Journal of Consumer Behaviour最新文献

The article explores life-role transitions, which refer to the changes in a person's identity, roles, and responsibilities as they progress through different life stages. This study posits nostalgic consumption as a novel coping mechanism for managing life-role transitions. Across four studies, we discovered that consumers showed a preference for nostalgic products during periods of life-role transition, with self-authenticity threat serving as the core mechanism that could be mitigated through the consumption of nostalgic items. Individuals with an independent self-construal are less influenced by external environments and thus may experience a mitigated impact of life-role transitions on nostalgic consumption preferences. Theoretically broadening life-role transition studies and deepening insights into self-authenticity, this research practically equips marketers with strategies to target consumers during life-role transitions, thereby enhancing the effectiveness of nostalgic consumption marketing.

This research explores the potential of imbuing AI-based chatbots with human-like communication styles, such as warmth or competence, and suggests that tailoring a chatbot's communication style to align with customer characteristics can be a strategic approach that enhances consumers' purchase intentions. To test the hypotheses, I conducted two pre-tests and three experiments. The results indicate that individuals with a promotion-focused orientation exhibit enhanced purchase intentions when interacting with a warm-style chatbot, while prevention-focused individuals show increased purchase intentions when engaging with a competent-style chatbot. Additionally, this effect is mediated by perceived engagement. The current research enriches the literature on AI-powered chatbots by applying regulatory fit theory to explore ways to enhance the efficiency of human–chatbot interaction in digital environments and provides valuable managerial insights.

The development of artificial intelligence (AI) technology has driven the widespread use of smart (AI) services and significantly enhanced consumer convenience and personalized experiences. However, contextual bias in smart (AI) services can significantly and negatively impact consumers' experiences and hinder the sustainable development of smart (AI) services. To investigate the effect of contextual bias in smart (AI) services on consumers' usage intention and identify its mediating mechanism and ways to mitigate the negative impact, we introduce the explanatory role of information processing fluency to examine the moderating role of anthropomorphism. We adopted an experimental approach, setting up four different experiments. Studies 1 and 2 investigated the effects of different forms of contextual bias on consumers' usage intention; cultural bias impacted consumers more negatively than personal bias did, and information processing fluency mediated the effects of contextual bias on the consumers' usage intention of smart (AI) services. Studies 3 and 4 showed that this process was moderated by anthropomorphism. Social orientation (vs. task orientation) better moderated cultural bias, and low-form anthropomorphism (vs. high-form anthropomorphism) better moderated personal bias.

As technology evolves, balancing product and service personalization with privacy protection remains a critical challenge for businesses and consumers. So, researchers have raised concerns about the potential negative effects of data-driven marketing. This study embarks on a journey to unravel the intricacies of consumer attitudes toward privacy within data-centric marketing. Our research design is underpinned by a mixed methodology that uses qualitative and quantitative research methods. Initially, we presented text mining of Iranian tweets on X (Twitter). Subsequently, we expounded upon the intricacies of the structural equation model and the clustering process. The research findings highlight cultural disparities in attitudes toward privacy and collectivist countries such as Iran prioritize privacy vigilance, as they are meticulous about information disclosure. Notably, Iranians of varying genders, ages, and educational backgrounds displayed distinct levels of privacy apprehension. Based on the text of Twitter data mining, data confidentiality stands as the paramount pillar of data privacy, and they have expressed dissatisfaction with things like “Leakage of information and sale of users' data” and “Hacking the data of an online business”. Also, four clusters were identified for privacy in data-driven marketing: (1) Privacy Balancers, (2) Privacy Guardians, (3) Privacy Nomads, and (4) Privacy Advocates. Finally, suggestions were presented to businesses and policymakers. Especially, businesses can use gamification techniques such as interactive challenges to engage customers in reading and understanding privacy policies.

This study explores the positive and negative effects of perceived smartness and humanness on consumer acceptance of service robotic agents, particularly, regarding the formation of value creators such as trust and positive attitude toward human–robot interactions (HRIs) as well as value destructors such as perceived stress and negative emotion. Data were collected through a combination of fieldwork and experimental methods. The first study, a fieldwork approach, was conducted in a library that deployed the Temi robot. Findings from the fieldwork show the significant effects of robot smartness on stress and robot humanness on trust. Moreover, trust partially mediated the effect of robot humanness on intention to use. The second study comprised an online scenario-based experiment designed to extend the findings from Study 1. The experiment validated the effects of perceived smartness on the value destructors and the effects of perceived humanness on the value creators. The study pinpoints the distinctive factors that impact consumer acceptance of service robots, offering actionable insights for deploying service robotic agents in frontline settings. By prioritizing design features that optimize HRIs, this research bridges the gap between theory and practice, providing a realistic view of consumer interactions with service robots.

Advances in artificial intelligence (AI) have changed the relationships between humans and machines. AI can exhibit human-like characteristics in its behavior, prompting humans to view it as a semi-human. Companies embed humanlike traits in AI to facilitate interaction with consumers. As humanlike traits in AI increase, people may perceive it as eerie. Yet, there is no consensus on the effect of search modalities (text vs. voice) on humanlike traits in AI. In addition, it is not clear which humanlike traits in AI influence eeriness and purchase intention. To address the gaps, we utilized anthropomorphism theory and human psychological needs to identify why people perceive more autonomy, competence, and social presence in voice-based AI compared with text-based AI. We employed a quasi-experiment (one group) consisting of 385 participants, and two experiments: pretest 2 consisted of 130 participants (two groups: experimental and control groups) and the main experiment consisted of 528 participants (two groups: experimental and control groups). We used Amazon Mechanical Turk and recruited participants in the USA who completed between 500 to 1000 HITS with a 90% approval rate. Results reveal that voice searching in AI evokes greater autonomy, competence, and social presence. Utilizing the uncanny valley effect, results showed that perceived competence lowers perceived eeriness and thereby enhances purchase intention. Although social presence enhances perceived eeriness, it increases purchase intention. In addition, perceived autonomy triggers eeriness, yet it increases consumers' purchase intention for low-involvement products. Additionally, we examined the interaction effects of self-construal and autonomy, competence, and social presence on eeriness. We also suggest practical implications for AI developers and research limitations, and directions for future research.

This study seeks to address the existing gap by examining how consumer responses vary based on the type of corporate social responsibility (CSR) activity and communication channels through two experimental studies. Study 1 investigates the effects of CSR activity on CSR perception and moral elevation, while also exploring the moderating role of cultural orientation, specifically individualism versus collectivism. Study 2 focuses on the influence of CSR activity and communication channels on consumer attitudes, moderated by consumer skepticism. The findings indicate that CSR activity significantly shapes consumer perceptions and moral elevation. Additionally, individualism and collectivism were found to moderate the impact of CSR activity on CSR perception. Furthermore, the interaction between CSR activity and communication channels differentially affects consumer attitudes depending on the level of consumer skepticism. Lastly, CSR perception and moral elevation emerged as important mediators in the relationships between CSR activity and consumer citizenship behaviors.

While existing studies primarily explore the echo chamber effect in bipolar discourse, this study demonstrates that echo chambers also influence consumer behavior, where like-minded consumers significantly shape their peers' preferences. We propose a comprehensive model that identifies and analyzes echo chambers through consumers review text and network structures. Key findings from two real-world datasets reveal that like-minded consumers exhibit greater alignment in review content, stronger network cohesion, and more consistent behavioral patterns over time compared to non-like-minded consumers. These findings highlight the short-term influence of peers and the reinforcement of opinion trajectories, providing valuable insights into consumer behavior and marketing strategies. Furthermore, our results validate existing theories in consumer behavior, including social influence, confirmation bias, and online brand communities.