Consumer lying behavior in service encounters

Snyder, Hannah; Witell, Lars; Gustafsson, Anders; McColl‐Kennedy, Janet R.

doi:10.1016/j.jbusres.2021.11.075

Cited by 6 publications

(2 citation statements)

References 60 publications

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“…Most of the research in this area assumes that these conversations are always truthful, with consumers sharing their real experiences; however, studies show that exaggerated WOM is common (Harris et al , 2016). Consumers lying and exaggerating their complaints and WOM, both negatively and positively, is pervasive and was widespread even before the advent of social media (Harris et al , 2016; Arora and Chakraborty, 2020; Snyder et al , 2022) but social media have made these comments accessible by a greater audience (Istanbulluoglu et al , 2017).…”

Section: Falsified Online Reviewsmentioning

confidence: 99%

“…Consumer lying in service situations is found to be motivated by gaining economic or psychological benefits (Snyder et al , 2022). In this regard, the reasons for consumers to post FORs can also be linked to monetary reasons and psychological reasons such as revenge or seeking social status (Wu et al , 2020; Thakur et al , 2018).…”

Section: Generating Falsified Online Reviewsmentioning

confidence: 99%

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Forms of falsified online reviews: the good, the bad, and the downright ugly

Istanbulluoglu,

Harris

2023

EJM

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Purpose Falsified online reviews (FORs) are the published/viewable consumer-generated online content regarding a firm (or its representatives) or its services and goods that is, to some degree, untruthful or falsified. The purpose of this study is first to explore the nature of FORs, focusing on reviewers' interpretations and refections on falsity, intent, anonymity and the target of their FOR. Secondly, the authors examine the valence and veracity dimensions of FORs and introduce a typology to differentiate their variations. Design/methodology/approach using an exploratory research design, 48 interviews were conducted with participants who post online reviews on social media about their experiences with food and beverage serving outlets. Findings The results show four common forms of FORs on social media. These are reviews focused on equity equalizing, friendly flattery, opinionated opportunism and malicious profiteering. Research limitations/implications The authors provide exploratory and in-depth information via interviews, but do not analyse the content of FORs. Practical implications Firms should be aware of varieties of FORs and that these may not be limited to malicious content. This is important in terms of showing that in dealing with FORs, a one-size-fits-all approach will not work. FORs are not always entirely fabricated, and instead various levels of falseness are observed, ranging from slight alterations to complete fabrications. Originality/value Previous research explored how to identify and differentiate FORs from truthful ones, focusing on the reviews or how they are perceived by readers. However, comparatively little is known of the reviewers of FORs. Hence, this study focuses on reviewers and offers new insights into the nature of FORs by identifying and examining the main forms of FORs on social media.

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Section: Falsified Online Reviewsmentioning

confidence: 99%

Section: Generating Falsified Online Reviewsmentioning

confidence: 99%

Forms of falsified online reviews: the good, the bad, and the downright ugly

Istanbulluoglu,

Harris

2023

EJM

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Dishonesty Through AI: Can Robots Engage in Lying Behavior?

Witell,

Snyder

2024

Humane Autonomous Technology

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This book chapter addresses how artificial intelligence (AI) engages in lying behavior in service encounters when customers interact with it when booking trips, investing money, or using customer service. The chapter concerns how AI learns from human behavior and how it practices the ethics of humans in service encounters. We identify three types of lying behavior from AI: (a) hallucinatory lying behavior, (b) manipulative lying behavior, and (c) directed lying behavior. Further, we show that mechanical AI, thinking AI, and feeling AI engage in these behaviors to different extents. By becoming familiar with concepts such as corporate digital responsibility and AI lying behavior, managers of service firms will be better equipped to provide service in the future.

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Die Perspektive des Kunden analysieren

Hasebrook¹,

Buermeyer²

2023

Kunden Begeistern

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Consumer lying behavior in service encounters

Cited by 6 publications

References 60 publications

Forms of falsified online reviews: the good, the bad, and the downright ugly

Forms of falsified online reviews: the good, the bad, and the downright ugly

Dishonesty Through AI: Can Robots Engage in Lying Behavior?

Die Perspektive des Kunden analysieren

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