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In this chapter, we consider collaborative models of engaged research in comparison to models of team science that include persons with lived experience of the topic area as team members. ‘Co-led’, ‘co-design’ and ‘co-research’ are all terms used in the literature with distinct, but not precise, definitions and approaches. These collaborative models tend to describe methods that allow those with lived experience to be treated differently than other academic members of the research team. Power imbalances between those with lived experiences and researchers persist in such models, in spite of researcher efforts. For example, persons with lived experience are often described as being compensated with gift cards which may be welcomed but can be perceived as diminishing their role and contribution. In contrast, participatory team science involves persons with lived experience as full members of the research team. In the model that we propose, power is balanced through mutual planning and consensus-based decision-making. We contend that using participatory team science advances research through egalitarian consideration of team members' perspectives of the research problem and the designs necessary to knowledge development.

The authors introduce a new construct, reputational self-awareness (RSA). RSA represents the congruence between how individuals think they are viewed by others (i.e. metaperceptions) versus how they are actually viewed (i.e. other ratings). The authors sought to demonstrate that RSA is a superior predictor of performance indices.

Personality self-ratings from 381 business students and their ratings by 966 others were collected via online surveys. Other raters rated self-raters' personalities as well as their task performance, organizational citizenship behaviors (OCBs) and counterproductive work behaviors (CWBs).

Results indicate that RSA predicts variance in performance above and beyond self-report ratings, and performance is highest when metaperceptions and other ratings of performance are aligned. These results support the use of a multi-perspective approach to personality assessment as a useful tool for coaching and career development.

The authors' results support the use of a multi-perspective approach to personality assessment as a useful tool for coaching and career development. A cross-sectional design was used in which personality and performance data were gathered from respondents, and the P 720 is a relatively new personality instrument.

RSA is a valuable tool for employee development, coaching and counseling because, as extant research and the authors' findings demonstrate, awareness of how others view and judge one, one's reputation is essential information to guide work behaviors and career success. Therefore, a key career-development goal for trainers and counselors should be to use a multi-perspective approach to maximize clients' RSA.

Use of other ratings as opposed to traditional self-rating of personality provides superior prediction of behavior and is more useful for career development.

This is the first study to demonstrate utility of RSA, i.e. that individuals who more accurately assess their personality are rated as performing better by others. The authors' results offer new insights for personality research and career development and support the use of personality assessment from multiple perspectives, thus enabling the exploration of potentially insightful research questions that cannot be examined by assessing personality from a single perspective.

High-quality nursing home (NH) care has long been a challenge within the United States. For decades, policymakers at the state and federal levels have adopted and implemented regulations to target critical components of NH care outcomes. Simultaneously, our delivery system continues to change the role of NHs in patient care. For example, more acute patients are cared for in NHs, and the Center for Medicare and Medicaid Services (CMS) has implemented value payment programs targeting NH settings. As a part of these growing pressures from the broader healthcare delivery system, the culture-change movement has emerged among NHs over the past two decades, prompting NHs to embody more person-centered care as well as promote settings which resemble someone's home, as opposed to institutionalized healthcare settings.

Researchers have linked culture change to high-quality outcomes and the ability to adapt and respond to the ever-changing pressures brought on by changes in our regulatory and delivery system. Making enduring culture change within organizations has long been a challenge and focus in NHs. Despite research suggesting that culture-change initiatives that promote greater resident-centered care are associated with several desirable patient outcomes, their adoption and implementation by NHs are resource intensive, and research has shown that NHs with high percentages of low-income residents are especially challenged to adopt these initiatives.

This chapter takes a novel approach to examine factors that impact the adoption of culture-change initiatives by assessing knowledge management and the role of knowledge management activities in promoting the adoption of innovative care delivery models among under-resourced NHs throughout the United States. Using primary data from a survey of NH administrators, we conducted logistic regression models to assess the relationship between knowledge management and the adoption of a culture-change initiative as well as whether these relationships were moderated by leadership and staffing stability. Our study found that NHs were more likely to adopt a culture-change initiative when they had more robust knowledge management activities. Moreover, knowledge management activities were particularly effective at promoting adoption in NHs that struggle with leadership and nursing staff instability. Our findings support the notion that knowledge management activities can help NHs acquire and mobilize informational resources to support the adoption of care delivery innovations, thus highlighting opportunities to more effectively target efforts to stimulate the adoption and spread of these initiatives.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

Drawing from conservation of resources (COR) and regulatory fit theories, this paper aims to propose and examine moderated mediation model of service innovative behavior among salespeople.

The hypothesized links were gauged based on time-lagged and multiple sources of data collected from salespeople and their supervisors in a large-scale multi-brand retail firm.

The hypothesized relationships were confirmed, and the moderated mediation model proposed in this paper was viable. Results suggest that person–job (P-J) fit boosts salespeople’s service innovative behavior, and intrinsic motivation (INTMOT) mediates this relationship. Promotion focus strengthens the positive influence of P-J fit on salespeople’s INTMOT. More importantly, promotion focus moderates the indirect positive link between P-J fit and service innovative behavior through INTMOT.

This research enhances the current knowledge by assessing promotion focus as a moderator of the impact of P-J fit on service innovative behavior via INTMOT among salespeople. To the best of the authors’ knowledge, there is no established research examining the abovementioned links in the sales literature.

Avoidable voluntary turnover negatively impacts an organisation’s workforce and decreases its sustainability and productivity. His Majesty’s Prison and Probation Service’s (HMPPS) leaving rates are among the highest in the public sector. The purpose of this study is, thus, to support HMPPS in improving Band 3 prison officers’ (POs) retention and in developing an effective employee retention strategy.

Grounded in retention literature, the present study uses a mixed-methods, cross-sectional, phenomenological research design. Primary data was gathered using an online qualitative survey, which was sent to POs working at a public sector prison in the Northwest of England with less than five years of work experience.

The results highlight the impact of career development and training and development due to their importance to POs in comparison to the POs’ dissatisfaction with HMPPS’ performance in both factors. Furthermore, most expectations of retention factors were only partially met, illustrating the need to reform the existing recruitment process and the translation of expectations into the reality of the role. In conclusion, HMPPS should focus attention on performance-improvement, especially in relation to career development and training and development, as well as investigating and reforming the current recruitment processes.

Recommendations to improve the retention of POs include the improved management of career plans, an increased selection of managers based on their management abilities, increasing training opportunities and equating staff's access to them, and evaluating the effect of payment boosts.

The role of POs and their professional environment has not previously been combined with contemporary retention literature. To the best of the authors’ knowledge, this research paper is the first of its kind using qualitative data to understand retention in the English and Welsh prison service.

Domestic violence is a universal social concern, and its implication on children’s mental health is a global health predicament. Although the aftereffect of domestic violence on the mental health of women is well researched, mental health disorders of children in terms of attention deficit hyperactivity disorder (ADHD), conduct disorder (CD), oppositional defiant disorder (ODD), general anxiety disorder (GAD), separation anxiety disorder (AD) and mood disorder (MD) on account of domestic violence is rarely investigated. Hence, the purpose of the study is to investigate the impact of exposure to domestic violence on children’s mental health.

To examine the correlation between domestic violence and mental health among children, in a survey of public primary schools in Ekiti State, Nigeria, the authors employed 664 pupils with simple random techniques. The Multidimensional Domestic Violence Scale assessed the participants’ exposure to domestic violence. The Child & Youth Mental Health General Screening Questionnaire was used to examine respondents’ mental health.

The results revealed a high incidence of domestic violence among children. It also showed a substantial correlation between domestic violence and the mental health of primary school pupils. Children living with domestic violence experience significantly increased rates of ADHD, ODD, AD, GAD and MD as forms of mental health disorders.

Given the unpleasantness of this social issue affecting the well-being of children globally, it is imperative to engage in intervention and prevention packages that will assist the victims, perpetrators, parents, teachers, schools and other stakeholders. Introducing counselling services into the primary school curriculum will assist victims and those at risk develop self-confidence that will enable them to report their violators. Although counselors do not diagnose, early detection of victims would assist in early intervention where counselors can use different techniques and approaches to help such victims to resolve all forms of cognitive distortions that can lead to mental health disorders. Counselling services can help in providing referral opportunities to victims or “at risk children,” rehabilitation and follow-up services for victims of domestic violence.

Government organizations should also reintroduce health-care services where clinical psychologists will be available in primary schools to provide psychological services to meet the needs of the victims.

Conclusively, the study presents evidence that children who witness domestic violence face a significant risk of developing mental health disorders. The findings highlight the potential harm that domestic violence can inflict on children’s mental well-being. Mental health conditions such as ADHD, CD, ODD, GAD, AD and MD are commonly observed in these children. It recommends establishing early intervention programs for children witnessing domestic violence in schools and communities and programs to detect and address mental health issues promptly.

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.