Problematising reality: the promises and perils of synthetic media

Kalpokas, Ignas

doi:10.1007/s43545-020-00010-8

Cited by 18 publications

(9 citation statements)

References 20 publications

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“…Furthermore, organizations have started using unique virtual influencers for developing deepfakes. Hence, future studies can be conducted to understand the effect of virtual influencers on online shopping intention (Kalpokas, 2021; Lee and Kim, 2022). Studies can also be performed on deepfakes and their impact on customers' experience, satisfaction, loyalty and word-of-mouth regarding online shopping on various online portals and e-commerce websites.…”

Section: Discussionmentioning

confidence: 99%

“…Personalized advertising plays an important role in online buying behavior (Bleier and Eisenbeiss, 2015). Deepfakes for online shopping websites are made using AI and ML technology, which help marketers provide personalized product videos available on various social media platforms and e-commerce portals (Kalpokas, 2021). These personalized deepfakes are provided to customers through various social media websites and online shopping portals that cater to the customers' interests enticing them to shop online (Roy et al, 2017).…”

Section: Ai-based Deepfake Advertisementsmentioning

confidence: 99%

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Customers' online shopping intention by watching AI-based deepfake advertisements

Pillai¹,

Metri

2022

IJRDM

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PurposeThe purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using media richness (MR) theory and Information Manipulation Theory 2 (IMT2).Design/methodology/approachA conceptual model was developed to understand customers' online shopping intention by watching deepfake videos. A quantitative survey was conducted among the 1,180 customers using a structured questionnaire to test the conceptual model, and data were analyzed with partial least squares structural equation modeling.FindingsThe outcome of this research provides the antecedents of the online shopping intention of customers after watching AI-based deepfake videos. These antecedents are MR, information manipulation tactics, personalization and perceived trust. Perceived deception negatively influences customers' online shopping intention, and cognitive load has no effect. It also elucidates the manipulation tactics used by the managers to develop AI-based deepfake videos.Practical implicationsThe distinctive model that emerged is insightful for senior executives and managers in the e-commerce and retailing industry to understand the influence of AI-based deepfake videos. This provides the antecedents of online shopping intention due to deepfakes, which are helpful for designers, marketing managers and developers.Originality/valueThe authors amalgamate the MR and IMT2 theory to understand the online shopping intention of the customers after watching AI-based deepfake videos. This work is a pioneer in examining the effect of AI-based deepfakes on the online shopping intention of customers by providing a framework that is empirically validated.

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Section: Discussionmentioning

confidence: 99%

Section: Ai-based Deepfake Advertisementsmentioning

confidence: 99%

Customers' online shopping intention by watching AI-based deepfake advertisements

Pillai¹,

Metri

2022

IJRDM

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“…The impact of manipulated advertising on the consumer is discussed in the literature; however, the advanced form of manipulation using AI and ML technology-based deepfake is not much explored (Campbell et al , 2021). There is no research that divulges the effect of deepfakes advertising on hotel booking intention (Kalpokas, 2021; Kietzmann et al , 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Online deepfake video advertisements are alarming for the hospitality industry, keeping in sight its latent impact on the hotel image and branding since they mislead the audience into thinking the content is genuine (Kwok and Koh, 2020a; Tuomi, 2021). Hence, scholars mandate research on consumer behavior after watching deepfake video advertisements (Kalpokas, 2021; Kietzmann et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

The effect of deepfake video advertisements on the hotel booking intention of tourists

Pillai¹

2022

JHTI

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PurposeThis 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).Design/methodology/approachA 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).FindingsThe 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.Practical implicationsThe 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.Originality/valueMR 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.

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“…Deepfakes also create the opportunity for businesses to cater to each of their clients individually, employing neural networks to deliver personalized product placement and customized shopping opportunities to all. 6 These applications just scratch the surface of what experiences deepfakes could make possible.…”

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confidence: 99%

Can Deepfakes Improve Therapy?

Wiederhold¹

2021

Cyberpsychology, Behavior, and Social Networking

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Problematising reality: the promises and perils of synthetic media

Cited by 18 publications

References 20 publications

Customers' online shopping intention by watching AI-based deepfake advertisements

Customers' online shopping intention by watching AI-based deepfake advertisements

The effect of deepfake video advertisements on the hotel booking intention of tourists

Can Deepfakes Improve Therapy?

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