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This paper seeks to provide a view on the relevance of spirituality to leadership at various levels and areas of the practice of psychiatry.
Abstract
Purpose
This paper seeks to provide a view on the relevance of spirituality to leadership at various levels and areas of the practice of psychiatry.
Design/methodology/approach
The paper provides a background and discussion on the relevance of spirituality to leadership at various levels and areas of the practice of psychiatry, with particular reference to Australia.
Findings
The author argues that spirituality is relevant to leadership in educating medical undergraduates, training professional psychiatrists, conducting clinical research, delivering mental health services and removing public stigma of mental health problems.
Originality/value
The author provides the unique perspective of a medical specialist practising in different areas and levels of psychiatry on spirituality and leadership.
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Keywords
Gábor Nagy, Carol M. Megehee and Arch G. Woodside
The study here responds to the view that the crucial problem in strategic management (research) is firm heterogeneity – why firms adopt different strategies and structures, why…
Abstract
The study here responds to the view that the crucial problem in strategic management (research) is firm heterogeneity – why firms adopt different strategies and structures, why heterogeneity persists, and why competitors perform differently. The present study applies complexity theory tenets and a “neo-configurational perspective” of Misangyi et al. (2016) in proposing complex antecedent conditions affecting complex outcome conditions. Rather than examining variable directional relationships using null hypotheses statistical tests, the study examines case-based conditions using somewhat precise outcome tests (SPOT). The complex outcome conditions include firms with high financial performances in declining markets and firms with low financial performances in growing markets – the study focuses on seemingly paradoxical outcomes. The study here examines firm strategies and outcomes for separate samples of cross-sectional data of manufacturing firms with headquarters in one of two nations: Finland (n = 820) and Hungary (n = 300). The study includes examining the predictive validities of the models. The study contributes conceptual advances of complex firm orientation configurations and complex firm performance capabilities configurations as mediating conditions between firmographics, firm resources, and the two final complex outcome conditions (high performance in declining markets and low performance in growing markets). The study contributes by showing how fuzzy-logic computing with words (Zadeh, 1966) advances strategic management research toward achieving requisite variety to overcome the theory-analytic mismatch pervasive currently in the discipline (Fiss, 2007, 2011) – thus, this study is a useful step toward solving the crucial problem of how to explain firm heterogeneity.
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Helen Bishop, Michael Bradbury and Tony van Zijl
We assess the impact of NZ IAS 32 on the financial reporting of convertible financial instruments by retrospective application of the standard to a sample of New Zealand companies…
Abstract
We assess the impact of NZ IAS 32 on the financial reporting of convertible financial instruments by retrospective application of the standard to a sample of New Zealand companies over the period 1988 ‐ 2003. NZ IAS 32 has a broader definition of liabilities than does the corresponding current standard (FRS‐31) and it does not permit convertibles to be reported under headings that are intermediate to debt and equity. The results of the study indicate that in comparison with the reported financial position and performance, the reporting of convertibles in accordance with NZ IAS 32 would result in higher amounts for liabilities and higher interest. Thus, analysts using financial statement information to assess risk of financial distress will need to revise the critical values of commonly used measures of risk and performance when companies report under NZ IAS
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Johnny Kwok Wai Wong, Mojtaba Maghrebi, Alireza Ahmadian Fard Fini, Mohammad Amin Alizadeh Golestani, Mahdi Ahmadnia and Michael Er
Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes…
Abstract
Purpose
Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.
Design/methodology/approach
To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.
Findings
The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.
Originality/value
The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.
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