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This research investigates the roles that resources, organisational structure and climate play in the performance management of National Sport Organisations (NSOs).

This qualitative study draws data from 31 interviews, five focus groups conducted amongst Botswana National Sport Organisations. To corroborate the data collected, documents from these sport organisations were content analysed.

The amount and type of resources available, the degree to which decision-making is centralised, practices formalised and roles specialised affects how NSOs implement performance management. NSOs were not implementing performance management systems and could not tell whether they were creating favourable environments to implement the practices.

Sport managers, policymakers and educators can use insights from this study to improve their practices. This study also proposes avenues for further research.

This study contributes to sport management literature on performance management, and it is original because such as study has not been conducted before.

This study aims to investigate the facilitating conditions (FCs) and how these FC affect institutional repository (IR) sustainability practices in public universities in Nigeria.

A survey research design was adopted in this study. The study population comprised 542 librarians from public universities that have IRs across Nigeria. A sample size of 230 librarians was determined using Taro Yamane’s formula. A multi-stage sampling technique was used to select the respondents in three stages, which were purposive, stratified and purposive sampling. A structured, validated questionnaire was used for data collection. Data were analyzed using descriptive and inferential (simple and multiple regression) statistics at a 5% level of significance.

The result revealed that the availability of FCs (ßeta = 0.459, t(211) = 7.719, p = 0.000) has a positive and significant influence on IR sustainability in public university libraries in Nigeria. The F-test (1, 223) value of 59.582 shows that there is sufficient evidence to substantiate the model’s usefulness in explaining IR sustainability. The R² (0.211) indicates that 21.1% of the variation in IR sustainability is explained by the availability of FCs in public university libraries in Nigeria. The finding suggests that the availability of FCs is a vital predictor of IR sustainability in public university libraries in Nigeria. The result also depicts that out of the eight parameters that measure the availability of FCs, it was current awareness of IR that had a positive and significant influence on IR sustainability.

This study concluded that ICT skills and FCs are contributory factors to IR sustainability practices by librarians in public university libraries in Nigeria. It was recommended that university administrators formulate policies that promote the sustainability of IR and provide adequate funds to support IR sustainability. Furthermore, the library management in public university libraries in Nigeria should drive content recruitment and create awareness of the IRs among students and faculty to ensure continued use.

This paper aims to explore the common ethical decision-making challenges faced by financial advisers and how they meet these challenges. The purpose is to identify successful decision-making tools used by investment advisers in doing business ethically. Additionally, the authors uncover common challenges and offer decision-making tools to provide support for supplemental ethics training in the future.

Questions were analyzed through a qualitative approach using individual interviews to examine a range of experiences and attitudes of active financial advisers. The sample was represented by 11 practicing financial advisers affiliated with US independent broker-dealers: six women and five men, each with 10 or more years of experience, ranging in age from 35 to 75. Grounded in four ethical decision-making models, this research examines individual ethical decision-making using individual (internal, personal) and organizational (external, situational) factors.

The method used uncovered struggles and revealed strategies used in making ethical decisions. Two research questions were examined: what are the common ethical decision-making challenges faced by financial advisers in the US financial industry? How do financial advisers handle ethical decision-making challenges? Four themes emerged that impacted ethical decision-making: needs of the individual, needs of others, needs of the firm and needs of the marketplace. Financial advisers identified moral obligation, self-control and consulting with others as major considerations when they contemplate difficult decisions.

A limitation of this review is its small sample size. A more robust sample size from investment advisers with a broader range of experiences could have widened the findings from the study.

Investment advisers can use the findings of this study as a tool for improving their own ethical decision-making or designing training for their employees to be better decision-makers.

The study explores the decision-making experiences of investment advisers to reveal multifaceted, often private struggles that qualitative methods can uncover. The study provides support for the development of additional training in ethical decision-making specific to investment advisers.

Indoor air quality monitoring is extremely important in urban, industrial areas. Considering the devastating effect of declining quality of air in major part of the countries like India and China, it is highly recommended to monitor the quality of air which can help people with respiratory diseases, children and elderly people to take necessary precautions and stay safe at their homes. The purpose of this study is to detect air quality and perform predictions which could be part of smart home automation with the use of newer technology.

This study proposes an Internet-of-Things (IoT)-based air quality measurement, warning and prediction system for ambient assisted living. The proposed ambient assisted living system consists of low-cost air quality sensors and ESP32 controller with new generation embedded system architecture. It can detect Indoor Air Quality parameters like CO, PM2.5, NO2, O3, NH3, temperature, pressure, humidity, etc. The low cost sensor data are calibrated using machine learning techniques for performance improvement. The system has a novel prediction model, multiheaded convolutional neural networks-gated recurrent unit which can detect next hour pollution concentration. The model uses a transfer learning (TL) approach for prediction when the system is new and less data available for prediction. Any neighboring site data can be used to transfer knowledge for early predictions for the new system. It can have a mobile-based application which can send warning notifications to users if the Indoor Air Quality parameters exceed the specified threshold values. This is all required to take necessary measures against bad air quality.

The IoT-based system has implemented the TL framework, and the results of this study showed that the system works efficiently with performance improvement of 55.42% in RMSE scores for prediction at new target system with insufficient data.

This study demonstrates the implementation of an IoT system which uses low-cost sensors and deep learning model for predicting pollution concentration. The system is tackling the issues of the low-cost sensors for better performance. The novel approach of pretrained models and TL work very well at the new system having data insufficiency issues. This study contributes significantly with the usage of low-cost sensors, open-source advanced technology and performance improvement in prediction ability at new systems. Experimental results and findings are disclosed in this study. This will help install multiple new cost-effective monitoring stations in smart city for pollution forecasting.

Meetings with colleagues are an essential activity in workplace collaboration. The iterative nature of collaborative work demands spaces that team members can access quickly and easily. Creating suitable meeting spaces will become more critical if the hybrid work model continues and the workplace environment becomes the hub for face-to-face collaborative time, learning and training. Workspace and fit-out is expensive so it is crucial that the investment in meeting spaces supports employees’ collaboration activities.

This paper presents a case study of a corporate organisation undertaken in New Zealand to investigate how employees from two business units use their workspace to collaborate within their own team and across other teams in their organisation. The study uses ethnographic techniques, including participant observation and in-depth face-to-face interviews.

The findings show that the frequency and nature of small group work in collaboration was underestimated in the initial planning of the new workspace. Although participants found the design and fit-out of the formal meeting rooms supportive of collaborative work, the meeting rooms were in high demand, and it was difficult to find a room at short notice. The breakout spaces were confusing because they lacked key design attributes identified by the participants as conducive to small group work. Design shortfalls together with fit-out features perceived as supportive of collaborative work are identified.

The research reports on employees’ perceptions and experiences across two functionally diverse business units, reflecting their different needs and concerns.