Long distance calling? Spatial preference patterns in enterprise microblogging in the retail industry

We examine enterprise social network usage data obtained from a community of store managers in a leading Australian retail organization, over a period of fifteen months. Our interest in examining this data is in spatial preferences by the network users, that is, to ascertain who is communicating with whom and where. We offer several contrasting theoretical perspectives for spatial preference patterns and examine these against data collected from over 12,000 messages exchanged between 530 managers in 897 stores. Our findings show that interactions can generally be characterized by individual preferences for local communication but also that two different user communities exist – locals and globals. We develop empirical profiles for these social network user communities and outline implications for theories on spatial influences on communication behaviours on enterprise social networks.

Final : report assessing risk and variation in maintenance and rehabilitation costs for road network

This report presents the results of research projects conducted by The Australian Cooperative Research Centre for Construction Innovation, Queensland University of Technology, RMIT University, Queensland Government Department of Main Roads and Queensland Department of Public Works. The research projects aimed at developing a methodology for assessing variation and risk in investment in road network, including the application of the method in assessing road network performance and maintenance and rehabilitation costs for short- and long-term future investment.

Management and organisational barriers in the acquisition of computer usage skills by mature age workers

Aim: To investigate workplace cultures in the acquisition of computer usage skills by mature age workers. Methods: Data were gathered through focus groups conducted at job network centres in the Greater Brisbane metropolitan region. Participants who took part were a mixture of workers and job-seekers. Results: The results suggest that mature age workers can be exposed to inappropriate computer training practices and age-insensitive attitudes towards those with low base computer skills. Conclusions: There is a need for managers to be observant of ageist attitudes in the work place and to develop age-sensitive strategies to help mature age workers learn computer usage skills. Mature age workers also need to develop skills in ways which are practical and meaningful to their work.

Trust and reputation management in web-based social network

know personally. They also communicate with other members of the network who are the friends of their friends and may be friends of their friend’s network. They share their experiences and opinions within the social network about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Opinions, reputations and ecommendations will influence users' choice and usage of online resources. Recommendations may be received through a chain of friends of friends, so the problem for the user is to be able to evaluate various types of trust recommendations and reputations. This opinion or ecommendation has a great influence to choose to use or enjoy the item by the other user of the community. Users share information on the level of trust they explicitly assign to other users. This trust can be used to determine while taking decision based on any recommendation. In case of the absence of direct connection of the recommender user, propagated trust could be useful.

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.

Enhancing enterprise social network use : a control theory study

Organizations employ Enterprise Social Networks (ESNs) (e.g., Yammer) expecting better intra-organizational communication, effective knowledge sharing and, in general, greater collaboration. Despite their similarities with Public Social Networks (PSNs) (e.g., Twitter), ESNs are struggling to gain credence with employees. This paper is part of a larger research project that investigates mechanisms to enhance employees’ engagement in the ESNs. Through the lens of Control Theory, this paper reports preliminary findings of a pilot case study aimed to propose formal and informal mechanisms that impact employees’ intrinsic and extrinsic motivations to encourage their use of ESNs. The study results highlight (i) the need to better understand employees’ extrinsic and intrinsic motivations to use Social Networks, and (ii) that unlike a PSN which acts as a hedonic system, an ESN acts as a utilitarian system, highlighting the importance of supporting intrinsic motivations in its implementation.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Facebook for adults ? A longitudinal study of MBA student’s use of an enterprise social network for collaborative learning

The rapid pace of social media means that our understanding of the way in which it facilitates the learning process continues to lag. The findings of a longitudinal study of an executive MBA cohort over the period of eight months in their use of the social media application is presented. Over time the ownership and use of the Yammer site shifted to become student driven and facilitated. The motivations behind the site’s use, perceived advantages and disadvantages and changes in usage patterns are documented. The case provides a useful insight into the way in which students used this technology to facilitate their learning goals and how patterns of behaviour changed in response to the changing needs of the cohort.

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 R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis 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.

Developing an international survey of bicycle and helmet usage

The European Union‐funded collaborative network, COST Action TU1101: Towards safer bicycling through optimization of bicycle helmets and usage, aims to increase scientific knowledge about bicycle helmets in regards to traffic safety and to disseminate this knowledge to stakeholders, including cyclists, legislators, manufacturers, and the scientific community. The COST research team has developed a uniform international survey to better understand attitudinal and other factors that may influence bicycle and helmet usage, as well as crash risk. The online survey is being distributed by project partners in Europe, Israel, Australia, and potentially the US and Canada. The survey contains four types of questions: (1) biographical data, (2) frequency of cycling and amount of cycling for different purposes (e.g., commuting, health, recreation) and in different environments (e.g., bicycle trails, bike lanes, on sidewalks, in traffic), (3) frequency and circumstances for use and non‐use of helmets, attitudes and reasons for it, and; (4) crash involvement and level of reporting to the police. While the potential value of comparative data across countries with very different cycling cultures and safety levels is substantial, there are numerous challenges in developing, conducting, and analyzing the results of the survey. This presentation will focus on the scope of the international study, methodological issues and pitfalls of such a collaborative effort, and on initial results from one country (Israel). To illustrate, two findings from the preliminary Israeli survey indicate that: (1) none of the crashes were reported to the police including the ones involving hospital admission. Although underreporting of bicycle crashes by police is well documented in all countries the extent is unknown, and can be extreme. (2) Older riders tend to ride more for health/exercise reasons, while younger riders tend to ride more for commuting. Thus there is an interaction between riders’ age and the place and times of riding.

Impact of technology uptake on an Australian electricity distribution network

This paper presents simulation results for future electricity grids using an agent-based model developed with MODAM (MODular Agent-based Model). MODAM is introduced and its use demonstrated through four simulations based on a scenario that expects a rise of on-site renewable generators and electric vehicles (EV) usage. The simulations were run over many years, for two areas in Townsville, Australia, capturing variability in space of the technology uptake, and for two charging methods for EV, capturing people's behaviours and their impact on the time of the peak load. Impact analyses of these technologies were performed over the areas, down to the distribution transformer level, where greater variability of their contribution to the assets peak load was observed. The MODAM models can be used for different purposes such as impact of renewables on grid sizing, or on greenhouse gas emissions. The insights gained from using MODAM for technology assessment are discussed.

Residential tariff structure and battery energy storage impact in queensland LV network

Distributed renewable energy has become a significant contender in the supply of power in the distribution network in Queensland and throughout the world. As the cost of battery storage falls, distribution utilities turn their attention to the impacts of battery storage and other storage technologies on the low voltage (LV) network. With access to detailed residential energy usage data, Energex's available residential tariffs are investigated for their effectiveness in providing customers with financial incentives to move to Time-of Use based tariffs and to reward use of battery storage.