Innovation implementation effectiveness : a multiorganizational test of Klein Conn and Sorra’s model.

In an empirical test and extension of Klein Conn and Sorra’s model of innovation implementation effectiveness, we apply structural equation modelling to identify the generalizability of their data-modified model in comparison with their theorised model. We examined the implementation of various types of innovations in a sample of 135 organizations. We found that the data supported the original model rather than the data-modified model, such that implementation climate mediated polices and practices and implementation effectiveness, while implementation effectiveness partially mediated the relationship between implementation climate and innovation effectiveness. Furthermore, we extend their model to suggest that non-financial resources availability plays a critical role in implementation policies and practices.

Multi-vehicles interaction graph model for cooperative collision warning system

Cooperative collision warning system for road vehicles, enabled by recent advances in positioning systems and wireless communication technologies, can potentially reduce traffic accident significantly. To improve the system, we propose a graph model to represent interactions between multiple road vehicles in a specific region and at a specific time. Given a list of vehicles in vicinity, we can generate the interaction graph using several rules that consider vehicle's properties such as position, speed, heading, etc. Safety applications can use the model to improve emergency warning accuracy and optimize wireless channel usage. The model allows us to develop some congestion control strategies for an efficient multi-hop broadcast protocol.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

Efficient Voltage/Current Spike Reduction by Active Gate Signaling

This paper presents an Active Gate Signaling scheme to reduce voltage/current spikes across insulated gate power switches in hard switching power electronic circuits. Voltage and/or current spikes may cause EMI noise. In addition, they increase voltage/current stress on the switch. Traditionally, a higher gate resistance is chosen to reduce voltage/current spikes. Since the switching loss will increase remarkably, an active gate voltage control scheme is developed to improve efficiency of hard switching circuits while the undesirable voltage and/or current spikes are minimized.

Eco-retrofitting with building integrated living systems

Building integrated living systems (BILS), such as green roofs and living walls, could mitigate many of the challenges presented by climate change and biodiversity protection. However, few if any such systems have been constructed, and current tools for evaluating them are limited, especially under Australian subtropical conditions. BILS are difficult to assess, because living systems interact with complex, changing and site-specific social and environmental conditions. Our past research in design for eco-services has confirmed the need for better means of assessing the ecological values of BILS - let alone better models for assessing their thermal and hydrological performance. To address this problem, a research project is being developed jointly by researchers at the Central Queensland University (CQ University) and the Queensland University of Technology (QUT), along with industry collaborators. A mathematical model under development at CQ University will be applied and tested to determine its potential for predicting their complex, dynamic behaviour in different contexts. However, the paper focuses on the work at QUT. The QUT school of design is generating designs for living walls and roofs that provide a range of ecosystem goods and services, or ‘eco-services’, for a variety of micro-climates and functional contexts. The research at QUT aims to develop appropriate designs, virtual prototypes and quantitative methods for assessing the potential multiple benefits of BILS in subtropical climates. It is anticipated that the CQ University model for predicting thermal behaviour of living systems will provide a platform for the integration of ecological criteria and indicators. QUT will also explore means to predict and measure the value of eco-services provided by the systems, which is still largely uncharted territory. This research is ultimately intended to facilitate the eco-retrofitting of cities to increase natural capital and urban resource security - an essential component of sustainability. The talk will present the latest range of multifunctional, eco-productive living walls, roofs and urban space frames and their eco-services.

The explicit hazard model – part 1: theoretical development

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

Mechanisms of improvement in treatment for depression : test of a self-efficacy and performance model

Tested D. J. Kavanagh's (1983) depression model's explanation of response to cognitive-behavioral treatment among 19 20–60 yr old Ss who received treatment and 24 age-matched Ss who were assigned to a waiting list. Measures included the Beck Depression Inventory and self-efficacy (SE) and self-monitoring scales. Rises in SE and self-monitored performance of targeted skills were closely associated with the improved depression scores of treated Ss. Improvements in the depression of waiting list Ss occurred through random, uncontrolled events rather than via a systematic increase in specific skills targeted in treatment. SE regarding assertion also predicted depression scores over a 12-wk follow-up.

The Explicit Hazard Model – Part 2 : Applications

Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).

High porosity chained aggregates from the topsoil of the lunar regolith dust

The unusual behaviour of fine lunar regolith like stickiness and low heat conductivity is dominated by the structural arrangement of its finest fraction. Here, we show the previously unknown phenomenon of a globular 3D superstructure within the dust fraction of regolith. A study using the recently developed Transmission X-ray Microscopy (TXM) with tomographic reconstruction reveals a highly porous network of cellular voids in the finest dust fraction aggregates in lunar soil. Such porous chained aggregates are composed of sub-micron particles that form a network of cellular voids a few micrometers in diameter. Discovery of such a superstructure within the finest fraction of lunar topsoil enables a model of heat transfer to be constructed.

A model of project complexity : distinguishing dimensions of complexity from severity

There is increasing agreement that understanding complexity is important for project management because of difficulties associated with decision-making and goal attainment which appear to stem from complexity. However the current operational definitions of complex projects, based upon size and budget, have been challenged and questions have been raised about how complexity can be measured in a robust manner that takes account of structural, dynamic and interaction elements. Thematic analysis of data from 25 in-depth interviews of project managers involved with complex projects, together with an exploration of the literature reveals a wide range of factors that may contribute to project complexity. We argue that these factors contributing to project complexity may define in terms of dimensions, or source characteristics, which are in turn subject to a range of severity factors. In addition to investigating definitions and models of complexity from the literature and in the field, this study also explores the problematic issues of ‘measuring’ or assessing complexity. A research agenda is proposed to further the investigation of phenomena reported in this initial study.

Explaining International new venture internationalisation: an innovation adoption model

The increasing prevalence of International New Ventures (INVs) during the past twenty years has been highlighted by numerous studies (Knight and Cavusgil, 1996, Moen, 2002). International New Ventures are firms, typically small to medium enterprises, that internationalise within six years of inception (Oviatt and McDougall, 1997). To date there has been no general consensus within the literature on a theoretical framework of internationalisation to explain the internationalisation process of INVs (Madsen and Servais, 1997). However, some researchers have suggested that the innovation diffusion model may provide a suitable theoretical framework (Chetty & Hamilton, 1996, Fan & Phan, 2007).The proposed model was based on the existing and well-established innovation diffusion theories drawn from consumer behaviour and internationalisation literature to explain the internationalisation process of INVs (Lim, Sharkey, and Kim, 1991, Reid, 1981, Robertson, 1971, Rogers, 1962, Wickramasekera and Oczkowski, 2006). The results of this analysis indicated that the synthesied model of export adoption was effective in explaining the internationalisation process of INVs within the Queensland Food and Beverage Industry. Significantly the results of the analysis also indicated that features of the original I-models developed in the consumer behaviour literature, that had limited examination within the internationalisation literature were confirmed. This includes the ability of firms, or specifically decision-makers, to skip stages based om previous experience.

Towards a model of the institutional logics of climate change

The proliferation of innovative schemes to address climate change at international, national and local levels signals a fundamental shift in the priority and role of the natural environment to society, organizations and individuals. This shift in shared priorities invites academics and practitioners to consider the role of institutions in shaping and constraining responses to climate change at multiple levels of organisations and society. Institutional theory provides an approach to conceptualising and addressing climate change challenges by focusing on the central logics that guide society, organizations and individuals and their material and symbolic relationship to the environment. For example, framing a response to climate change in the form of an emission trading scheme evidences a practice informed by a capitalist market logic (Friedland and Alford 1991). However, not all responses need necessarily align with a market logic. Indeed, Thornton (2004) identifies six broad societal sectors each with its own logic (markets, corporations, professions, states, families, religions). Hence, understanding the logics that underpin successful –and unsuccessful– climate change initiatives contributes to revealing how institutions shape and constrain practices, and provides valuable insights for policy makers and organizations. This paper develops models and propositions to consider the construction of, and challenges to, climate change initiatives based on institutional logics (Thornton and Ocasio 2008). We propose that the challenge of understanding and explaining how climate change initiatives are successfully adopted be examined in terms of their institutional logics, and how these logics evolve over time. To achieve this, a multi-level framework of analysis that encompasses society, organizations and individuals is necessary (Friedland and Alford 1991). However, to date most extant studies of institutional logics have tended to emphasize one level over the others (Thornton and Ocasio 2008: 104). In addition, existing studies related to climate change initiatives have largely been descriptive (e.g. Braun 2008) or prescriptive (e.g. Boiral 2006) in terms of the suitability of particular practices. This paper contributes to the literature on logics by examining multiple levels: the proliferation of the climate change agenda provides a site in which to study how institutional logics are played out across multiple, yet embedded levels within society through institutional forums in which change takes place. Secondly, the paper specifically examines how institutional logics provide society with organising principles –material practices and symbolic constructions– which enable and constrain their actions and help define their motives and identity. Based on this model, we develop a series of propositions of the conditions required for the successful introduction of climate change initiatives. The paper proceeds as follows. We present a review of literature related to institutional logics and develop a generic model of the process of the operation of institutional logics. We then consider how this is applied to key initiatives related to climate change. Finally, we develop a series of propositions which might guide insights into the successful implementation of climate change practices.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

The right person, in the right job, with the right skills, at the right time. A workforce-planning model that goes beyond metrics

Purpose – The paper aims to describe a workforce-planning model developed in-house in an Australian university library that is based on rigorous environmental scanning of an institution, the profession and the sector. Design/methodology/approach – The paper uses a case study that describes the stages of the planning process undertaken to develop the Library’s Workforce Plan and the documentation produced. Findings – While it has been found that the process has had successful and productive outcomes, workforce planning is an ongoing process. To remain effective, the workforce plan needs to be reviewed annually in the context of the library’s overall planning program. This is imperative if the plan is to remain current and to be regarded as a living document that will continue to guide library practice. Research limitations/implications – Although a single case study, the work has been contextualized within the wider research into workforce planning. Practical implications – The paper provides a model that can easily be deployed within a library without external or specialist consultant skills, and due to its scalability can be applied at department or wider level. Originality/value – The paper identifies the trends impacting on, and the emerging opportunities for, university libraries and provides a model for workforce planning that recognizes the context and culture of the organization as key drivers in determining workforce planning. Keywords - Australia, University libraries, Academic libraries, Change management, Manpower planning Paper type - Case study

A model to predict hypovigilance during a monotonous task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create drowsiness or hypovigilance and impair the ability to react to critical events. Identifying vigilance decrement in monotonous conditions has been a major subject of research, but no research to date has attempted to predict this vigilance decrement. This pilot study aims to show that vigilance decrements due to monotonous tasks can be predicted through mathematical modelling. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants’ performance. This task models the driver’s ability to cope with unpredicted events by performing the expected action. A Hidden Markov Model (HMM) is proposed to predict participants’ hypovigilance. Driver’s vigilance evolution is modelled as a hidden state and is correlated to an observable variable: the participant’s reactions time. This experiment shows that the monotony of the task can lead to an important vigilance decline in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.