Journal of Consumer Behaviour最新文献

The promise of the metaverse as a collective, virtual, and shared social space is revolutionizing digital retail. This study provides groundbreaking insights into customer experience in immersive metaverse environments, as well as into how these experiences on metaverse platforms influence customers' real-world consumption behaviors. Drawing upon data from metaverse platform users in the US, this study identifies the specific antecedents of a positive customer experience on metaverse platforms, including the role of social presence and trialability. Further, it demonstrates the potential for purchase spillovers from the metaverse to traditional retail channels, extending the omnichannel retail literature. In addition, it examines how early-stage versus long-term users of the metaverse shape users' intentions to revisit metaverse platforms. Based on our results, we offer a comprehensive model of customers' metaverse behaviors, which may be used to predict and enhance customers' purchase intentions across channels. Our results also demonstrate that the metaverse is not merely a parallel digital retail channel but instead an influential extension of the customers' real-world consumption. From a managerial perspective, we offer metaverse operators and retail brand managers insights into how an engaging and immersive customer experience in the metaverse can be developed to support metaverse platform growth, and targeted brand strategies that translate into real-world gain for both the brand and the customer. The findings suggest that metaverse platforms must deliver customer experiences at a very high level to prevent stagnation in metaverse usage intentions; therefore, managers can confidently continue investing in relevant strategies to fuel metaverse platform growth.

Research suggests that authentic branding strategies should focus on consumers' actual self rather than their ideal self; that is, brands that match consumers' ideal self are perceived as too psychologically distant from their present self and, thus, as inauthentic. This study challenges this prevailing notion by proposing the novel perspective that ideal self-congruence is more influential than actual self-congruence in driving authenticity. Contrary to the view that brands matching consumers' ideal self are deemed inauthentic due to psychological distance, our research, encompassing four empirical studies, demonstrates that ideal self-congruence significantly enhances positive authentic pride while effectively reducing negative hubristic pride more than actual self-congruence. Furthermore, this study not only reveals that ideal self-congruence is more strongly associated with authentic pride than actual self-congruence but also reshapes the theoretical understanding of the role of self-congruence in the realm of authenticity. Our findings therefore contradict previously cited but hardly empirical arguments by demonstrating that ideally self-congruent brands positively affect perceived brand authenticity more than actually self-congruent brands. Thus, we recommend brands to focus authentic marketing strategies on consumers' ideal self to positively influence consumer behavior.

Metaverse is an emergent technology that facilitates consumer interaction and participation in various activities within an integrated virtual environment. Considering the Metaverse's swift growth, comprehension of the perspectives and inclinations of its prospective users is critical. Considering configuration and complexity theories, this article examines the causal patterns of factors and fragmented perspectives concerning using Metaverse applications (M-apps). It does so by examining how functional (ease of use, privacy), social (interactivity, presence), and personality (locus of control, openness to experience) factors combine as causal configurations to describe consumer adoption (MTA). Hence, fuzzy-set qualitative comparative analysis is employed to empirically examine the proposed configurational model by analyzing a sample of 372 Chinese consumers of different M-Apps. The notable MTA was determined to be explained under four distinct solutions with varying configurations of function, social, and personality in various combinations. The findings of this paper's complexity analysis constitute a scholarly and practical contribution to consumer acceptance of M-apps, allowing for the customization of Metaverse functionality to meet every consumer's needs.

This study aims to investigate various types of values consumers experience within the meal kit delivery context, their influences on satisfaction and word-of-mouth (WOM), and the moderating effects of demographics between consumer values and satisfaction with a mixed-method approach. The qualitative study employed a critical incident technique that analyzed consumers' online reviews, resulting in 285 critical incidents. The analysis revealed five themes of consumer value unique to the meal kit usage, including excellence, convenience, monetary value, epistemic value, and self-esteem. The quantitative study from an online survey of 300 consumers used a structural equation modeling, which provided support for the influences of the five consumer values on satisfaction, subsequently enhancing consumers' WOM behavior. Besides, the multi-group analysis revealed that the impacts of consumer values on satisfaction depended on their marital status and household income. This study contributes to the consumer behavior literature in three areas. First, it expands the consumer value literature by identifying multiple dimensions of consumption values unique to meal kit delivery that gained popularity during the COVID-19 pandemic. Second, this study contributes to the consumer satisfaction and loyalty literature by demonstrating the impacts of different dimensions of values on consumer responses. Lastly, it expands our knowledge of consumer demographic characteristics that change the dynamics between consumer values and satisfaction. The findings provide valuable insights into the fast-growing meal kit industry and allow the service providers to better align their products/service attributes with the values consumers appreciate.

When exposed to advertisements, consumers are often suspicious of brand claims. To that end, prior research has explored how individuals evaluate claims to form a judgement under a state of suspicion. Yet, consumer research has not examined how suspicion affects consumers' suspension of their judgement towards the brand. We experimentally investigate the effects of three (low vs. moderate vs. high) levels of consumer suspicion on judgement suspension. Study 1 shows that compared with low or high levels, moderate levels of suspicion lead to significantly higher judgement suspension. Studies 2 and 3 replicate this inverted U-shaped effect for additional brand and product category contexts and unveil that uncertainty towards the brand mediates the effect of suspicion on judgement suspension. In turn, the impact of uncertainty towards the brand on judgement suspension is mediated by product imagery. This research corroborates the effects of suspicion on consumer judgement suspension.

The wall of differentiation between genuine recommendations by social media influencers and brand-sponsored promotions has become thinner since brands are increasingly sponsoring influencers to promote their products and services. This study has followed a qualitative research method using the grounded theory approach to conduct in-depth, one-to-one, semi-structured interviews with 25 social media users to delve into influencers' brand paid promotions and sponsorship disclosure, which marks a grey area in influencer marketing. The results delineate the grey characteristics of influencers through three main themes: (1) Disclosure of paid promotions/ non-promotions (i.e., content factors), (2) Consumer conviction conundrum (i.e., context factors), and (3) Social media users' avoidance behaviour (i.e., consequences). This study also defines ‘Sinfluencer’ (i.e., commercially motivated influencers who hide their paid partnerships) and elucidates ‘evaluation’ as a critical step, thereby extending the discussion on the social media engagement cycle.

The conversational, social and intelligent capabilities of Artificial Intelligence (AI) enabled voice assistants (VAs) to assist humans have grown. However, their use still remains limited for complex tasks such as shopping. While some studies find that consumers are willing to use them, others report negative reactions that lead to rejection, especially for complex activities. This study aims to bridge the gap between the dichotomous streams of literature by investigating the overall attitude towards the use of AI VAs for a multi-step task that is, shopping. We first identify 27 attitudinal criteria through a comprehensive literature review in light of the Uncanny Valley Theory and the Self Determination Theory. The criteria are organized using the cognitive, affective and conative framework of attitude, and ranked using the Fuzzy Analytical Hierarchy Process. Sensitivity analysis is done to affirm the robustness of the framework. Findings reveal that the behavioral intentions to use (conative criteria) are the strongest, followed by feelings evoked during use (affective criteria), followed by beliefs people hold regarding AI VAs (cognitive criteria). Intention to use AI voice assistants during all stages of the purchase journey takes precedence over negative feelings such as loss of control, unfulfillment and vulnerability. This study reconciles the existing stream of literature on conversational AI and provides managerial implications based on the dimensions of attitude.

This article sheds light on the profound impact of technology on consumer behavior, specifically focusing on the rise of generative AI tools. It highlights how these advancements have revolutionized consumer engagement, purchase decision-making, and technology interaction. The article underscores the transformative potential of generative AI in shaping consumer behavior through personalized recommendations and interactive shopping experiences. It emphasizes the need for continued research and exploration to comprehend and effectively navigate the ever-evolving landscape of consumer behavior influenced by generative AI. Additionally, the article identifies implications for research and practice, offers valuable strategies for brands, and presents a comprehensive research agenda to delve deeper into this field. Ultimately, it provides valuable insights into the challenges and opportunities presented by generative AI in consumer behavior, serving as a guiding resource for advancing theory, practice, and policy in this domain.

Whereas consumer satisfaction is critical for the success of services, we research how providers evaluate customers in the sharing economy represented by the rideshare marketplace. We examine anticipated customer evaluation (ACE) as the underlying link and the provider's sense of power as a moderator for the relationship between customer ingratiation and provider evaluations. We first conducted a field pilot study and analyzed the content of rideshare trips described by drivers. Then, we tested the conceptual framework in four experiments that manipulated different rideshare customer behaviors (self-presentation, other-enhancement, and customer conformity). Our study contributes to the consumer research literature by examining provider evaluation and discovering the peer-to-peer (P2P) dynamic evaluation mechanisms that adopt a two-way rating system.