A design led innovation approach to gathering deep customer insights in the aviation industry

Research has long documented the value that design brings to the innovation of products and services. The research landscape has transformed in the last decade and now reflects the value of design as a different way thinking that can be applied to the innovation of business models and catalyst for strategic growth. This paper presents a case study of gathering deep customer insights through a design led innovation approach and reveals industry perspectives and attitudes towards the value of deep customer insights within the context of a leading Australian airport corporation. The findings highlight that the process of gathering deep customer insights encourages a design led approach to testing assumptions and developing stronger customer engagement. The richness of the deep customer insights also provided a bridge to future thought by provoking possible product, service and business innovations which aligned to the airport corporation’s vision. The implications of the study reveal how quantitative market data, which reveals broad sociocultural trends into ‘how’ and ‘what’ customers interact with within an airport, can be strongly validated and built upon through qualitative deep customer insights that explore ‘why’ those choices to interact are made. Future research is then presented which aims to widely disseminate a design led approach to innovation within internal stakeholders of the airport corporation through the development of a digital strategy.

A Kansei approach to passenger terminal design

Current approaches to passenger terminal design are based on a direct relationship between the number of travelers and the size of the passenger terminal building: as one increases, so does the other. Over the next several decades, it is believed that the number of travelers worldwide will increase significantly. It follows, therefore, that in order to process these additional passengers, airports will need to build larger terminal facilities. Unfortunately, this is not a viable option for many airports due to financial, economic, operational and general space constraints. In this paper, we explore a new way of approaching terminal design based on a passenger oriented perspective. In doing so, we extend an interpretation of the Kansei design concept and show how it may be applicable towards the creation of new design paradigms in aviation. Our results are based on data collected in-situ at a major international terminal during 2012.

Spatio-temporal modelling of ultrafine particle number concentration

This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

A Hybrid Queue-based Bayesian Network Framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sizedtrucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Sex and the virtual suburbs : the pornosphere and community standards

This chapter looks at the management and zoning of online sexual culture–the web sites which make up the pornosphere (McNair 2013). It explores the concept of ‘community standards’, which has been a central part of the management of sexually explicit materials in the offline world, and asks what it might mean to talk about ‘community standards’ on the Internet. And finally, it uses the concept of virtual-community standards to revisit the question of managing access to sexually explicit materials on the Internet.

Can Business Continuity Management Create Reliability in Airports? (Issues from Theory into Practice)

The advances made within the aviation industry over the past several decades have significantly improved the availability, affordability and convenience of air travel and have been greatly beneficial in both social and economic terms. Air transport has developed into an irreplaceable service being relied on by millions of people each day and as such airports have become critical elements of national infrastructure to facilitate the movement of people and goods. As components of critical infrastructure (CI), airports are integral parts of a national economy supporting regional as well as national trade, commercial activity and employment. Therefore, any disruption or crisis which impacts the continuity of operations at airports can have significant negative consequences for the airport as a business, for the local economy and other nodes of transport infrastructure as well as for society. Due to the highly dynamic and volatile environment in which airports operate in, the aviation industry has faced many different challenges over the years ranging from terrorist attacks such as September 11, to health crises such as the SARS epidemic to system breakdowns such as the recent computer system outage at Virgin Blue Airlines in Australia. All these events have highlighted the vulnerability of airport systems to a range of disturbances as well as the gravity and widespread impact of any kind of discontinuity in airport functions. Such incidents thus emphasise the need for increasing resilience and reliability of airports and ensuring business continuity in the event of a crisis...

Security metrics for Java bytecode programs

Although there are many approaches for developing secure programs, they are not necessarily helpful for evaluating the security of a pre-existing program. Software metrics promise an easy way of comparing the relative security of two programs or assessing the security impact of modifications to an existing one. Most studies in this area focus on high level source code but this approach fails to take compiler-specific code generation into account. In this work we describe a set of object-oriented Java bytecode security metrics which are capable of assessing the security of a compiled program from the point of view of potential information flow. These metrics can be used to compare the security of programs or assess the effect of program modifications on security using a tool which we have developed to automatically measure the security of a given Java bytecode program in terms of the accessibility of distinguished ‘classified’ attributes.

Airports of the future : improving operation, security and experience

The final report for the ARC project "Airports of the Future". It contains the findings and recommendations provided by the various teams to the industry partners.