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The purpose of this study is to investigate the extent to which a sample of the Australian cybersecurity industry is impacted by burnout.

Based on the review of the literature, this research investigates the following three hypotheses. Gender will significantly predict burnout scores. Those who identify as women will score higher on average than those who identify as men (because of being in a male-dominated industry). Self-reported burnout will differ across job roles. In addition, the authors expect these relationships to hold across the three dimensions of burnout, namely, emotional exhaustion, depersonalisation and professional efficacy. Sleep quality will be associated with burnout.

Gender and job role were significant predictors of emotional exhaustion, but not depersonalisation or professional efficacy. The interaction between gender and job role was also significant. Senior managers experienced poorer quality sleep, and poorer sleep quality was associated with greater reported emotional exhaustion at work. For emotional exhaustion, female respondents who worked in security consultant roles tended to score higher than their male counterparts.

Left unaddressed, the high level of workplace burnout may add to the well-being and retention problems developing within the cybersecurity community. These results indicate that organisations should look to measure the well-being of their own cyber workforce and implement meaningful changes if they wish to keep their cyber talent and enable them to thrive at work.

This research paper is an extension of a previous paper by the same authors which is titled “Is Your CISO Burnt Out Yet”. This paper examined the demographic differences in workplace burnout among cybersecurity professionals.

The purpose of this paper is to gain insight into how management accountants can become relevant business partners out of respect for existing locally developed accounts of economic performance for decision-making.

The paper is based on qualitative semi-structured interviews with local business actors, in this case, families from seven financially successful Danish dairy farms. The casework and the analysis have been informed by pragmatic constructivism.

The local business actors do not use the official accounting system for ongoing cost-management-related decision-making. Instead, they use several epistemic methods that include locally developed decision models, experiences, rules of thumb and intuition. The farmers use these vernacular accountings to compensate for the cost management illusion that the formal accounting system tends to create. What the study suggests is that when management accountants engage as business partners, they are likely to enter a space where accounting is already present.

This paper argues that local business actors practice epistemic methods where they develop and use vernacular accountings to support their managerial practice, also in the absence of a professional management accountant. These vernacular accountings may lead the local actors into an illusion because the vernacular accountings do not necessarily have an inherent economic logic and theoretical reliability. The role of the management accountant in such a setting is hence to understand, support and advance local epistemic methods. Becoming a business partner requires a combination of management accounting analytical skills and a sense of empathy and sensitivity regarding what is already at play and how this can become an object of discussion without violating the values of the other.

The exact process of construction projects performance assessment and benchmarking still remains subjective relying on qualitative techniques, which does not allow stakeholders to address the issues and the drawbacks of their respective projects as effectively as possible for performance improvement purposes. Hence, this research aims to establish a unified project performance score (PPS) for assessing and comparing projects performance.

Data were collected from Construction Industry Institute (CII) members and through University of Wisconsin active research projects. Exploratory data analysis was done to investigate the calculated performance metrics and the collected data characteristics. Data were converted into six performance metrics which were used as the independent variables in creating the PPS model. Logistic regression model was developed to generate the unified PPS equation in order to explain the variables that significantly affect construction projects successful post-completion performance. The PPS model was then applied on the collected dataset to benchmark projects in terms of project delivery systems, compensation types and project types in order to showcase the PPS capabilities and possible applications.

The model revealed that construction cost and schedule growth are the most important metrics in assessing projects performance, while RFIs’ processing time and change orders per million dollars were the features with the least effect on the PPS value. The authors found that integrated project delivery (IPD) and target value (TV) projects outperformed all other project delivery and compensation types. While, industrial projects showed the worst performance, as compared to commercial or institutional projects.

The PPS model can be used to assess the performance of any pool of executed projects, and introducing a novel addition to the field of construction business analytics which is a supplementary tool to successful decision making and performance improvement. Additionally, the bidding selection system can be revolutionized from a cost-based to a performance based one using the PPS model to improve the outcomes of the buyout process.