A multidimensional model of client success when engaging external consultants

Too often the relationship between client and external consultants is perceived as one of protagonist versus antogonist. Stories on dramatic, failed consultancies abound, as do related anecdotal quips. A contributing factor to many "apparently" failed consultancies is a poor appreciation by both the client and consultant of the client's true goals for the project and how to assess progress toward these goals. This paper presents and analyses a measurement model for assessing client success when engaging an external consultant. Three main areas of assessment are identified: (1) the consultant;s recommendations, (2) client learning, and (3) consultant performance. Engagement success is emperically measured along these dimensions through a series of case studies and a subsequent survey of clients and consultants involved in 85 computer-based information system selection projects. Validation fo the model constructs suggests the existence of six distinct and individually important dimensions of engagement success. both clients and consultants are encouraged to attend to these dimensions in pre-engagement proposal and selection processes, and post-engagement evaluation of outcomes.

Developing a multidimensional scale of customer-oriented deviance (COD)

Although frontline employees' bending of organizational rules and norms for customers is an important phenomenon, marketing scholars to date only broadly describe over-servicing behaviors and provide little distinction among deviant behavioral concepts. Drawing on research on pro-social and pro-customer behaviors and on studies of positive deviance, this paper develops and validates a multi-faceted, multi-dimensional construct term customer-oriented deviance. Results from two samples totaling 616 frontline employees (FLEs) in the retail and hospitality industries demonstrate that customer-oriented deviance is a four-dimensional construct with sound psychometric properties. Evidence from a test of a theoretical model of key antecedents establishes nomological validity with empathy/perspective-taking, risk-taking propensity, role conflict, and job autonomy as key predictors. Results show that the dimensions of customer-oriented deviance are distinct and have significant implications for theory and practice.

Property-performance control of multidimensional, hierarchical, single-crystalline ZnO nanoarchitectures

Diverse morphologies of multidimensional hierarchical single-crystalline ZnO nanoarchitectures including nanoflowers, nanobelts, and nanowires are obtained by use of a simple thermal evaporation and vapour-phase transport deposition technique by placing Au-coated silicon substrates in different positions inside a furnace at process temperatures as low as 550 °C. The nucleation and growth of ZnO nanostructures are governed by the vapour–solid mechanism, as opposed to the commonly reported vapour–liquid–solid mechanism, when gold is used in the process. The morphological, structural, compositional and optical properties of the synthesized ZnO nanostructures can be effectively tailored by means of the experimental parameters, and these properties are closely related to the local growth temperature and gas-phase supersaturation at the sample position. In particular, room-temperature photoluminescence measurements reveal an intense near-band-edge ultraviolet emission at about 386 nm for nanobelts and nanoflowers, which suggests that these nanostructures are of sufficient quality for applications in, for example, optoelectronic devices.

Using digital projection to evoke aesthetic ideas in performance

This practice-led research project investigated the use of digital projection as a compositional tool in live performance. The project was carried out through the creation of a new Australian theatre work called Genesis that poetically integrated digital projection and live performance. The investigation produced a framework for creating powerful theatrical sequences where the themes and ideas of the show were embedded inside particular performance gestures prompting an expanded aesthetic perception of the content.

Public relations and engagement : theoretical imperatives of a multidimensional concept

Engagement has emerged as important concept in public relations, as stakeholders challenge the discourse of organizational primacy and organizations prioritize the need for authentic stakeholder involvement. As a multidimensional concept, engagement offers a foundation for building organizational relationships, and provides a means to facilitate community–organization interaction. This special issue on engagement and public relations presents a body of work that both explicates and expands the theoretical foundations of engagement, and contributes to scholarly understanding of its contexts, processes, and outcomes.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

Multidimensional classroom support to inclusive education teachers in Beijing, China

Classroom support plays a salient role in successful inclusive education, hence it has been widely debated in the literature. Much extant work has only focused on a particular aspect of classroom support. A comprehensive, systematic discussion of classroom support is sporadic in the literature. Relevant research concerning the Chinese context is even more limited. To address this gap, our study developed and validated a multidimensional classroom support model conducive to teachers’ inclusive education practices. Data were drawn from our large-scale survey with inclusive education teachers in Beijing. Further analyses were conducted to compare different dimensions within the classroom support model. Drawing insights from the results, we provide some recommendations for practice and research.

A stochastic exponential Euler scheme for simulation of stiff biochemical reaction systems

In order to simulate stiff biochemical reaction systems, an explicit exponential Euler scheme is derived for multidimensional, non-commutative stochastic differential equations with a semilinear drift term. The scheme is of strong order one half and A-stable in mean square. The combination with this and the projection method shows good performance in numerical experiments dealing with an alternative formulation of the chemical Langevin equation for a human ether a-go-go related gene ion channel mode

Unsupervised Domain Adaptation by Domain Invariant Projection

Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset

Is the mental wellbeing of young Australians best represented by a single, multidimensional or bifactor model?

Internationally there is a growing interest in the mental wellbeing of young people. However, it is unclear whether mental wellbeing is best conceptualized as a general wellbeing factor or a multidimensional construct. This paper investigated whether mental wellbeing, measured by the Mental Health Continuum-Short Form (MHC-SF), is best represented by: (1) a single-factor general model; (2) a three-factor multidimensional model or (3) a combination of both (bifactor model). 2,220 young Australians aged between 16 and 25 years completed an online survey including the MHC-SF and a range of other wellbeing and mental ill-health measures. Exploratory factor analysis supported a bifactor solution, comprised of a general wellbeing factor, and specific group factors of psychological, social and emotional wellbeing. Confirmatory factor analysis indicated that the bifactor model had a better fit than competing single and three-factor models. The MHC-SF total score was more strongly associated with other wellbeing and mental ill-health measures than the social, emotional or psychological subscale scores. Findings indicate that the mental wellbeing of young people is best conceptualized as an overarching latent construct (general wellbeing) to which emotional, social and psychological domains contribute. The MHC-SF total score is a valid and reliable measure of this general wellbeing factor.

Comprehending adverbs of doubt and certainty in health communication: A multidimensional scaling approach

This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.

Effective Cell-Centred Time-Domain Maxwell's Equations Numerical Solvers

This research work analyses techniques for implementing a cell-centred finite-volume time-domain (ccFV-TD) computational methodology for the purpose of studying microwave heating. Various state-of-the-art spatial and temporal discretisation methods employed to solve Maxwell's equations on multidimensional structured grid networks are investigated, and the dispersive and dissipative errors inherent in those techniques examined. Both staggered and unstaggered grid approaches are considered. Upwind schemes using a Riemann solver and intensity vector splitting are studied and evaluated. Staggered and unstaggered Leapfrog and Runge-Kutta time integration methods are analysed in terms of phase and amplitude error to identify which method is the most accurate and efficient for simulating microwave heating processes. The implementation and migration of typical electromagnetic boundary conditions. from staggered in space to cell-centred approaches also is deliberated. In particular, an existing perfectly matched layer absorbing boundary methodology is adapted to formulate a new cell-centred boundary implementation for the ccFV-TD solvers. Finally for microwave heating purposes, a comparison of analytical and numerical results for standard case studies in rectangular waveguides allows the accuracy of the developed methods to be assessed.

Implication of global warming on air-conditioned office buildings in Australia

With the accelerated trend of global warming, the thermal behavior of existing buildings, which were typically designed based on current weather data, may not be able to cope with the future climate. This paper quantifies, through computer simulations, the increased cooling loads imposed by potential global warming and probable indoor temperature increases due to possible undersized air-conditioning system. It is found from the sample office building examined that the existing buildings would generally be able to adapt to the increasing warmth of 2030 year Low and High scenarios projections and 2070 year Low scenario projection. However, for the 2070 year High scenario, the study indicates that the existing office buildings, in all capital cities except for Hobart, will suffer from overheating problems. When the annual average temperature increase exceeds 2°C, the risk of current office buildings subjected to overheating will be significantly increased. For existing buildings which are designed with current climate condition, it is shown that there is a nearly linear correlation between the increase of average external air temperature and the increase of building cooling load. For the new buildings, in which the possible global warming has been taken into account in the design, a 28-59% increase of cooling capacity under 2070 High scenario would be required to improve the building thermal comfort level to an acceptable standard.

Characterisation of indoor air organic pollutants in Brisbane

The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.