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The Mary Marlborough Disability Service, a specialist NHS unit providing non‐acute support which enables people with physical disabilities to lead independent lives, established an inter‐disciplinary team which addresses any problem of relevance to an individual which might affect their daily existence, social life, work, education or leisure pursuits. Identifies three areas of change: the style of service; its effectiveness; its efficiency. Finds, although the unit perceived itself to be working as a team, there were major operational difficulties which led to lack of cohesion and communication. As the unit was resistant to change, a clinical co‐ordinator experienced in the field of disability was seconded to the unit to guide the necessary changes, and a number of lessons were learned.

Despite popular portrayals of women's current success in public accounting, labour force statistics indicate that few women actually advance to partnership level positions. Accounting research on the scarcity of female partners tends to approach this issue from a person‐centred perspective and to focus on the characteristics of women as an explanation for their occupational status. Demonstrates that a situation‐centred perspective provides a useful contribution in understanding the scarcity of women partners. The findings are based on a survey of 188 male and 184 female accountants.

The purpose of this research is to investigate the implementation of green supply chain management (GSCM) practices and its impact on corporate performance (CP). The research in particular examines the results of implementing a set of GSCM practices on different dimensions of the CP.

This study, being the first of its kind in the Middle East, developed a research model to test the relationship between four main GSCM practices namely, eco-design, green purchasing, environmental cooperation and reverse logistics, and four dimensions of CP: operational performance, environmental performance, economic performance and social performance, while controlling three main variables (firm size, firm age and environment management system certification). Statistical analyses were based on the data collected, through survey questionnaires, from 117 firms in the manufacturing industry in the UAE. Reliability and validity of the research model were tested by the commonly accepted statistical tools. To test the hypotheses relating implementation of GSCM practice and CP, multiple regression analysis was used.

The finding of the study was that GSCM practices impact the CP dimensions differently. While none of the four GSCM practices were found to have any impact on the environmental performance, green purchasing and environmental cooperation were found to have a significant impact on the operational performance. The study found that only green purchasing plays a role in improving the economic performance, while only reverse logistics practices were found to impact the social performance of the firm positively.

Research on GSCM is still in the nascent stage. Further refinement of the survey to differentiate between different manufacturing industries might be needed. Generalizability of the findings is also limited because of data collected from manufacturing firms in the UAE. This research provides important insights. The findings of this research are generally consistent with those of prior studies in other parts of the world. Firms in manufacturing industry in the UAE believe that GSCM practices help the company design and develop better products which, in turn, increase the company chances in selling its products in the international markets while, at same time, improving the average profit and market share. It was also found that the UAE firms believe that implementation of GSCM practices help improve the corporate image, enhance employees’ job satisfaction and improve employees’ health and safety.

Implementation of GSCM practices improves CP in different ways. Supply chain managers are required to decide on the CP dimension they want to improve and accordingly select the appropriate GSCM practices mix that leads to the desired level of improvement.

Although few earlier researches studied the impact of GSCM on CP, this study is different and makes a unique contribution by offering a holistic view of the impact of implementing four main GSCM practices on all dimensions of CP. The study offers some insights on the type of GSCM practices the firm needs to adopt to improve the targeted performance dimension.

The aim of the research was to find out a method of adaptive speed control robust against variation of selected parameters of system like moment of inertia, time constant of torque control loop or torque coefficient of the motor.

The main goal of the research was achieved due to application of artificial neural network (ANN), which was trained on line on the base of speed control error. The good results were gained by elaboration of enough fast and precise training algorithm and proper ANN structure.

The work shows a structure of artificial neural network (ANN), applied as adaptive speed controller, and presents an algorithm of ANN training. Some versions of this algorithm were analysed and verified by simulation and experimental tests.

The research should be continued to determine a final version of training algorithm and its influence on controller properties.

The elaborated adaptive controller can be easily used by applying microprocessor system available now on the market. The proposed control solution is robust against parameters variation as well as their imprecise identification. The controller has ability of self‐tuning which can have great practical advantage.

Social implications are difficult to determine.

The paper presents a new solution of adaptive speed controller, which means a new ANN structure and new training algorithm.

Aims: To produce an audit tool which incorporates patient views on the whole process of care, for use in any district. Design and methods: A steering group with multi‐professional and lay representation, from primary and secondary care, was set up to oversee the project. A representative sample of 123 women with breast cancer was identified from participating practices. Audit of care as described in general practitioner notes was combined with patient questionnaires and interviews. Results: Worthwhile information of patients' concerns and the process of care can be collected by this combined approach. A questionnaire format is suitable for many aspects; offering an interview as an alternative encourages some women to participate who would otherwise refuse. The information collected by both techniques is broadly similar, and interface issues are well covered. Conclusions: This audit tool can be used by different providers or purchasers to give comparative information that addresses both patient and professional concerns.

Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

Presents a special issue, enlisting the help of the author’s students and colleagues, focusing on age, sex, colour and disability discrimination in America. Breaks the evidence down into manageable chunks, covering: age discrimination in the workplace; discrimination against African‐Americans; sex discrimination in the workplace; same sex sexual harassment; how to investigate and prove disability discrimination; sexual harassment in the military; when the main US job‐discrimination law applies to small companies; how to investigate and prove racial discrimination; developments concerning race discrimination in the workplace; developments concerning the Equal Pay Act; developments concerning discrimination against workers with HIV or AIDS; developments concerning discrimination based on refusal of family care leave; developments concerning discrimination against gay or lesbian employees; developments concerning discrimination based on colour; how to investigate and prove discrimination concerning based on colour; developments concerning the Equal Pay Act; using statistics in employment discrimination cases; race discrimination in the workplace; developments concerning gender discrimination in the workplace; discrimination in Japanese organizations in America; discrimination in the entertainment industry; discrimination in the utility industry; understanding and effectively managing national origin discrimination; how to investigate and prove hiring discrimination based on colour; and, finally, how to investigate sexual harassment in the workplace.

Historical bazaars, a huge treasure of Iranian culture, art and economy, are places for social capital development. Un-supervised management in past decades has led to the demolition and change of historical bazaars and negligence of its different aspects. The present research aims to investigate the resilience of historical bazaars preserving their identity and different developments.

The artificial neural network (ANN) has been applied to investigate the resilience of historical bazaars. This model consists of three main networks for evaluating the resilience of historical networks in terms of adaptability, variability and reactivity.

The ANN proposed to evaluate the resilience of historic bazaars based on the mentioned factors is efficient. By calculating mean squared error (MSE), the model accuracy for evaluating adaptability, variability and reactivity were obtained at 7.62e-25, 2.91e-24 and 1.51e-24. The correlation coefficient was obtained at a significance level of 99%. This indicates the considerable effectiveness of the artificial intelligence model in modeling and predicting the qualitative properties of historical bazaars resilience.

This paper clarifies indexes and components of resilience in terms of adaptability, variability and reactivity. Then, the ANN model is obtained with the least error and very high accuracy that predict the resilience of historical bazaars.

The application of an artificial neural network (ANN) to forecast the construction duration of buildings at the predesign stage is described in this paper. A three‐layered back‐propagation (BP) network consisting of 11 input nodes has been constructed. Ten binary input nodes represent basic information on building features (i.e. building function, structural system, foundation, height, exterior finishing, quality of interior decorating, and accessibility to the site), and one real‐value input represents functional area. The input nodes are fully connected to one output node through hidden nodes. The network was implemented on a Pentium‐150 based microcomputer using a neurocomputer program written in C+ +. The Generalized Delta Rule (GDR) was used as learning algorithm. One hundred and thirty‐six buildings built during the period 1987–95 in the Greater Bangkok area were used for training and testing the network. The determination of the optimum number of hidden nodes, learning rate, and momentum were based on trial‐and‐error. The best network was found to consist of six hidden nodes, with a learning rate of 0.6, and null momentum. It was trained for 44700 epochs within 943 s such that the mean squared error (judgement) of training and test samples were reduced to 1.17 × 10−7 and 3.10 × 10−6, respectively. The network can forecast construction du‐ration at the predesign stage with an average error of 13.6%.

Explores the extent of employee surveillance in the western world and queries why the USA uses surveillance measures to a greater extent than other developed nations. Suggests that American managers choose surveillance methods which include the control of workers’ bodies in the production process. Lists the batteries of tests and monitoring to which US employees can now be subjected – including searching employee computer files, voice/e‐mail, monitoring telephone calls, drug tests, alcohol tests, criminal record checks, lie detector and handwriting tests. Notes also the companies which are opposed to worker and consumer privacy rights. Pinpoints the use of surveillance as a means to ensure that employees do not withold production. Reports that employees dislike monitoring and that it may adversely affect their performance and productivity. Argues that Americans like to address complex social problems with technological means, there are no data protection laws in the USA, and that these two factors, combined with the “employment‐at‐will” doctrine, have all contributed to make it possible (and easy) for employers to use technological surveillance of their workforce. Outlines some of the ways employers insist on the purification of workers’ bodies.