Quality Assurance Driving Factors as Antecedents of Knowledge Management: a Stakeholder-Focussed Perspective in Higher Education

Similar to many other types of organisations, the successful development of higher education institutions generally depends on proactive multi-stakeholder management strategy. As a social responsibility of universities, quality assurance (QA) of higher education is already an established research domain. However, the issues that serve as driving factors in higher education’s quality are acknowledged in this vast knowledge stream in a dispersed way. An objective of this paper is to provide a quick snapshot of the major QA driving factors in higher education. Another objective here is to discuss the significance of these existing QA driving factors in higher education as prospective antecedents of knowledge management among the key stakeholders in the higher education sector and beyond. An inductive constructivist approach is followed to review the relevant QA driving factors from the extant scholarly views. A number of relevant factors are précised from the literature that would be instrumental to uphold quality in higher education. The discussion demonstrates that these factors are also significant to transfer and share knowledge between the key stakeholders not only for universities, but also for businesses, governments and other organisational stakeholders. The paper proposes a framework of the QA drivers’ application for meaningful knowledge transfer between diverse stakeholders and clarifies the framework’s managerial implications. This conceptual framework specifies different scenarios and perspectives of QA drivers’ application in the global education sector. The academic novelty is based on the inductive approach applied in the paper. QA practitioners will be able to follow these factors as steering phenomena to effectively assure quality, in relation to their multi-stakeholder relationships in higher education and beyond

Carcass persistence and detectability : reducing the uncertainty surrounding wildlife-vehicle collision surveys

Carcass persistence time and detectability are two main sources of uncertainty on roadkill surveys. In this study, we evaluate the influence of these uncertainties on roadkill surveys and estimates. To estimate carcass persistence time, three observers (including the driver) surveyed 114km by car on a monthly basis for two years, searching for wildlife-vehicle collisions (WVC). Each survey consisted of five consecutive days. To estimate carcass detectability, we randomly selected stretches of 500m to be also surveyed on foot by two other observers (total 292 walked stretches, 146 km walked). We expected that body size of the carcass, road type, presence of scavengers and weather conditions to be the main drivers influencing the carcass persistence times, but their relative importance was unknown. We also expected detectability to be highly dependent on body size. Overall, we recorded low median persistence times (one day) and low detectability (<10%) for all vertebrates. The results indicate that body size and landscape cover (as a surrogate of scavengers' presence) are the major drivers of carcass persistence. Detectability was lower for animals with body mass less than 100g when compared to carcass with higher body mass. We estimated that our recorded mortality rates underestimated actual values of mortality by 2±10 fold. Although persistence times were similar to previous studies, the detectability rates here described are very different from previous studies. The results suggest that detectability is the main source of bias across WVC studies. Therefore, more than persistence times, studies should carefully account for differing detectability when comparing WVC studies