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This research explored the impact that the relatively new role of the Health and Wellbeing Lead upon the health and wellbeing of children and their families at this school.

This case study took place in a primary school (children aged 4–11) in the South-West of England. Data was collected through activities with children, semi-structured interviews with senior staff and parents and a “learning walk”.

Our data suggested that this role provided compassion, unconditional positive regard and respect for parents, factors that are frequently absent from research into parent partnerships in education. The role presented as invaluable in tackling the many mental and physical challenges that parents faced in rearing their children, and in providing their children with the best possible chance of success.

This is a single Case Study and, as such, may or may not be representative of similar schools. We also question to what extent the findings demonstrated the strength of this role per se, or whether the impact could simply be the result of a uniquely caring and passionate individual.

We concluded that this was a role needed in all schools, recognising the key role that parents play in their child’s wellbeing, and the indirect impact that parent mental health can have upon their child’s success.

It is vital that this role is not used as an excuse by the government to further reduce the already denuded Social Services landscape within communities. It is also important that this responsibility does not become yet another burden added to already overstretched teaching staff.

This research presents a fresh perspective on the multiple pressures that parents face and how these can impact upon their child's education.

Given its ability to improve user interaction and labor productivity, ease human workloads and cut maintenance costs, public sectors are using AI-based robotic technology (AI-RT) at an accelerated rate. There is, however, little knowledge about the variables affecting citizens' participation when services backed by AI-RT are offered. In order to better understand the elements that influence AI-RT citizens' involvement and the moderating function of trusts in governmental organizations, this article draws on ideas from the Consumer Value Theory.

Out of 500 survey forms that were distributed to Indonesian people who had experience in using AI-RT devices in public service hall (e.g. airport’s Auto Gate), 367 returned the completed feedbacks. Data analysis used a step-by-step hierarchical moderated regression examination using SPSS 24 version.

Citizens’ involvement is positively correlated with esthetics and customization and adversely correlated with period expended using the AI-RT. Additionally, the findings imply that citizens who have greater levels of faith in governmental institutions are more likely to benefit favorably from the customization and esthetics of AI-RT.

The AI-RT must be capable of customizing the distribution of the appropriate materials to the appropriate individual at the appropriate moment, and public managers should guarantee that it is esthetically pleasing. Additionally, they ought to place a high priority on winning the trust of the populace in order to increase citizens’ involvement.

This paper was among the initial efforts that discover the determinants of citizens’ involvement in the AI-RT and the moderating effect of trusts in governmental organizations on the links between predictors and predicted variable, especially in an emerging country such as Indonesia.

This study aims to examine the effect of faultline based on job responsibility and their interaction with the incentive scheme on knowledge-sharing behavior.

This research is an experimental study with a 2 × 2 factorial design between subjects. Faultline and incentive schemes are manipulated into two groups (strong faultline–weak faultline and group incentive–individual incentives). This study involved 89 undergraduate accounting students as participants.

This research shows that a strong faultline created a strong social identity effect. Hence, the knowledge-sharing behavior among group members tends to be lower than the weak faultline. Knowledge-sharing behavior tends to be higher in group incentive schemes than individual ones. However, there is no support for interactions between incentive schemes and faultline effects on knowledge-sharing behavior. The results indicate that forming a working subgroup based on informational characteristics attributes reduces cooperative behavior and knowledge sharing between groups.

This study adds a new addition to faultline literature by examining the effect of faultline and incentive schemes on knowledge-sharing behavior based on informational characteristics attributes. Previous research on faultline and knowledge sharing was limited and primarily focused on faultlines created by demographic attributes. This study also enriches faultline literature on knowledge-sharing behavior using an experimental design.

This paper aims to provide an in-depth examination of culturally and linguistically diverse older adults’ perceptions of and experiences with the Toronto Police Service to inform the development of a training curriculum for police officers working with older persons.

A qualitative descriptive study using virtual focus groups with 26 older adults from Toronto was conducted.

Three main themes emerged: understanding intersectionality; the impact of police officer attitudes and biases; and the need for age-friendly policing. Although many older adults rely on police services to keep them safe, there is dissatisfaction with some aspects of how police interact with older adults, particularly from minority groups.

Participants were older adults from culturally, ethnically and linguistically diverse backgrounds who are not usually included in studies on improving police services.

The purpose of this paper is to explore the connection between initial public offerings (IPOs) and knowledge management (KM). Specifically, the manuscript critically examines the literature on IPOs and KM underlying how KM practices influence the IPO processes of companies.

The authors employ a systematic literature review methodology to identify and thematically investigate 21 articles published in journals by the Chartered Association of Business Schools (ranked 2, 3, 4, 4*).

This research sheds new light on the relevance of KM practices in the context of IPOs. Specifically, the authors identify four crucial aspects concerning companies that opt for an IPO: (i) reasons for IPO and the role of KM; (ii) IPO process and the role of KM; (iii) underpricing and the role of KM; (iv) post-IPO and the role of KM.

This paper shows the pivotal role of effective KM strategies in fostering a successful IPO. Additionally, it provides practical recommendations for companies seeking to effectively harness their intellectual assets during the IPO process.

This study aims to investigate the implications, risks and challenges of data privacy due to the use of immersive technology in the hospitality industry.

The authors adopt a mixed-method approach. Study 1 is a focus group. The authors then provide external and ecological validity with a field experiment conducted with 139 hotel clients at a three-star continental European hotel.

Collecting biometric data results in unbalanced privacy compared to biographic data, as it diminishes individuals’ control over their data and grants organizations absolute power. This unbalanced privacy directly influences consumers’ willingness to disclose information, affecting their choice of hotels and access to services.

Hotels should redesign their strategies to accommodate heightened privacy risks with biometric data. This can be obtained by introducing systems that foster customer confidence in data usage and facilitate customers’ willingness to disclose biometrics through immersive technology or biographic data.

This study introduces unbalanced privacy as a unique state due to sharing biometric data. The authors propose a novel doctrine, the uncontrollable privacy paradox, which is a shift from the privacy paradox. The uncontrollable privacy paradox addresses the unbalanced privacy envisaged through consumer powerlessness in data management. This research addresses the literature gap on the privacy paradox by offering a broader perspective, including business, industry and mixed reality considerations.

The purpose of this paper is to present an empirical analysis, which consists of interviews with executive trainee programs of three international companies. The results of this analysis offer answers to questions currently being discussed in the corporate social responsibility (CSR) literature, namely, on the effects of CSR communication on top talent attraction.

The study uses structured interviews to analyze the communication perceptions and expectations of (n = 15) top talents when making employer decisions. It compares these with the expectations and intentions of HR managers responsible for programs and communications (n = 15).

The study found that HR managers only partially reflect top talents’ specific communication expectations. In addition to the program-specific CSR content, corporate communications have an overarching optimization potential in the communication mode and information architecture. It is particularly striking that future executives proactively seek CSR content in hiring and access corporate and brand communications for this purpose.

The study was conducted during the COVID-19 pandemic, which made a digital interview setting necessary and did not allow to react in detail on every physical signal. On top, the study has only 30 participants (15 HR/15 talents) from three different talent programs.

The study identifies practical, gender-specific and industry-specific implications for corporate communications regarding content and mode of communication. Companies should specify concrete measures for recruiting future executives, but they can also indicate efforts and first initiatives, thus setting a more decisive stage for an aspiration.

The study is characterized by its unique data set. Only a few companies have explicit programs for the development of future executives. The study also examines HR managers’ communication planning and expectations and future executives’ effective communication perceptions and perspectives.

It is unclear what constitutes the tourism live streaming (TLS) servicescape and how it affects users' travel intention (TI). The study aims to explore the composition of the TLS servicescape, the influence mechanism of the TLS servicescape on users' TI and the formation of users' TI.

Based on stimulus organism response theory (SOR), we develop a mediation model to explore the influence of TLS servicescape on users' TI. This study collected data from 432 Chinese TLS users through an online questionnaire, and we used the structural equation model and the SPSS PROCESS macro to test the proposed model. In addition, we tested the variable relationships using fuzzy-set qualitative comparative analysis (fsQCA).

TLS servicescape is a second-order variable that can be categorized into physical element (PE), social element (SOE), symbolic element (SYE) and natural element (NE). TLS servicescape influences TI by affecting social presence (SP) and customer engagement (CE). The fsQCA reveals seven combinations of PE, SOE, SYE, NE, SP and CE that form a high TI for TLS users.

Using multiple data analysis methods, the study emphasizes the significance of the TLS servicescape for TLS. It explores how to evoke users' TI in TLS and provides a reference for TLS marketing.

This study aims to test the relationship between feedback-seeking behavior (FSB) and knowledge sharing. The study also proposes the moderating role of gender in the relationship between FSB and knowledge sharing. In this study, the author draws on the social exchange theory to propose FSB as a driver of knowledge sharing. Ultimately, the study seeks to contribute to a better understanding of the role that FSB plays in triggering knowledge sharing and the ways in which gender can influence this dynamic.

A survey was conducted with 290 knowledge workers from the manufacturing and service sectors of India. FSB and knowledge sharing were assessed with a purposive sample (n = 290). The hypotheses were tested using confirmatory factor analysis (CFA), structural equation modeling (SEM) and multi-group moderation analysis.

The study found that FSB is positively related to knowledge sharing and gender moderates the relationship between FSB and knowledge sharing.

This study adds to the literature by investigating the potential interplay between FSB, knowledge sharing and gender. By uncovering the ways in which gender differences can impact FSB and knowledge sharing, this study provides valuable insights for organizations seeking to promote knowledge sharing and improve communication and collaboration among employees.

The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.