A study of the informal interactions between audit committees and internal auditors in Australia

This paper finds evidence for the growing importance of informal interactions between the internal audit function and the audit committee (AC) in Australia – a relatively unexplored topic in the literature – using a survey of Chief Audit Executives (CAEs). It also describes the nature of these informal interactions. The most innovative elements of this paper are the findings that certain personal characteristics of CAEs, the specific knowledge and expertise of the AC chair, as well as some of the AC chair’s personal characteristics are associated with the existence (and increase) of informal interactions.

Informal interactions between audit committees and internal audit functions : exploratory evidence and directions for future research

Purpose – This paper aims to recognise the importance of informal processes within corporate governance and complement existing research in this area by investigating factors associated with the existence of informal interactions between audit committees and internal audit functions and in providing directions for future research. Design/methodology/approach – To examine the existence and drivers of informal interactions between audit committees and internal audit functions, this paper relies on a questionnaire survey of chief audit executives (CAEs) in the UK from listed and non-listed, as well as financial and non-financial, companies. While prior qualitative research suggests that informal interactions do take place, most of the evidence is based on particular organisational setting or on a very small range of interviews. The use of a questionnaire enabled the examination of the existence of internal interactions across a relatively larger number of entities. Findings – The paper finds evidence of audit committees and internal audit functions engaging in informal interactions in addition to formal pre-scheduled regular meetings. Informal interactions complement formal meetings with the audit committee and as such represent additional opportunities for the audit committees to monitor internal audit functions. Audit committees’ informal interactions are significantly and positively associated with audit committee independence, audit chair’s knowledge and experience, and internal audit quality. Originality/value – The results demonstrate the importance of the background of the audit committee chair for the effectiveness of the governance process. This is possibly the first paper to examine the relationship between audit committee quality and internal audit, on the existence and driver of informal interactions. Policy makers should recognize that in addition to formal mechanisms, informal processes, such as communication outside of formal pre-scheduled meetings, play a significant role in corporate governance.

Understanding Formal and Informal Governance on Infrastructure Projects - Literature Review [industry report]

In Australia, collaborative contracts have been increasingly used to govern infrastructure projects. These contracts combine formal and informal mechanisms to manage project delivery. Formal mechanisms (e.g. financial risk sharing) are specified in the contract, while informal mechanisms (e.g. integrated team) are not. The paper reports on a literature review to operationalise the concepts of formal and informal governance, as the literature contains a multiplicity of, often un-testable, definitions. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operatinalise formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. Formal governance mechanisms were found to be usefully broken down into four measurable categories: (1) target cost arrangement (2) financial risk and reward sharing regime (3) transparent financials and (4) collaborative multi-party agreement Informal governance mechanisms were found to be usefully broken down into three measurable categories: (1) leadership structure (2) integrated team (3) joint management system We expect these categories to effectively capture the key governance drivers of outcomes on infrastructure projects. These categories will be further refined and broken down into individual governance mechanisms for assessment through a large-scale Australian survey planned for late 2012. These individual mechanisms will feature in the questionnaire that QUT will deliver to AAA in October 2012.

Inference and hypothesis in ethnographic studies

This chapter explores the possibility and exigencies of employing hypotheses, or educated guesses, as the basis for ethnographic research design. The authors’ goal is to examine whether using hypotheses might provide a path to resolve some of the challenges to knowledge claims produced by ethnographic studies. Through resolution of the putative division between qualitative and quantitative research traditions , it is argued that hypotheses can serve as inferential warrants in qualitative and ethnographic studies.

Exploiting inference from semantic annotations for information retrieval

The increasing amount of information that is annotated against standardised semantic resources offers opportunities to incorporate sophisticated levels of reasoning, or inference, into the retrieval process. In this position paper, we reflect on the need to incorporate semantic inference into retrieval (in particular for medical information retrieval) as well as previous attempts that have been made so far with mixed success. Medical information retrieval is a fertile ground for testing inference mechanisms to augment retrieval. The medical domain offers a plethora of carefully curated, structured, semantic resources, along with well established entity extraction and linking tools, and search topics that intuitively require a number of different inferential processes (e.g., conceptual similarity, conceptual implication, etc.). We argue that integrating semantic inference in information retrieval has the potential to uncover a large amount of information that otherwise would be inaccessible; but inference is also risky and, if not used cautiously, can harm retrieval.

Strong inference in functional neuroimaging

A recurring question for cognitive science is whether functional neuroimaging data can provide evidence for or against psychological theories. As posed, the question reflects an adherence to a popular scientific method known as 'strong inference'. The method entails constructing multiple hypotheses (Hs) and designing experiments so that alternative possible outcomes will refute at least one (i.e., 'falsify' it). In this article, after first delineating some well-documented limitations of strong inference, I provide examples of functional neuroimaging data being used to test Hs from rival modular information-processing models of spoken word production. 'Strong inference' for neuroimaging involves first establishing a systematic mapping of 'processes to processors' for a common modular architecture. Alternate Hs are then constructed from psychological theories that attribute the outcome of manipulating an experimental factor to two or more distinct processing stages within this architecture. Hs are then refutable by a finding of activity differentiated spatially and chronometrically by experimental condition. When employed in this manner, the data offered by functional neuroimaging may be more useful for adjudicating between accounts of processing loci than behavioural measures.

Designing informal learning experiences for early career academics using a knowledge ecosystem model

This article presents a ‘knowledge ecosystem’ model of how early career academics experience using information to learn while building their social networks for developmental purposes. Developed using grounded theory methodology, the model offers a way of conceptualising how to empower early career academics through 1) agency (individual and relational) and 2) facilitation of personalised informal learning (design of physical and virtual systems and environments) in spaces where developmental relationships are formed including programs, courses, events, community, home and social media. It is suggested that the knowledge ecosystem model is suitable for use in designing informal learning experiences for early career academics.

Sharing social space with strangers: Setting, signalling and policing informal rules of driving etiquette

Recent research suggests that aggressive driving may be influenced by driver perceptions of their interactions with other drivers in terms of ‘right’ or ‘wrong’ behaviour. Drivers appear to take a moral standpoint on ‘right’ or ‘wrong’ driving behaviour. However, ‘right’ or ‘wrong’ in the context of road use is not defined solely by legislation, but includes informal rules that are sometimes termed ‘driving etiquette’. Driving etiquette has implications for road safety and public safety since breaches of both formal and informal rules may result in moral judgement of others and subsequent behaviours designed to punish the ‘offender’ or ‘teach them a lesson’. This paper outlines qualitative research that was undertaken with drivers to explore their understanding of driving etiquette and how they reacted to other drivers’ observance or violation of their understanding. The aim was to develop an explanatory framework within which the relationships between driving etiquette and aggressive driving could be understood, specifically moral judgement of other drivers and punishment of their transgression of driving etiquette. Thematic analysis of focus groups (n=10) generated three main themes: (1) courtesy and reciprocity, and the notion of two-way responsibility, with examples of how expectations of courteous behaviour vary according to the traffic interaction; (2) acknowledgement and shared social experience: ‘giving the wave’; and (3) responses to breaches of the expectations/informal rules. The themes are discussed in terms of their roles in an explanatory framework of the informal rules of etiquette and how interactions between drivers can reinforce or weaken a driver’s understanding of driver etiquette and potentially lead to driving aggression.

Human mating in the informal market for sperm donation: Preferences and decision making

Choosing a mate is one of the largest (economic) decisions humans make. This thesis investigates this large scale decision and how the process is changing with the advent of the internet and the growing market for online informal sperm donation. This research identifies individual factors that influence female mating preferences. It explores the roles of behavioural traits and physical appearance, preferences for homogamy and hypergamy, and personality, and how these impact the decision to choose a donor. Overall, this thesis makes contributions to both the literature on human behaviour, and that on decision-making in extreme and highly important situations.

On the axiomatic approach to the maximum entropy principle of inference

Recent axiomatic derivations of the maximum entropy principle from consistency conditions are critically examined. We show that proper application of consistency conditions alone allows a wider class of functionals, essentially of the form ∝ dx p(x)[p(x)/g(x)] s , for some real numbers, to be used for inductive inference and the commonly used form − ∝ dx p(x)ln[p(x)/g(x)] is only a particular case. The role of the prior densityg(x) is clarified. It is possible to regard it as a geometric factor, describing the coordinate system used and it does not represent information of the same kind as obtained by measurements on the system in the form of expectation values.

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.

Turnover intentions of employees with informal eldercare responsibilities: The role of core self-evaluations and supervisor support

As longevity increases, so does the need for care of older relatives by working family members. This research examined the interactive effect of core self-evaluations and supervisor support on turnover intentions in two samples of employees with informal caregiving responsibilities. Data were obtained from 57 employees from Australia (Study 1) and 66 employees from the United States and India (Study 2). Results of Study 1 revealed a resource compensation effect, that is, an inverse relationship between core self-evaluations and turnover intentions when supervisor care support was low. Results of Study 2 extended these findings by demonstrating resource boosting effects. Specifically, there was an inverse relationship between core self-evaluations and subsequent turnover intentions for those with high supervisor work and care support. In addition, employees' satisfaction and emotional exhaustion from their work mediated the inverse relationship between core self-evaluations and subsequent turnover intentions when supervisor work support and care support were high. Overall, these findings highlight the importance of employee- and supervisor-focused intervention strategies in organizations to support informal caregivers.

Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering

The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.