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The financial world of today is evolving at a rate that can be challenging to keep up with and comprehend due to developments in information and communication technology. When compared to a conventional disclosure, the eXtensible Business Reporting Language (XBRL), which was named one of the top ten accounting technologies, has a clear advantage in reducing information asymmetry by providing interactive data disclosure. This study aims to examine whether forcing companies to adopt XBRL would cause them to prefer misclassifying income statement items as an alternative to more risky earnings management methods.

The study sample includes nonfinancial UAE companies listed on Dubai Financial Market and Abu Dhabi Securities Exchange from 2012 to 2019. Fixed effect and system General Method of Moments regressions were used to analyze the study data.

The study found that XBRL reporting resulted in lowering the quality of financial reporting as companies have a higher tendency to misclassify income statement items as earnings management mechanism.

The findings of this research can be used by stakeholders and practitioners in the UAE to better understand whether the use of XBRL is linked to the engagement of financial reporting manipulative practices. The findings of this study also inform policymakers and regulators about the consequences of companies formally adopting digital disclosure language in an effort to improve the quality of their reporting. Besides, the results offer guidance to regulators considering imposing XBRL usage regulations.

Limited number of studies have tested the association between XBRL mandatory adoption and misclassification of income statement items as an earnings management tool in the Gulf Cooperation Council region.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

This research paper aims to investigate the predictors and outcomes of immersive technology adoption in tourism.

PLS-SEM is used for data collected from tourists visiting the UAE and Egypt to examine predictors and consequences of adoption.

It is revealed that perceived ease of use, enjoyment, immersion, usefulness and attitude towards technology predict immersive technology adoption. It is also revealed that the adoption affects tourists’ perceived value and engagement, which, in turn, affects tourists’ satisfaction and loyalty.

The study has integrated a research model that combines both antecedents and consequences of immersive technology adoption where few empirical investigations were revealed to draw conclusions on this research area. Also, missing relations have been included and tested in the research model.

The purpose of this study is to conduct a systematic literature review of the adoption of immersive marketing technology (IMT) in terms of strategic planning of its adoption, resource requirements and its implications and challenges.

This study categorizes and contextualizes qualitative approaches to evaluate the literature, with Scopus databases serving as the primary source of 90 selected articles in the areas of information technology, business and marketing strands. Theme analysis was carried out using thematic techniques and grounded approach principles to facilitate thematic coding and generate theme analysis.

The analysis was supported by the three concepts of business flexibility, agility and adaptability, which were drawn as a strategy for IMT adoption. The findings presented three main themes: proactive flexibility, responsive agility and reactive adaptability that enable business owner–managers to craft a strategy for IMT adoption.

The novel contribution of this study is the inclusion of key implications related to IMT as a starting point of the next level of innovative marketing for all academics, practitioners and business owner–managers.

The rapid advancement of Education Technology (EdTech) offers promising opportunities for educational institutions to integrate sustainable business practices into their operations and curriculum. The integration of EdTech into sustainability education has emerged as a powerful tool to promote environmental awareness, foster sustainable behavior, and address the pressing challenges of climate change and resource depletion. This chapter explores the growing significance of EdTech in sustainability education, analyzing its potential to cultivate a generation of environmentally conscious and responsible global citizens. It also aims at identifying and examining the most prominent emerging EdTech tools specifically designed to promote sustainability in educational settings. Furthermore, it aims to comprehend the institutional elements that have successfully incorporated and expanded the utilization of EdTech tools to promote enduring business practices. Additionally, the chapter addresses the challenges and obstacles faced by educational institutions in adopting and implementing these technologies and propose strategies to overcome these barriers.

The purpose of this paper is to examine the factors that influence older adults' intention to use virtual fitting room technology during the COVID-19 pandemic based on the extended technology acceptance model (TAM).

An online survey was conducted with a sample of older adults from 60 to 90 years old (n = 819). A structural equation modeling was conducted to test a proposed research model.

The results revealed that older adults' behavioral intentions were positively influenced by perceived usefulness and ease of use, and fear of infection during the pandemic was significantly related to the perceived usefulness. Fit concern was not significantly related to perceived usefulness of virtual fitting room technology.

This research extends the TAM by adding antecedents to perceived usefulness in explaining older adults' adoption of virtual fitting technology.

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.

This paper aims to explore ChatGPT’s (generative pre-trained transformers) potential as a tool for retailers to improve customer experience and boost sales. While it provides benefits like personalized recommendations and 24/7 assistance, there are limitations, like difficulty in understanding unconventional language. The paper stresses careful integration to overcome these limitations and create a better customer experience. Additionally, it discusses the potential for further development and integration of ChatGPT in retail, such as generating product descriptions and virtual try-on experiences. Finally, the paper encourages retailers to embrace ChatGPT to meet their customer needs.

Case-based methodology involves using specific cases or examples to explore a broader issue or phenomenon. Researchers have analysed real-world cases to identify patterns, themes and insights that can be applied to other contexts or situations. This was useful for understanding complex and multifaceted issues as it allowed us to delve deeper into specific examples and explore the nuances of the situation.

While ChatGPT is a powerful tool for retailers, limitations such as difficulty in understanding non-standard accents and unconventional language can arise, causing customer frustration. Retail managers must integrate ChatGPT in a way that enhances customer experience. In the future, ChatGPT has the potential to generate product descriptions, provide virtual try-on experiences and integrate with augmented or virtual reality technology to offer more immersive experiences. Careful consideration and integration can help retailers overcome these limitations and offer personalized recommendations, round-the-clock assistance and an engaging customer experience that improves sales.

The case topic is very much in a novel stage of research and writing.

Occupational safety issues among employees remains a contemporary and omnipresent concern. In developing countries, safety-related problems are amplified, resulting in higher incidences of serious accidents and occupational diseases. This study aims to evaluate employees’ knowledge and attitudes toward occupational health and safety, and how these influence overall occupational health and safety compliance. Ghana’s oil and gas industry provides the contextual backdrop for this research, given it is characterized by high rates of injury.

A positivist and deductive research strategy was used to quantitatively analyze both primary and secondary data sources. A structured survey was administered to industry employees, and multiple linear regression was used to establish the effects of employee’s knowledge and attitude toward occupational health hazards on overall health and safety compliance.

The findings indicate that most employees had both a high level of knowledge and positive attitude toward mitigating occupational health hazards. Moreover, the study reveals that most employees complied with occupational health safety practices. However, the study also reveals that the effect of employees’ knowledge and attitude toward occupational health hazards does not translate into deployment of comprehensive safety practices. Interestingly, female employees were found to be more knowledgeable and compliant with occupational health and safety practices than their male counterparts.

Premised upon the findings, the study recommends: implementation of relevant education and training programs encompassing the proper usage of machinery and equipment, tailored hazard safety training appropriate to specific employee job requirements, effective dissemination of risk information and governance initiatives that enforce strict adherence to correct safety procedures.

The study uniquely examines the influence of employee’s knowledge of health and safety to overall compliance within the oil and gas industry. Cumulatively, the study’s findings and recommendations contribute to improving the occupational health and safety outcomes within the industry.