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The research essay aims to understand investor's ability to forecast having the perception of status quo and monetary loss-aversion in the situation of amygdala damages and asymmetry during decisions regarding stock's investment and use of several techniques to make efficient investment decisions based on optimal forecasting. The objectives of this study are to inquire about the irrationalities in investors at the time of stock's investment, having status quo and monetary loss-averse bias of investors at the time of amygdala damages and asymmetry and find-out the ways to deal with these situations. A qualitative research style was used for data collection for the subject study. Partially-organized discussions were arranged to get information in detail. A sample of 15 experienced stock marketers and brokers and 35 investors from the Pakistan stock exchange were selected for this study. This inquiry found the definite type of edgy and biased investor's attitude in the market and also found their solutions. This study perceptibly peaks the ways to deal with stress and biasness through optimal forecasting techniques and some other suggestions.

AbstractPrior research suggests that undertaking corporate social responsibility (CSR) activities affect firm value. We extend this line of research by considering CSR activities over a longer period (a consistent CSR behavior) and examine the impact of CSR permanency on firm value. Using a cross‐country sample of 600 top‐listed firms from four leading emerging economies, Brazil, Russia, India, and China (BRIC) over the period 2010–2018, we find that CSR permanency positively impacts firm value after controlling for various firm and country characteristics. This effect is observed more pronounced for family‐owned firms. Additional analysis reveals that permanent CSR activities in both social and environmental dimensions positively influence firm value, however, CSR permanent activities in the social dimension exert a larger impact on firm value. Our results make important contributions to theory and practice.

Abstract: Physical activity has a strong influence on mental and physical health and is essential in healthy ageing and wellbeing for the ever-growing elderly population. Wearable sensors can provide a reliable and economical measure of activities of daily living (ADLs) by capturing movements through, e.g., accelerometers and gyroscopes. This study explores the potential of using classical machine learning and deep learning approaches to classify the most common ADLs: walking, sitting, standing, and lying. We validate the results on the ADAPT dataset, the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate video labelled data recorded in a free-living environment from older adults living independently. The findings suggest that both approaches can accurately classify ADLs, showing high potential in profiling ADL patterns of the elderly population in free-living conditions. In particular, both long short-term memory (LSTM) networks and Support Vector Machines combined with ReliefF feature selection performed equally well, achieving around 97% F-score in profiling ADLs. This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors' view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.

Sustainable project management (SPM) is pivotal for enhancing sustainable project success (SPS) and transforming organizations into sustainable practices. Many prior studies empirically found that SPM is positively associated with SPS. This association can be further enhanced through sustainable leadership. However, the role of sustainable leadership as a moderator on the association between SPM and SPS has not been fully grabbed in the prior studies, especially the public sector development program (PSDP) in Pakistan remained unexplored. The study aimed to investigate the moderating role of sustainable leadership on the association between SPM and SPS in the PSDP projects in Pakistan. Using a quantitative survey-based design and the data from 285 completed PSDP projects collected through a single informant strategy, the hypothesized relationships were tested with the PLS-SEM-based hierarchical component modeling approach. The results revealed that SPM is positively associated with SPS and sustainable leadership moderates the association between SPM and SPS in this context. The study provides important insights into the emerging trend of SPM and SPS and evocatively contributes to the existing literature. The study also contributes to the practice and assists project managers, decision-makers, and policy-makers in planning and developing PSDP projects more effectively to achieve sustainable development goals (SDGs). The findings are also beneficial for other countries operating in similar circumstances.