Managing customer knowledge through the use of big data analytics in tourism research

The use of big data is growing in relevance and importance in tourism management research. Companies operating in this industry are exploiting big data analytics and developing systems to manage customer knowledge and provide the best service in the right place at the right time. This paper aims to provide a systematic literature review to present issues associated with the use of big data in tourism and identify future research directions on the topic. To achieve this aim, this paper develops a citation network analysis methodology to drive the content analysis and explore the content of 109 selected papers. The findings of this review highlight that although there is an increasing number of contributions on the topic, there are yet some issues that require to be further developed. In particular, the paper identifies research gaps and consequent research questions that represent an agenda for both researchers and practitioners.     

A causal factors analysis of aircraft incidents due to radar limitations: The Norway case study

Provision of seamless, safe and effective surveillance services to airspace users requires high performance surveillance sensor coverage in the whole airspace. Limitations in the surveillance system will lead to an inability to provide the required surveillance services to the users. This may result in aircraft incident and accident occurrences. In this paper a case study is developed for the Norwegian airspace, based on five years of safety reports, to identify causal factors of incidents/accidents due to radar system limitations. This is conducted with a safety data analysis from Avinor – Norway's Air Navigation Service Provider (ANSP) and structured communication with Surveillance/ATM safety experts from Avinor. The case study shows that, 76 out of 124 occurrences within the five years in the Norwegian airspace/airport were related to the surveillance function, and 34 out of the 76 occurrences were due to limitations in the radar systems. The analysis identified that the highest contributing causal factors of the occurrences due to radar system limitations were limited surveillance coverage, followed by the lack of situational awareness for flight crew/controllers and unsynchronised surveillance information between flight crew and controllers.     

Drone service response: Spatiotemporal heterogeneity implications

Unmanned Aerial Vehicles, often called drones, have rapidly emerged for commercial and personal use in recent years. Drones are a promising and effective transportation mode because they can travel faster than traditional ground-based vehicles, particularly when obstacles limit quick response or in cases of congestion. An important consideration for drones is that travel times are impacted in various ways by real-time local conditions, including weather and terrain. While goods and supplies can be acquired at more traditional outlets (e.g., stores, warehouses, restaurants, hospitals, fire stations, etc.), drones are being increasingly relied upon to extend access, particularly for special services associated with food, drug, and equipment delivery. The reason is that they can reliably access almost anywhere, providing quick response without the need for more expensive (and larger) vehicles that are restricted to congested roadways. How to locate drone base stations and allocate service in order to optimize overall response is a challenging task, especially given spatiotemporal heterogeneity in distributed demand and service response times/costs that can vary over a day. This paper introduces an extension of p-median problem to aid in the deployment of a drone system that accounts for continuous planar travel costs. Results show that drone travel times can be significantly reduced across a region. A key feature in this work is the representation of both demand and flight trajectories across a continuous terrain.     

Estimation of traffic density from drone-based delivery in very low level urban airspace

Driven by rising consumer demand, interest is growing in the application of autonomous unmanned aerial vehicles (drones) for the last-mile delivery of small express packages and fast-food meals in cities. To be realised, this would require the Very Low Level (VLL) urban airspace to be able to cope with high traffic densities of commercial delivery drones. The potential benefits of such novel drone-based applications are a reduction of traffic congestion in cities, lower greenhouse gas emissions and more efficient transportation operations. To help realise this concept, programs such as U-Space, the unmanned traffic management system for Europe, are developing important services such as deconfliction management and dynamic capacity management. However, for several of these services, design choices will depend on how, and how extensive they will be used. It therefore becomes important to estimate how many delivery drones would operate in a typical city. This paper aims to provide an estimate by establishing a framework to determine the traffic demand for express drone-based package delivery of five European countries. In addition, a detailed case-study is presented for determining traffic density of express package drone delivery for Paris metropolitan area in order to assess the feasibility from a user's perspective. The paper also discusses the potential of fast-food meal delivery drones compared to traditional delivery modes for Paris. Results suggest that hourly traffic densities culminating from express package and fast-food meal delivery drones will exceed today's global commercial aircraft traffic of 10,000 per day by more than six-fold for just one potential metropolitan city.     

Analyzing the effect of aviation infrastructure over aviation fuel consumption reduction

The purpose of this paper is to examine the effect of various aviation infrastructure dimensions over aviation fuel consumption reduction (AFCR) performance. This study is an effort that considers the role of dimensions collectively from all aspects belonging to aviation infrastructure. The relevance of dimensions and constructs for hypothesis development are based on extensive literature review. Exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were performed in the consecutive purification processes. Also, hypothesis testing was conducted using Structural Equation Modeling (SEM). A customized questionnaire was developed for collecting data from both kinds of respondents: Aviation industry experts and academic experts. Out of 382 approaches through mail survey, a total of 194 valid responses were collected. Analysis of the results shows the positive and significant impact of various factors such as: airport design, airspace management and air traffic control over the aviation fuel consumption reduction. Maximum importance is adjudged on air traffic control (ATC) and airspace route flexibility. The results of this study will encourage airlines and airport development authorities to increase their insight over aviation infrastructure, also to perform deeper analysis and find out precise values for real life implications.     

An empirically grounded agent based simulator for the air traffic management in the SESAR scenario

In this paper we present a simulator allowing to perform policy experiments relative to the air traffic management. Different SESAR solutions can be implemented in the model to see the reaction of the different stakeholders as well as other relevant metrics (delay, safety, etc). The model describes both the strategic phase associated to the planning of the flight trajectories and the tactical modifications occurring in the en-route phase. An implementation of the model is available as an open-source software and is freely accessible by any user.More specifically, different procedures related to business trajectories and free-routing are tested and we illustrate the capabilities of the model on an airspace which implements these concepts. After performing numerical simulations with the model, we show that in a free-routing scenario the controllers perform less operations but the conflicts are dispersed over a larger portion of the airspace. This can potentially increase the complexity of conflict detection and resolution for controllers.In order to investigate this specific aspect, we consider some metrics used to measure traffic complexity. We first show that in non-free-routing situations our simulator deals with complexity in a way similar to what humans would do. This allows us to be confident that the results of our numerical simulations relative to the free-routing can reasonably forecast how human controllers would behave in this new situation. Specifically, our numerical simulations show that most of the complexity metrics decrease with free-routing, while the few metrics which increase are all linked to the flight level changes. This is a non-trivial result since intuitively the complexity should increase with free-routing because of problematic geometries and more dispersed conflicts over the airspace.     

Characterizing the Brazilian airspace structure and air traffic performance via trajectory data analytics

This paper presents a data-driven approach for multi-scale characterization of the Brazilian airspace structure and air traffic operational performance from aircraft tracking data recorded by surveillance systems. Unsupervised learning is performed with a flight trajectory clustering analysis to automatically identify spatial traffic patterns in both the terminal and the en route airspace for major origin-destination pairs of the Brazilian air transportation system. Based on the as-flown route structure learned, quantitative metrics are developed to describe the structural efficiency of the airspace and the operational efficiency of the traffic flows. For this, actual flight trajectories are projected onto reference nominal trajectories in space and time. The results allowed for cross-route comparisons of air traffic flow efficiency across multiple flight phases as well as for the identification of causal factors for trajectory deviations from nominal routes. An interactive data analytics tool is also created to output performance statistics and air traffic visualizations. With the provision of a systematic data-driven approach for characterizing actual air traffic operations, the analytics framework is envisioned to assist airspace design and performance monitoring processes and to provide the basis for developing predictive capabilities in support of traffic flow management.     

Strategic design and operational management optimization of a multi stage physical distribution system

Design and management of logistic networks is one of the most critical issues in supply chain management. However, the literature does not contain any effective models, methods, and applications that simultaneously support management decisions in the strategic design of the distribution system, in the operational planning and organization of vehicles, and in container trips organization adopting different modes of transportation. The aim of this paper is to illustrate an original framework for the design and optimization of a multi echelon and multi level production/distribution system that combines mixed-integer linear programming modeling with cluster analysis, heuristic algorithms, and optimal transportation rules. A significant case study is illustrated revealing the effectiveness of the approach and tools proposed.     

Choice model based analysis of consumer preference for drone delivery service

It is anticipated that drones will soon be utilized for a range of applications, including delivery service. However, there has been a lack of research on consumer preference between drone delivery service and traditional delivery service. This is the first study to analyze the consumer preference for drone delivery based on a discrete choice model between the drone delivery service and traditional delivery services by truck or motorcycle. The discrete choice model is estimated using a stated preference survey, and potential consumers’ preference is analyzed for representative commodities with different price. The results show that the price and type of commodities influence consumer preference, which also depends on socio-demographic characteristics such as gender, age, and household income. Specifically, it was consistently observed in all cases that the younger the age, the higher the preference for drone delivery service. This study contributes to predicting the consumer preference for drone delivery service before real service offerings and to supporting the establishment of business strategies for companies who prepare for the new market of drone-based delivery.     

Holiday users of the Internet — ease of use,functionality and novelty

This study is based upon a sample of 517 international visitors to New Zealand. It suggests that Internet usage is based upon perceived usefulness and ease of system use. Of additional importance is user confidence about system security. Functional issues of purchasing seem to take priority over information search as users become more familiar with web pages. An additional finding is that entertainment needs are arguably better met by other Internet functions than those provided by destination web pages. Novelty on the Net is perhaps sought from specific sources, and not from the Net generally. Implications are discussed for both measurement and marketing. Copyright © 2008 John Wiley & Sons, Ltd.     

Tourist use of public transport at destinations – a review

Understanding tourists' use of public transport (PT) at the destination is important for sustainable mobility, destination satisfaction, PT management and destination management. This paper provides an overview of research in PT and tourism since 2000. The review identifies main topics and issues including how PT is used for tourism purposes in different contexts. It also recommends policies and strategies for a modal shift to PT in tourism, and identifies potential areas for future research. The review indicates that there are differences in the level of PT use by visitors between rural and urban destinations. PT is often not favoured by visitors in remote areas, although the situation is more promising in urban destinations. However, the overall potential of PT as an alternative mode for travelling is unclear, given tourist motivations and behaviours, and provision of visitor-oriented PT services including the need for appropriate communication and social marketing strategies.     

Global supply chain design: A literature review and critique

In this paper, we review decision support models for the design of global supply chains, and assess the fit between the research literature in this area and the practical issues of global supply chain design. The classification scheme for this review is based on ongoing and emerging issues in global supply chain management and includes review dimensions for (1) decisions addressed in the model, (2) performance metrics, (3) the degree to which the model supports integrated decision processes, and (4) globalization considerations. We conclude that although most models resolve a difficult feature associated with globalization, few models address the practical global supply chain design problem in its entirety. We close the paper with recommendations for future research in global supply chain modeling that is both forward-looking and practically oriented.     

The hidden cost of uncertainty for airspace users

This article highlights the importance of uncertainty in day-to-day operations, and the need to take it into account to properly assess the cost of delay for airspace users. It defines a cost of uncertainty and estimates it using real data. It provides some easily computable models based on the average and standard deviation of delay to estimate the cost of delay in general. The article shows that uncertainty is also important in the formulation of buffers for airlines and provides a simple model to estimate the optimal assignment, further using real data to compute the optimal value at different airports.     

Impacts on travel behaviour of Greater Manchester’s light rail investment (Metrolink Phase 1): evidence from household surveys and Census data

Household survey data from 1990 and 1993 and Census data from 1991 and 2001 are used to detect some short and medium term impacts on travel of the Metrolink light rail services which opened in 1992. Particular attention is paid to research design issues to try to isolate Metrolink’s impacts from those of other influences on travel behaviour. In the short term a more marked decline in the frequency of bus use is found in the Metrolink corridor compared with conventional rail and ‘no rail’ corridors. Changes in the frequency of rail use are more prominent in the Metrolink corridor, both to the highest frequency use but also to lower frequency use. Higher frequency rail use tends to be associated with respondents who have limited or no car availability, who are in employment, who are of non-manual social class and who are aged 18–44 years. Metrolink appears to have attracted at least as many former car users as former bus users, but the former car users tend to use the light rail services less frequently. Census commuting data suggest that, in the medium term, Metrolink has increased rail’s share of trips, especially to the city centre, contributed to the declining share of bus trips and may have helped to restrain work trips by car.     

Estimating entry counts and ATFM regulations during adverse weather conditions using machine learning

In recent years, convective weather has been the cause of significant delays in the European airspace. With climate experts anticipating the frequency and intensity of convective weather to increase in the future, it is necessary to find solutions that mitigate the impact of convective weather events on the airspace system. Analysis of historical air traffic and weather data will provide valuable insight on how to deal with disruptive convective events in the future. We propose a methodology for processing and integrating historic traffic and weather data to enable the use of machine learning algorithms to predict network performance during adverse weather. In this paper we develop regression and classification supervised learning algorithms to predict airspace performance characteristics such as entry count, number of flights impacted by weather regulations, and if a weather regulation is active. Examples using data from the Maastricht Upper Area Control Centre are presented with varying levels of predictive performance by the machine learning algorithms. Data sources include Demand Data Repository from EUROCONTROL and the Rapid Developing Thunderstorm product from EUMETSAT.     

Mitigation of airspace congestion impact on airline networks

In recent years European airspace has become increasingly congested and airlines can now observe that en-route capacity constraints are the fastest growing source of flight delays. In 2010 this source of delay accounted for 19% of all flight delays in Europe and has been increasing with an average yearly rate of 17% from 2005 to 2010. This paper suggests and evaluates an approach to how disruption management can be combined with flight planning in order to create more proactive handling of the kind of disruptions, which are caused by congested airspace. The approach is evaluated using data from a medium size European carrier and estimates a lower bound saving of several million USD.     

Policy-feasibility study of vertical/horizontal moving-assistant systems for the mobility-disabled using a contingent valuation method

The development of vertical/horizontal moving-assistant systems is at an initial stage. However, it is expected to enhance the efficiency of mobility-disabled individuals when it is used in the field of public transportation systems. Hence, this study involved analyzing the benefits and whether users would be willing to pay more as a type of tax to install the new systems into the public transportation sector by using the contingent valuation method as well as their willingness-to-pay for these systems. A survey was conducted among Seoul metropolitan subway users to establish a model and compute the total annual benefits of the new systems. The results indicated that individuals are willing to pay more of USD 1.65 for the installation of a new system. The findings also determined that the minimum and maximum total annual benefits of establishing these systems are USD 69.81 million and USD 200.32 million, respectively. Additionally, an analysis was performed to separately compare the value of installing these systems from the viewpoints of general and mobility-disabled users. This analysis indicated that general users consider the value of new systems that is not directly related to their own convenience as more necessary and valuable when compared to the perceptions of mobility-disabled users. There is a paucity of studies on vertical/horizontal moving-assistant systems in the field of transportation. Nevertheless, the results of the study suggest that the proliferation of the systems is feasible and leads to enhancements in the sustainability of the public transportation sector.     

Understanding the urban travel attitudes and behavior of Tbilisi residents

In recent decades the public transport network in Tbilisi, Georgia has decayed, while the number of private automobiles has increased dramatically. This study seeks to expand our understanding of the Tbilisi population’s urban transport attitudes and behavior. It elaborates on the perceived strengths, weaknesses, and potentials of the public transport system, and seeks to understand the reasons for the increased use of private automobiles. A questionnaire survey was conducted among Tbilisi car drivers (n=159) and public transport users (n=163). The results show that most of the survey respondents preferred to use a private car and avoid using public transport. Particularly important factors include time issues such as schedules and frequency, plus comfort and safety issues. Tbilisi residents value their time and want to use it efficiently. Changing residents’ travel behavior will require making the public transport options competitive with the perceived advantages of the car. The study offers recommendations for more effective urban transport policy, including incentives to encourage greater use of public transport in Tbilisi.     

Airline type and tourist expenditure: Are full service and low cost carriers converging or diverging?

Since some years ago low-cost carriers (LCCs) are becoming less and less low-cost-like, as well as full-service airlines are becoming less and less full-service-like, thus contributing to lessen the differences between users of one airline type and the other. LCCs have made air travel available to all budgets and enabled tourists to spend more at destination by reallocating their trip expenditure. The objective of this article is to observe if airline types have been converging regarding travellers’ expenditure allocation and total trip expenditure. We use repeated cross sections of the Spanish tourist expenditure survey between 2006 and 2014, and compositional data analysis with a total in order not to confound effects involving expenditure allocation with those involving expenditure volume. Results show that users of both airline types converge in their allocation of the trip budget (between transportation and at-destination expenses, and within at-destination expenses), but diverge with regard to total trip expenditure.     

Monitoring social network formation and information content analysis of transport anomalies: The case of airline crashes

Airliners' industry corresponds to an extremely sensitive and volatile sector, especially subject to information related to flight safety. Possible negative publicity on such issues may result to sudden and abrupt fluctuations of air travel demand, accompanied with phenomena of panic or feelings of generalized insecurity. The proliferation of social media platforms that offer a direct and immediate two-way communication channel contributes to the overall information propagation related to flights security (as exposed in the recent airlines crashes) and can be viewed as a proxy of the social network formation of such paradigms. The current paper aims to offer a framework for quantitatively analyzing social network formation, based on comprehensive network metrics, valuable in cases of commercial airliners accidents. Moreover, the use of data from social media connectivity offers one more extremely valuable piece of information related to the messages that connected users exchange, mention or are exposed to. Such large datasets are quantitatively analyzed here based on methods used in content analysis, exposing valuable information on the interest of the general public (potential airliners users) of anomalies in the airline industry. The analysis is based on data from two real events (airliners’ crashes), which attracted the international public interest and significantly affected air travel demand. Finally, the results are analyzed and presented in detail such as to contribute to the air demand treatment, especially in terms of optimal communication operational management in cases of crises.