Ticket Prices Research Articles

Cluster analysis of travel behaviour threats in chosen European functional urban areas during the economic crisis

Motives: Urban mobility models are constantly changing due to economic, social, infrastructural, and geographical factors. Preferences for transport modes vary by country, region, and city, and transport infrastructure and policy have a significant impact on residents’ choices. Additionally, economic factors such as economic crises, public policy decisions, and events such as armed conflicts have a significant impact on the dynamics of mobility in functional urban areas (FUAs).Aim: The main goal of the research was to create groups of countries (clusters) that have similar priorities regarding travel behaviour threats revealed as a result of the economic crisis resulting from the conflict in Ukraine.Results: The study shows that the main threats during the economic crisis (resulting from the war in Ukraine) are economic factors (e.g., ticket prices, an increase in fuel costs), legal factors (e.g., loss of a driving license or passenger transport license), and infrastructural factors (e.g., poor condition of infrastructure). The analysed countries were grouped based on the hierarchical prioritization of threats, using Ward’s hierarchical clustering method. Interestingly, the distance from the conflict epicentre did not significantly influence the prioritization of threat factors influencing transportation behaviour in FUAs. Instead, factors such as membership in international organizations, energy dependence on Russia, the level of economic growth, and transport infrastructure played a more key role in the priority-setting process.

Strategi Pengembangan Daya Tarik Wisatawan terhadap Minat Kunjung pada New Celosia Bandungan

The Indonesian region has a wealth of natural and cultural resources that provide large capital for the tourism sector. Tourism is one of the creative economies that is currently in the development stage. New Celosia Bandungan is one of the tourist destinations that has high appeal in the Bandungan area, Central Java. This research aims to analyze strengths, weaknesses, opportunities, and threats (SWOT) as well as policy analysis that can be carried out to develop tourist attractions owned by New Celosia as a tourist destination. The method used in this research is a qualitative approach with data collection through field observations, interviews with informants, and documentation. The analysis results show that New Celosia has several strengths, such as affordable ticket prices, attractive photo spots, and complete facilities. However, weaknesses were also found, such as non-functioning rides and relatively expensive food prices. Regarding opportunities, the strategic location and increasing tourism demand provide potential for further development. On the other hand, threats such as competition with other tourist attractions and extreme weather must also be anticipated. Based on this SWOT analysis, it is recommended that New Celosia Tourism improve the management of facilities and services, as well as take advantage of existing development opportunities to increase visiting interest and competitiveness in the tourism industry.

Study on the Optimization Strategy of Chinese Film Ticket Price Pricing

Film, as an important cultural industry and entertainment mode, has developed over the years and formed a relatively complete industrial chain. However, in the long-term development process, movie ticket pricing has always been a hot issue that has attracted much attention. In recent years, China's film market has shown a trend of rapid development, and the box office has repeatedly reached a new high, but the level of movie ticket prices has also been rising, which has triggered widespread social concern and discussion.Research and optimization of movie ticket pricing strategy is of great significance to improve the competitiveness of the movie market and promote the sustainable development of the movie industry.This paper first reviews the current research status of the predecessors, summarizes the relevant theoretical basis needed for the study, analyzes the existing problems in movie ticket pricing, conducts an analysis of the change in domestic ticket prices and compares it with international prices, and finally concludes with an optimal strategy.

THE INFLUENCE OF TOURISM ATTRACTION, ENTRY TICKET PRICES, AND WORD OF MOUTH ON THE DECISION TO VISIT TIRTA WAHYU ARTA TOURISM ATTENTION IN PEKALONGAN DISTRICT

<p>This research aims to analyze the influence of tourist tricks, entrance ticket prices, and word of mouth on the decision to visit Tirta Wahyu Arta Tourism. The type of research used in this research is Associative Quantitative. The data collected uses primary data, namely data collected or obtained directly in the field. In this study there were 97 respondents used as samples. The sampling method uses purpose sampling, namely determining samples based on criteria. The analytical tool used is multiple linear regression analysis. Based on the results of the analysis, it is stated that tourist attraction has a positive and significant effect on the decision to visit with a calculated t value of 5.188 and a significant value of 0.000. The entrance ticket price has a positive and significant effect on the decision to visit with a calculated t value of 3.954 and a significant value of 0.000. Word of Mouth has a positive and significant effect on Visiting Decisions with a calculated t value of 2.698 and a significant value of 0.008.</p><p><strong><br /></strong></p>

Choosing a flat rate over a pay-per-use tariff for public transport: Do psychological factors matter?

We investigate the relationship between various psychological factors (taximeter effect, flexibility effect, cost control effect, pre-commitment effect), annual distance traveled, and public transport tariff preferences (pay-per-use vs. flat rate). While a pay-per-use tariff entails ticket prices depending on usage intensity, a flat rate involves an annual public transport subscription covering all journeys within a year. Drawing from a sample of 3,381 Swiss public transport customers utilizing either the pay-per-use option or holding a flat-rate subscription, a binomial logistic regression highlights that the number of passenger kilometers traveled (pkm) predominantly influences the choice of a flat rate. However, the examined psychological factors also significantly shape decision-making. Notably, these effects vary based on the quantity of the product consumed. Specifically, both the taximeter and cost-control effects tend to increase with pkm. Conducting a simulation using binomial logistic regression, we illustrate how different psychological factors are related to the likelihood of opting for a flat-rate subscription. The findings suggest that the level of importance of the psychological factors are relevant to predict the odds of selecting a flat-rate subscription. Hence, emphasizing product advantages in marketing communications and strategically adjusting product design to leverage these psychological factors emerge as effective strategies for enhancing sales promotion and fostering customer loyalty. These results offer insights into consumer psychology and decision-making within the transportation sector. The implications are particularly valuable for managers aiming to address barriers to public transport use. By strategically refining ticket product ranges, managers can actively contribute to reducing CO2 emissions through induced modal shifts.

Analysis and Box Office Prediction of Chinese High Box Office Films- Empirical Analysis Based on the Top250 Movies on Maoyan.com

This project focuses on analyzing and predicting box-office performance using data from Maoyan.com. Several key factors, including release year and month, ticket price, movie duration, and the proportion of positive reviews, are examined for their influence on box-office revenue. We begin by employing simple linear regression to investigate the relationship between Maoyan.com ratings for the top 250 movies and their box-office performance. Additionally, we construct an Autoregressive Distributed Lag (ARDL) model to assess the impact of these factors over time. The model parameters are estimated using the least squares regression method, and the Mean Absolute Percentage Error (MAPE) is minimized to achieve optimal prediction accuracy. Extensive data cleaning and preprocessing ensure the reliability of our analysis. The findings from this study provide valuable insights into the determinants of box-office success and offer a robust predictive model for future revenue estimation.

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.

Do uncertain outcomes matter for ticket prices? Examination of the National Football League's secondary ticket market

PurposeThis study examines the impact of outcome uncertainty on the National Football League (NFL) secondary ticket market prices. As a demand-driven market, it is essential to comprehend how resellers respond to outcome uncertainty, one of the consumer demand factors in sports.Design/methodology/approachUsing real-time ticket prices and money lines as a proxy of the probabilities of winning, this study employs a regression analysis and examines 33,554 price observations from the NFL’s secondary ticket market partner, StubHub.FindingsThe result shows a positive relationship between outcome uncertainty and secondary market ticket prices, indicating that resellers adjust the prices in response to the level of outcome uncertainty and put more value on games with greater uncertainty. This finding confirms the demand-driven nature of the secondary ticket market, as outcome uncertainty is one of the demand factors in sports.Originality/valueThis study links the uncertainty of outcome hypothesis with secondary ticket market pricing and fills a gap in the literature by providing an important perspective on games with uncertainty in the secondary ticket market. Outcome uncertainty has limited understanding in relation to secondary ticket market pricing despite its relationship with consumer demand. The positive relationship between outcome uncertainty and the ticket prices, grounded in real-time price data and win probability from sport betting markets, enhances our understanding of price determinations in the secondary ticket market.

Pengaruh Harga Tiket Online dan Pelayanan Terhadap Keputusan Pembelian Tiket Maskapai Garuda Indonesia Pada Mahasiswa di Yogyakarta

The advancement of information technology and the internet has enabled the emergence of various online ticket booking platforms, providing users with a convenient and efficient way to purchase flight tickets. This research aims to analyze and determine the extent of the influence of online ticket prices and service quality on the ticket purchasing decisions for Garuda Indonesia. This study employs a quantitative method with data collection techniques obtained directly through observation, documentation, and questionnaire distribution, targeting 200 undergraduate students in the Yogyakarta province from December 2023 to January 2024. The t-test results indicate that the ticket price variable (HT) has a significant impact on the ticket purchasing decision (KPM) for Garuda Indonesia among students in Yogyakarta, as evidenced by a t-value of 2.026 with a significance value (Sig.) of 0.044. The partial test results also show that service quality (KPY) has a very significant impact on the ticket purchasing decision (KPM) for Garuda Indonesia among students in Yogyakarta, with a t-value of 6.448 and a significance value (Sig.) of 0.000. The findings reveal that both ticket price and service quality significantly influence the ticket purchasing decisions for Garuda Indonesia, with service quality having a greater impact.

Memantik Keputusan Pembelian Ulang Jasa Wisata dan Faktor Pengaruhnya (Studi kasus Wisatawan Di Kebun Binatang Mangkang Semarang)

The research objective is to analyze the impact of ticket prices and service quality on the decision to repurchase tourism services at the Mangkang Zoo, Semarang. This research uses IBM SPSS version 25 regression analysis. Accidental sampling technique was used to take a sample of 100 respondents. The results of this research show that ticket prices and service quality have a positive and significant effect on the decision to repurchase tourism services at the Mangkang Zoo, Semarang. This study can be used as reference material for managers of the Mangkang Zoo in Semarang to design and establish effective and efficient marketing policies. The results of this study also contribute to the development of knowledge and input for the Mangkang Zoo in Semarang to focus more on developing the performance facilities of the Mangkang Zoo in Semarang

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.

A study on Korean Musical Ticket Prices: Focusing on Big Theatre Musical from 2019 to 2023

A study on Korean Musical Ticket Prices: Focusing on Big Theatre Musical from 2019 to 2023

Prediction of Flight Areas using Machine Learning Algorithm

Anyone who often uses the airways wants to predict when it will be best to purchase a ticket in order to get the best possible value. Aircraft firms continuously adjust ticket prices in an effort to maximize profits. When it's anticipated that demand for more income will grow, aircraft manufacturers may raise flying prices. Information analysis for a given air route, comprising the features like take-off time, entrance time, and airways during a specified period, has been gathered in order to decrease costs. To use the machine learning models, qualities are arranged based on the information that has been gathered. The machine learning approach to determine costs based on attributes is presented in the paper below.

Studi Probabilitas Pemilihan Moda Transportasi Kereta Api Eksekutif Gajayana dan Kereta Api Eksekutif Jayabaya dengan Rute Jakarta-Malang

The train is a means of land transportation that continues to experience improvements in its services. Services and regulations change with the times, thus making PT. The Railways are making efforts to improve quality in terms of service, comfort and safety where all trains use AC facilities and eliminate all hawkers who sell on trains and at train stations in order to provide comfort to passengers. From these changes, each mode of transportation, especially the Gajayana Executive Train and the Jayabaya Executive Train, has different characteristics in terms of travel time and travel fare. Therefore, the aim of this research is to determine the probability of train selection based on the factors reviewed by distributing questionnaires and using the Stated Preference method to obtain primary data. The data obtained was then analyzed using Binomial Logit regression with Microsoft Excel software. From this research, significant results were obtained regarding the probability value of choosing a mode of transportation based on the difference in ticket prices of IDR. 40,000,- then the PKAG probability value is 0.226 and the PKAJ probability value is 0.774. So it can be concluded that respondents have more interest in the Jayabaya Executive Train because ticket prices are cheaper than the Gajayana Executive Train. Meanwhile, the probability value for choosing a mode of transportation is based on the travel time difference of -62 minutes, so the PKAG probability value is 0.904 and the PKAJ probability value is 0.096. So it can be concluded that respondents have more interest in the Gajayana Executive Train because the travel time is faster.

Penerapan Metode Simple Additive Weighting (SAW) Dalam Sistem Pendukung Keputusan Pemilihan Kapal Sebagai Moda Transportasi Laut

Maritime transportation has become the primary choice for Indonesian society due to its ability to carry passengers and goods in large quantities at relatively low costs. Based on data from the Indonesian Ministry of Transportation, there are 306 ships operating in domestic crossings, with 118 managed by ASDP Ferry Indonesia, 170 private ships, and 18 BUMF ships. Based on deep learning, this study aims to assist students of the Selaparang Lombok Yogyakarta dormitory in recommending the best ship selection for the Surabaya-Lombok route and vice versa. The decision support system is evaluated based on criteria including ticket prices, travel time, travel comfort, facilities, ship capacity, safety, departure schedule regularity, and operator reputation. This study uses a simple Weighted Evaluation Method called Simple Additive Weighting to determine the best alternative ranking. The results show that the comparison test between the system calculation and Microsoft Excel calculation results in 100% similarity. KMP Kirana VII occupies the first rank with a value of 0.95, making it the best ship solution suitable for student use

Who will board urban air taxis? An analysis of advanced air mobility demand and value of travel time for business, airport access, and regional tourism trips in Iran

Recent advancements in the development of a comprehensive urban air mobility ecosystem promise the opportunity for its implementation in the near future. However, the utility of this emerging mode of transportation in comparison to the existing modes varies for different trip purposes and geographical contexts. It is, therefore, imperative to assess its usage potential for various scenarios before moving forward with implementation efforts. This paper presents the findings of three stated preference surveys aimed at characterizing prospective urban air mobility travel demand for weekly business, airport access, and regional tourism trips in Iran. Hybrid multinomial logit and hybrid nested logit models are estimated for each trip purpose. The results indicate that urban air mobility for weekly business trips represents the most viable market segment. Value-of-time estimates for weekly business trips are more than two and a half times higher than those for airport access trips, and tourism trips are valued even less. There is a trend towards delaying the adoption of air taxis to gain trust, and reducing ticket prices is seen as the most effective incentive for increasing the adoption rate. This study pioneers research on urban air mobility in a developing country context, offering valuable insights into market viability for investors and policymakers.

Road–Rail Intermodal Travel Mode Choice Behavior Considering Attitude Factors

Road–rail intermodal transportation (RRIT) leverages the advantages of multiple transport modes and is crucial for addressing the current issue of imbalanced development in the transportation sector. However, passengers’ behavior in choosing RRIT remains unclear, and it is necessary to optimize travel service quality through analyzing RRIT choice behavior based on user perceptions. This study designed a stated preference experiment that included both direct and multi-modal travel options. A hybrid choice model considering attitude variables was constructed, and four latent attitude variables—convenience, economy, comfort, and riskiness—were extracted to analyze their impact on intercity travel mode choice behavior under conditions of ticket booking uncertainty. The results revealed that the ticket booking success rate is a critical factor in travelers’ decision-making. Passengers tend to choose travel options with higher ticket booking success rates, even if it entails a slight increase in the ticket prices for the high-speed rail to high-speed rail transfer option. The attitude variables significantly influence intercity travel mode choice behavior, with travelers generally exhibiting a preference for risk avoidance in their travel options. Moreover, there are differences among various groups of travelers in their preferences and demands for the convenience, economy, and comfort aspects of travel options. These research findings can enhance our understanding of the key factors influencing the selection of RRIT services, thereby supporting RRIT designers and planners in improving service quality and facilitating the future growth of RRIT.

Who uses night trains and why? A mixed-method study profiling night train users in Switzerland

Addressing air travel demand is a key open challenge in transitioning to a low-carbon society. In Switzerland, where most flights are from/to nearby European countries, their substitution with night train services is a promising alternative. However, still little research investigates whether the demand for night trains is well-established and the motivations behind it. We aim to bridge this gap through a mixed-method study involving 389 Swiss residents who travelled by night train in 2022/23. A web survey was first conducted to identify latent classes of participants based on their daily and long-distance travel mode choices and evaluate relevant predictors of class membership. Participants of each class were then randomly selected to be involved in an in-depth interview on personal experiences and motivations underlying their choices. Results identify three classes of travellers distinguished by a predominant use of rail and public transport (greens), mixed long-distance travel mode choices and car-oriented daily mobility (pragmatists), preference for flying combined with public transport and active daily mobility (dissonants). Travel cost reduction is the only motivation significantly differentiating pragmatists and dissonants from the greens. This result suggests that fluctuations in ticket prices are the main driving force in shifting demand from flights to night trains.

The Regulation Impact of Foreign Ownership on the Cooperation Projects Air Transportation

<div><table cellspacing="0" cellpadding="0" align="left"><tbody><tr><td align="left" valign="top"><p class="AbstractText">This study aims to identify, locate, and analyze constitutional issues regarding the impact of foreign capital ownership above 50% (fifty percent) in government-business cooperation projects, particularly in the area of public interest projects involving air transportation infrastructure. This normative research examines legal texts, mainly primary and secondary legal materials. This research found that, first, the changes in the Presidential Regulation regarding foreign investment in the field of public interest, such as airport services, were incompatible with the Constitution. The changes abolished the maximum percentage limit of foreign investment regulated in the previous provisions so that currently, foreign investment may carry out Government Cooperation with Business Entities on air transportation infrastructure projects without a percentage limit. Second, based on the Indonesian Constitution, ownership of air transportation should be under the state's authority, learning from China, which excessively applies foreign investors in the air transportation sector, causing consumer welfare to be affected by very high airplane ticket prices.</p></td></tr></tbody></table></div>