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Evidence from a variety of sources suggests that there has been an increase of around 1% per annum in the prevalence of learning disability (LD) in adults over the last 35 years, due mainly to increases in survival. This trend is likely to continue for at least another ten years. Ninety‐six percent of adults notified to the Leicestershire LD register have an estimated IQ below 50 or need supervision every day to remain safe. Three‐quarters have additional significant disabilities including behaviour problems, psychological symptoms, physical dependencies or epilepsy. In one quarter the behaviour problem poses a major challenge to the achievement of an ordinary life. Two‐thirds indicate a need for help from one or other specialist. Informal carers are actively providing care for nearly half the adults, but a quarter are not content with care‐giving. Carers Report 40% more limiting health problems than their counterparts in the general population, in particular depression in women and cardiovascular problems in men. The specific areas of unmet need among carers Reporting depression are for financial help, long‐term social support and medical advice. Resource allocation for this client group needs to be reviewed in the light of substantial and unrecognised increases in prevalence which are continuing to occur, and the need for long‐term support.

This paper aims to examine the effects of travel experience dimensions on tourist satisfaction and destination loyalty.

Data were collected from 457 international tourists visiting Phuket through a convenience sampling method. The structural equation modeling approach by AMOS was used to test the effects.

In case of island destination, beach attraction is not the only factor contributing to tourists’ loyalty, but hospitality of local people also plays an essential component to retain loyal tourists.

This study examined only one construct (i.e. travel experience) affecting tourist satisfaction and destination loyalty.

Tourist experience in beach attractions and local people are the key factors to retain royal tourists.

Quality of beaches and friendliness of local people are important factors to promote island tourism.

Two key factors of tourist experience were found to affect tourists’ loyalty in the case of island destination: beach attractions and local people.

This chapter uses multiple research methods, including quantitative science mapping analysis (SciMat) and a qualitative literature review, to provide insight into the academic debate unfolding at the intersection of big data and business processes. SciMat analysis based on keyword co-occurrence enabled identifying 12 of the most productive research themes, as reflected in a poll of 301 articles about big data and business processes. The three most important themes are: firm performance, Industry 4.0, and innovation. The traditional literature review on firm performance indicated that big data analytics (BDA) positively influence business process performance and have a beneficial impact on a firm’s performance, that is, the role of big data is viewed as critical in the context of Industry 4.0 because it enhances productivity and improves business processes. The benefits of BDA can be achieved only if the organizational obstacles related to planning, workforce attitude, and alignment with strategy are overcome. Moreover, big data is perceived as a significant source of innovation in an organization and can be conceptualized with the use of a resource-based view (RBV) of the firm. BDA positively influence business processes, which is strengthened by adequate implementation and openness to innovation.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI.

Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM.

Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices.

Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM.

Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.

Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.

A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.

The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.

This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.

Supply chain (SC) and knowledge management (KM) have been studied; still, there is a need to understand how KM can be used for SC resilience and improving the firm’s performance. The purpose of the paper is to study and analyze SC resilience strategies based on KM processes to enhance SC performance considering six SC strategies: SC reengineering, collaboration, SC innovation, SC integration, SC agility and SC risk management.

By adopting the dynamic capability theory, the empirical research is conducted on a sample of 312 Indian micro, small to medium enterprises. To evaluate 312 samples, the structural equation modeling approach is adopted.

The study found a is a positive relationship between SC reengineering, SC collaboration, SC integration, SC agility, SC risk management and KM. Nevertheless, the relationship between SC innovation and KM is not significant. This study also found the mediating effect of KM on SC performance, and the results shows that SC reengineering, SC collaboration, SC agility and SC risk management are having complementary mediation, while SC innovation and SC integration did not show any mediation.

This is the only research that integrates resilience strategies and KM for improving SC performance. Using KM, SC reengineering will improve SC performance by enhancing readiness and recovery strategies to avoid SC disruption. KM will improve SC collaboration. It will enhance the SC process’ overall visibility, transparency and so on. Agility leads to increased speed, visibility and flexibility, which aids in dealing with uncertainty in the environment. SCRM entails investments and additional resources (such as equipment and labor) to navigate uncertainty and risks in the SC and improve SC performance.