphasis on personalized and user-centric experiences. Modern travelers increasingly expect tailored recommendations, flexible search filters, and intuitive interfaces that cater to their specific needs and preferences. Flight search providers are responding by leveraging big data analytics and customer profiling to deliver customized offerings, such as fare alerts, loyalty program integration, and ancillary service suggestions. This focus on personalization not only improves customer engagement and retention but also provides opportunities for value-added revenue streams through targeted advertising and cross-selling of related travel services. As a result, flight search platforms are evolving into comprehensive travel ecosystems that go beyond simple fare comparison.

Furthermore, strategic collaborations and partnerships between airlines, online travel agencies (OTAs), and technology providers are playing a vital role in shaping the Flight Search market. These alliances enable seamless integration of flight data, real-time inventory management, and enhanced booking capabilities, fostering a more competitive and efficient marketplace. The adoption of open APIs and standardized data protocols has facilitated interoperability between different platforms, ensuring that users have access to the most up-to-date and comprehensive flight information. Additionally, the growing trend of direct bookings through airline websites, supported by advanced search functionalities, is encouraging airlines to invest heavily in their digital infrastructure, thereby contributing to the overall growth and innovation within the market.

The concept of Travel Metasearch has become increasingly pivotal in the Flight Search market. Travel Metasearch platforms aggregate data from various travel service providers, offering users a one-stop solution to compare prices and services across multiple airlines and travel agencies. This not only enhances the transparency of travel options but also empowers consumers to make well-informed decisions based on comprehensive data. As the demand for personalized and efficient travel solutions grows, Travel Metasearch platforms are leveraging advanced algorithms and AI technologies to refine search results and offer tailored recommendations. By integrating with various travel databases and APIs, these platforms ensure that users have access to the most current and relevant information, further solidifying their role as essential tools in the modern traveler's toolkit.

From a regional perspective, North America continues to dominate the Flight Search market, owing to its mature travel industry, high consumer awareness, and early adoption of digital technologies

Airfare Intelligence Market Outlook

According to our latest research, the global airfare intelligence market size reached USD 1.72 billion in 2024, driven by the increasing adoption of advanced analytics and AI-driven solutions within the aviation and travel sectors. The market is exhibiting a robust growth trajectory, with a compound annual growth rate (CAGR) of 10.3% projected over the forecast period. By 2033, the market is expected to reach USD 4.25 billion, propelled by rising demand for dynamic pricing models, enhanced revenue management strategies, and the proliferation of digital travel platforms. This growth is underpinned by the increasing complexity of airfare structures and the need for real-time, data-driven decision-making in a rapidly evolving global travel landscape.

One of the primary growth factors for the airfare intelligence market is the widespread integration of artificial intelligence and machine learning technologies into pricing and revenue management systems. Airlines and travel agencies are leveraging these technologies to process massive datasets, enabling them to predict demand fluctuations, optimize pricing strategies, and maximize profitability. The ability to harness real-time data from various sources, such as competitor fares, historical booking trends, and macroeconomic indicators, provides unparalleled insights that drive smarter decision-making. This technological evolution is not only enhancing operational efficiency but also offering a competitive edge in a market where consumer expectations for transparency and personalization are higher than ever before.

Another significant growth driver is the increasing competition among airlines and online travel agencies (OTAs), which has intensified the need for advanced airfare intelligence solutions. As the global travel industry continues to recover and expand post-pandemic, airlines are under pressure to differentiate themselves through innovative pricing models and tailored offerings. Airfare intelligence platforms enable these organizations to monitor competitor pricing in real time, identify market opportunities, and adjust their fare structures dynamically. This capability is crucial in capturing price-sensitive travelers and optimizing load factors, particularly in markets where demand is highly elastic and subject to rapid change due to external events or seasonal fluctuations.

Furthermore, the growing adoption of cloud-based solutions is facilitating the scalability and accessibility of airfare intelligence tools across organizations of all sizes. Cloud deployment offers flexibility, cost-effectiveness, and the ability to integrate seamlessly with other enterprise applications such as customer relationship management (CRM) and enterprise resource planning (ERP) systems. This has democratized access to sophisticated analytics, allowing not only major airlines but also smaller carriers, OTAs, and corporate travel managers to leverage advanced airfare intelligence capabilities. The trend towards digital transformation in the travel and hospitality sector is expected to further accelerate the adoption of these solutions, driving sustained market growth through the forecast period.

From a regional perspective, North America currently dominates the airfare intelligence market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of leading airlines, advanced IT infrastructure, and a high degree of digitalization in the travel sector are key factors contributing to North America’s market leadership. Europe is also witnessing significant growth, driven by the increasing adoption of dynamic pricing and data analytics among low-cost carriers and traditional airlines alike. Meanwhile, the Asia Pacific region is expected to register the fastest CAGR through 2033, fueled by rapid air travel expansion, rising middle-class incomes, and the proliferation of digital travel platforms in emerging economies such as China and India.

Component Analysis

The airfare intelligence market is segmented by component into software and services, each playing a critical role in the overall ecosystem. The software segment comprises advanced analytics platforms, AI-driven pricing engines, and data visualization tools that enable airlines and travel agencies to collect, process, and analyze vast amounts of fare-related data. These solutions are designed to deliver actionable insights, automate complex pricing decisions, an

Graph and download economic data for Revenue Passenger Miles for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (RPMD11) from Jan 2000 to Jul 2025 about flight, miles, passenger, air travel, travel, revenue, domestic, and USA.

Operational Data Store for Real-Time Flights Market Outlook

According to our latest research, the Global Operational Data Store for Real-Time Flights market size was valued at $1.75 billion in 2024 and is projected to reach $4.82 billion by 2033, expanding at a CAGR of 11.7% during 2024–2033. The primary driver of this robust growth is the increasing demand for real-time data integration and analytics solutions across the aviation industry, which has become essential for enhancing operational efficiency, reducing delays, and improving passenger experience. As airlines, airports, and air traffic control agencies strive to modernize their digital infrastructure, the adoption of operational data stores (ODS) capable of aggregating and processing real-time flight information is accelerating rapidly on a global scale.

Regional Outlook

North America currently holds the largest share of the global Operational Data Store for Real-Time Flights market, accounting for approximately 39.2% of the total market value in 2024. This dominance is attributed to the region’s mature aviation infrastructure, early adoption of advanced data management technologies, and the presence of major market players. The United States, in particular, has been at the forefront of implementing real-time data integration platforms within both commercial and private aviation sectors. The Federal Aviation Administration’s (FAA) regulatory framework and robust investments in digital transformation initiatives have further propelled the uptake of ODS solutions. Additionally, the region’s focus on enhancing passenger experience through seamless information sharing and operational transparency continues to drive sustained demand for innovative data solutions.

Asia Pacific is emerging as the fastest-growing region in the Operational Data Store for Real-Time Flights market, with a forecasted CAGR of 14.5% from 2024 to 2033. This rapid growth is underpinned by significant investments in airport modernization, surging air passenger traffic, and an increasing number of airline startups across countries like China, India, and Southeast Asian nations. Governments in the region are prioritizing smart airport projects and digital transformation in air traffic management, which is leading to a surge in demand for real-time data stores. Furthermore, the expansion of low-cost carriers and the adoption of cloud-based deployment models are lowering entry barriers for smaller airlines, thereby accelerating market penetration and innovation in operational data management.

Emerging economies in Latin America, the Middle East, and Africa are gradually integrating operational data store solutions but face unique challenges. Limited IT infrastructure, budget constraints, and varying regulatory standards present obstacles to widespread adoption. However, localized demand is growing, particularly as airlines and airports in these regions recognize the value of real-time data in minimizing disruptions and optimizing resource allocation. Strategic partnerships with global technology providers and support from international aviation organizations are helping to address skill gaps and promote best practices. As these markets mature, tailored solutions that account for regional nuances and policy frameworks are expected to drive incremental growth and foster greater digitalization within the aviation ecosystem.

Report Scope

Context

The European Flights Dataset from 2016 to 2022 provides an extensive record of air traffic activities across various European airports. The data includes essential metrics related to IFR (Instrument Flight Rules) movements, covering both departures and arrivals as reported by the Network Manager and Airport Operator. The dataset is comprehensive, with 688,099 entries and 14 columns, detailing flights over a span of seven years.

Content

Geography: Europe

Time period: Jan 2016- May 2022

Unit of analysis: European Flights Dataset

Variables

Acknowledgements

Datasource: Aviation Intelligence Unit Portal

Inspiration: Commercial air transport in August 2021: in recovery

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Airline Branded Fares Retailing Market Outlook

According to our latest research, the global airline branded fares retailing market size reached USD 6.3 billion in 2024, with a robust CAGR of 8.7% expected through the forecast period. By 2033, the market is projected to reach USD 13.2 billion, propelled by evolving passenger preferences, digital transformation, and airlines’ strategic focus on ancillary revenue streams. The growth in this sector is primarily driven by the increasing demand for personalized travel experiences and the rise in digital retailing capabilities among airlines.

One of the most significant growth drivers for the airline branded fares retailing market is the shift toward passenger-centric strategies. Airlines are increasingly recognizing the importance of offering differentiated fare products that cater to diverse traveler needs and preferences. The segmentation of fare types, ranging from basic economy to premium cabins, enables carriers to target a wider spectrum of customers and capture incremental revenue from ancillary services. The proliferation of branded fares allows airlines to unbundle services, offering customers the flexibility to pay only for what they value most, such as additional baggage, seat selection, or priority boarding. This approach not only enhances customer satisfaction by providing transparency and choice but also boosts airlines’ profitability by optimizing yield management and upselling opportunities.

Digital transformation is another pivotal factor fueling the expansion of the airline branded fares retailing market. The integration of advanced retailing platforms, artificial intelligence, and machine learning technologies has revolutionized the way airlines market and distribute their branded fare products. Enhanced data analytics capabilities enable airlines to personalize offers, predict customer preferences, and dynamically adjust pricing strategies in real time. The rise of mobile applications and user-friendly websites has further streamlined the booking process, making it easier for travelers to compare, select, and purchase branded fares. These technological advancements have not only improved operational efficiency but also empowered airlines to engage with customers throughout the travel journey, fostering loyalty and repeat business.

Additionally, the growing emphasis on ancillary revenue generation has become a cornerstone of airline business models, particularly in the wake of fluctuating fuel prices and competitive pressures. Branded fares serve as a powerful tool for airlines to diversify income streams beyond traditional ticket sales. By offering tiered fare options bundled with various services and amenities, airlines can maximize revenue per passenger while addressing the unique requirements of both leisure and business travelers. This trend is further amplified by the increasing adoption of direct distribution channels, which enable airlines to maintain greater control over their product offerings and customer relationships, thereby enhancing overall profitability and market competitiveness.

From a regional perspective, North America currently dominates the airline branded fares retailing market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The strong presence of major carriers, high digital adoption rates, and a mature travel ecosystem contribute to North America’s leadership in this space. Europe is witnessing steady growth, driven by regulatory support for transparent pricing and the proliferation of low-cost carriers. Meanwhile, the Asia Pacific region is emerging as a high-growth market, fueled by rising disposable incomes, expanding air travel networks, and increasing demand for differentiated travel experiences. Latin America and the Middle East & Africa are also expected to see notable growth, albeit from a smaller base, as airlines in these regions invest in digital retailing capabilities and branded fare strategies to capture new market segments.

Fare Type Analysis

Daily data showing UK flight numbers and rolling seven-day average, including flights to, from, and within the UK. These are official statistics in development. Source: EUROCONTROL.

Hey everyone!

I've put together a cool dataset on Korean domestic airline ticket data for the whole year of 2022, collected daily. With this data, we can check out daily changes in available seat count, ticket prices, and class codes. It's a great opportunity to try forecasting passenger movement and predicting ticket price changes.

Let's dive in and see what we can discover together!