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Investor risk perception is a personalized judgement on the uncertainty of returns pertaining to a financial instrument. This study identifies key psychological and demographic factors that influence risk perception. It also unravels the complex relationship between demographic attributes and investor's risk attitude towards equity investment.

Exploratory factor analysis is used to identify factors that define investor risk perception. Multiple regression is used to assess the relationship between demographic traits and factor groups. Kruskal–Wallis test is used to ascertain whether the factors extracted differ across demographic categories. A risk perception framework based on these findings is developed to provide deeper insight.

There is evidence of the relationship and influence of demographic factors on risk propensity and behavioural bias. From this study, it is apparent that return expectation, time horizon and loss aversion, which define the risk propensity construct, vary significantly based on demographic traits. Familiarity, overconfidence, anchoring and experiential biases which define the behavioural bias construct differ across demographic categories. These factors influence the risk perception of an individual with respect to equity investments.

The reference for the framework of this study is limited as there has been no precedence of similar work in academia.

This paper establishes that information seekers make rational decisions. The paper iterates the need for portfolio managers to develop and align investment strategies after evaluation of investors' risk by including these behavioural factors, this can particularly be advantageous during extreme volatility in markets that concedes the possibility of irrational decision making.

This study highlights that regulators need to acknowledge the investor's affective, cognitive and demographic impact on equity markets and align risk control measures that are conducive to market evolution. It also creates awareness among market participants that psychological factors and behavioural biases can have an impact on investment decisions.

This is the only study that looks at a three-dimensional perspective of the investor risk perception framework. The study presents the relationship between risk propensity, behavioural bias and demographic factors in the backdrop of “information” being the mediating variable. This paper covers five characteristics of risk propensity and eight behavioural biases, such a vast coverage has not been attempted within the academic realm earlier with the aforesaid perspective.

To examine demographic factors and travel motivations among leisure tourists in Tanzania. Specifically by examining the influence of demographic factors on travel motivation among local and international leisure tourists in Tanzania.

Approach is quantitative and applied descriptive statistics, independent t-test and ANOVA.

The findings showed that age, gender and family size as demographic factors significantly influenced travel motivation among local and international leisure tourists.

Future studies to consider different approaches including collection of data during the peak season, use qualitative method and conduct studies in other parts of the country to explore demographic factors and travel motivations of tourists.

To assist tourism stakeholders in their design of promotional tools to market tourism products/services to different tourists as opposed to homogeneous marketing campaigns.

Examined the influence of demographic factors and travel motivation among local and international leisure tourists in the context of Tanzania.

This study aims to build a framework of the influencing factors of construction workers' career promotion and identifies the critical determinants so as to propose suggestions for the government and enterprises to offer construction workers a path for career promotion.

In line with the theory of human resources, such as Herzberg's two-factor theory, this study constructs a theoretical framework that affects the career promotion of construction workers. Using evidence from Guangzhou city, valid data provided by 464 workers from 50 sites were collected by a questionnaire survey, and the significance test on the influencing factors of construction workers' career promotion was taken by binary logistic regression.

The overall career development of construction workers in Guangzhou is worrying. The binary logistic regression indicates that age, working years, type of work, career development awareness, legal awareness, professional mentality, vocational psychological training and career development path are critical factors that affect construction workers' career promotion.

This study for the first time explores the career promotion of frontline construction workers. Specifically, it identifies the critical factors that affect the career promotion of workers and thus lays a foundation for further research and the promotion and continuous and healthy development of the construction industry. Thus, this study is original and has theoretical and practical significance.

To deal with highly energetic younger generation patiently, need academicians who can spread happiness while teaching/mentoring are needed. This is possible when an academician himself is a happy person. This paper aims to explore the factors that generate happiness among academicians, studies the impact of demographic variables on academicians’ happiness and examines the relationship between academicians’ happiness and their performance.

Convenience purposive sampling method was used to obtain data through self-administered survey questionnaire based on a five-point Likert scale, delineating the research purpose and assurance of confidentiality. For data analysis, statistical techniques like mean, percentage method, Levene’s test, t-test and analysis of variance were used. To study the relationship between performance and happiness, the attitude, motivation and outcome theory was applied and happiness index was developed.

After analyzing the various factors impacting academicians’ happiness, this study found that except for work–life balance, research activities and working environment, all other factors are available to academicians according to their ranked importance assigned to them. This study also obtained a happiness index using matrix and has developed an equation which can be applied to find out the relationship between happiness and performance in future.

This study has certain limitations, first, this study has been conducted on academicians working in higher education institutes situated in Delhi/NCR and thus entails a specific socio-cultural environment that may limit the potential level of generalization.

The results of this research might help institutes/higher education bodies to make rules and policies which may further augment academicians’ happiness to accomplish their desired goals.

An academician who is happy, satisfied and motivated can easily deal with today's enthusiastic younger generation and can spread happiness amongst them. so it is very much necessary for an academician to be happy and energetic all the time.

This study found the factors impacting higher education academicians’ happiness and its impact on their teaching performance.

Improving employee’s performance has always remained an area of concern in the hospitality industry where employees’ performance is related to customers’ satisfaction. The inadequacy of research work on demographics and organization variables’ influence on contextual and task performance has led to present research. Thus, the purpose of this study is to identify role of demographic and organizational variables in affecting contextual and task performance of hotel employees.

Data was collected from a sample of 350 hotel employees. The research is based on primary data and a structured questionnaire.

Task performance of employees increases with the age but contextual performance improves up to 40-50 years and then remains constant. Low salaries and job insecurity affected the performance of employees. A change of designation alone, without a corresponding increase in pay, did not enhance the performance of the employees. The type and size of the organization significantly affect job performance.

The study is a contribution to the theory and practice of employee management and improving employee’s performance. Factors affecting contextual and task performance have been identified. Future research can be conducted based on this study.

The study has highlighted the significant effect of demographic variables, organizational variables on contextual and task performance of hotel employees. The hotel industry plays an important role in economic development of a country. The study is practically helpful for hotel industry to understand what demographical and organizational variables can be considered to enhance employee’s performance.

Previous literature has lacked in identifying factors, which can affect the contextual and task performance of hotel employees. The paper is contributing to the existing body of knowledge related to employees’ performance. The managers of hotel industry can use outcome of this research to improve job performance of the employees. Findings open new avenues for future research.

This study aims to explore the risk and protective factors of abuse on older adults by family caregivers, with a special focus on the protective role of caregiver resilience in elder abuse.

This cross-sectional survey was conducted on a purposive sample of 600 family caregivers of community-dwelling older adults in Hong Kong (mean age = 71.04 and female = 67.2%). Caregivers reported in a guided interview about elder abuse behaviours, caregiver burden, care recipients’ agitated behaviours, caregiver resilience, self-efficacy, social support and basic demographic characteristics. Hierarchical linear regression analyses were conducted to examine the predictors of different forms of elder abuse.

Caregiver resilience was predictive of lower levels of verbal abuse, physical abuse, injury and financial exploitation but not potentially harmful behaviour (PHB). Social support was independent with all forms of elder abuse, while self-efficacy predicted greater physical abuse after the adjustment of confounding variables. Caregiver burden and agitated behaviours by care recipients remained as significant risk factors in the final models when protective factors were considered.

This study extends current knowledge on the protecting role of resilience in elder abuse in family caregiving. Mixed findings revealed on social support and self-efficacy also highlight the complexity of the prediction of caregiver abuse. Further research should address this area.

The findings of this study warrant the inclusion of caregiver resilience as a key component in developing interventions to prevent elder abuse. Addressing caregiver burden and agitated behaviours have the potential in preventing elder abuse.

The findings raise awareness of the importance of supporting caregivers in the community to prevent elder abuse.

Research concerning the protective factors of elder abuse is in a preliminary stage. To the best of the authors’ knowledge, this study is among the first which successfully demonstrates the protective role of resilience in caregiver abuse on older adults. The findings shed invaluable light on the design of effective interventions.

Although 76% of the population of the United Arab Emirates (UAE) is Muslim, takāful (Islamic insurance) has a much smaller share of business in the UAE than conventional insurance does. The purpose of this study is to highlight the importance of brand equity (BE), which is known as the incremental value that provides reason to buy a brand. This study provides useful insights that can help the health takāful industry to gain a feasible market share in the UAE.

This is a quantitative study in which stratified random sampling was adopted for data collection from 300 respondents through a self-administered questionnaire from August to November 2018. Underpinning the study is the theory of planned behavior (TPB) and the structural equation modeling (SEM) technique has been used to examine the impact of BE on purchase intentions (PI) through the moderating role of demographic factors such as age, income, education and religion. Three dimensions of BE, i.e. brand awareness (BAW), brand association (BAS) and perceived quality (PQ), are evaluated in terms of their significance as dimensions of BE.

The major findings of this study confirm that BE has a strong positive influence on the PIs of health takāful customers in the UAE and that all three dimensions of BE make significant contributions to the overall BE. The results show that education does moderate the relationship between BE and PI while age, income and religion do not. A new finding of this study is the nonsignificant moderating role of religion, whereby it was found that takāful products in the UAE are not limited to Muslim customers but can include potential customers who are followers of other religions.

To the best of our knowledge, the present study is the first of its kind to examine the impact of BE on the PI of health takāful customers in the UAE. The findings of the study give academia, researchers and marketers a better understanding of the importance of BE and of its vital role in promoting takāful products in the Gulf Cooperation Council (GCC) countries such as the UAE.

Stock markets are considered as the largest and most important units for the development and growth of the economy. The present study attempts to provide a comprehensive view of factors influencing investment decision making process of stock market investors. A multi group analysis of gender is also carried out on the proposed model.

The data of 402 valid responses are collected through structured questionnaires from individual investors of North India. SPSS 23 is used to do the descriptive analysis and AMOS 22 is used to establish the validity of the constructs and for hypotheses testing. For performing multi group analysis, several invariance tests have also been conducted to check the robustness of the model.

The results reveal that all the factors such as firm image, accounting information, neutral information, advocate recommendation and personal financial needs significantly influence investment decision making concluding image of the firm being the most influential factor and advocate recommendation being the least influential factor for investment decisions. No significant differences between males and females were found.

The current study suffers from the limitation of restricted geographical area of North India. Moreover, there is also a scope to incorporate more demographic factors for predicting investment decisions.

This study incorporates a range of factors which covers all the aspects of investment decision making. This study also highlights the notion of signaling theory, thus contributing to the limited literature in Indian context.

Smallholder farmers have always been profoundly the first to be impacted by climate change, and therefore, farmers understanding of climate change and accessibility to alternative adaptation strategies are crucial for reducing the effect of climate change. The purpose of this study is to assess the perception of farmers to climate change, adaptation strategies and determinants of adaptation choice in central Ethiopia.

The study used data from randomly selected 240 farm households. Descriptive statistics were used to describe farmers’ perceptions of climate change and adaptation strategies. Also, a multivariate probit model was used to identify the major factors affecting farmers’ choice of adaptation strategies to climate change in central Ethiopia.

Smallholder farmers perceive climate change in the past two decades in response; the majority (91.47%) of farmers used adaptation options. Improved crop varieties and input intensity, crop diversification, planting date adjustment, soil and water conservation activities and changing of the crop type were used as adaptation options in the study area. A few of these strategies were significantly confirmed a complementary and supplementary relationship. The study identified sex, family size, agroecology, climate information, crop-fail history and formal extension service as significant determinants for farmers’ adaptation choices as these variables significantly affected more than two farmers’ adaptation strategies simultaneously.

Farmers’ choice of adaptation was highly constrained by institutional factors and all these identified factors can be possibly addressed through a better institutional service provision system. It is, therefore, recommended that local administrators should explore the institutional service provision system for a better farm-level adaptation while considering demographic characteristics as well.

This study identified factors affecting farmers’ several adaptation strategies at a time and provides information for the policymaker to make cost-effective interventions for better farm-level adaptation practices.

Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.