Explaining voice behaviour: The roles of personal resources, social interdependence, and supervisor leadership style

This study contributes to current research on voice behaviour by investigating several under-explored drivers that motivate employees’ expression of constructive ideas about work-related issues. It draws from the concept of psychological climate to examine how voice behaviour is influenced by employees’ (1) personal resources (tenacity and passion for work), (2) perceptions of social interdependence (task and outcome interdependence), and (3) supervisor leadership style (transformational and transactional). Using a multi-source research design, surveys were administered to 226 employees and to 24 supervisors at a Canadian-based not-for-profit organization. The hypotheses are tested with hierarchical regression analysis. The results indicate that employees are more likely to engage in voice behaviour to the extent that they exhibit higher levels of passion for work. Further, their voice behaviour is lower to the extent that their supervisor adopts a transformational leadership style characterized by high performance expectations or a transactional leadership style based on contingent rewards and contingent punishment behaviours. The study reveals that there are no significant effects of tenacity, social interdependence, and behaviour-focused transformational leadership on voice. The findings have significant implications for organizations that seek to encourage employee behaviours that help improve current work practices or undo harmful situations.

New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry

This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.

Hearing voice and silence during stressful economic times

Purpose - It is ironic that in stressful economic times, when new ideas and positive behaviors could be most valuable, employees may not speak up, leading to reduced employee participation, less organizational learning, less innovation and less receptiveness to change. The supervisor is the organization’s first line of defense against a culture of silence and towards a culture of openness. This research asks what helps supervisors to hear prosocial voice and notice defensive silence. Design/methodology/approach - We conducted a cross-sectional field study of 142 supervisors. Findings - Our results indicate that prosocial voice is increased by supervisor tension and trust in employees, while defensive silence is increased by supervisor tension but reduced by unionization of employees and trust in employees. This indicates that, as hypothesized by others, voice and silence are orthogonal and not opposites of the same construct. Research limitations/implications - The data is measured at one point in time, and further longitudinal study would be helpful to further understand the phenomena. Practical implications - This research highlights the potential for supervisors in stressful situations to selectively hear voice and silence from employees. Originality/value - This study adds to our knowledge of prosocial voice and defensive silence by testing supervisors’ perceptions of these constructs during difficult times. It provides valuable empirical insights to a literature dominated by conceptual non-empirical papers. Limited research on silence might reflect how difficult it is to study such an ambiguous and passive construct as silence (often simply viewed as a lack of speech). also contribute to trust literature by identifying its role in increasing supervisor’s perceptions of prosocial voice and reducing perceptions of defensive silence.

Finding your research voice : the application of bibliometrics as an analytic literature tool on the pedagogic field of higher education

This paper documents the use of bibliometrics as a methodology to bring forth a structured, systematic and rigorous way to analyse and evaluate a range of literature. When starting out and reading broadly for my doctoral studies, one article by Trigwell and Prosser (1996b) led me to reflect about my level of comprehension as the content, concepts and methodology did not resonate with my epistemology. A disconnection between our paradigms emerged. Further reading unveiled the work by Doyle (1987) who categorised research in teaching and teacher education by three main areas: teacher characteristics, methods research and teacher behaviour. My growing concerns that there were gaps in the knowledge also exposed the difficulties in documenting said gaps. As an early researcher who required support to locate myself in the field and to find my research voice, I identified bibliometrics (Budd, 1988; Yeoh & Kaur, 2007) as an appropriate methodology to add value and rigour in three ways. Firstly, the application of bibliometrics to analyse articles is systematic, builds a picture from the characteristics of the literature, and offers a way to elicit themes within the categories. Secondly, by systematic analysis there is occasion to identify gaps within the body of work, limitations in methodology or areas in need of further research. Finally, extension and adaptation of the bibliometrics methodology, beyond citation or content analysis, to investigate the merit of methodology, participants and instruments as a determinant for research worth allowed the researcher to build confidence and contribute new knowledge to the field. Therefore, this paper frames research in the pedagogic field of Higher Education through teacher characteristics, methods research and teacher behaviour, visually represents the literature analysis and locates my research self within methods research. Through my research voice I will present the bibliometrics methodology, the outcomes and document the landscape of pedagogy in the field of Higher Education.

The impact of interface modality on police officers' visual behaviour when using an in-vehicle system

Background Standard operating procedures state that police officers should not drive while interacting with their mobile data terminal (MDT) which provides in-vehicle information essential to police work. Such interactions do however occur in practice and represent a potential source of driver distraction. The MDT comprises visual output with manual input via touch screen and keyboard. This study investigated the potential for alternative input and output methods to mitigate driver distraction with specific focus on eye movements. Method Nineteen experienced drivers of police vehicles (one female) from the NSW Police Force completed four simulated urban drives. Three drives included a concurrent secondary task: imitation licence plate search using an emulated MDT. Three different interface methods were examined: Visual-Manual, Visual-Voice, and Audio-Voice (“Visual” and “Audio” = output modality; “Manual” and “Voice” = input modality). During each drive, eye movements were recorded using FaceLAB™ (Seeing Machines Ltd, Canberra, ACT). Gaze direction and glances on the MDT were assessed. Results The Visual-Voice and Visual-Manual interfaces resulted in a significantly greater number of glances towards the MDT than Audio-Voice or Baseline. The Visual-Manual and Visual-Voice interfaces resulted in significantly more glances to the display than Audio-Voice or Baseline. For longer duration glances (>2s and 1-2s) the Visual-Manual interface resulted in significantly more fixations than Baseline or Audio-Voice. The short duration glances (<1s) were significantly greater for both Visual-Voice and Visual-Manual compared with Baseline and Audio-Voice. There were no significant differences between Baseline and Audio-Voice. Conclusion An Audio-Voice interface has the greatest potential to decrease visual distraction to police drivers. However, it is acknowledged that an audio output may have limitations for information presentation compared with visual output. The Visual-Voice interface offers an environment where the capacity to present information is sustained, whilst distraction to the driver is reduced (compared to Visual-Manual) by enabling adaptation of fixation behaviour.

Robust recognition of human behaviour in challenging environments

Novel techniques have been developed for the automatic recognition of human behaviour in challenging environments using information from visual and infra-red camera feeds. The techniques have been applied to two interesting scenarios: Recognise drivers' speech using lip movements and recognising audience behaviour, while watching a movie, using facial features and body movements. Outcome of the research in these two areas will be useful in the improving the performance of voice recognition in automobiles for voice based control and for obtaining accurate movie interest ratings based on live audience response analysis.

Atypical processing of voice sounds in infants at risk for Autism Spectrum Disorder

Adults diagnosed with autism spectrum disorder (ASD) show a reduced sensitivity (degree of selective response) to social stimuli such as human voices. In order to determine whether this reduced sensitivity is a consequence of years of poor social interaction and communication or is present prior to significant experience, we used functional MRI to examine cortical sensitivity to auditory stimuli in infants at high familial risk for later emerging ASD (HR group, N = 15), and compared this to infants with no family history of ASD (LR group, N = 18). The infants (aged between 4 and 7 months) were presented with voice and environmental sounds while asleep in the scanner and their behaviour was also examined in the context of observed parent-infant interaction. Whereas LR infants showed early specialisation for human voice processing in right temporal and medial frontal regions, the HR infants did not. Similarly, LR infants showed stronger sensitivity than HR infants to sad vocalisations in the right fusiform gyrus and left hippocampus. Also, in the HR group only, there was an association between each infant's degree of engagement during social interaction and the degree of voice sensitivity in key cortical regions. These results suggest that at least some infants at high-risk for ASD have atypical neural responses to human voice with and without emotional valence. Further exploration of the relationship between behaviour during social interaction and voice processing may help better understand the mechanisms that lead to different outcomes in at risk populations.

Modelling data and voice traffic over IP networks using continuous-time Markov models

Common approaches to IP-traffic modelling have featured the use of stochastic models, based on the Markov property, which can be classified into black box and white box models based on the approach used for modelling traffic. White box models, are simple to understand, transparent and have a physical meaning attributed to each of the associated parameters. To exploit this key advantage, this thesis explores the use of simple classic continuous-time Markov models based on a white box approach, to model, not only the network traffic statistics but also the source behaviour with respect to the network and application. The thesis is divided into two parts: The first part focuses on the use of simple Markov and Semi-Markov traffic models, starting from the simplest two-state model moving upwards to n-state models with Poisson and non-Poisson statistics. The thesis then introduces the convenient to use, mathematically derived, Gaussian Markov models which are used to model the measured network IP traffic statistics. As one of the most significant contributions, the thesis establishes the significance of the second-order density statistics as it reveals that, in contrast to first-order density, they carry much more unique information on traffic sources and behaviour. The thesis then exploits the use of Gaussian Markov models to model these unique features and finally shows how the use of simple classic Markov models coupled with use of second-order density statistics provides an excellent tool for capturing maximum traffic detail, which in itself is the essence of good traffic modelling. The second part of the thesis, studies the ON-OFF characteristics of VoIP traffic with reference to accurate measurements of the ON and OFF periods, made from a large multi-lingual database of over 100 hours worth of VoIP call recordings. The impact of the language, prosodic structure and speech rate of the speaker on the statistics of the ON-OFF periods is analysed and relevant conclusions are presented. Finally, an ON-OFF VoIP source model with log-normal transitions is contributed as an ideal candidate to model VoIP traffic and the results of this model are compared with those of previously published work.