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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.

The purpose of this study is to understand the association between health behaviours of diet, physical activity, smoking cigarettes, alcohol consumption, safe sex and sleep quality with demographic (e.g. age, gender) and psychological (i.e. stress, self-esteem and sense of coherence) factors in Indian residential college students.

Students studying for Bachelor of Technology at residential colleges in India were invited to complete an online questionnaire regarding their health behaviours, demographics and psychological variables. Each health behaviour was regressed onto demographic and psychological factors to determine which of them were associated with performing each behaviour.

There was no clear pattern of predictors for the health behaviours overall. Self-esteem was related to healthy diet, being single was related to adequate sleep, higher parental income was related to safer sex and being older was related to more alcohol use and safer sex.

This study revealed that health education efforts may need to be designed for specific behaviours and correlates among Indian college students. Interventions regarding (1) healthy eating should target students with lower self-esteem, (2) sleep should target students in a relationship and (3) safer sex should target younger students and those from less affluent backgrounds.

This research is one of the first attempts to study the predictors of health behaviours among Indian college students. The study highlighted that psychological factors (e.g. self-esteem) and demographic factors (e.g. relationship status, parental income, age) affect different health behaviours. These findings can help health educators to design tailored interventions and aid in health education and promotion among Indian college students.

Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market research surveys. Covariate data associated with the judges are also often recorded. Such covariate data should be used in conjunction with preference data when drawing inferences about judges.

To cluster a population of judges, the population is modeled as a collection of homogeneous groups. The Plackett-Luce model for ranked data is employed to model a judge's ranked preferences within a group. A mixture of Plackett- Luce models is employed to model the population of judges, where each component in the mixture represents a group of judges.

Mixture of experts models provide a framework in which covariates are included in mixture models. Covariates are included through the mixing proportions and the component density parameters. A mixture of experts model for ranked preference data is developed by combining a mixture of experts model and a mixture of Plackett-Luce models. Particular attention is given to the manner in which covariates enter the model. The mixing proportions and group specific parameters are potentially dependent on covariates. Model selection procedures are employed to choose optimal models.

Model parameters are estimated via the ‘EMM algorithm’, a hybrid of the expectation–maximization and the minorization–maximization algorithms. Examples are provided through a menu survey and through Irish election data. Results indicate mixture modeling using covariates is insightful when examining a population of judges who express preferences.

The purposes of this paper is to segment spectators of collegiate football game using a cluster analysis and to determine differences between spectator clusters based on motivations, satisfaction, and demographic characteristics.

A survey instrument was utilized, and a total of 407 usable data were gathered through a convenience sampling method at a main campus in the Southern USA. A discriminant analysis was employed to create cluster profiles including demographic variables not previously included in the clustering procedure. Cluster analysis is a procedure used to determine best group segmentation.

Through a factor-cluster analysis, two distinct groups are identified as attendees of collegiate football games: far-away fans and seasoned sideliners. Knowing the different spectators in event attendance allows marketers of collegiate sport events to effectively target segments and attract larger numbers of visitors to each event. Although the results indicated lower satisfaction with the far-away fans cluster, they are nonetheless spending their money at these events. A concerted effort to better welcome tourists that are supporting the visiting team may help boost their image of the local community and thus increase their spending level.

The current study adds to the literature on sport event research, while providing great insight for researchers and practitioners how to segment their target market. Therefore, it is believed that the results of the present study will help future researchers and industry practitioners make use of the implications and findings to broaden their knowledge about sport marketing.

The purpose of this paper is to explore use of community treatment orders (CTOs) in adults with intellectual disability (ID) and mental health problems across England and Wales.

A web-based exploratory survey was sent to 359 consultants on the database of the Faculty of the Psychiatry of ID, Royal College of Psychiatrists who had declared ID as their main speciality. Socio-demographic details of responding consultants, clinical characteristics of adults with ID on CTO, subjective views of consultants on using CTOs in people with ID were collected and analysed.

In total, 94 consultant questionnaires were returned providing information on 115 patients detained under CTO. More than 75 per cent of the respondents had used CTO in their clinical practice. Patients subject to CTO were generally young, white males with mild ID and living in supported accommodation. CTOs were primarily used in situations of non-engagement (52.2 per cent), non-compliance with medication (47 per cent) or non-compliance with social care supports (49.6 per cent).

Responding consultants expressed concerns about encroachment of civil liberties and ethics of using CTOs in people with ID who may lack capacity and stressed that decision to use CTOs needs to be therefore done on individual basis.

This is the first national study to examine the practice of applying CTOs in adults with ID and mental disorders. Current practice is based on evidence from research done in adults with normal intelligence. Further research is needed to investigate the utility of CTOs in routine clinical practice in adults with ID and mental disorders.

Research on the demographic characteristics of top management team (TMT) on e-commerce adoption has really advanced. Although some of such studies factored location factors as e-commerce adoption drivers, rare attempts have been made to unravel if the differences in the demographic composition of TMT and the rate of adoption may be explained by the differences in the firm’s geographical location. Therefore, the purpose of this paper is to bridge this knowledge gap by proposing a framework that conceives and measures geographical location as a contextual variable between e-commerce adoption and TMT composition.

Data were generated from the opinions of owners/managers of 226 SMEs drawn purposefully from registered SMEs in five industries located in three geo-political zones of Nigeria. Two cities (a state capital and a commercial nerve centre) were studied and a four-step hierarchical regression (spanning factor-loading) was used to test the hypotheses.

Evidence from the study shows that the hypothesized relationships between demographic factors and e-commerce adoption (main/direct effects) were statistically significant (supporting H1-H4). The two moderators (physical infrastructures and industrial specialization) that explained location factors were equally statistically significant in moderating the relationship between the demographic composition of TMT and e-commerce adoption.

Sampling the opinions of SMEs in some industries of three geo-political zones of Nigeria limits the power of generalization. Therefore, extended data and measures are required to replicate the study in order to build external validity and reliability, and possibly theories. Further, some errors seem unavoidable in the course of converting the data through SPSS procedure just as all the measures used appear subjective and prone to common method bias. Other demographic and location factors not captured in the study may be handled by future studies.

The work will be of benefit to the academia and practitioners in terms of showing how location factors dictate the relationship between the demographic composition of top management and e-commerce adoption. The paper raises pointers that stimulate future research and advised policy-makers on even or near-even distribution of infrastructural facilities.

The advocacy to extend relationship marketing into the management of the exchange processes within retailing and consumer service markets has meant a growing interest in the opportunities which are offered by technology‐based systems of customer management. A prerequisite for the successful translation of the relationship marketing paradigm from organizational to retailing and consumer service markets is customer information. As the technology for collecting customer data has become more sophisticated, so marketing managers have witnessed an increasing concern among consumers about the impact of these new marketing management techniques on their private rights. Discusses different aspects of information privacy and reports an exploratory study of consumers’ different privacy thresholds. The results indicate different levels of involvement towards privacy issues, and different perceptions of the trustworthiness of service sector companies, among consumers. The implications for relationship marketing strategies are discussed.

This paper attempts to explore and identify the growing segments of online buyers of premium brands in the context of the post-pandemic market in India. The multi-dimensional trait of fashion orientation has been used as the psychographic construct for segmenting young urban consumers who shop on e-commerce platforms.

An online study across major cities resulted in a sample of 555 urban consumers of premium apparel and accessories brands. Hierarchical, two-step and k-means cluster analysis were conducted to identify diverse consumer segments and arrive at a demographic and usage-based profiling of the clusters. Furthermore, one-way analysis of variance was conducted to assess the key drivers for an online purchase among the obtained segments.

The pioneering use of fashion orientation as a base for segmentation helped identify three distinct clusters of socially conscious fashionistas, fashion involved and fashion indifferent buyers. The study identified significant differences in the demographic composition as well as their usage patterns and purchase motivations to shop online.

The study looks at an extremely important but neglected category of premium brands. The distinct clusters of premium brand buyers highlighted by the study adds theoretical value as well as managerial insights for the premium brand marketer as they seek to target consumers in Asian economies.

The study aimed to assess the relationship between emotional intelligence and work engagement among employees of automobile sectors in Chennai, Tamil Nadu, South India, and also to find out various demographic factors of subordinates who are able to engage vigorously, meaningfully and committedly on their work through their emotional intelligence.

A descriptive cross-sectional study was conducted, and 184 employees were recruited through random sampling to take part in the study. A Google Forms questionnaire consisting of the demographic questionnaire Utrecht Work Engagement Scale (UWES) and Emotional Intelligence Scale (EIS) was constructed and sent via e-mail to the employees, and the data were collected; after the data cleaning process, it was analysed through SPSS Version 20 using independent t-test, ANOVA and Pearson's correlation.

The results showed that educational qualification and income significantly influenced work engagement in all dimensions, while gender, designation and work experience partially influenced work engagement. It showed a strong correlation between work engagement and emotional intelligence.

This study assessed a small number of employees due to which the external validity reduces, and it assessed only the interplay between different dimensions of work engagement and emotional intelligence but not linked with any other mediating factors. The final sample size of the present study was relatively small due to the time constraint; hence, the study yielded less accurate results. Some linking variables, such as job security, motivation, knowledge management and transformational leadership, can be added to find out the association of emotional intelligence and work engagement and to understand how the factors influence each other.

For every output in the organisation, the work engagement or performance, there is an emotion behind each and every individual. The person cannot put his/her whole effort at work and concentrate without his/her self-awareness and management; at the same time, socialising is also very important to maintain good relationships at work; without these influences, one cannot have engagement in his/her work, which ultimately leads to  job satisfaction. It improves the strong attitude and behaviour that intend to be engaged at work.

This study would benefit in focusing more on rewards and recognition, empowering employees and building a bond between the organisation and employees in a strategic manner. The management can utilise the employee's engagement and make various financial outcomes, such as profitability and growth, increasing the share value and the turnover of the productivity. It improves the communication between business leaders and the organisation that benefits the business practices to be more effective which leads to a positive social change. Employee engagement strategies could fill the gap between employees' job involvement and the productive outcome. On the whole, employees' work engagement makes them to invest themselves wholeheartedly into cognitively, physically and emotionally on the job.

Work engagement and emotional intelligence, as well as their dimensions, illustrate a clear relationship and are also shown to be predictive of each other in the workplace.

This study aims to empirically indicate that environment-friendly products may be used as a consumption strategy for improving the environmental well-being of a sizable consumer base and show that there are great possibilities and opportunities available for companies to come up with the right marketing mix for consumers in the rural market. There is a great dearth of empirical research on consumer behavior facets on environment-friendly products for rural market in India.

Conclusive cross-sectional descriptive research design has been used to study the environmentally concerned consumer behavior (ECCB) for environment-friendly products with the help of a survey instrument relevant for empirical research. This paper adds to the existing literature by developing one model in the Indian context for the rural market. The research study used exploratory factor analysis and confirmatory factor analysis with structural equation modeling approach to analyze the collected data from consumers.

The major finding of the study is that consumers living in rural areas are aware about the environmental movement, but marketers have probably not fully explored the potential for environment-friendly products. The study strongly argues that organizations should leverage on the rural market opportunity in India. It confirms the need to tailor marketing mix for rural markets for determining behavioral dimensions of consumer decision-making.

This empirical research paper is developed and applied in the Indian context, with special reference to the rural market of the country. Results may change when applied to different rural locations in the same country and/or different countries depending on their demographic variables, psychosocial factors and socioeconomic conditions. The findings of this study need to be viewed within the context of certain limitations of location, social and economic issues. The study provides the initial base for further research on the theme, as there are no such studies available on environment-friendly products.

This research study is highly useful for the business firms deciding on marketing mix variables for environment-friendly products in rural market scenario in India, and it provides inputs for formulating major policy decisions in marketing. The study provides insights for managers, policymakers and organizations operating in rural markets and working on different facets of environmental protection issues in different forms.

It has been investigated across global markets that human activities have altered the natural ecosystem, so to make natural resources available for the future generation, there is a greater need to achieve more sustainable forms of development. The study provides insights from the rural Indian market for better adoption of environment-friendly products and will motivate marketers to explore the rural market horizon.

The study has been conducted with consumers who are residents of one small town in India. So far, no study has been conducted, and it is first such attempt to analyze the rural Indian market for environment-friendly products and consumer behavior ever since such products were launched in the country. This study provides an early glimpse into the workings of marketing practitioners who work on consumer strategy formulation and rural marketing decision-making for environment-friendly products.