Decision support system architecture for consultant selection

Decision Support System (DSS) has played a significant role in construction project management. This has been proven that a lot of DSS systems have been implemented throughout the whole construction project life cycle. However, most research only concentrated in model development and left few fundamental aspects in Information System development. As a result, the output of researches are complicated to be adopted by lay person particularly those whom come from a non-technical background. Hence, a DSS should hide the abstraction and complexity of DSS models by providing a more useful system which incorporated user oriented system. To demonstrate a desirable architecture of DSS particularly in public sector planning, we aim to propose a generic DSS framework for consultant selection. It will focus on the engagement of engineering consultant for irrigation and drainage infrastructure. The DSS framework comprise from operational decision to strategic decision level. The expected result of the research will provide a robust framework of DSS for consultant selection. In addition, the paper also discussed other issues that related to the existing DSS framework by integrating enabling technologies from computing. This paper is based on the preliminary case study conducted via literature review and archival documents at Department of Irrigation and Drainage (DID) Malaysia. The paper will directly affect to the enhancement of consultant pre-qualification assessment and selection tools. By the introduction of DSS in this area, the selection process will be more efficient in time, intuitively aided qualitative judgment, and transparent decision through aggregation of decision among stakeholders.

Exploring the impact of context-specific job stressors on employee work outcomes

A path model was developed to examine the impact of context-specific job stressors on the work outcomes of 132 customer service employees. Respondents who reported a moderate and high level of context-specific stressors report a higher level of job demand and work family conflict. Respondents who reported a higher level of job control tend to receive more work-related support and are more satisfied with their job. Surprisingly, respondents who experienced a higher level of work family conflict tend to receive less work-related support. We found that respondents who obtained more work-related support tend to report a higher level of job satisfaction. There was also a positive relationship between positive job satisfaction and a lower level of intention to quit.

Does 'fit' matter in nonprofits? Exploring value congruence, role stressors and employee health

The number of employees working in nonprofit organisations has grown significantly. These employees are often motivated to join these organisations by a strong desire to fulfil the particular vision and mission of that nonprofit (such as helping the community). While the effects of employee organisation value congruence on job-related attitudes are reasonably well documented, little consideration has been given to the nonprofit context and also perceptions of work stressors and health outcomes. A sample on nonprofit employees from a human services organisation (N = 181) was surveyed with results suggesting that value congruence was related to lower perceptions of role stressors. The results further revealed that value congruence was related to less favourable employee health in some circumstances. Outcomes are discussed in terms of theoretical and practical importance.

Improved GMM-based speaker verification using SVM-driven impostor dataset selection

The problem of impostor dataset selection for GMM-based speaker verification is addressed through the recently proposed data-driven background dataset refinement technique. The SVM-based refinement technique selects from a candidate impostor dataset those examples that are most frequently selected as support vectors when training a set of SVMs on a development corpus. This study demonstrates the versatility of dataset refinement in the task of selecting suitable impostor datasets for use in GMM-based speaker verification. The use of refined Z- and T-norm datasets provided performance gains of 15% in EER in the NIST 2006 SRE over the use of heuristically selected datasets. The refined datasets were shown to generalise well to the unseen data of the NIST 2008 SRE.

Data-driven impostor selection for T-norm score normalisation and the background dataset in SVM-based speaker verification

A data-driven background dataset refinement technique was recently proposed for SVM based speaker verification. This method selects a refined SVM background dataset from a set of candidate impostor examples after individually ranking examples by their relevance. This paper extends this technique to the refinement of the T-norm dataset for SVM-based speaker verification. The independent refinement of the background and T-norm datasets provides a means of investigating the sensitivity of SVM-based speaker verification performance to the selection of each of these datasets. Using refined datasets provided improvements of 13% in min. DCF and 9% in EER over the full set of impostor examples on the 2006 SRE corpus with the majority of these gains due to refinement of the T-norm dataset. Similar trends were observed for the unseen data of the NIST 2008 SRE.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

An investigation into how work-related road safety can be enhanced

Despite the facts that vehicle incidents continue to be the most common mechanism for Australian compensated fatalities and that employers have statutory obligations to provide safe workplaces, very few organisations are proactively and comprehensively managing their work-related road risks. Unfortunately, limited guidance is provided in the existing literature to assist practitioners in managing work-related road risks. The current research addresses this gap in the literature. To explore how work-related road safety can be enhanced, three studies were conducted. Study one explored the effectiveness of a range of risk management initiatives and whether comprehensive risk management practices were associated with safety outcomes. Study two explored barriers to, and facilitators for, accepting risk management initiatives. Study three explored the influence of organisational factors on road safety outcomes to identify optimal work environments for managing road risks. To maximise the research sample and increase generalisability, the studies were designed to allow data collection to be conducted simultaneously drawing upon the same sample obtained from four Australian organisations. Data was collected via four methods. A structured document review of published articles was conducted to identify what outcomes have been observed in previously investigated work-related road safety initiatives. The documents reviewed collectively assessed the effectiveness of 19 work-related road safety initiatives. Audits of organisational practices and process operating within the four researched organisations were conducted to identify whether organisations with comprehensive work-related road risk management practices and processes have better safety outcomes than organisations with limited risk management practices and processes. Interviews were conducted with a sample of 24 participants, comprising 16 employees and eight managers. The interviews were conducted to identify what barriers and facilitators within organisations are involved in implementing work-related road safety initiatives and whether differences in fleet safety climate, stage of change and safety ownership relate to work-related road safety outcomes. Finally, questionnaires were administered to a sample of 679 participants. The questionnaires were conducted to identify which initiatives are perceived by employees to be effective in managing work-related road risks and whether differences in fleet safety climate, stage of change and safety ownership relate to work-related road safety outcomes. Seven research questions were addressed in the current research project. The key findings with respect to each of the research questions are presented below. Research question one: What outcomes have been observed in previously investigated work-related road safety initiatives? The structured document review indicated that initiatives found to be positively associated with occupational road safety both during and after the intervention period included: a pay rise; driver training; group discussions; enlisting employees as community road safety change agents; safety reminders; and group and individual rewards. Research question two: Which initiatives are perceived by employees to be effective in managing work-related road risks? Questionnaire findings revealed that employees believed occupational road risks could best be managed through making vehicle safety features standard, providing practical driver skills training and through investigating serious vehicle incidents. In comparison, employees believed initiatives including signing a promise card commitment to drive safely, advertising the organisation’s phone number on vehicles and consideration of driving competency in staff selection process would have limited effectiveness in managing occupational road safety. Research question three: Do organisations with comprehensive work-related road risk management practices and processes have better safety outcomes than organisations with limited risk management practices and processes? The audit identified a difference among the organisations in their management of work-related road risks. Comprehensive risk management practices were associated with employees engaging in overall safer driving behaviours, committing less driving errors, and experiencing less fatigue and distraction issues when driving. Given that only four organisations participated in this research, these findings should only be considered as preliminary. Further research should be conducted to explore the relationship between comprehensiveness of risk management practices and road safety outcomes with a larger sample of organisations. Research question four: What barriers and facilitators within organisations are involved in implementing work-related road safety initiatives? The interviews identified that employees perceived six organisational characteristics as potential barriers to implementing work-related road safety initiatives. These included: prioritisation of production over safety; complacency towards work-related road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. In comparison, employees perceived three organisational characteristics as potential facilitators to implementing work-related road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Research question five: Do differences in fleet safety climate relate to work-related road safety outcomes? The interviews and questionnaires identified that organisational climates with high management commitment, support for managing work demands, appropriate safety rules and safety communication were associated with employees who engaged in safer driving behaviours. Regression analyses indicated that as participants’ perceptions of safety climate increased, the corresponding likelihood of them engaging in safer driving behaviours increased. Fleet safety climate was perceived to influence road safety outcomes through several avenues. Some of these included: the allocation of sufficient resources to manage occupational road risks; fostering a supportive environment of mutual responsibility; resolving safety issues openly and fairly; clearly communicating to employees that safety is the top priority; and developing appropriate work-related road safety policies and procedures. Research question six: Do differences in stage of change relate to work-related road safety outcomes? The interviews and questionnaires identified that participants’ perceptions of initiative effectiveness were found to vary with respect to their individual stage of readiness, with stage-matched initiatives being perceived most effective. In regards to safety outcomes, regression analyses identified that as participants’ progress through the stages of change, the corresponding likelihood of them being involved in vehicle crashes decreases. Research question seven: Do differences in safety ownership relate to work-related road safety outcomes? The interviews and questionnaires revealed that management of road risks is often given less attention than other areas of health and safety management in organisations. In regards to safety outcomes, regression analyses identified that perceived authority and perceived shared ownership both emerged as significant independent predictors of self-reported driving behaviours pertaining to fatigue and distractions. The regression models indicated that as participants’ perceptions of the authority of the person managing road risks increases, and perceptions of shared ownership of safety tasks increases, the corresponding likelihood of them engaging in driving while fatigued or multitasking while driving decreases. Based on the findings from the current research, the author makes several recommendations to assist practitioners in developing proactive and comprehensive approaches to managing occupational road risks. The author also suggests several avenues for future research in the area of work-related road safety.

Employee engagement : the development of a three dimensional model of engagement; and an exploration of its relationship with affective leader behaviours

This study was designed to examine affective leader behaviours, and their impact on cognitive, affective and behavioural engagement. Researchers (e.g., Cropanzano & Mitchell, 2005; Moorman et al., 1998) have called for more research to be directed toward modelling and testing sets of relationships which better approximate the complexity associated with contemporary organisational experience. This research has attempted to do this by clarifying and defining the construct of engagement, and then by examining how each of the engagement dimensions are impacted by affective leader behaviours. Specifically, a model was tested that identifies leader behaviour antecedents of cognitive, affective and behavioural engagement. Data was collected from five public-sector organisations. Structural equation modelling was used to identify the relationships between the engagement dimensions and leader behaviours. The results suggested that affective leader behaviours had a substantial direct impact on cognitive engagement, which in turn influenced affective engagement, which then influenced intent to stay and extra-role performance. The results indicated a directional process for engagement, but particularly highlighted the significant impact of affective leader behaviours as an antecedent to engagement. In general terms, the findings will provide a platform from which to develop a robust measure of engagement, and will be helpful to human resource practitioners interested in understanding the directional process of engagement and the importance of affective leadership as an antecedent to engagement.

Subjective fit with organizational culture : an investigation of moderating effects in the work stressor-employee adjustment relationship

Occupational stress has been a concern for human resource managers in light of research investigating the work stressor-employee adjustment relationship. This research has consistently demonstrated many negative effects between stressors in the workplace and employee adjustment. A considerable amount of literature also describes potential moderators of this relationship. Subjective fit with organizational culture has been established as a significant predictor of employee job-related attitudes; however, research has neglected investigation of the potential moderating effect of subjective fit in the work stressor-employee adjustment process. It was predicted that perceptions of subjective fit with the organization’s values and goals would mitigate the negative effect of work stressors on employee adjustment in an employee sample from three organizations (N ¼ 256). Hierarchical multiple regression analyses revealed support for the stress-buffering effects of high subjective fit in the prediction of physical symptoms, job satisfaction, and intentions to leave. The theoretical and practical implications of the results are discussed.

The applicability of biased estimation in model and model order selection

Biased estimation has the advantage of reducing the mean squared error (MSE) of an estimator. The question of interest is how biased estimation affects model selection. In this paper, we introduce biased estimation to a range of model selection criteria. Specifically, we analyze the performance of the minimum description length (MDL) criterion based on biased and unbiased estimation and compare it against modern model selection criteria such as Kay's conditional model order estimator (CME), the bootstrap and the more recently proposed hook-and-loop resampling based model selection. The advantages and limitations of the considered techniques are discussed. The results indicate that, in some cases, biased estimators can slightly improve the selection of the correct model. We also give an example for which the CME with an unbiased estimator fails, but could regain its power when a biased estimator is used.

Employee work motivation and discretionary work effort

The focus of this thesis is discretionary work effort, that is, work effort that is voluntary, is above and beyond what is minimally required or normally expected to avoid reprimand or dismissal, and is organisationally functional. Discretionary work effort is an important construct because it is known to affect individual performance as well as organisational efficiency and effectiveness. To optimise organisational performance and ensure their long term competitiveness and sustainability, firms need to be able to induce their employees to work at or near their peak level. To work at or near their peak level, individuals must be willing to supply discretionary work effort. Thus, managers need to understand the determinants of discretionary work effort. Nonetheless, despite many years of scholarly investigation across multiple disciplines, considerable debate still exists concerning why some individuals supply only minimal work effort whilst others expend effort well above and beyond what is minimally required of them (Le. they supply discretionary work effort). Even though it is well recognised that discretionary work effort is important for promoting organisational performance and effectiveness, many authors claim that too little is being done by managers to increase the discretionary work effort of their employees. In this research, I have adopted a multi-disciplinary approach towards investigating the role of monetary and non-monetary work environment characteristics in determining discretionary work effort. My central research questions were "What non-monetary work environment characteristics do employees perceive as perks (perquisites) and irks (irksome work environment characteristics)?" and "How do perks, irks and monetary rewards relate to an employee's level of discretionary work effort?" My research took a unique approach in addressing these research questions. By bringing together the economics and organisational behaviour (OB) literatures, I identified problems with the current definition and conceptualisations of the discretionary work effort construct. I then developed and empirically tested a more concise and theoretically-based definition and conceptualisation of this construct. In doing so, I disaggregated discretionary work effort to include three facets - time, intensity and direction - and empirically assessed if different classes of work environment characteristics have a differential pattern of relationships with these facets. This analysis involved a new application of a multi-disciplinary framework of human behaviour as a tool for classifying work environment characteristics and the facets of discretionary work effort. To test my model of discretionary work effort, I used a public sector context in which there has been limited systematic empirical research into work motivation. The program of research undertaken involved three separate but interrelated studies using mixed methods. Data on perks, irks, monetary rewards and discretionary work effort were gathered from employees in 12 organisations in the local government sector in Western Australia. Non-monetary work environment characteristics that should be associated with discretionary work effort were initially identified through a review of the literature. Then, a qualitative study explored what work behaviours public sector employees perceive as discretionary and what perks and irks were associated with high and low levels of discretionary work effort. Next, a quantitative study developed measures of these perks and irks. A Q-sorttype procedure and exploratory factor analysis were used to develop the perks and irks measures. Finally, a second quantitative study tested the relationships amongst perks, irks, monetary rewards and discretionary work effort. Confirmatory factor analysis was firstly used to confirm the factor structure of the measurement models. Correlation analysis, regression analysis and effect-size correlation analysis were used to test the hypothesised relationships in the proposed model of discretionary work effort. The findings confirmed five hypothesised non-monetary work environment characteristics as common perks and two of three hypothesised non-monetary work environment characteristics as common irks. Importantly, they showed that perks, irks and monetary rewards are differentially related to the different facets of discretionary work effort. The convergent and discriminant validities of the perks and irks constructs as well as the time, intensity and direction facets of discretionary work effort were generally confirmed by the research findings. This research advances the literature in several ways: (i) it draws on the Economics and OB literatures to redefine and reconceptualise the discretionary work effort construct to provide greater definitional clarity and a more complete conceptualisation of this important construct; (ii) it builds on prior research to create a more comprehensive set of perks and irks for which measures are developed; (iii) it develops and empirically tests a new motivational model of discretionary work effort that enhances our understanding of the nature and functioning of perks and irks and advances our ability to predict discretionary work effort; and (iv) it fills a substantial gap in the literature on public sector work motivation by revealing what work behaviours public sector employees perceive as discretionary and what work environment characteristics are associated with their supply of discretionary work effort. Importantly, by disaggregating discretionary work effort this research provides greater detail on how perks, irks and monetary rewards are related to the different facets of discretionary work effort. Thus, from a theoretical perspective this research also demonstrates the conceptual meaningfulness and empirical utility of investigating the different facets of discretionary work effort separately. From a practical perspective, identifying work environment factors that are associated with discretionary work effort enhances managers' capacity to tap this valuable resource. This research indicates that to maximise the potential of their human resources, managers need to address perks, irks and monetary rewards. It suggests three different mechanisms through which managers might influence discretionary work effort and points to the importance of training for both managers and non-managers in cultivating positive interpersonal relationships.

Security of employee entitlements : corporate governance issues

Following the collapse across the last decade of a number of large organizations such as Enron in the USA and several domestic organizations including Ansett Airlines, HIH Insurance and One.Tel, much discussion has ensued about the need to secure employee entitlements. However, tangible improvements in this area are elusive. Good corporate governance policies would suggest that deferred obligations as well as current debts should not be neglected and that appropriate arrangements be put in place to adequately fund employee entitlements. In this paper we consider recent Australian attempts to introduce better governance of employee entitlements.

Data-driven background dataset selection for SVM-based speaker verification

The recently proposed data-driven background dataset refinement technique provides a means of selecting an informative background for support vector machine (SVM)-based speaker verification systems. This paper investigates the characteristics of the impostor examples in such highly-informative background datasets. Data-driven dataset refinement individually evaluates the suitability of candidate impostor examples for the SVM background prior to selecting the highest-ranking examples as a refined background dataset. Further, the characteristics of the refined dataset were analysed to investigate the desired traits of an informative SVM background. The most informative examples of the refined dataset were found to consist of large amounts of active speech and distinctive language characteristics. The data-driven refinement technique was shown to filter the set of candidate impostor examples to produce a more disperse representation of the impostor population in the SVM kernel space, thereby reducing the number of redundant and less-informative examples in the background dataset. Furthermore, data-driven refinement was shown to provide performance gains when applied to the difficult task of refining a small candidate dataset that was mis-matched to the evaluation conditions.

Exploiting multiple feature sets in data-driven impostor dataset selection for speaker verification

This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally proposed technique to exploit support vector coefficients as an impostor suitability metric in the data-driven selection process. Using support vector coefficients improved the performance of the refined datasets in the evaluation of unseen data. Further, attempts are made to exploit the differences in impostor example suitability measures from varying features spaces to provide added robustness.