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The current study aims to propose and empirically investigate a conceptual model of the most relevant antecedents and consequences of Corporate Social Responsibility (CSR) attribution, thus providing a practical and concise model as well as examining brand attachment as a mediator explaining the relationship between CSR attribution and its consequences.

A between-subjects experimental design was employed. The study included two experimental conditions; intrinsic and extrinsic CSR attribution and a control condition. An online self-administered survey was utilised for data collection. The sample was a convenience sample of 336 university students. Both one-way between-groups ANOVA and Partial Least Squares-Structural Equation Modelling (PLS-SEM) were utilised for hypotheses testing.

The most significant antecedents of CSR attribution in order of importance are the firm's approach to CSR communication, past corporate social performance, CSR type and the firm's call for customers' participation in its CSR. CSR attribution exerted a significant direct positive impact on brand attachment and trust. Three significant indirect consequences of CSR attribution were PWOM intention, purchase intention and brand loyalty intention. Whereas trust played a significant mediating role between CSR attribution and its three indirect consequences, brand attachment exerted significant mediation only between CSR attribution and brand loyalty intention. Brand attachment might mediate the relationship between CSR attribution and purchase intention. However, brand attachment failed to play a mediating role between CSR attribution and PWOM intention.

Several studies marginally investigated CSR attribution. Despite the vital role of CSR attribution in how consumers receive firms' CSR engagement, the availability of CSR attribution-centric studies is limited. By introducing a model of the most relevant antecedents and consequences of CSR attribution, this study aids in understanding the psychological mechanism underlying consumers' CSR attribution and provides valuable implications.

The objective of this study was to conduct a bibliometric analysis of the existing literature on organizational deviance to assess how far this concept has progressed since its introduction in the domain of organizational behavior.

This study employs bibliometric methodologies (citation analysis, co-citation analysis and co-occurrence of author keywords) using VOSviewer. The Scopus database was used, as it is the largest database of scholarly literature.

The findings indicate the character and direction of organizational research over the past two decades. Organizational deviance due to psychological contract breach, organizational deviance in the context of organizational cynicism and organizational deviance in the context of psychological capital are the three major themes in the literature on organizational deviance. In addition, the study highlights the most significant authors, journals, institutions and nations in the field of value co-creation research as well as potential future research areas in this area.

The use of a single database and the inability to contextualize the citation structure of papers revealed by the review are limitations of this study.

This study examines the structure of the literature on organizational deviance and charts the field's evolution over time.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

We examined skill building techniques and changes over the course of a semester with pre and post-test data collection after implementing experiential learning assignments.

The Schutte Self-Report Emotional Intelligence Test (SEEIT) was used to measure emotional intelligence among students who interned for a 16-week period.

We found a significant difference using a paired samples t-test in SSEIT scores between the pre (M = 126.6, SD = 4.3) and the post-internship (M = 133.8, SD = 5.7) scores. t(5) = -5.61, p = 0.002. Students had an overall increase in mean scores over the course of one semester.

This was a pilot study that we completed to determine applicability of internship and increasing emotional intelligence. Overall, we saw an increase in EI in pre and post-test comparisons. This was a pilot study, so more research is needed on this topic.

Students were placed in situations during the internship process to help facilitate real world problems and were required to apply applicable textbook knowledge, develop theory-based activities and report their findings. Students worked with various age groups and learned how to work with a variety of populations including faculty, teachers, children and parents on a regular basis and this process contributed to their experience and potentially increased emotional intelligence over a 16-week period.

This research addresses the importance of emotional intelligence (EI) in career readiness and its role in potentially mitigating burnout in psychological professions.

This is important to those in the field of psychology and child development and family studies because it addresses concerns with the shortage of skilled and prepared workers.

This paper aims to examine prospective graduate students' attitudes toward educational loan borrowing in an experimental setting.

Participants were randomly assigned to two treatment groups and one control group. Subjects in experimental group 1 received financial education: a short online course on the economic viability of getting a master's degree and how to finance it with a graduate student loan, while subjects in experimental group 2 received financial education along with information on the availability bias.

Relying on a control group in the assessment of financial literacy education intervention impacts, this research finds positive causal treatment effects on individuals’ attitudes toward debt-financed graduate education. In comparison to the control group, experimental subjects perceived the possibility of going into debt with a graduate loan to complete a master’s degree as less stressful and worrying.

This study has important educational policy implications to prevent students from stopping investing in human capital by perceiving educational loan debt as something stressful or worrying. The results can help potential (and current) grad students develop a feasible financial plan for graduate school by encouraging higher education institutions to implement educational loan information and financial education into university seminar courses for better graduate student loan decision-making.

Student attitudes toward debt have been analyzed in the context of higher education, but only a few researchers internationally have used an experimental design to study personal financial decision-making.

This systematic review aims to examine integrating innovative work behavior through transformational leadership in the Saudi healthcare sector. A thorough literature research was carried out to address this problem.

A total of 50 papers reporting research on innovative work behavior, healthcare organizational performance and transformational leadership were included in the review.

As employees are motivated and developed, their innovative work behaviors are boosted, which improves organizational performance. It can be concluded that innovative work behavior and transformational leadership are correlated. The capacity of a healthcare company to create and execute benefits to the employees may assure service delivery efficiency in employees' performance.

This systematic review will allow contemporary advancements, efficient health status monitoring and reliable solutions that aid optimal, equal and effective treatment in Saudi’s healthcare industry.

In an innovative workplace, workers may pitch fresh ideas to their management. Hence, employees see their employer as more transformational.

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 construct of psychological capital or PsyCap (consisting of the positive psychological resources of hope, self-efficacy, optimism and resilience) has been demonstrated to relate to employees’ attitudinal and behavioral outcomes. The purpose of this study is to investigate the influence of positive psychological capital on mental health, readiness for organizational change, and job insecurity in the wake of COVID-19 pandemic.

Data were collected from 567 hotel employees working in hotels in the Kingdom of Saudi Arabia. A quantitative approach was used and employees were requested to fill the questionnaires.

Results show that psychological capital enhances an employee’s mental health and readiness for the organizational change. Moreover, PsyCap is found to negatively impact the perceptions of job insecurity among hotel employees. The study has useful managerial implications for hoteliers, especially, in the wake of COVID-19 pandemic.

This is the first study of its kind to link hotel employees’ positive psychological capital with their perceptions about job insecurity and mental health. COVID-19 pandemic has hit the world fiercely and new normal expects employees to be ready to embrace changes in organizations. This study contributes to the literature on hospitality management by linking psychological capital with hotel employees’ readiness for organizational change in the context of Coronavirus.

Listening is often considered the cornerstone of the communication process, with feedback being a crucial skill for effective management. The primary objective of this article was to investigate the relationship between managers’ listening skills and feedback skills from their subordinates’ perspectives. Moreover, it explores the mediating effect of message-sending skills and the ability to deal with interference in this relationship.

This article deployed a quantitative, descriptive research design. The authors developed and distributed a self-administered questionnaire via non-probability convenience sampling, resulting in 304 useable responses.

The results of the main direct effect test (model 1) indicate that listening is positively associated with feedback. Model 2 established that message-sending skills did not directly mediate that relationship. On the other hand, the ability to deal with interference was found to mediate the relationship. Finally, model 4 showed the multi-mediating effect of message-sending skills and the ability to deal with interference in the relationship between listening and feedback.

As far as the researchers are aware, this paper is the first of its kind to show the ability to deal with interference as a mediating factor in a statistical model. Moreover, this study is the first to present a continuous intermediary role played by message-sending skills and the ability to deal with interference in the relationship between listening and feedback.

A wide gap exists between the innovation and development of self-monitoring, analysis and reporting technology (SMART) technologies and the actual adoption by older adults or those caring for them. This paper aims to increase awareness of available technologies and describes their suitability for older adults with different needs. SMART technologies are intelligent devices and systems that enable autonomous monitoring of their status, data analysis or direct feedback provision.

This is a scoping review of SMART technologies used and marketed to older adults or for providing care.

Five categories of SMART technologies were identified: (1) wearable technologies and smart tools of daily living; (2) noninvasive/unobtrusive technology (i.e. passive technologies monitoring the environment, health and behavior); (3) complex SMART systems; (4) interactive technologies; (5) assistive and rehabilitation devices. Technologies were then linked with needs related to everyday practical tasks (mainly applications supporting autonomous, independent living), social and emotional support, health monitoring/managing and compensatory assistance rehabilitation.

When developing, testing or implementing technologies for older adults, researchers should clearly identify concrete needs these technologies help meet to underscore their usefulness.

Older adults and caregivers should weigh the pros and cons of different technologies and consider the key needs of older adults before investing in any tech solution.

SMART technologies meeting older adult needs help support both independent, autonomous life for as long as possible as well as aiding in the transition to assisted or institutionalized care.

This is the first review to explicitly link existing SMART technologies with the concrete needs of older adults, serving as a useful guide for both older adults and caregivers in terms of available technology solutions.