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Provides a brief history of employment law in relation to sexual orientation discrimination. Outlines current legislation before considering the case of the military. Provides examples of conflicting application of law in different states. Considers the problems of those who suffer from AIDS. Concludes that legal protection is unlikely whilst public perception remains against such lifestyles and pressure from religious and moral leaders remains strong.

The boiler pressure parts are a major asset of a power station, and the maintenance cost is often accountable for a huge portion of the annual budget. In the power generation industry, the outage costs due to loss of production, both planned or forced, are very significant and thus it is of interest to seek for a meaningful approach to the management of boiler pressure parts maintenance such that the enterprise performance is optimised. This paper aims to do this.

This paper proposes a framework that introduces the division of the enterprise objectives into the three decision dimensions. The framework is applied to the case of power station boiler pressure parts maintenance to optimise maintenance outages decisions for Loy Yang, a power station in Victoria, Australia.

The study finds that the framework provides meaningful approach to optimising maintenance decisions and is generic for application in different cases.

The paper provides a new insight and integrated approach to optimising asset maintenance for an enterprise with the use of a case study.

The purpose of this paper is to investigate what factors can affect individuals’ knowledge sharing on social media from the perspectives of personality traits and social capital.

A theoretical model was developed with reference to the personality traits theory and the social capital theory. Accordingly, a questionnaire was designed to collect the individuals’ ideas on knowledge sharing on social media and further test the model. The questionnaire was then distributed to two LINE groups. Finally, the collected data were analyzed using the partial least squares (PLS) approach.

Personality traits not only directly affect knowledge sharing, but also indirectly influence it via social capital. Of all personality traits, agreeableness, openness and extraversion directly and indirectly influence knowledge sharing.

Knowledge sharing is undertaken by individuals and social groups. It starts with individuals and then diffuses to other members of a group.

Group managers have to identify the members who are friendly, open-minded or extroverted and encourage them to act as the bellwethers for knowledge sharing under an effective regulatory regime, through which intra-group knowledge sharing can be promoted.

This study introduces a new model to explore knowledge sharing on social media from individual and social perspectives. It illustrates what will affect individuals’ knowledge sharing on social media.

This study aims to examine the relationship of work–family demands with employees’ well-being, and the role of management/supervisory support in this relationship. The following hypotheses were proposed: work–family demands would be negatively related to employees’ well-being; management/supervisory support would moderate the relationship of work–family demands with employees’ well-being.

The researchers used 250 working female academicians as respondents, working in the research universities in Kuala Lumpur, Malaysia. Their ages ranged from 30 to 60 years.

The findings of the present study proved that the work–family demands were negatively associated with employees’ well-being. Results also revealed that management and supervisory support strengthens the relationship between work–family demands and employees’ well-being. Thus, management and supervisory support plays an important role in balancing work demands and family roles and also in increasing working female academicians’ well-being.

In this study, management and supervisory support was found to be directly related to well-being, including life satisfaction, job satisfaction and family satisfaction. However, the direct relationship between management/supervisory support and well-being was positive and significant. This study also found that management/supervisor support reduced work–family conflict and work–family demands. Also, supervisory and management support was found to have a significant and positive relationship with well-being. Given these findings, supervisory and management support plays a very important role as a moderator of work–family demands and in developing and improving well-being in working women.

This paper aims to empirically investigate the role of product positioning in the launch of food and drink products using a large dataset of new product development by food companies in Australia (AU) and New Zealand (NZ). As such, positioning through credence attribute claims can be associated with product launch strategies, including brand-new products, expansion of product ranges, new packaging and relaunch, as a response to market demand.

Text analysis was used to investigate the descriptions of food claims using Structured Query Language, providing a word list of food claims and further filtered and categorised into groups of claims. Multinomial regression models were then employed to analyse the association between product launch strategies and food claims adopted by firms.

The results of this paper provide evidence that positioning via food claims play an important role in product launch strategies in both AU and NZ. Types of food claims matter differently to firms' product launch decisions in the two markets. The “green” and “ethical” attributes are found to be associated with new launches in NZ but not in AU. Claims that are seen as most important for consumers are more likely to be engendered for the more costly launch approach.

This study is amongst the first studies that addresses the role of positioning in product launch strategies of food companies. The results and findings provide insights into the different prevailing credence attributes from the firm side and help policymakers to regulate the delivery of information about credence attributes to consumers.

This paper aims to investigate the extent international and domestic guidelines have influenced the content of corporate environmental reporting (CER) in the context of China’s radical institutional transition from bureaucratic secrecy to openness, marked by the first nationwide guidelines on Open Government Information (OGI) and Open Environment Information (OEI), effective in 2008.

The study develops a research instrument that captures international and Chinese national guidelines pertaining to environmental information disclosure. This instrument is used to analyse 471 reports of leading 100 listed Chinese companies for the critical period between 2006 and 2010. Chi-square test statistics are used to analyse the significance of differences in reporting items supported by Chinese guidelines versus those supported by international reporting guidelines only.

Partial convergence in climate-change reporting co-exists with divergent China specific interpretation of climate change. The coercive institutional influences of the Chinese government’s guidance in OGI and OEI led to the rapid growth of CER in 2008 compared to 2006, despite compliance being voluntary.

The study is innovative in explicitly measuring any changes in reporting relative to the potential for additional reporting. Such a method more accurately evaluates the effect of institutional influences on reporting. The study provides a fresh profile of the content and the reporting medium of CER, with a particular focus on climate change in the Chinese context. The findings highlight research into CER based on annual reports risks results being incomplete and misleading. Findings have practical implications for policy makers in other emerging economies.

This paper aims to propose a three-phase interpenetrating continua model for the numerical simulation of water waves and porous structure interaction.

In contrast with one-fluid formulation or multi-component methods, each phase has its own characteristics, density, velocity, etc., and each point is occupied by all phases. First, the porous structure is modelled as a phase of continua with a penalty force adding on the momentum equation, so the conservation of mass is guaranteed without source terms. Second, the adaptive unstructured mesh modelling with P1DG-P1 elements is used here to decrease the total number of degree of freedom maintaining the same order of accuracy.

Several benchmark problems are used to validate the model, which includes the Darcy flow, classical collapse of water column and water column with a porous structure. The interpenetrating continua model is a suitable approach for water wave and porous structure interaction problem.

The interpenetrating continua model is first applied for the water wave and porous structure interaction problem. First, the structure is modelled as phase of non-viscous fluid with penalty force, so the break of the porous structure, porosity changes can be easily embedded for further complex studies. Second, the mass conservation of fluids is automatically satisfied without special treatment. Finally, adaptive anisotropic mesh in space is employed to reduce the computational cost.

China is conducting an open market policy and Chinese firms are seeking independent audit services. As a result, the Chinese accounting profession is expanding at a tremendous speed, and has played an important role in economic reform. However, Chinese auditing operates in a very different environment from those experienced in Western countries. Consequently, there is considerable concern about auditor independence in China. The purpose of this paper is to examine some reasons for a lack of independence in the Chinese audit profession. We critically review empirical evidence regarding auditor practice in China. We then make some suggestions that might improve auditor independence.

This study aims to propose a novel method based on model learning with sparsity inducing norms for estimating dynamic gravity terms of the serial manipulators. This method is realized by operating the robot, acquiring data and filtering the features in signal acquisition to adapt to the dynamic gravity parameters.

The core principle of the method is to analyze the dictionary composition of the basis function of the model based on the dynamic equation and the Jacobian matrix of an arm. According to the structure of the basis function and the sparsity of the features, combined with joint-angle and driving-torque data acquisition, the effective features of dynamic gravity parameters are screened out using L1-norm optimization and learning algorithms.

The theoretical analysis revealed that training data obtained based on joint angles and driving torques could rapidly update dynamic gravity parameters. The simulation experiment was carried out by using the publicly available robot model and compared with the previous disassembly method to evaluate the feasibility and performance. The real 7-degree of freedom (DOF) industrial manipulator was used to further discuss the effects of the feature selection. The results show that this estimation method can be fully operational and efficient in industrial applications.

This approach is applicable to most serial robots with multi-DOF and the dynamic gravity parameters of the robot are estimated through learning and optimization. The method does not require prior knowledge of the robot arm structure and only requires joint-angle and driving-torque data acquisition under low-speed motion. Furthermore, as it is a data-driven-based method, it can be applied to gravity parameters updating.

Different from previous general robot dynamic modelling methods, the sparsity of the analytical form of dynamic equations was exploited and model learning was formulated as a convex optimization problem to achieve effective gravity parameters screening. The novelty of this estimation approach is that the method does not only require any prior knowledge but also does not require a specifically designed trajectory. Thus, this method can avoid the laborious work of parameter calibration and the induced modelling errors. By using a data-driven learning approach, the new parameter updating process can be completed conveniently when the robot carries additional mass or the end-effector changes for different tasks.