Determinants of airport retail revenue: a review of literature

ABSTRACT

As the airport retail industry continues to grow due to increasing travel demands, airport operators are increasingly developing their retail revenue potential to ensure financial viability. This study aims to provide a review of airport retail literature and identify the salient factors associated with passenger shopping behaviour. The paper presents a review of contemporary airport retail literature, covering a total of 50 studies from 1998 to 2018. The review identified 26 factors, which could broadly be grouped into five categories: airport/operator related; passengers' demographic related; passengers’ travel related; passengers’ psychological related and passengers’ resources related. In addition to providing a summary of the statistically significant factors across studies, the review identifies and discusses potential approaches for future research. These include the importance of considering both “to spend or not” decision and how much to spend and how most empirical studies focussed on the former; the gap in empirical analysis on the impact of airport terminal design layout on retail performance; and the gap in application of general consumer shopping behavioural models to airport retail problems. The paper concludes with the suggestion that we can build on the existing studies to develop a hybrid approach to solve several of the identified gaps simultaneously.     

Using longitudinal methods for analysis of a short-term transportation demonstration project

This paper documents an application of panel, or longitudinal data collection in the evaluation of a TSM (Transportation Systems Management) demonstration project. The project was a four-week demonstration of staggered work hours in downtown Honolulu during February–March 1988. The 4 wave panel survey elicited commuting experiences of approximately 2,000 downtown employees at two week intervals before and during the project. The sample involved both employees who participated in the project by shifting their work hours, and those who did not. The panel survey was augmented by floating-car observations of travel times on major routes into downtown Honolulu on the same four dates.The purpose of the analysis was to determine whether employee commute times were affected, and if so, how these changes were distributed among various employee segments. Two methods were used. First, travel time changes were estimated using paired t-tests. Second, regression equations were used to estimate project time savings as a function of trip length, route, and location of residence. Results show that travel time savings due to the project were typically small, less than ten percent. Nonparticipants experienced greater savings than participants, and some segments of participants experienced longer travel times during the project. The panel method proved to be an effective way to measure project travel time impacts and shows that the method is appropriate in short time applications.Presented at the Annual Meeting of Transportation Research Board, January 7–11. 1990, Washington, D.C.     

Trip distribution for limited destinations: a case study for grocery shopping trips in the Netherlands

In this paper, we introduce a new trip distribution model for destinations that are not homogeneously distributed. The model is a gravity model in which the spatial configuration of destinations is incorporated in the modeling process. The performance was tested on a survey with reported grocery shopping trips in the Dutch city of Almelo. The results show that the new model outperforms the traditional gravity model. It is also superior to the intervening opportunities model, because the distribution can be described as a function of travel costs, without increasing the computational time. In this study, the distribution was described by a simple function of Euclidean distance, which provides a good fit to the survey data. The slope of the distribution is quite steep. This shows that most trips are made to nearby supermarkets. However, a significant fraction of trips, mainly made by car, still goes to supermarkets further away. We argue that modeling of these trips by the new method will improve traffic flow predictions.     

Evaluating locational accessibility to the US air transportation system

Although there are hundreds of airports that support commercial air passenger traffic in the United States (US), not all areas are equivalently served by the commercial air transportation system. Locations in the US differ with respect to their level of access to the commercial air network and their overall accessibility within the system. Given the complexity of the domestic commercial air passenger network and supporting infrastructure, past research has only been able to provide a limited assessment of locational accessibility within the United States. To address these complexities, this paper proposes a new metric that incorporates measures of access to air transport as well as accessibility within air transportation networks. Using a comprehensive dataset on scheduled airline service, the developed approach is then applied to the US domestic commercial passenger air transportation network to explore geographic differentials in accessibility. Results suggest marked differences between core-based statistical areas throughout the US.     

Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling

This study reviews the 50-year history of travel demand forecasting models, concentrating on their accuracy and relevance for public decision-making. Only a few studies of model accuracy have been performed, but they find that the likely inaccuracy in the 20-year forecast of major road projects is ±30 % at minimum, with some estimates as high as ±40–50 % over even shorter time horizons. There is a significant tendency to over-estimate traffic and underestimate costs, particularly for toll roads. Forecasts of transit costs and ridership are even more uncertain and also significantly optimistic. The greatest knowledge gap in US travel demand modeling is the unknown accuracy of US urban road traffic forecasts. Modeling weaknesses leading to these problems (non-behavioral content, inaccuracy of inputs and key assumptions, policy insensitivity, and excessive complexity) are identified. In addition, the institutional and political environments that encourage optimism bias and low risk assessment in forecasts are also reviewed. Major institutional factors, particularly low local funding matches and competitive grants, confound scenario modeling efforts and dampen the hope that technical modeling improvements alone can improve forecasting accuracy. The fundamental problems are not technical but institutional: high non-local funding shares for large projects warp local perceptions of project benefit versus costs, leading to both input errors and political pressure to fund projects. To deal with these issues, the paper outlines two different approaches. The first, termed ‘hubris’, proposes a multi-decade effort to substantially improve model forecasting accuracy over time by monitoring performance and improving data, methods and understanding of travel, but also by deliberately modifying the institutional arrangements that lead to optimism bias. The second, termed ‘humility’, proposes to openly quantify and recognize the inherent uncertainty in travel demand forecasts and deliberately reduce their influence on project decision-making. However to be successful either approach would require monitoring and reporting accuracy, standards for modeling and forecasting, greater model transparency, educational initiatives, coordinated research, strengthened ethics and reduction of non-local funding ratios so that localities have more at stake.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Improving the predictiveness of the quasi-d combustion model for spark ignition engines with flexible intake systems

Fast and predictive simulation tools are prerequisites for pursuing simulation based engine control development. A particularly attractive tradeoff between speed and fidelity is achieved with a co-simulation approach that marries a commercial gas dynamic code WAVE™ with an in-house quasi-dimensional combustion model. Gas dynamics are critical for predicting the effect of wave action in intake and exhaust systems, while the quasi-D turbulent flame entrainment model provides sensitivity to variations of composition and turbulence in the cylinder. This paper proposes a calibration procedure for such a tool that maximizes its range of validity and therefore achieves a fully predictive combustion model for the analysis of a high degree of freedom (HDOF) engines. Inclusion of a charge motion control device in the intake runner presented a particular challenge, since anything altering the flow upstream of the intake valve remains “invisible” to the zero-D turbulence model applied to the cylinder control volume. The solution is based on the use of turbulence multiplier and scheduling of its value. Consequently, proposed calibration procedure considers two scalar variables (dissipation constant C _β and turbulence multiplier C _M ), and the refinements of flame front area maps to capture details of the spark-plug design, i.e. the actual distance between the spark and the surface of the cylinder head. The procedure is demonstrated using an SI engine system with dual-independent cam phasing and charge motion control valves (CMCV) in the intake runner. A limited number of iterations led to convergence, thanks to a small number of adjustable constants. After calibrating constants at the reference operating point, the predictions are validated for a range of engine speeds, loads and residual fractions.     

Design of power split transmission: Design of dual mode power split transmission

The power split type hybrid system transmits engine power by dividing it into the electrical unit and the mechanical unit. Its power transmission efficiency is highest at the mechanical point (MP), where the full power is transmitted to the mechanical unit. In this study, the equation for the MP was derived for the gear ratios of a general 4-node lever model. The MP characteristics for the transmission ratio (TR) of the input split and compound split structures were examined using the equation derived. Using the examined input split and compound split structures, a systematic design method for the dual mode power split transmission was proposed. In the dual mode power split transmission, the MP could be positioned at the desired TR, and the input split and compound split modes could be selectively used according to the clutch combination, which leads to the operation of the vehicle within a high system efficiency range.     

Robust lane markings detection and road geometry computation

Detection of lane markings based on a camera sensor can be a low-cost solution to lane departure and curve-over-speed warnings. A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue because of cast shadows, worn and occluded markings, variable ambient lighting conditions, for example. We focus on increasing detection reliability in two ways. First, we employed an image feature other than the commonly used edges: ridges, which we claim addresses this problem better. Second, we adapted RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane lines to the image features, based on both ridgeness and ridge orientation. In addition, the model was fitted for the left and right lane lines simultaneously to enforce a consistent result. Four measures of interest for driver assistance applications were directly computed from the fitted parametric model at each frame: lane width, lane curvature, and vehicle yaw angle and lateral offset with regard the lane medial axis. We qualitatively assessed our method in video sequences captured on several road types and under very different lighting conditions. We also quantitatively assessed it on synthetic but realistic video sequences for which road geometry and vehicle trajectory ground truth are known.     

Operating speed pattern optimization of railway vehicles with differential evolution algorithm

The railway transportation system has much advantage in eco-friendliness, punctuality and safety compared to any other transportation system. Most of the railway system administrators have to control and operate under limited resources such as trains and facilities. It is necessary to control traveling time and energy consumption for efficient operation in the railway systems, because the board rate of passenger is inconstant with time variance. It is common that the shorter traveling time causes the greater energy consumption. In this study, a new optimization method considering operation time or energy consumption is proposed by using differential evolution algorithm and some cases are reviewed. The total energy change due to operation time variation are investigated by using the proposed optimization method for tangent and gradient track conditions. Both cases, the total energy decreases exponentially. However, because of gradient the total energy are saturated after a certain time for gradient track.