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This study aims to examine the tourists' visit intention by watching deepfake destination videos, using Information Manipulation and Media Richness Theory.

This study conducted a primary survey utilizing a structured questionnaire. In total, 1,360 tourists were surveyed, and quantitative data analysis was done using PLS-SEM.

The results indicate that the factors that affect the tourists' visit intention after watching deepfake videos include information manipulation tactics, trust and media richness. This study also found that perceived deception and cognitive load do not influence the tourists' visit intention.

The originality/salience of this study lies in the fact that this is possibly among the first to combine the Media Richness Theory and Information Manipulation for understanding tourists' visit intention and post-viewing deepfake destination videos.

Deepfake information poses more ethical risks than traditional disinformation in terms of fraud, slander, rumors and other malicious uses. However, owing to its high entertainment value, deepfake information with ethical risks has become popular. This study aims to understand the role of ethics and entertainment in the acceptance and regulation of deepfake information.

Mixed methods were used to qualitatively identify ethical concerns and quantitatively evaluate the influence of ethical concerns and perceived enjoyment on the ethical acceptability and social acceptance of deepfake information.

The authors confirmed that informed consent, privacy protection, traceability and non-deception had a significantly positive impact on ethical acceptability and indirectly influenced social acceptance, with privacy protection being the most sensitive. Perceived enjoyment impacts the social acceptance of deepfake information and significantly weakens the effect of ethical acceptability on social acceptance.

The ethical concerns affecting acceptance behavior identified in this study provide an entry point for the ethical regulation of deepfake information. The weakening effect of perceived enjoyment on ethics serves as a wake-up call for regulators to guard against pan-entertainment deepfake information.

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 establish a comprehensive understanding of the intricacies of how individuals engage with deepfakes, focusing on limiting adverse effects and capitalizing on their benefits.

This study conducted a meta-synthesis of qualitative studies on deepfakes, incorporating study-specific analysis followed by a cross-study synthesis.

Based on the meta-synthesis, the study developed an integrated conceptual framework based on the perspectives from the social shaping of technology theory embedding deepfake-related assertions, motivations, the subtleties of digital platforms, and deepfake-related repercussions.

The study offers crucial insights into the evolving nature of deepfakes as a socio-technical phenomenon and the significance of platform dynamics in deepfake production. It enables researchers to comprehend the cascading effects of deepfakes and positions them to evaluate deepfake-related risks and associated mitigation mechanisms.

The framework that emerges from the study illustrates the influence of platforms on the evolution of deepfakes and assists platform stakeholders in introducing effective platform governance structures to combat the relentless proliferation of deepfakes and their consequences, as well as providing guidance for governments and policymakers to collaborate with platform leaders to set guardrails for deepfake engagement.

Deepfakes have been extensively contested for both their beneficial and negative applications and have been accused of heralding an imminent epistemic threat that has been downplayed by some quarters. This diversity of viewpoints necessitates a comprehensive understanding of the phenomenon. In responding to this call, this is one of the first to establish a comprehensive, theoretically informed perspective on how individuals produce, process, and engage with deepfakes through a meta-synthesis of qualitative literature on deepfakes.

Deepfakes are fabricated content created by replacing an original image or video with someone else. Deepfakes have recently become commonplace in politics, posing serious challenges to democratic integrity. The advancement of AI-enabled technology and machine learning has made creating synthetic videos relatively easy. This study explores the role of political brand hate and individual moral consciousness in influencing electorates' intention to share political deepfake content.

The study creates and uses a fictional deepfake video to test the proposed model. Data are collected from N = 310 respondents in India and tested using partial least square–structural equation modelling (PLS-SEM) with SmartPLS v3.

The findings support that ideological incompatibility with the political party leads to political brand hate, positively affecting the electorates' intention to share political deepfake videos. This effect is partially mediated by users' reduced intention to verify political deepfake videos. In addition, it is observed that individual moral consciousness positively moderates the effect of political brand hate on the intention to share political deepfake videos. Intention to share political deepfake videos thus becomes a motive to seek revenge on the hated party, an expression of an individual's ideological hate and a means to preserve one's moral self-concept and strengthen their ideologies and moral beliefs.

The study expands the growing discussion about disseminating political deepfake videos using the theoretical lens of the negative consumer-brand relationship. It validates the effect of political brand hate on irrational behavior that is intended to cause harm to the hated party. Further, it provides a novel perspective that individual moral consciousness may fuel the haters' desire to engage in anti-branding behavior. Political ideological incompatibility reflects ethical reasons for brand hate. Therefore, hate among individuals with high moral consciousness serves to preserve their moral self.

The purpose of this study is to discuss the harmful use of deepfakes in an organizational context, based on the only two cases the authors found that were addressed by the media from the perspective of corporate fraud. This study offers an overview of deepfake technology, and in particular, examines five W questions to better decipher the impact of these tools on organizations: What is deepfake? Who is the fraudster and who is targeted? Why use them and how? And What after? Based on these five W questions, this study provides an in-depth discussion of the two cases identified. Even though this technology has several advantages, this study examines its dark side.

Using comparative analysis, the authors study the only two known and publicized fraud cases by using deepfakes that have targeted chief executive officers to date.

The paper provides an extensive picture of the unethical and illicit use of deepfakes in an organizational context and discusses how this technology could affect fraud risk. In addition, the analysis of cases shows that voice-generating software, combined with other fraud schemes such as business email compromise, facilitates the commission of the fraud, as the victims feel confident because they recognize the speaker’s voice and emails. The analysis shows that any organization could be vulnerable to this technology. The median costs of this type of fraud can be high. For the two cases identified, the estimated losses amounted to US$243,000 and US$35,000,000, respectively.

This paper adds new insights to the scarce research on deepfakes and financial crime by investigating the causes and consequences of the unethical and illicit use of deepfakes. It has several implications for organizations, boards of directors, management and regulatory authorities.

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.