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This study aims to investigate the effect of deepfake video advertisements on hotel booking intention by applying the media richness theory (MRT) and information manipulation theory (IMT).

A quantitative survey was conducted using a structured questionnaire to understand the effect of deepfake hotel video advertisements on booking intention. A large cross-section of 1,240 tourists was surveyed and data were analyzed with partial least squares structural equation modeling (PLS-SEM).

The outcome of this research provides the factors affecting the booking intention due to deepfake hotel video advertisements. These factors are media richness (MR), information manipulation (IM) tactics, perceived value (PV) and perceived trust (PT). Cognitive load and perceived deception (DC) negatively influence the hotel booking intention.

The distinctive model that emerged is insightful for senior executives and managers in the hospitality sector to understand the influence of deepfake video advertisements. This research provides the factors of hotel booking intention due to deepfake video advertisements, which are helpful for designers, developers, marketing managers and other stakeholders in the hotel industry.

MR and IMT are integrated with variables such as PT and PV to explore the tourists' hotel booking intention after watching deepfake video advertisements. It is the first step toward deepfake video advertisements and hotel booking intentions for tourists. It provides an empirically tested and validated robust theoretical model to understand the effect of deepfake video advertisements on hotel booking intention.

This study aims to identify the risks to corporate reputation presented by deepfakes and how to manage them.

The approach involves a review of the current literature on deepfakes across different sectors to create a clear picture of the risks that deepfakes entail and how best to deal with them.

While deepfakes are still mostly easily detectable, their sophistication increases daily, and corporations need both technology and culture shifts to deal with this evolving threat.

While deepfakes have been the subject of intense interest, to the best of the author’s knowledge, this is the first attempt to look at the problem from the perspective of corporate enterprise risk.

In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature.

Using in-depth surveys across varied sectors (N = 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness.

A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information.

This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries.

It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront.

Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life.

Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.

The impact of artificial intelligence (AI) and extended reality (XR, including virtual reality [VR], augmented reality [AR], and mixed reality [MR]) on marketing in Industry 5.0 and Society 5.0 is explored with systematic literature review in this chapter. AIXR is becoming a necessary aspect of marketing, driven by efficiency, productivity, and innovation. Despite AI's capabilities, the human touch in marketing is preferred due to superior adaptive, creative, and innovative abilities. The use of fully automated marketing systems is limited to specific tasks. This research will benefit both practitioners and academics focusing on AIXR in marketing and is limited by the number of included literature.

The work connects classic theories of selfing to the COVID-19 pandemic to make fresh connections between pandemic-induced trauma to the self and digital resources. This research introduces the concept of the “traumatized self” emerging from the COVID-19 pandemic in relation to digital disadvantage and digital hyperconnectivity. From Cooley’s original “looking glass self” to Wellman’s “hyperconnected” individualist self, social theories of identity work, and production of the self have a long and interdisciplinary history. In documenting this history, the discussion outlines key foci in the theorizing of the digital self by mapping how digital selfing and identity work have been treated from the inception of the internet to the epoch of the pandemic. The work charts the evolution of the digital selfing project from key theoretical perspectives, including postmodernism, symbolic interactionism, and dramaturgy. Putting these approaches in dialogue with the traumatized self, this research makes a novel contribution by introducing the concept of digitally differentiated trauma, which scholars can employ to better understand selfing processes in such circumstances and times.