Organisational culture, leadership behaviour and job satisfaction among primary health care professionals in Saudi Arabia : a mixed-methods study

The purpose of this study was to improve individual and organisational performance in primary health care (PHC) by identifying the relationship between organisational culture, leadership behaviour and job satisfaction. The study used a sequential explanatory mixed methods design, to investigate the relationships between organisational culture, leadership behaviour, and job satisfaction among 550 PHCC professionals in Saudi Arabia. From surveying the PHC professionals, the results highlighted the importance of human caring qualities, including praise and recognition, consideration, and support, with respect to their perceptions of job satisfaction, leadership behaviour, and organisational culture. As a consequence a management framework was proposed to address these issues.

Complementary surface-enhanced resonance raman spectroscopic biodetection of mixed protein solutions by chitosan- and silica-coated plasmon-tuned silver nanoparticles

Silver nanoparticles with identical plasmonic properties but different surface functionalities are synthesized and tested as chemically selective surface-enhanced resonance Raman (SERR) amplifiers in a two-component protein solution. The surface plasmon resonances of the particles are tuned to 413 nm to match the molecular resonance of protein heme cofactors. Biocompatible functionalization of the nanoparticles with a thin film of chitosan yields selective SERR enhancement of the anionic protein cytochrome b5, whereas functionalization with SiO2 amplifies only the spectra of the cationic protein cytochrome c. As a result, subsequent addition of the two differently functionalized particles yields complementary information on the same mixed protein sample solution. Finally, the applicability of chitosan-coated Ag nanoparticles for protein separation was tested by in situ resonance Raman spectroscopy.

Wood density : a tool to find complementary species for the design of mixed species plantations

The successful establishment and growth of mixed-species forest plantations requires that complementary or facilitatory species be identified. This can be difficult in many tropical areas because the growth characteristics of endemic species are often unknown, particularly when grown at potentially higher densities in plantations than in natural forests. Here, we investigate whether wood density is a useful and readily accessible trait for choosing complementary species for mixed species plantations. Wood density represents the carbon investment per unit volume of stem with a trade-off generally found between fast (low wood density) and slow (high wood density) growing species. To do this, we use data collected from 18 highly diverse mixed species plantations (4–23 mostly native species) aged from 6 to 11 years at the time of data collection located on Leyte Island, Philippines. We found significant negative correlations between wood densities and the height of the most abundant species, as well as with measures of overall stand growth and tree diameter size distribution. Not only do species with denser woods have slower growth rates, but also mixed-species plantations with higher average wood density and higher stem density were also less productive, at least in these young plantations. Similarly, stands with a high diversity in wood densities were less productive. There is growing interest in making greater use of native multi-species mixtures in smallholder and community planting programs in the tropics, and our results show databases of wood density values may help improve their design. In the early development stages of plantations, canopy closure and rapid height growth are usually key silvicultural targets, and wood density values can predict the rapid height development of species. If plantations are being grown for the livelihood of small landholders then the best target is to choose some species with different wood densities. This allows an early harvest of low-wood density species for early income, and will also reduce competition for slower growing trees with higher wood densities for later income generation.

Indigenous students transitioning to school : responses to pre-foundational mathematics

Australian Indigenous students' mathematics performance continues to be below that of non-Indigenous students. This occurs from the early years of school, due largely to knowledge and social differences on entry to formal schooling. This paper reports on a mathematics research project conducted in one Aboriginal community school in New South Wales, Australia. The project aimed to identify and explain the ways that young Australian Indigenous students (age 2-4 years) learn number language and processes, specifically attribute language, sorting, 1-1 correspondence and, counting. The project adopted a mixed methods approach. That is, the methodology was decolonising (Smith 1999) in that it collaborated with and gave benefit back to the Indigenous community and school being researched. It was qualitative and interpretative (Burns 2000) and incorporated an action-research teaching-experiment approach where and teachers collaborated with the researchers to try new teaching methods. This paper draws on data pertaining to students' response to diagnostic interview questions, the pre- and post-test results of the interview and photographic evidence as observations during mathematics learning time. Participants referred to in this paper include one female principal (N = 1), and the transition class of students' pre- (N = 6) and post-test (N = 3) results of the pre-foundational processes (also referred to as attributes). The results were encouraging with improvements in colour (34%), patterns (33%); capacity (38%). As a result of this project, our epistemology regarding the importance of finding out about students' pre-foundational knowledge and understandings and providing a culturally appropriate learning environment with resources has been built upon.

It wasn't my fault : does crash culpability improve predictive outcomes in a self-report study?

Introduction: Research that has focused on the ability of self-report assessment tools to predict crash outcomes has proven to be mixed. As a result, researchers are now beginning to explore whether examining culpability of crash involvement can subsequently improve this predictive efficacy. This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to predict crash involvement among a sample of general Queensland motorists, and in particular, whether including a crash culpability variable improves predictive outcomes. Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results: Consistent with previous research, a factor analysis revealed a three factor solution for the DBQ accounting for 40.5% of the overall variance. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement. Rather, exposure to the road was found to be predictive of crashes. An analysis into culpability revealed 88 participants reported being “at fault” for their most recent crash. Corresponding between and multi-variate analyses that included the culpability variable did not result in an improvement in identifying those involved in crashes. Conclusions: While preliminary, the results suggest that including crash culpability may not necessarily improve predictive outcomes in self-report methodologies, although it is noted the current small sample size may also have had a deleterious effect on this endeavour. This paper also outlines the need for future research (which also includes official crash and offence outcomes) to better understand the actual contribution of self-report assessment tools, and culpability variables, to understanding and improving road safety.

Integrated approach to optimize open-pit mine block sequencing

Critical stage in open-pit mining is to determine the optimal extraction sequence of blocks, which has significant impacts on mining profitability. In this paper, a more comprehensive block sequencing optimisation model is developed for the open-pit mines. In the model, material characteristics of blocks, grade control, excavator and block sequencing are investigated and integrated to maximise the short-term benefit of mining. Several case studies are modeled and solved by CPLEX MIP and CP engines. Numerical investigations are presented to illustrate and validate the proposed methodology.

Using qualitative mixed methods to study small health care organizations while maximising trustworthiness and authenticity

Background The primary health care sector delivers the majority of health care in western countries through small, community-based organizations. However, research into these healthcare organizations is limited by the time constraints and pressure facing them, and the concern by staff that research is peripheral to their work. We developed Q-RARA—Qualitative Rapid Appraisal, Rigorous Analysis—to study small, primary health care organizations in a way that is efficient, acceptable to participants and methodologically rigorous. Methods Q-RARA comprises a site visit, semi-structured interviews, structured and unstructured observations, photographs, floor plans, and social scanning data. Data were collected over the course of one day per site and the qualitative analysis was integrated and iterative. Results We found Q-RARA to be acceptable to participants and effective in collecting data on organizational function in multiple sites without disrupting the practice, while maintaining a balance between speed and trustworthiness. Conclusions The Q-RARA approach is capable of providing a richly textured, rigorous understanding of the processes of the primary care practice while also allowing researchers to develop an organizational perspective. For these reasons the approach is recommended for use in small-scale organizations both within and outside the primary health care sector.

Onset of transition in mixed convection of a lid-driven trapezoidal enclosure filled with water-Al2O3 nanofluid

A numerical study is carried out to investigate the transition from laminar to chaos in mixed convection heat transfer inside a lid-driven trapezoidal enclosure. In this study, the top wall is considered as isothermal cold surface, which is moving in its own plane at a constant speed, and a constant high temperature is provided at the bottom surface. The enclosure is assumed to be filled with water-Al2O3 nanofluid. The governing Navier–Stokes and thermal energy equations are expressed in non-dimensional forms and are solved using Galerkin finite element method. Attention is paid in the present study on the pure mixed convection regime at Richandson number, Ri = 1. The numerical simulations are carried out over a wide range of Reynolds (0.1 ≤ Re ≤ 103) and Grashof (0.01 ≤ Gr ≤ 106) numbers. Effects of the presence of nanofluid on the characteristics of mixed convection heat transfer are also explored. The average Nusselt numbers of the heated wall are computed to demonstrate the influence of flow parameter variations on heat transfer. The corresponding change of flow and thermal fields is visualized from the streamline and the isotherm contour plots.

A methodology for mapping Instagram hashtags

While social media research has provided detailed cumulative analyses of selected social media platforms and content, especially Twitter, newer platforms, apps, and visual content have been less extensively studied so far. This paper proposes a methodology for studying Instagram activity, building on established methods for Twitter research by initially examining hashtags, as common structural features to both platforms. In doing so, we outline methodological challenges to studying Instagram, especially in comparison to Twitter. Finally, we address critical questions around ethics and privacy for social media users and researchers alike, setting out key considerations for future social media research.

Gen Y recruitment: Understanding graduate intentions to join an organisation using the Theory of Planned Behaviour

Purpose Using the Theory of Planned Behaviour (TPB) framework, this study explored whether the standard TPB constructs explained variance in Gen Y individuals’ intentions to join their ideal organisation. Design/methodology/approach A mixed methods approach was used featuring qualitative and quantitative methods. Findings The overall TPB model accounted for a significant 51.6% of the variance in intention to join one’s ideal organisation in the next six months with the significant predictors in the model being subjective norm and perceived behaviour control but not attitude. Research limitations/implications Using graduating students from a single Australian university sample may mean that the current findings may not extend to all Gen Y individuals. The current study has demonstrated the explanatory utility of the TPB in relation to graduate Gen Y’s intention to join their ideal organisation, providing further evidence of the robustness of the TPB framework in an organisational setting. Practical implications These findings have implications for enhancing understanding of the most effective recruitment processes for Gen Y students entering the workforce. The findings could inform recruitment policies and strategies to attract Gen Y applicants. Originality/value To our knowledge this study is the first application of the TPB to this topic. The current research extends the recruitment literature with a theoretically-based investigation. Identification of factors which inform organisational recruitment strategies, allow organisations to stand out from their competitors and potentially achieve a larger application pool from which to select the best human capital and sustain competitive advantage.

Analyzing busway station potential capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.

Analysing busway station capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.