Character in the workplace : self directedness mediates harm avoidance in the prediction of job performance

The purpose of this study was to test a model of the relationship between temperament, character and job performance, in order to better understand the cause of stable individual differences in job performance. Personality was conceptualized in terms of Cloninger, Svrakic and Przybeck’s (1993) theoretical framework of personality. It was expected that Self Directedness (character) would mediate Harm Avoidance and Persistence (temperament) in the prediction of job performance. In order to test the hypotheses, a sample of 94 employee/supervisor pairs was recruited from several organizations across Australia. Participants completed a number of questionnaires online, regarding their personality traits (completed by employees) and Job Performance (completed by Supervisors). Consistent with the hypothesis, Self Directedness was found to be a moderate, direct predictor of job performance. Also consistent with the hypothesis, Self Directedness mediated Harm Avoidance in the prediction of job performance. Results show that character (Self Directedness) is important in the prediction of job performance, and also suggests that fearful, avoidant individuals are less likely to perform well in the workplace, based on their low level of character development.

Integrating collaborative filtering and matching-based search for product recommendation

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and thus help them in making good decisions about which product to buy from the vast number of product choices available to them. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.

The Levels of Job Satisfaction, Stress and Burnout In Australian and New Zealand Haemodialysis Nurses

Background: Job dissatisfaction, stress and burnout is linked to high rates of nurses leaving the profession, poor morale, poor patient outcomes and increased financial expenditure. Haemodialysis nurses find their work satisfying although it can be stressful. Little is known, however, about job satisfaction, stress or burnout levels of haemodialysis nurses in Australia and New Zealand. Aims: To assess the current levels of job satisfaction, stress, burnout and nurses’ perception of the haemodialysis work environment. Methods: An observational study involved a cross-sectional sample of 417 registered or enrolled nurses working in Australian or New Zealand haemodialysis units. Data was collected using an on-line questionnaire containing demographic and work characteristics as well as validated measures of job satisfaction, stress, burnout and the work environment Results: 74% of respondents were aged over 40 and 75% had more than six years of haemodialysis nursing experience. Job satisfaction levels were comparable to studies in other practice areas with higher satisfaction derived from professional status and interactions with colleagues. Despite nurses viewing their work environment favourably, moderate levels of burnout were noted with frequent stressors related to workload and patient death and dying. Interestingly there were no differences found between the type or location of dialysis unit. Conclusion: Despite acceptable levels of job satisfaction and burnout, stress with workloads and facets of patient care were found. Understanding the factors that contribute to job satisfaction, stress and burnout can impact the healthcare system through decreased costs by retaining valued staff and through improved patient care.

Job changes, occupational mobility and human capital acquisition : an empirical analysis

Most individuals have more than one job or occupation in their working lives. Most employees are repeatedly faced with the choice of whether to remain in their present job (with the possibility of promotion), or quit to another job in the same occupation with a different firm, or - more radically change occupation. At each stage in an individual's career, the scope for future job or occupational mobility is largely conditioned by the type and quantity of their human capital. This paper presents an empirical study of the factors which link occupational mobility and the acquisition of either firm-based, occupation-specific or general human capital. The data employed are from a cohort of 1980 UK graduates drawn from the Department of Employment Survey 1987. The econometric work presents estimates of the role of firm-based training and occupation-specific training in the career mobility of qualified manpower in the first seven years in the labour market

A recommendation for designing mobile pedestrian navigation system in university campuses

University campuses have thousands of new students, staff and visitors every year. For those who are unfamiliar with the campus environment, an effective pedestrian navigation system is essential to orientate and guide them around the campus. Compared to traditional navigation systems, such as physical signposts and digital map kiosks, a mobile pedestrian navigation system provides advantages in terms of mobility, sensing capabilities, weather-awareness when the user is on the go. However, how best to design a mobile pedestrian navigation system for university campuses is still vague due to limited research in understanding how pedestrians interact with the system, and what information is required for traveling in a complex environment such as university campus. In this paper, we present a mobile pedestrian navigation system called QUT Nav. A field study with eight participants was run in a university campus context, aiming to identify key information required in a mobile pedestrian navigation system for user traveling in university campuses. It also investigated user's interactions and behaviours while they were navigating in the campus environment. Based on the results from the field study, a recommendation for designing mobile pedestrian navigation systems for university campuses is stated.

Work environment, job satisfaction, stress and burnout among haemodialysis nurses

Aim To examine the relationships among nurse and work characteristics, job satisfaction, stress, burnout and the work environment of haemodialysis nurses. Background Haemodialysis nursing is characterised by frequent and intense contact with patients in a complex and intense environment. Method Cross-sectional online survey of 417 haemodialysis nurses that included nurse and work characteristics, the Brisbane Practice Environment Measure, Index of Work Satisfaction, Nursing Stress Scale and the Maslach Burnout Inventory. Results Haemodialysis nurses reported an acceptable level of job satisfaction and perceived their work environment positively, although high levels of burnout were found. Nurses who were older and had worked in haemodialysis the longest had higher satisfaction levels, experienced less stress and lower levels of burnout than younger nurses. The in-centre type of haemodialysis unit had greater levels of stress and burnout than home training units. Greater satisfaction with the work environment was strongly correlated with job satisfaction, lower job stress and emotional exhaustion. Conclusion Haemodialysis nurses experienced high levels of burnout even though their work environment was favourable and they had acceptable levels of job satisfaction. Implications for Nursing Management: Targeted strategies are required to retain and avoid burnout in younger and less experienced nurses in this highly specialised field of nursing.

An ontology-based method for sparsity problem in tag recommendation

Tags or personal metadata for annotating web resources have been widely adopted in Web 2.0 sites. However, as tags are freely chosen by users, the vocabularies are diverse, ambiguous and sometimes only meaningful to individuals. Tag recommenders may assist users during tagging process. Its objective is to suggest relevant tags to use as well as to help consolidating vocabulary in the systems. In this paper we discuss our approach for providing personalized tag recommendation by making use of existing domain ontology generated from folksonomy. Specifically we evaluated the approach in sparse situation. The evaluation shows that the proposed ontology-based method has improved the accuracy of tag recommendation in this situation.

A combined method for mitigating sparsity problem in tag recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

Organisational change stressor and nursing job satisfaction : the mediating effect of coping strategies

Aim To examine the mediating effect of coping strategies on the consequences of nursing and non-nursing (administrative) stressors on the job satisfaction of nurses during change management. Background Organisational change can result in an increase in nursing and nonnursing- related stressors, which can have a negative impact on the job satisfaction of nurses employed in health-care organisations. Method Matched data were collected in 2009 via an online survey at two timepoints (six months apart). Results Partial least squares path analysis revealed a significant causal relationship between Time 1 administrative and role stressors and an increase in nursing-specific stressors in Time 2. A significant relationship was also identified between job-specific nursing stressors and the adoption of effective coping strategies to deal with increased levels of change-induced stress and strain and the likelihood of reporting higher levels of job satisfaction in Time 2. Conclusions The effectiveness of coping strategies is critical in helping nurses to deal with the negative consequences of organisational change. Implications for nursing management This study shows that there is a causal relationship between change, non-nursing stressors and job satisfaction. Senior management should implement strategies aimed at reducing nursing and nonnursing stress during change in order to enhance the job satisfaction of nurses. Keywords: Australia, change management, job satisfaction, nursing and non-nursing stressors, public and non-profit sector

The wrong tool for the job? The predictive powers of the DBQ in a sample of Queensland motorists

Introduction This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours (e.g., speeding, errors & aggressive manoeuvres) and predict crash involvement among a sample of general Queensland motorists. Material and Methods Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results A factor analysis revealed a three factor solution for the DBQ which was consistent with previous Australian-based research. It accounted for 40.5% of the total variance, although some cross-loadings were observed on nine of the twenty items. The internal reliability of the DBQ was satisfactory. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement or demerit point loss e.g. violation notices. Rather, exposure to the road was found to be predictive of crashes, although speeding did make a small contribution to those who recently received a violation notice. Conclusions Taken together, the findings contribute to a growing body of research that raises questions about the predictive ability of the most widely used driving assessment tool globally. Ongoing research (which also includes official crash and offence outcomes) is required to better understand the actual contribution that the DBQ can make to understanding and improving road safety. Future research should also aim to confirm whether this lack of predictive efficacy originates from broader issues inherent within self-report data (e.g., memory recall problems) or issues underpinning the conceptualisation of the scale.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.

A social matching system : using implicit and explicit information for personalized recommendation in online dating service

Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.

A multilevel model of work-life : examining the impact of group structure and relational job design

One in five Australian workers believes that work doesn’t fit well with their family and social commitments. Concurrently, organisations are recognising that to stay competitive they need policies and practices that support the multiple aspects of employees’ lives. Many employees work in group environments yet there is currently little group level work-life balance research. This paper proposes a new theoretical framework developed to understand the design of work groups to better facilitate work-life balance. This new framework focuses on task and relational job designs, group structures and processes and workplace culture.