g4c2c: A model for citizen engagement at arms' length from government

The recognition that Web 2.0 applications and social media sites will strengthen and improve interaction between governments and citizens has resulted in a global push into new e-democracy or Government 2.0 spaces. These typically follow government-to-citizen (g2c) or citizen-to-citizen (c2c) models, but both these approaches are problematic: g2c is often concerned more with service delivery to citizens as clients, or exists to make a show of ‘listening to the public’ rather than to genuinely source citizen ideas for government policy, while c2c often takes place without direct government participation and therefore cannot ensure that the outcomes of citizen deliberations are accepted into the government policy-making process. Building on recent examples of Australian Government 2.0 initiatives, we suggest a new approach based on government support for citizen-to-citizen engagement, or g4c2c, as a workable compromise, and suggest that public service broadcasters should play a key role in facilitating this model of citizen engagement.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

Validating the design science research roadmap : through the lens of "the idealised model for theory development"

Design Science Research (DSR) has emerged as an important approach in Information Systems (IS) research. However, DSR is still in its genesis and has yet to achieve consensus on even the fundamentals, such as what methodology / approach to use for DSR. While there has been much effort to establish DSR methodologies, a complete, holistic and validated approach for the conduct of DSR to guide IS researcher (especially novice researchers) is yet to be established. Alturki et al. (2011) present a DSR ‘Roadmap’, making the claim that it is a complete and comprehensive guide for conducting DSR. This paper aims to further assess this Roadmap, by positioning it against the ‘Idealized Model for Theory Development’ (IM4TD) (Fischer & Gregor 2011). The IM4TD highlights the role of discovery and justification and forms of reasoning to progress in theory development. Fischer and Gregor (2011) have applied IM4TD’s hypothetico-deductive method to analyze DSR methodologies, which is adopted in this study to deductively validate the Alturki et al. (2011) Roadmap. The results suggest that the Roadmap adheres to the IM4TD, is reasonably complete, overcomes most shortcomings identified in other DSR methodologies and also highlights valuable refinements that should be considered within the IM4TD.

A formative measurement model of business process model quality

Business process management (BPM) is becoming the dominant management paradigm. Business process modelling is central to BPM, and the resultant business process model the core artefact guiding subsequent process change. Thus, model quality is at the centre, mediating between the modelling effort and related growing investment in ultimate process improvements. Nonetheless, though research interest in the properties that differentiate high quality process models is longstanding, there have been no past reports of a valid, operationalised, holistic measure of business process model quality. In attention to this gap, this paper reports validation of a Business Process Model Quality measurement model, conceptualised as a single-order, formative index. Such a measurement model has value as the dependent variable in rigorously researching the drivers of model quality; as antecedent of ultimate process improvements; and potentially as an economical comparator and diagnostic for practice.

A safety adapted car following model for traffic safety studies

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time To Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.