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This paper aims to investigate the impact of financial anxiety and convenience on the relation between cashier-less versus traditional checkouts and purchase intentions among Saudi Arabian consumers.

In an online experiment, 329 Saudi participants were randomly assigned to one of two checkout conditions (traditional vs. AI-enabled) in a between-subjects design and indicated their financial anxiety. Through moderation-of-process design, the authors examine and showcase that the effect of convenience leads to higher purchase intent for AI-enabled checkouts. Moreover, the authors examine financial anxiety as an underlying mechanism and show that for high-convenience consumers, this enacts higher purchase intent.

The effect of AI-enabled checkouts depends on consumers' convenience perception. High-convenience consumers prefer AI-enabled checkouts over traditional ones, whereas low-convenience consumers are indifferent. Based on the Roy adaptation model theoretical framework, this occurs because high-convenience consumers experience greater financial anxiety when using AI-enabled checkouts, which in turn leads to higher purchase intent.

To the authors’ knowledge, this is the first study to explore the reactions of Saudi Arabian consumers toward cashier-less stores versus traditional stores. Interestingly, their intent to purchase increases, due to the financial anxiety they experience while encountering AI-enabled transactions. Due to the limited research of retailers going cashier less, little is known about consumer reactions and how they may differ culturally.

This research examines whether anthropomorphizing artificial intelligence (AI) chatbots alters consumers' risk preferences toward financial investment options involving differential risks.

An experimental approach has been adopted with three studies, all featuring a between-subjects design.

Through three studies, the findings document that, in a financial decision-making context, anthropomorphizing AI leads to significantly greater risk aversion in investment decision-making (Study 1). This occurs because AI-enabled chatbot anthropomorphization activates greater psychological risk attachment, which enacts consumers to manifest stronger risk aversion tendency (Studies 2 and 3).

Anthropomorphizing AI has undeniable relevance in the contemporary marketing landscape, such as humanoid robotics and emotion AI algorithms. Despite of anthropomorphism's significance and relevance, the downstream impact of anthropomorphism remains unfortunately underexplored.

Given the socialisation of men and women to their gender roles and expression of emotion, this study aims to investigate whether there are gender differences in the use of emotive language in electronic word-of-mouth (eWOM), specifically in online reviews. The authors propose that female reviewers will use strong emotive terms, such as love, more frequently in online reviews than do male reviewers. The authors further propose that the gender of the reviewer influences audience responses to the reviewer’s use of emotive terms in online reviews.

The authors conducted secondary data analysis of restaurant reviews (Study 1) to provide evidence on whether the gender of the reviewer affects the frequency of use of emotive terms in an online review. In addition, three separate experiments (Studies 2–4) were conducted to test the theoretical arguments.

The results of the secondary data analysis indicated that female online reviewers used the term “love” much more frequently in their reviews than male reviewers, whereas there was no usage difference for the term “like”. The experimental studies further showed that an emotive review by a male reviewer containing the word “love” resulted in a higher evaluation of the restaurant being reviewed than a non-emotive review containing the word “like”. This difference was stronger when the overall rating was less salient and for consumers who believe (vs do not believe) that men and women use emotional language differently.

First, the paper extends our understanding of gender differences in emotional expression within the domain of eWOM and online reviews as well as our understanding of consumer responses to these gender differences. Second, the authors identify a boundary condition for these gender effects, namely, the overall rating score. Third, the authors find that consumer beliefs regarding gender stereotypes in emotional expression provide an explanation for these effects.

The results of the research indicate that the electronic algorithms operating on review sites might be modified in terms of their criteria for selecting the reviews to display to consumers, as consumer decision-makers may find greater utility in reviews written by male reviewers that contain strongly positive emotive terms.

The research extends the knowledge on gender differences in emotional expression in online reviews by demonstrating the actual usage patterns and differing responses to the emotional expressions of each gender.

This paper aims to examine how consumers make choices when they are faced with a fixed set of available options, consisting of both preferred and less-preferred choices, in the domain of food consumption. Specifically, the paper offers a novel perspective to predict repeated choice decisions in food consumption, which is termed as “pattern-seeking” – a consumption choice pattern that involves a coherent repetitive sequence of sub-groupings or coherently concentrated sub-groupings of options.

Eight experimental studies that contrast the existing theoretical predictions regarding repeated choices (e.g. primacy effect, recency effect, variety vs consistency) against pattern-seeking were conducted using hypothetical and actual food choices.

The results of experimental studies show that an explicit decision pattern (i.e. pattern-seeking) emerges as the most significant predictor of repeated choice in the food consumption domain.

This study offers a novel perspective on how consumers make repeated choices in the domain of food consumption.

The results show that consumers prefer food consumption with a pattern (vs non-pattern). Thus, it would be better to generate marketing activities that allow customers to satisfy their pattern-seeking more easily.

This study advances the literature on repeated food choices by demonstrating that people possess an inherent preference for patterns in food consumption.

This paper aims to investigate the effect of artificial intelligence (AI)-enabled checkouts on consumers’ purchase intent and evaluations of the retailing atmosphere. It also offers novel findings pertaining to the mediating role of arousal and moderation by innovativeness importance on consumers’ responses toward AI-enabled checkouts.

Three pilot studies, two field studies and one online experiment featuring 1,567 respondents were conducted by manipulating checkout methods.

AI-enabled checkouts lead to a higher level of arousal, which, in turn, yields more favorable store atmosphere evaluations and higher purchase intent. Furthermore, the positive effect of AI-enabled checkouts is moderated by consumers’ innovativeness importance.

This research contributes to the emerging body of AI research and demonstrates a novel perspective by illuminating that under certain circumstances, AI-enabled checkouts lead to more positive outcomes relating to store atmosphere evaluations and purchase intent, as well as the unintended effect of heightened arousal.

This study shows how marketers and practitioners can promote consumers’ evaluations and patronage likelihood effectively by harnessing AI-enabled checkouts for those who consider innovativeness as important.

This research documents the novel findings of how and when AI-enabled checkouts garner more favorable consumer responses.

This study aims to extend the study of COVID-19 effects by identifying different consumer behaviors beyond panic buying during the pandemic.

A systematic review was based on Herjanto et al.’s (2020a) thematic analysis and Paul et al.’s (2021) 5W1H framework, and the authors analyzed 52 related papers.

The result findings indicated that during the COVID-19 pandemic, consumers fell into five different consumer behavior categories: health-related behaviors, consumption behaviors, ethical behaviors, behavioral intentions, and other related behaviors, and social connectedness behaviors. Findings show that consumer behaviors were increasingly complex and dynamic during the pandemic.

This systematic review will provide significant contributions to academia by offering general and technical insights and to practitioners by presenting guidelines on dealing with such different behaviors.