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This study aims to investigate the fit of a promotion (prevention) focus with malicious (benign) envy and how this fit influences positive and negative behaviours, depending on the context.

Four empirical studies (two laboratory and two online experiments) were used to test key hypotheses. Study 1 manipulated regulatory focus and envy in a job application setting with university students. Study 2 engaged similar manipulations in a social media setting. Studies 3 and 4 extended the regulatory focus and envy manipulations to the general population in pay-what-you-want (PWYW) and pay-it-forward (PIF) restaurant contexts.

The findings showed that a promotion (prevention) focus fits with the emotion of malicious (benign) envy. In the social media context, promotion and prevention foci demonstrated negative behaviour, including unfollowing the envied person, when combined with malicious and benign envy. In the PWYW and PIF contexts, combining envy with a specific type of regulatory focus encouraged both positive and negative behaviours through influencing payments.

Future research could validate and extend this study’s findings with different product/service categories, cross-cultural samples and research methods such as field experiments.

The four studies’ findings will assist managers in formulating marketing strategies to enhance their positioning of target products/services, possibly leading to higher prices for PWYW and PIF businesses.

The conceptual model is novel as, to the best of the authors’ knowledge, no prior research has proposed and tested the fit between envy type and regulatory foci.

The purpose of this study is to develop an efficient prediction model using vital signs and standard medical score systems, which predicts the clinical severity level of the patient in advance based on the quick sequential organ failure assessment (qSOFA) medical score method.

To predict the clinical severity level of the patient in advance, the authors have formulated a training dataset that is constructed based on the qSOFA medical score method. Further, along with the multiple vital signs, different standard medical scores and their correlation features are used to build and improve the accuracy of the prediction model. It is made sure that the constructed training set is suitable for the severity level prediction because the formulated dataset has different clusters each corresponding to different severity levels according to qSOFA score.

From the experimental result, it is found that the inclusion of the standard medical scores and their correlation along with multiple vital signs improves the accuracy of the clinical severity level prediction model. In addition, the authors showed that the training dataset formulated from the temporal data (which includes vital signs and medical scores) based on the qSOFA medical scoring system has the clusters which correspond to each severity level in qSOFA score. Finally, it is found that RAndom k-labELsets multi-label classification performs better prediction of severity level compared to neural network-based multi-label classification.

This paper helps in identifying patient' clinical status.

Najib Mahfuz is the first Arab‐language author to win the Nobel Prize in literature. Born in 1911 the son of a middle‐class Jamaliyah merchant, he became the most popular novelist in Egypt and the Arab countries.

The purpose of this paper is to examine whether the impact of persistent racial bias, discrimination and racial violence is facilitated by otherwise well-intentioned individuals who fail to act or intercede. Utilizing the aversive racism framework, the need to move beyond awareness raising to facilitate behavioral changes is discussed. Examining the unique lens provided by the aversive racism framework and existing research, the bystander effect provides important insights on recent acts of racial violence such as the murder of Mr. George Floyd. Some promise is shown by the work on effective bystander behavior training and highlights the need for shared responsibility in preventing the outcomes of racial violence and discrimination to create meaningful and long-lasting social change.

This paper uses literature based on the aversive racism framework together with the literature on the bystander effect to understand the factors, conditions and consequences for lack of intervention when the victim is African American. This paper also provides evidence and theory-based recommendations for strategies to change passive bystanders into active allies.

The use of the aversive racism framework provides a powerful lens to help explain the inconsistencies in the bystander effect based on the race of the victim. The implications for intervention models point to the need for behavioral and competency-based approaches that have been shown to provide meaningful change.

Several different approaches to address incidents of racial aggression and violence have been developed in the past. However, given the principles of aversive racism, a unique approach that considers the inconsistencies between self-perceptions and actions is needed. This sets a new agenda for future research and meaningful behavioral intervention programs that seek to equip bystanders to intercede in the future.

The need to address and provide effective strategies to reduce the incidence of racial aggression and violence have wide-ranging benefits for individuals, communities and society.

By connecting the aversive racism framework to the bystander effect, the need for different models for developing responsive and active bystanders can be more effectively outlined.

The purpose of this paper is to analyze the relationship between the factors influencing investors sentiment and investment decision-making (DM) of the individual investors. This paper proposes a unique conceptual framework that incorporates the herding, market and awareness factors that are leading to investor sentiment (IS) and decision-making process of the individual investors.

This study has conducted a questionnaire-based survey to collect data from 875 individual investors through the convenience sampling method. Structural equation modeling was used to evaluate the relationship between factors, namely, market effect, herd behavior, media, social interaction and advocate recommendation that influences IS and DM.

The present study found that market effect and herding are the most significantly influencing factors of investors sentiment. Among the sources of awareness, the internet has the lowest influence when compared to media, social interaction and advocate recommendation.

This study will help individual investors to avoid the problems faced while making an investment decision. The study could help investors to select a suitable investment aid and avoid repeating expensive errors, which arise due to investors’ sentiment. It is recommended to increase the awareness regarding investors’ sentiment among individuals, so as to increase their understanding about the financial settings and to make them confident while investing. The present study also sheds light upon the behavior of Indian individual investors so that policymakers can take appropriate measures to provide the proper guidance. Policymakers can conduct awareness campaigns to increase investors’ knowledge on the market condition and to enhance proper investment DM among them.

To best of the authors’ knowledge, previous studies have focused on limited factors at a time. The present study has investigated how factors influencing investors sentiment, namely, market factors (MF), herding as well as awareness would influence investment DM among individual investors in India. The influence of these factors has never been studied simultaneously in the context of Indian individual investors’ DM.