Passenger Profiles Research Articles

The Impact of Cruise Product Consumption Phases on Cruise Passenger Spending in a Non-Overnight Stay Port: Implications for Destination Managers

The level of expenditure by cruise passengers in the various cities visited during their journey is a crucial variable for the key stakeholders involved in this industry. Promoting higher spending by cruise passengers in non-overnight stay ports is a challenge led by the destination manager. This study aims to shed light on the effect that different phases in the cruise passenger’s travel cycle have on their propensity to spend during their stay. Our case focuses on the city of A Coruña, a non-overnight stay port on Europe’s Atlantic arc routes, where the average spending per cruise passenger during their visit is quite low. The analysis considers the impact of passenger profiles and the cruise product consumption phases on the average spending per passenger. From a methodological perspective, we have applied logistic regression. The results indicate that the profile of the cruise passenger, variables related to the onboard journey, and the experience of the city are the factors with the greatest potential to increase cruise passenger spending during their visit to the city. This has allowed the areas of greatest impact and where actions should be focused to be identified for both the destination manager and key stakeholders.

Bus Network Adjustment Pre-Evaluation Based on Biometric Recognition and Travel Spatio-Temporal Deduction

A critical component of bus network adjustment is the accurate prediction of potential risks, such as the likelihood of complaints from passengers. Traditional simulation methods, however, face limitations in identifying passengers and understanding how their travel patterns may change. To address this issue, a pre-evaluation method has been developed, leveraging the spatial distribution of bus networks and the spatio-temporal behavior of passengers. The method includes stage of travel demand analysis, accessible path set calculation, passenger assignment, and evaluation of key indicators. First, we explore the actual passengers’ origin and destination (OD) stop from bus card (or passenger Code) payment data and biometric recognition data, with the OD as one of the main input parameters. Second, a digital bus network model is constructed to represent the logical and spatial relationships between routes and stops. Upon inputting bus line adjustment parameters, these relationships allow for the precise and automatic identification of the affected areas, as well as the calculation of accessible paths of each OD pair. Third, the factors influencing passengers’ path selection are analyzed, and a predictive model is built to estimate post-adjustment path choices. A genetic algorithm is employed to optimize the model’s weights. Finally, various metrics, such as changes in travel routes and ride times, are analyzed by integrating passenger profiles. The proposed method was tested on the case of the Guangzhou 543 route adjustment. Results show that the accuracy of the number of predicted trips after adjustment is 89.6%, and the predicted flow of each associated bus line is also consistent with the actual situation. The main reason for the error is that the path selection has a certain level of irrationality, which stems from the fact that the proportion of passengers who choose the minimum cost path for direct travel is about 65%, while the proportion of one-transfer passengers is only about 50%. Overall, the proposed algorithm can quantitatively analyze the impact of rigid travel groups, occasional travel groups, elderly groups, and other groups that are prone to making complaints in response to bus line adjustment.

Self-service check-in kiosks in airport terminal planning: Static analysis on the airport check-in space

Self-service check-in kiosks are increasingly recognized as a cost-effective solution for expanding check-in capacity without the need for terminal building expansion. These kiosks serve as essential airport infrastructure, providing time savings for passengers, cost reductions for airlines, and optimized space utilization for airports. This study aims to investigate whether the claimed 49 percent reduction in required check-in space with the adoption of self-service check-in kiosks is valid and examines how various factors influence this space saving. A small sized airport with an average annual traffic of 1 million passengers and 500 Typical Peak Hour Passenger (TPHP) serves as the case study. Through static analysis, the study assesses the impact of failure rates associated with self-service check-in kiosks on overall space savings. The findings indicate that failure rates significantly diminish space savings, underscoring the importance of technology reliability in maximizing efficiency. Additionally, space savings are influenced by passenger demand, passenger profiles, processing times, queuing/waiting times and space per passenger. These results suggest that while self-service check-in kiosks can enhance operational efficiency and passenger satisfaction, their effectiveness is contingent upon managing technology reliability and understanding diverse passenger needs. Overall, this study highlights the potential of self-service check-in kiosk in improving airport operations while providing valuable insights for future implementations.

Analysis of passenger perception heterogeneity and differentiated service strategy for air-rail intermodal travel

Air-rail intermodal services (ARISs) represent a highly promising multimodal solution within the transportation sector. Nonetheless, various uncertainties and challenges persist across multiple dimensions of air-rail interline travel, with discrepancies in passenger perceptions being a notable aspect. In an effort to pinpoint the pivotal factors contributing to these disparities among distinct passenger profiles, this study employs the Structural Equation Modeling-Multiple Indicator Multiple Cause-Artificial Neural Network (SEM-MIMIC-ANN) methodology. This approach explores the impact of numerous attributes on passenger perceptions in the context of air-rail intermodal travel, leveraging questionnaire data gathered from Shijiazhuang multimodal passengers. Furthermore, the study utilizes the Classification and Regression Tree (CART) decision tree algorithm to categorize actual passengers into distinct characteristic groups. Subsequently, the perception levels of these diverse passenger groups are quantified through the calculation of comprehensive evaluation function values. In conclusion, taking into account the real-world conditions of air-rail interline travel, this research formulates a tailored service strategy aimed at enhancing the overall passenger experience.

Factors of the Evolution of Air Passenger Segmentation: The Case of the Serbian Air Travel Market

The paper investigates the evolution of air passenger profiles in terms of regulatory environment, competitive landscape, socio-economic and demographic trends. The research is supported by passenger surveys carried out since 2001. The surveys have been designed to provide objective and in-depth insights into the preferences and behaviors of air passengers in the Serbian market. The resulting passenger segments are categorized based on socioeconomic and travel purpose criteria, but the surveys conducted at Serbian airports reveal that competition triggered the service quality to become a major issue in the Serbian market, after the entrance of low-cost carriers. The research of future projections of air passengers in Serbia is based on the Delphi method for two-time horizons (2025 and 2035) and three future scenarios are proposed.

Passenger satisfaction assessment in the aviation industry using Type-2 fuzzy TOPSIS

Assessment of passenger satisfaction (PS) ratings is a noteworthy component of evaluating the service quality metrics used by airline companies. One of the most popular ways for airline companies to gauge customer satisfaction (CS) and determine what needs to be improved is by conducting surveys of their customers. In this study, we used an extended version of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique, which is one of the most important multi-criteria decision-making (MCDM) methods, with type-2 fuzzy sets to evaluate PS for the first time in the literature. Using this systematic technique, we have reflected to the model the uncertainty that may affect the evaluations of the passengers when making their assessments. Our study is considerably beneficial since it enables not only the PS evaluation of airline companies but also it is a generalization to analyze any type of CS that may be found in the aviation sector. We used our technique on questionnaires answered by 129,880 US Airlines passengers concerning 14 criteria and compared our results with studies in the literature using the same dataset. Unlike the literature, in this paper, passenger segmentation has been done to obtain effective results. Different scenarios are created for each emerging segment. While creating the scenarios, the passenger profiles of overall satisfaction, flight class, and customer loyalty are considered and different priorities are given to these variables in each scenario. We have utilized these scenarios to help airlines determine the demands of each consumer segment to improve service quality. Our study provides airline companies with an integrated decision system, with a holistic perspective, in which they can take into account not only their customers as one type, but also the differences they may experience in evaluating both their flight habits and flight experiences.

CONFIDENTIAL INTERACTION BETWEEN PASSENGERS AND CUSTOMS OFFICERS AT MAKASSAR SULTAN HASANUDDIN INTERNATIONAL AIRPORT

In addition to their other duties as civil servants of the state, customs officers at Sultan Hasanuddin Makassar International Airport are tasked with safeguarding the local populace from the introduction of harmful foreign substances like drugs. According to the latest data from the National Narcotics Agency Survey, one in every 55 Indonesians (between the ages of 15 and 64) has a problem with substance use. One of the customs officers has made stopping the entry of illegal drugs into Indonesia his top priority after learning the truth about these substances. Passenger conduct can be detected through conversation with other passengers. The customs officer must learn about the passenger's background during the conversation to check for illegal items being smuggled. Uncertainty in interpersonal communication arises for customs personnel when they meet people entering Indonesia. The study's goal is to examine the methods used by customs agents to make passenger interactions more certain by reducing ambiguity. Descriptive qualitative research using the interactive model of Miles and Huberman was employed for this study's data collection and analysis. The research concluded that customs officers can lessen communication risks by gathering information about passengers through direct interpersonal communication with passengers and by asking a variety of questions that can describe the passenger profile, as well as through observation of passengers' verbal and nonverbal behavior.

A systematic review of passenger profiling in airport security system: Taking a potential case study of CAPPS II

A systematic review of passenger profiling in airport security system: Taking a potential case study of CAPPS II

To profile or not?

Developing effective inspection processes at border crossings in order to identify violators within large groups of mostly innocent people is an important and difficult task. Passenger profiling is a tool used to deal with this task, but it raises many public concerns and ongoing debates about its usefulness. In this article, we study whether profiling is helpful, how it should be used to maximize its effectiveness, and how social utility is affected by its use. We consider two game models that take place at a crowded border crossing, where passengers are divided into different groups based on their risk profile. The models involve three players: the defender, the attacker, and the passenger recruited to engage in a violation. The defender decides on an inspection policy for every group of passengers. The attacker decides from which group to recruit a single passenger as a violator. The recruited passenger has private knowledge about the likelihood that she/he will engage in the violation or not. We solve the game models and compare their solutions with those of a no-profiling inspection policy. We then study a model with four players, including a social planner who is concerned about social utility, and chooses the defender's inspection resources and policy. We show that the announced profiling policy provides the highest payoffs to the defender. Regarding social utility, profiling is always better than no profiling. However, there are cases where the unannounced profiling policy provides the most socialutility.

Public Transit Passenger Profiling by Using Large-Scale Smart Card Data

The term “user persona” recently has become more popular and can reflect the characteristics and needs of each user. To analyze the individual characteristics of each passenger in order to better implement targeted transportation policies, a method to mine travel profiles from each passenger based on their smart card transaction records is proposed, mainly mining six labels of passengers: activity, loyalty, whether they are stable commuters, where they live, where they work, and how they prefer to travel. A case study was conducted in the Huitian area of Beijing, the largest community in Asia, which demonstrated the high practicality and accuracy of the passenger profiling method. The results show that 33.06% of passengers were given the stable commuter label and were more likely to have high activity and loyalty labels, whereas 66.94% of other passengers were more likely to have low activity and loyalty labels; 88.9% of passengers were given the residence label and 67.71% of stable commuters received the workplace label, with an accuracy rate of over 90% according to a travel survey. In addition, the application of passenger labels during the design of demand responsive transit (DRT) was discussed to illustrate how to use the labels to improve the efficiency of DRT. The proposed passenger profiling method is applicable to the data mining of passenger travel labels in a simple and accurate way, and can help public transport service providers and researchers to study individual passenger characteristics and provide a theoretical basis for transit network planning and personalization measures.

Has passenger satisfaction at airports changed with the onset of COVID-19? The case of Seville Airport (Spain)

The changes that have come about at airports in recent decades in the areas of security, deregulation, and technological advances have affected both airport management and the passenger experience at airport facilities. In addition, all around the world, the airport sector has been struck by the COVID-19 pandemic during 2020 and 2021. Using a broad sample of data taken from Airport Service Quality (ASQ) surveys and robust econometric methodology, specifically, an Ordered Logit model with Principal Component Analysis, this paper seeks to cover the gap in the academic literature regarding the effect of a worldwide pandemic on passenger satisfaction at airports during the 2015–2021 period, while taking into consideration the passenger profile and journey and airport attributes. It takes as its reference a Spanish regional airport, which had been experiencing a strong expansion process prior to the pandemic. With respect to the variables linked to the passenger profile, a differential behavior is observed in satisfaction depending on nationality, motive for travel, and destination. In addition, the four facility- and airport process-related dimensions are significant, with cleanliness and comfort standing out above all others. These are even more important in a health emergency scenario such as is currently being experienced. Lastly, 2021 is shown to cause a downturn in the positive passenger satisfaction with the airport that had been observed during the first year of the pandemic. Therefore, more long-term management is required alongside the initial rapid and efficient action taken by airports, with up-to-date information for passengers to internalize the inconveniences associated with this long-drawn-out period of uncertainty.

Using machine learning to analyze and predict entry patterns of low-cost airlines: A study of Southwest Airlines

This paper uses machine learning to analyze and predict entry patterns of Southwest Airlines into various city pair. The purpose is to understand the parameters impacting the decision to enter into a city pair, by a low cost airline. Decision to enter (exit) from a market depends on endogenous factors and exogenous factors, such as decisions of other airlines, passenger profile, airport profile, competition on that sector, global economic conditions. The paper uses supervised machine learning to understand and predict a low cost airlines decision to enter (exit) a specific city pair. The uniqueness of this paper is that this kind of prediction was done for the first time using the existing data pre-processing and machine learning techniques. Moreover, an analysis of Southwest’s entry patterns would help (1) competing airlines to better plan their networks, (2) non-competing airlines to learn about how to plan their entry patterns and (3) airports to better plan their operations and slots. The analysis clearly showed a shift in Southwest’s entry and exit strategy over the last several years.

Evolutionary ensemble generative adversarial learning for identifying terrorists among high-speed rail passengers

As one of the most salient features of China’s economic development, high-speed rail (HSR) is considered to be an attractive target and travel mode for terrorists. Distinguishing potential terrorists from normal passengers is of critical importance to public security, but very challenging because terrorists constitute only a very small fraction of HSR passengers, especially when they can disguise their attributes and behaviors to deceive the classifiers. For this extremely imbalanced classification problem, we propose a novel evolutionary generative adversarial network (GAN) ensemble method, where each GAN in the ensemble simultaneously trains a discriminator to identify abnormal samples from a large number of passenger profiles and trains a generator to produce abnormal samples that are disguised as normal ones in a subspace of the sample space, and the final classifier combines these GANs using an evolutionary fusion method. Experiments on benchmark problems demonstrate that the proposed method has very competitive performance compared to popular imbalanced classifiers. The successful applications in terrorist identification for China Railway also demonstrate the feasibility and effectiveness of our approach.

Potential of harnessing operational flexibility from public transport hubs to improve reliability and economic performance of urban multi-energy systems: A holistic assessment framework

Growing penetration of renewable energy sources (RES) and emerging electrified loads (EEL) are bringing about increased difficulties for the power balancing and efficient operation of energy system, due to the impact of remarkable volatilities introduced. Public transport hub (PTH), as a new-style infrastructure of traffic service carriers, is regarded to offer a cogent solution to this problem, in terms of their potential operational flexibilities permitted by energy regulation, vehicular dispatch, and vehicle-to-grid (V2G) programs. As such, this paper carries out a comprehensive study to investigate the implication of harnessing PTH-enabled flexibility in a context of urban multi-energy system (UMES). The proposed methodology is established on a holistic reliability/economic analysis framework which is designed to indicate how UMES’s performances would vary with different utilization of PTH resources. In order to portray the real-time controllability of PTH during operation, a PTH model that takes into account the impacts of both energy- and service-related aspects has been developed, with particular focus on the interdependencies between the energy and transportation sector. The operational simulation of UMES in presence of PTHs is implemented by using a multi-modal-based optimization model, which captures the effects of PTH flexibility under both normal and contingency scenarios integratedly. By embedding the above formulation into a sequential Monte Carlo simulation-based assessment framework, the contribution of PTH to the reliability and economy of UMES can be determined. Numerical studies are conducted based on an illustrative electricity-gas-heat test case and the real PTH datasets in Beijing. The simulation results confirm the significance of PTH-enabled flexibility in improving the performances of UMES. Also, it is demonstrated that the reserving strategy adopted, the composition of vehicle model, and the travel demand profile of passengers are the noteworthy factors that influence the profitability of PTH exploitation.

Privacy, Data Protection and Law Enforcement. Opacity of the Individual and Transparency of Power

SUMMARY: Introduction; 1 Principles of the democratic constitutional state; 1.1 The Recognition of Human Rights in their Double Function; 1.2 The Rule of Law; 1.3 Democracy; 2 The democratic constitutional state and the invention of two complementary legal tools of power control; 2.1 Limiting power through opacity tools; 2.2 Channelling power through transparency tools; 3 Privacy as a tool for opacity (creating zones of non-interference); 3.1 The negative role of privacy; 3.2 The positive role of privacy; 3.3 The non-absolute nature of privacy; 4 Data protection as a tool for transparency; 4.1 Introduction; 4.2 The rationale behind data protection; 4.3 Data protection as an opacity tool?; 4.4 The charter of fundamental rights of the european union; 5 The shift from opacity towards transparency in european human rights law; 5.1 European human rights law and the legality requirement; 5.2 The success of the legality requirement; 5.3 A critical comment about the strasbourg focus on the legality requirement; 5.4 The danger of proceduralisation; 5.5 A requirement fundamental to opacity: necessary in a democratic state; 6. Combining privacy and data protection 6.1 Combining the tools; 6.2 Determining the switch; 6.3 An example: camera surveillance; 6.4 A second example: passenger profiling; 6.5 Workable criteria?; Conclusion.

Passengers' Shopping Preferences: A Study of Istanbul Airports

Today, a significant part of airports' revenues is derived from support services such as retail stores, food and beverage (F&B) services, and entertainment activities. These services are also vital for enhancing passenger experience, which plays a major role as arbiter of airport success. There are different typologies of passengers, and a successful airport must deliver an optimal service mix to satisfy the needs of different passenger typologies. This requires an adequate transformation of the voice of the customer with respect to different profiles. Hence, the first aim of this study is to distinguish the preferences of different passenger profiles at airports by examining their choice of retail stores, F&B services, and entertainment activities. The second aim of the study is to determine the relative importance of factors that affect passengers’ airport purchase behavior and transform them into recommendations for distinct airport strategies.

Determining Passenger Profile According to Types of Transport in Konya: A Clustering Analysis

Since the existence of humanity and especially the invention of the wheel, ensuring the movement of persons, objects, living and non-living beings between two points in an economical, ergonomic, fast and safe manner has been the subject of both theoretical and applied research. Today, relevant ministries and local administrations are working on the continuous improvement of transportation infrastructure and facilities. Alternative transportation possibilities about the transportation of people which are developed by taking into account the geographical characteristics, increase the competition in this area day by day. Transportation companies develop strategies directly for the customer in order to be successful in the competitive environment. In this study, the travel preferences and demographic structure of travellers were associated with a cluster analysis through the types of transportation that exist in the province of Konya. The survey study was analyzed with the SPSS program cluster analysis. As a result it was concluded that when the participants were grouped according to some demographic variables, it was seen that the most dominant modes of transportation were road and air. On the other hand because of Konya’s conditions like education / health and business (industry), road, air and railway transportations are preferred.

Analyzing heterogeneity in passenger satisfaction, loyalty, and complaints with air-rail integrated services

To increase the understanding of passenger choice of air-rail integrated services (ARIS), the present paper a) analyzes the profile of intermodal passengers by classifying them based on their socioeconomic and travel characteristics and (b) uncovers any heterogeneity in passenger satisfaction with ARIS among different passenger groups. Through collecting 1,345 passenger satisfaction questionnaires about ARIS, surveyed in Shijiazhuang, China, we first apply latent class clustering to classify passengers into three groups. Then, the key factors affecting passenger satisfaction and its subsequent effect on loyalty and complaints are identified using a partial least squares structural equation model. Finally, path heterogeneities in different passenger groups are explored using a multi-group analysis. The results show that the three passenger groups attach similar importance to ticket services, reliability, accessibility and comfort, while some noticeable differences in perception are identified in personalized services, information services, and connectivity.

Multi-Objective Energy Management and Charging Strategy for Electric Bus Fleets in Cities Using Various ECO Strategies

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.

Passenger profile and its effects on satisfaction level in food and beverage establishments: Case study of major Brazilian airports

Non-aeronautical revenues are becoming essential source in the financial health of airports, especially in the context of airport privatization through which the main Brazilian airports have been. The purpose of this study is to evaluate the Customer Experience (CX) in the commercial areas of the 20 main Brazilian airports, using a broad database from the Permanent Passenger Satisfaction Survey, conducted by SAC (from 2016 to 2018). This paper joins other recent work that has attempted to fill a gap in the academic literature, where the topic of customer experience in commercial activities, has not yet been extensively explored. To analyze passenger satisfaction at Brazilian airports, a logit discrete choice model is used. The key findings were the identification of variables (such as nationality, type of flight, frequency, whether the passenger was accompanied or not, whether it was in connection, airline, and gender), which affect passenger perception regarding food and beverage services. It was observed that passengers traveling alone are more satisfied with cafeterias and restaurants, while frequent passengers at airports have a worse degree of satisfaction with commercial services.