Managing impressions during institutional change – The role of organisational accounts in legitimation

Public relations literature has only recently drawn on institutional theory to provide insights into legitimacy that go beyond strategic organisational level processes. Many of the existing crisis management studies are approached from a strategic perspective, which have limitations in terms of how organizations manage their legitimacy in relation to broader and often changing social agendas. This study focuses on how impression management is used to deal with legitimacy gaps between organizations and public expectations that draw on an institutional theory perspective. This qualitative study examines the use of organizational accounts through a lens that marries institutional theory and impression management in order to understand how organizations manage their legitimacy. This study of accounts around legitimacy concerns of corporate social responsibility matters shows that organizations relied on their own tangible technical attributes rather than shared norms of what is considered responsible when there are no hard or institutionalised laws and regulations in place around corporate social responsibility concerns. This study offers insights into public relations concerns around impression management during institutional change and in doing so extends existing public relations approaches to crisis management.

Nutritional support in chronic obstructive Pulmonary Disease (COPD) a randomised trial

Rationale Nutritional support is effective in managing malnutrition in COPD (Collins et al., 2012) leading to functional improvements (Collins et al., 2013). However, comparative trials of first line interventions are lacking. This randomised trial compared the effectiveness of individualised dietary advice by a dietitian (DA) versus oral nutritional supplements (ONS). Methods A target sample of 200 stable COPD outpatients at risk of malnutrition (‘MUST’; medium + high risk) were randomised to either a 12-week intervention of ONS (ONS: ~400 kcal/d, ~40 g/d protein) or DA with supportive written advice. The primary outcome was quality of life (QoL) measured using St George’s Respiratory Questionnaire with secondary outcomes including handgrip strength, body weight and nutritional intake. Both the change from baseline and the differences between groups was analysed using SPSS version 20. Results 84 outpatients were recruited (ONS: 41 vs. DA: 43), 72 completed the intervention (ONS: 33 vs. DA: 39). Mean BMI was 18.2 SD 1.6 kg/m2, age 72.6 SD 10 years, FEV1% predicted 36 SD 15% (severe COPD). In comparison to the DA group, the ONS group experienced significantly greater improvements in protein intakes above baseline values at both week 6 (+21.0 SEM 4.3 g/d vs. +0.52 SEM 4.3 g/d; p < 0.001) and week 12 (+19.0 SEM 5.0 g/d vs. +1.0 SEM 3.6 g/d; p = 0.033;ANOVA). QoL and secondary outcomes remained stable at 12 weeks in both groups with slight improvements in the ONS group but no differences between groups. Conclusion In outpatients at risk of malnutrition with severe COPD, nutritional support involving either ONS or DA appears to maintain in tritional status, functional capacity and QoL. However, larger trials, and earlier, multi-modal nutritional interventions for an extended duration should be explored.

Decision support for the efficient annotation of bioacoustic events

Acoustic sensors allow scientists to scale environmental monitoring over large spatiotemporal scales. The faunal vocalisations captured by these sensors can answer ecological questions, however, identifying these vocalisations within recorded audio is difficult: automatic recognition is currently intractable and manual recognition is slow and error prone. In this paper, a semi-automated approach to call recognition is presented. An automated decision support tool is tested that assists users in the manual annotation process. The respective strengths of human and computer analysis are used to complement one another. The tool recommends the species of an unknown vocalisation and thereby minimises the need for the memorization of a large corpus of vocalisations. In the case of a folksonomic tagging system, recommending species tags also minimises the proliferation of redundant tag categories. We describe two algorithms: (1) a “naïve” decision support tool (16%–64% sensitivity) with efficiency of O(n) but which becomes unscalable as more data is added and (2) a scalable alternative with 48% sensitivity and an efficiency ofO(log n). The improved algorithm was also tested in a HTML-based annotation prototype. The result of this work is a decision support tool for annotating faunal acoustic events that may be utilised by other bioacoustics projects.

An investigation of problem-solving support and relaxation motivations on e-WOM

As a consequence of greater computer-mediated consumer-to-consumer communication within the firm's marketing communications, there has been a growing need to understand these digital interactions more explicitly. That is, we still know little about the exact extrinsic and intrinsic motivations that drive electronic word-of-mouth. The purpose of the paper is to better understand why members within community-based websites develop a need to exchange and/or develop a social bond within the community. Questionnaire data were gathered from 147 members of an online beauty forum in Australia. The findings highlight that those members seeking problem-solving support in combination with elements of relaxation will be more inclined to exchange with other community members and develop a social bond within that community. Marketing managers can capitalise these findings by strengthening problem-solving support systems and creating environments where community members can also relax and unwind to increase the exchange between members and also increase the social bonds within the community.

Classification of echolocation calls from 14 species of bat by Support Vector Machines and Ensembles of Neural Networks

Calls from 14 species of bat were classified to genus and species using discriminant function analysis (DFA), support vector machines (SVM) and ensembles of neural networks (ENN). Both SVMs and ENNs outperformed DFA for every species while ENNs (mean identification rate – 97%) consistently outperformed SVMs (mean identification rate – 87%). Correct classification rates produced by the ENNs varied from 91% to 100%; calls from six species were correctly identified with 100% accuracy. Calls from the five species of Myotis, a genus whose species are considered difficult to distinguish acoustically, had correct identification rates that varied from 91 – 100%. Five parameters were most important for classifying calls correctly while seven others contributed little to classification performance.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Social network resilience following organisational change

This paper presents two key findings from a longitudinal study examining the dynamics of social networks during organisational change. One, the degree to which users seek new sources of information while adapting to the change. Two, the degree to which social networks display structural resilience when undergoing significant structural and technological change. Users reported an increase in advice ties post-implementation, however a proportionally higher increase in ties within their work group compared to the wider network was identified. The results also supported the supposition that while IT driven change may initially disrupt social networks some networks possess a high degree of resilience, with key players reasserting their original positions of influence following the initial phase of change related disruption.

Portal-based support for mental health research

This paper describes experiences with the use of the Globus toolkit and related technologies for development of a secure portal that allows nationally-distributed Australian researchers to share data and application programs. The portal allows researchers to access infrastructure that will be used to enhance understanding of the causes of schizophrenia and advance its treatment, and aims to provide access to a resource that can expand into the world’s largest on-line collaborative mental health research facility. Since access to patient data is controlled by local ethics approvals, the portal must transparently both provide and deny access to patient data in accordance with the fine-grained access permissions afforded individual researchers. Interestingly, the access protocols are able to provide researchers with hints about currently inaccessible data that may be of interest to them, providing them the impetus to gain further access permissions.

Enhancing the auditor's report : to what extent is there support for the IAASB's proposed changes?

This article outlines proposed reforms to auditor reporting currently being considered by the International Auditing and Assurance Standards Board (IAASB), and other key national and transnational standard-setters and regulatory bodies. It adds to recent academic contributions on reforming the auditor’s report by analyzing the 165 stakeholder responses to the IAASB’s 2012 Invitation to Comment: Improving the Auditor’s Report to determine levels of support for the IAASB’s proposed reforms, and the differences, if any, between the views of various respondents based on stakeholder groups (e.g. audit and assurance firms, users, preparers, regulators, etc.) and regional classifications. Guided by insights from communication theory, our results show the levels of stakeholder support for the IAASB’s proposed reforms addressing auditors’ expectations, information and communication gaps are mixed. The strongest overall support was for enhanced auditor reporting on other information attached to, or intended to be read with, the financial statements, and the least supported initiative was including additional information in the auditor’s report about the auditor’s judgements and processes. Whilst overall there is generally consensus across both stakeholder groups and regions concerning the various questions investigated, we highlight where statistically significant differences between groups do exist. Notably, North American respondents were less likely to support a number of the IAASB’s proposed reforms than their counterparts from other regions.

Leadership to support quality improvement in Vietnamese higher education

The impetus for the study reported in this paper is the Higher Education (HE) reform agenda outlined by the Vietnamese Ministry of Education and Training (MOET). The paper reports on phase one of a mixed method research; a quantitative approach using the Multifactor Leadership Questionnaire (MLQ) to investigate the Vietnamese HE leaders’ leadership styles. The MLQ survey was administered to approximately 190 senior managers in State HE institutions in Mekong Delta region in Vietnam (nine of colleges). The psychometrics of the MLQ for the Vietnamese sample confirmed the reliability and validity of the instrument with a Cronbach’s alpha of 0.779. A CFA was conducted and all factor structures were stable and consistent. The demographic variables were used to analyse patterns of leadership behaviours by the different sub-groups. The findings suggest that leaders who have different educational background and different gender in Mekong Delta region, Vietnam do not differ significantly in their perceptions about leadership factors.