The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

BWW ontology as a lens on IS design theory: Extending the design science research roadmap

The Design Science Research Roadmap (DSR-Roadmap) [1] aims to give detailed methodological guidance to novice researchers in Information Systems (IS) DSR. Focus group evaluation, one phase of the overall study, of the evolving DSR-Roadmap revealed that a key difficulty faced by both novice and expert researchers in DSR, is abstracting design theory from design. This paper explores the extension of the DSR-Roadmap by employing IS deep structure ontology (BWW [2-4]) as a lens on IS design to firstly yield generalisable design theory, specifically 'IS Design Theory' (ISDT) elements [5]. Consideration is next given to the value of BWW in the application of the design theory by practitioners. Results of mapping BWW constructs to ISDT elements suggest that the BWW is promising as a common language between design researchers and practitioners, facilitating both design theory and design implementation

Indigenous/digital heterogeneities : an actor-network-theory approach

This thesis analysed the theoretical and ontological issues of previous scholarship concerning information technology and indigenous people. As an alternative, the thesis used the framework of actor-network-theory, especially through historiographical and ethnographic techniques. The thesis revealed an assemblage of indigenous/digital enactments striving for relevance and avoiding obsolescence. It also recognised heterogeneities- including user-ambivalences, oscillations, noise, non-coherences and disruptions - as part of the milieu of the daily digital lives of indigenous people. By taking heterogeneities into account, the thesis ensured that the data “speaks for itself” and that social inquiry is not overtaken by ideology and ontology.

Displacement motion prediction of a landing deck for recovery operations of rotary UAVs

This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.

Attitudinal, normative, and control beliefs underlying people’s curbside household waste recycling decisions

This study examined the beliefs underlying people’s decision-making, from a theory of planned behaviour (TPB) framework, in the prediction of curbside household waste recycling. Community members in Brisbane, Australia (N = 148) completed a questionnaire assessing the belief based TPB measures of attitudinal beliefs (costs and benefits), normative beliefs (important referents), and control beliefs (barriers) in relation to engaging in curbside household waste recycling for a 2-week period. Two weeks later, participants completed self report measures of recycling behaviour for the previous fortnight. The results revealed that the attitudinal, normative, and control beliefs for people who performed higher and lower levels of recycling differed significantly. A regression analysis identified both normative and control beliefs as the main determinants of recycling behaviour. For normative beliefs, high level recyclers perceived more approval from referents such as partners, friends, and neighbours to recycle all eligible materials. In addition, the strong results for control beliefs indicated that barriers such as forgetfulness, lack of time, and laziness were rated as more likely to hamper optimal recycling performance for low level recyclers. These findings provide important applied information about beliefs to target in the development of future community recycling campaigns.

Social influences and the physical activity intentions of parents of young-children families: An extended Theory of Planned Behavior Approach

Evidence within Australia and internationally suggests parenthood as a risk factor for inactivity; however, research into understanding parental physical activity is scarce. Given that active parents can create active families and social factors are important for parents’ decision making, the authors investigated a range of social influences on parents’ intentions to be physically active. Parents (N = 580; 288 mothers and 292 fathers) of children younger than 5 years completed an extended Theory of Planned Behavior questionnaire either online or paper based. For both genders, attitude, control factors, group norms, friend general support, and an active parent identity predicted intentions, with social pressure and family support further predicting mothers’ intentions and active others further predicting fathers’ intentions. Attention to these factors and those specific to the genders may improve parents’ intentions to be physically active, thus maximizing the benefits to their own health and the healthy lifestyle practices for other family members.

Predicting the retention of first-time donors using an extended Theory of Planned Behavior

BACKGROUND: Donor retention is vital to blood collection agencies. Past research has highlighted the importance of early career behavior for long-term donor retention, yet research investigating the determinants of early donor behavior is scarce. Using an extended Theory of Planned Behavior (TPB), this study sought to identify the predictors of first-time blood donors' early career retention. STUDY DESIGN AND METHODS: First-time donors (n = 256) completed three surveys on blood donation. The standard TPB predictors and self-identity as a donor were assessed 3 weeks (Time 1) and at 4 months (Time 2) after an initial donation. Path analyses examined the utility of the extended TPB to predict redonation at 4 and 8 months after initial donation. RESULTS: The extended TPB provided a good fit to the data. Post-Time 1 and 2 behavior was consistently predicted by intention to redonate. Further, intention was predicted by attitudes, perceived control, and self-identity (Times 1 and 2). Donors' intentions to redonate at Time 1 were the strongest predictor of intention to donate at Time 2, while donors' behavior at Time 1 strengthened self-identity as a blood donor at Time 2. CONCLUSION: An extended TPB framework proved efficacious in revealing the determinants of first-time donor retention in an initial 8-month period. The results suggest that collection agencies should intervene to bolster donors' attitudes, perceived control, and identity as a donor during this crucial post–first donation period.

Second international workshop on theory and applications of process visualization

The representation of business process models has been a continuing research topic for many years now. However, many process model representations have not developed beyond minimally interactive 2D icon-based representations of directed graphs and networks, with little or no annotation for information overlays. In addition, very few of these representations have undergone a thorough analysis or design process with reference to psychological theories on data and process visualization. This dearth of visualization research, we believe, has led to problems with BPM uptake in some organizations, as the representations can be difficult for stakeholders to understand, and thus remains an open research question for the BPM community. In addition, business analysts and process modeling experts themselves need visual representations that are able to assist with key BPM life cycle tasks in the process of generating optimal solutions. With the rise of desktop computers and commodity mobile devices capable of supporting rich interactive 3D environments, we believe that much of the research performed in computer human interaction, virtual reality, games and interactive entertainment have much potential in areas of BPM; to engage, provide insight, and to promote collaboration amongst analysts and stakeholders alike. We believe this is a timely topic, with research emerging in a number of places around the globe, relevant to this workshop. This is the second TAProViz workshop being run at BPM. The intention this year is to consolidate on the results of last year's successful workshop by further developing this important topic, identifying the key research topics of interest to the BPM visualization community.

Girls and violence : the case for a feminist theory of female violence

Rises recorded for girls’ violence in countries like Australia, Canada, United Kingdom and United States have been hotly contested. One view is these rising rates of violence are an artefact of new forms of policy, policing, criminalisation and social control over young women. Another view is that young women may indeed have become more violent as they have increasingly participated in youth subcultural activities involving gangs and drugs, and cyber‐cultural activities that incite and reward girls’ violence. Any comprehensive explanation will need to address how a complex interplay of cultural, social, behavioural, and policy responses contribute to these rises. This article argues that there is no singular cause, explanation or theory that accounts for the rises in adolescent female violence, and that many of the simple explanations circulating in popular culture are driven by an anti‐feminist ideology. By concentrating on females as victims of violence and very rarely as perpetrators, feminist criminology has for the most part ducked the thorny issue of female violence, leaving a discursive space for anti‐feminist sentiment to reign. The article concludes by arguing the case for developing a feminist theory of female violence.

Accurate pattern prediction of very closely spaced mismatched antennas using measured active element patterns

A method for prediction of the radiation pattern of N strongly coupled antennas with mismatched sources is presented. The method facilitates fast and accurate design of compact arrays. The prediction is based on the measured N-port S parameters of the coupled antennas and the N active element patterns measured in a 50 ω environment. By introducing equivalent power sources, the radiation pattern with excitation by sources with arbitrary impedances and various decoupling and matching networks (DMN) can be accurately predicted without the need for additional measurements. Two experiments were carried out for verification: pattern prediction for parasitic antennas with different loads and for antennas with DMN. The difference between measured and predicted patterns was within 1 to 2 dB.

Using cultural-historical activity theory (CHAT) to study the relationship between school leadership and organisational change

This study aimed to identify how school leaders’ practices influence department activities during school transformation. The method used to explore emerging disturbances and contradictions within and between school departments was based on Cultural Historical Activity Theory (CHAT). The findings show that in order to implement educational changes in schools successfully, leaders should promote the change they envision as being highly consistent with the current collective identity (shared object) of the departments. From this perspective, the systemic components of the school departments are given a sense of preservation and continuity, rather than loss.

A framework for cost-aware process management : cost reporting and cost prediction

Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

Travel time prediction on signalised urban arterials by applying SARIMA modelling on Bluetooth data

Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging. Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction. The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.