Live streaming has emerged as a critical channel for connecting farmers with markets. However, the majority of farmers lack e-commerce operation experience, often presenting awkwardly and expressing themselves inadequately during live streaming, which significantly hinders sales performance. Virtual streamers, with their characteristics of round-the-clock availability and extensive knowledge reserves, inject new momentum into agricultural live streaming. Nevertheless, how to efficiently leverage virtual streamers to expand sales channels remains a key issue requiring urgent resolution. Based on the source credibility theory and trust transfer theory, this study focuses on the influence of virtual streamers' source credibility (i.e., trustworthiness, expertise, attractiveness, similarity) on purchase intentions in agricultural live streaming, and explores the mediating role of swift trust and the moderating effect of platform reputation. An analysis of 607 valid questionnaires reveals that virtual streamers' source credibility has a positive impact on purchase intention, with swift trust playing a mediating role in this relationship. Moreover, platform reputation not only positively moderates the effect of virtual streamers' source credibility on swift trust but also moderates the effect of swift trust on purchase intention. Additionally, fuzzy-set qualitative comparative analysis (fsQCA) identifies five configurational paths that trigger high purchase intention. This research expands the research perspective on virtual streamers in agricultural live streaming and provides theoretical references and practical guidelines for optimizing the application strategies of virtual streamers in agricultural live streaming.
Crowdfunding platforms (CFP) are increasingly interested in enhancing their impact, by funding projects with positive environmental and social impacts. This article is the first that models the CFP strategies in this context. We compare two attitudes: a neutral (passive) facilitating attitude and an active one. In the latter case, the CFP implicitly favors a subset of the projects by promoting them to the crowd. We model the utility of the CFP, linked to its monetary outcome and the impact of the funded projects, and formulate an optimization problem that maximizes it by acting on the promotion strategy. We show how to solve this problem using real options and dynamic programming. For applying this framework, we perform an empirical study based on a large dataset that quantifies the attractiveness gain for projects when they are promoted by the platform. We then propose a novel hybrid empirical/analytical method, where platform data is processed and provides input parameters to the optimization tool. Our results show that substantial gains are expected when applying the optimization framework with respect to a platform adopting a classical passive attitude. Our study provides guidelines for platform managers on how to design and implement strategies that maximize their impact.
Livestreaming commerce has become a key sales channel, yet streamer communication effectiveness, particularly their spoken content volume across selling steps, remains underexplored. Drawing on social exchange and complexity theory, we argue that multiple interdependent configurations of selling steps can lead to high product sales, consistent with the principle of equifinality. Focusing on snack products, this research examines how content volume allocation across four selling steps-approach, presentation, overcoming objections, and close sales-impacts product sales. Using fuzzy-set qualitative comparative analysis on data from a major snack brand's livestreams, we identify three configurations associated with high product sales: (1) high content in approach, presentation, and close sales, with low overcoming objections; (2) high content in approach, overcoming objections, and close sales, with low presentation; and (3) high presentation with low approach and close sales (with overcoming objections as peripheral). Conversely, misalignment between approach and close sales, despite high presentation, is linked to low sales. These findings underscore the configurational nature of effective selling: multiple combinations of content volume across the four steps can drive high product sales. Further, the findings reveal that presentation and overcoming objections can substitute for each other, while approach and close sales are complementary. This research advances understanding of streamer communication effectiveness and provides actionable guidance for streamers on structuring scripts to improve sales.
In today's digital era, where celebrities hold immense influence over consumer behavior, understanding the factors that shape trust and online purchase toward endorsed brands is crucial. Especially, in the landscape of celebrity endorsement, the effectiveness of celebrity authenticity, online celebrity fandom, and their interaction has been fruitful yet underexplored research direction. Drawing upon signaling theory and trust transfer mechanism, we conducted a 2 & times;2 between-subjects factorial design experiment to examine how signals from celebrity authenticity and sense of online fandom affect trust development and subsequent online purchase among consumers. Data from 200 participants were analyzed using MANCOVA and PLS-SEM. Our findings indicate that high celebrity authenticity and a sense of healthy fandom lead to greater wishful identification and celebrity trust. Additionally, the effects of perceived celebrity authenticity on wishful identification and celebrity trust are stronger in the presence of a sense of healthy fandom compared to toxic fandom. Furthermore, wishful identification directly influences consumers' online purchase intentions, while brand trust fully mediates the effect of celebrity trust on purchase intention. This original study pioneers experimental research on the joint effects of celebrity authenticity and online fandom, advancing signaling theory and trust transfer literature within the e-commerce and celebrity endorsement context.
In the current e-commerce marketing environment, artificial intelligence (AI) recommendation systems are widely used in various business scenarios, but little attention has been given to their application to social goods. On the basis of the persuasion knowledge model and goal framing theory, this study explores the mechanism of the recommendation approach (AI vs. human) in promoting consumer purchase behavior related to social goods. Three experiments are conducted, which show that AI recommendations have significant advantages in increasing consumers' intention to purchase social goods on e-commerce platforms. Specifically, perceived manipulative intention serves as a mediator between the recommendation approach (AI vs. human) and consumers' purchase intentions. Additionally, goal framing moderates the effects of the recommendation approach on consumers' purchase intentions: consumers respond more positively to AI recommendations under loss framing, whereas human recommendations have greater persuasive power under gain framing. This study expands the application scenarios of AI recommendation in the field of social marketing and enriches the theoretical explanatory power of persuasion knowledge models in the promotion of social goods via e-commerce.
Online reviews are vital for e-commerce, yet motivating consumers to write them remains challenging. While financial incentives are commonly used, they can crowd out altruistic motives, leading to suboptimal outcomes. Drawing on Social Exchange Theory, this study examines how the beneficiary of altruism (the company vs. other customers) moderates the impact of incentives on review-writing decisions. We test our hypotheses in a quasi-experimental field study in collaboration with a major North American online retailer and a controlled experiment. Our findings show that reinforcing altruism through helping the company negatively interacts with financial incentives compared to helping other customers. We contribute to the literature on altruism, Social Exchange Theory, and eWOM creation and propose a cost-effective and straightforward modification to review solicitation messages to boost review volume.
Mobile health apps (mHealth apps) offer dietary guidance to consumers, and they often include recommendations for novel foods. While research has examined consumers' acceptance of novel foods, the role of mHealth apps in influencing consumers' decisions to accept novel foods is still unclear, given the novelty and uncertainty surrounding them. Based on the affordance theory, this paper explores how the affordances of mHealth apps influence consumers' perception of food novelty and food neophilia, and the moderating effect of novel food market availability on consumers' food neophilia. This study combines PLS-SEM with fsQCA to obtain a nuanced understanding of their role. The PLS analysis reveals that the two affordances of mHealth apps (i.e., food customization and food guidance) significantly influence consumers' formation of food neophilia. The results also indicate that the market availability of novel foods has a positive moderating effect on the shape of food neophilia. The fsQCA analysis identifies three configurations that lead to high food neophilia, with food novelty being an indispensable condition for the formation of high food neophilia. The findings of this paper enrich the theory of technology affordance and food neophilia and provide practical guidance for mHealth app development.
Social bots have emerged as sophisticated agents in online communities, serving as a practical lens through which the societal implications of artificial general intelligence can be explored. These bots can participate in various positive social interactions, including the provision of entertainment services and community moderation, but some bots have negative effects, such as spreading misinformation. Therefore, to maintain the harmony of online communities, it is crucial to distinguish between "good" and "bad" bots and to identify the characteristics that can be used to make this distinction. Using the elaboration likelihood model, this study integrates text and sentiment analysis with machine learning algorithms to explore what makes bots good from a user perspective. Drawing on data from Reddit, we analyze how the textual sentiment and textual paralanguage embedded in bot-generated comments drive positive social interactions. Our results indicate that textual sentiment, processed via the central route, has a stronger impact on user evaluations than textual paralanguage, which operates through the peripheral route. Overall, our study offers important insights into bot design and the factors that promote positive social interactions within online communities, thus supporting platform governance.
Negotiation, a time-consuming process, necessitates empathy to resolve conflicts and reach agreements. While AI-based automated agents gain prevalence in e-commerce, our understanding of how the evolution of empathic agents could function in human-to-agent negotiation is still lacking. Motivated thus, this study, drawing on social response theory and empathy literature, develops a research model to investigate how the user-perceived negotiation agent's empathic capability could influence their continuous use intention. The research model is tested with subjective (i.e., survey) data collected through a novel, self-developed e-commerce negotiation platform with an empathic agent. Our results show that the perceived agent's empathic capability positively influences users' trust and satisfaction towards the agent, further impacting their continuous use intention. Notably, users' perceived control over the negotiation moderates the relationship between the perceived empathic capability and trust. This study contributes to the research on automated negotiation agents and empathy, offering practical implications for designing negotiation agents.
Gamification has become a trend in the field of sustainability. To enhance consumers' intention to use and return reusable packaging, this study develops a gamified technology approach to elaborate on the motivations that drive users' engagement in sustainable behaviors. It investigates the impact of green psychological benefits generated during the gamification technology experience on the behavior of using and returning reusable packaging. A PLS-SEM model is developed to examine the influence of external and internal motivations stimulated by gamification design elements on the green psychological benefits, which drive consumers' behavioral outcomes of using and returning reusable packaging in e-commerce. This study finds that intrinsic and extrinsic motivations have a significant and positive impact on green psychological benefits and, in turn, significantly and positively influence consumers' intentions to use and return reusable packaging. Furthermore, the research confirms that the warm glow effect has a partial mediating effect on the link between intrinsic motivation and intention to use and return reusable packaging. This study contributes to the theory and practice of social sustainability marketing technology by enhancing the understanding of customer motivations and behavioral intentions in e-commerce in the sustainable gamification context.
This study explores how sensory experiences, specifically visual, audio, and haptic elements, influence user perceptions in mobile payment contexts. Using structural equation modelling, the findings reveal that hedonic factors have a stronger impact on user experience than utilitarian considerations, even when financial transactions are involved. A complete sensory experience was found essential, as the model became invalid when any single modality was removed. A multigroup analysis was conducted to examine the moderating effect of prior experience by comparing users and non-users of mobile payments. While users rated their experiences more favorably, only limited differences in the structural model were statistically significant. This suggests that familiarity may not play as strong a role as previously assumed. The findings offer insights into interface design and mobile technology adoption, highlighting the need to prioritize enjoyment and multisensory feedback in mobile payment systems.
The desire for luxury goods, such as boutique bags, is increasing, partly because of key opinion leaders on social media. However, the high price of these products poses a barrier to purchase. Although the subscription business model improves access to boutique bags for many people, whether consumers accept such a model is unclear. Therefore, we adopted and extended the scope of the unified theory of acceptable use of technology framework to understand which factors drive acceptance of subscription-based services. We replaced performance expectancy with perceived benefit, which comprises seven components, and we replaced effort expectancy with perceived risk, which covers psychological, social, and financial risks. Through survey data collected from 196 consumers who have experience with boutique bags, we discovered that although perceived benefit and social influence encourage use, perceived risks hinder subscription intention. Furthermore, with fsQCA, we identified the configurations of forming high subscription intention and low subscription intention.
The advancements in mobile technology have transformed the mobile shopping environment, providing consumers with greater convenience and personalized experiences. However, despite the proliferation of various platforms, product detail pages often follow a standardized design, missing opportunities to enhance consumer engagement. This study aims to investigate the impact of background colors on consumer perceptions and attitudes toward mobile shopping product pages, using Higgins' Regulatory Focus Theory as a theoretical foundation. The results indicate that black backgrounds, symbolizing stability and seriousness, foster positive attitudes among prevention-focused consumers by meeting their preference for reliability and security. In contrast, white backgrounds, associated with brightness, optimism, and vibrancy, are more appealing to promotion-focused consumers, who are driven by growth and achievement. These findings emphasize the psychological influence of background color, demonstrating its potential as a strategic element in e-commerce design. This study provides practical implications for marketers and designers aiming to deliver more tailored consumer experiences in mobile shopping environments.
Online social referral programs (SRPs) have emerged as a crucial marketing strategy in social e-commerce, and information presentation format significantly influences referral effectiveness. Online threshold social referral programs (TSRPs) were recently practiced by companies like Pinduoduo, which require the established consumer (referrer) to complete multiple tasks (e.g., inviting a specified number of new consumers to register or place an order) before rewards are cashed and provide no rewards in case of incompletion. This study explored the mechanisms by which information presentation format in TSRPs affect consumers' referral intentions. Based on the heuristicsystematic model, two information presentation formats were identified: reward- and task-oriented. Four experiments were conducted to examine their impact on consumers' referral intention and the mechanism. Reward-oriented information presentation was found to enhance consumer's referral intention, while social distance between referrer and referee moderated the referrer's referral intentions. By anchoring the consumer's attention on the benefits of the referral task, the reward-oriented presentation improved their referral intention, aligning with intuitive analysis in heuristic information processing. In contrast, task-oriented presentation, which draws attention to the cost associated with the referral task, did not significantly decrease referral intention, in accordance with rational analysis in systematic information processing. As social distance increases, consumers were more inclined to consider benefits for others in their decision-making processes, with their attention increasingly focused on the benefits gained from the referral task, which strengthens the enhancement effect of reward-oriented information presentation on referral intentions. This research offers valuable insights for improving information presentation formats to enhance the effectiveness of online social referral programs.
This research aims to discuss the advantages and disadvantages of native and display ads and argues that the winner-takes-all rule does not apply here. We conducted an experimental study and manipulated the two forms of advertising (native ad & display ad) on the news website page. Voluntary participants were recruited to the laboratory and were given the reading task. Participants' gaze behavior, brand attitude and brand memory were measured in this study. Across two experiments, this research demonstrated that native ad generates more consumer gaze and greater brand memory than do display ad, but display ads more effectively increase brand attitudes. Findings from this study provide insights into the difference advertising effectiveness between display ads and native ad. The winner-takes-all rule does not apply because different formats affect different aspects of consumer behavior. The finding suggests that advertisers should define their goal when choosing the types of ads to purchase.
The pervasive phenomenon of silence significantly impacts the operation and development of online communities; however, there is limited research on the positive and negative effects of the silent behavior of online community members. Drawing on social exchange theory, this study examines the influencing factors and consequences of two types of silent behavior of online community members: anti-community silent behavior and procommunity silent behavior, from the perspective of perceived trust in online communities. We further analyze the moderating role of online anonymity. Based on empirical research results from 538 valid questionnaires, we find that the silent behavior of online community members has a double-edged sword effect on performance, with perceived trust identified as a key factor influencing silent behavior. Additionally, it was further discovered that pro-community silent behavior mediates the impact of perceived trust on online community member performance, and online anonymity negatively moderates the influence of perceived interpersonal trust on anti-community silent behavior. This study extends the theoretical application of social exchange theory in the field of online silent behavior and provides constructive suggestions for the practical operation of online communities.
Online health platforms often struggle with high user turnover, making it essential to attract and retain patients. Knowledge sharing has emerged as a key strategy in this effort. However, previous studies have shown that physicians benefit from knowledge sharing through reputational gains and indirect financial returns, the mechanisms driving these effects remain unclear. This study draws on sensory marketing and feeling-as-information theory to examine how sensory cues of linguistic features in physicians' knowledge sharing influence their online service volume. Using structured and unstructured data from 307 physicians with 3,834 knowledge-sharing instances in online health platforms in China, we apply text mining and empirical modeling to test our hypotheses. Our findings indicate that haptic cues in physicians' knowledge sharing positively impact their online service volume, whereas auditory cues have a negative effect. Moreover, the influence of these sensory cues varies depending on physicians' specialties and professional capital. By integrating sensory marketing into the study of online healthcare, this research advances the understanding of how linguistic features in knowledge sharing drive physicians' financial returns.
Both academia and industry seek to design ad features that improve user experience, increase ad effectiveness, and retain users on video platforms. This study investigates ad exhibition, a key advertising strategy that manipulates distribution of ads within videos. Grounded in information processing theory, we examine how ad exhibition influences user cognitive and affective responses, including brand recall, perceived waiting time, purchase intention, and user satisfaction. Results from two online experiments reveal that dispersed ad exhibition enhances brand recall and reduces perceived waiting time; however, this effect is significant only for lengthy videos. Further analysis demonstrates that brand recall mediates the effect of ad exhibition on purchase intention, while perceived waiting time mediates its impact on satisfaction. A controlled lab experiment conducted with a student sample closely simulated real-world scenarios, providing robust evidence for the validity of the aforementioned conclusions. The present research adds to the existing literature on advertising by shedding light on the interaction of advertising. The study offers valuable insights on how to optimize the placement of ads in order to enhance revenue and attract users.
This study aims to present a comprehensive framework elucidating the trajectory from trust establishment to user adoption intention of chatbots. Through a quantitative analysis of the role of trust in user adoption intention of chatbots, we seek to reconcile and clarify inconsistencies found in previous research and evaluate the robustness of its antecedents. In total, 54 papers comprising 18,707 samples were summarized through the meta-analysis. We categorized trust antecedents based on the Heuristic Systematic Model, subsequently dissecting trust into cognitive and emotional dimensions to scrutinize their impact on user adoption intention. The findings indicate that among systematic factors, chatbot competence and risk exhibit strong correlations with emotional trust, whereas competence and personalization are positively correlated with cognitive trust. All heuristic factors (anthropomorphism, social presence, social influence) demonstrate relatively strong positive correlations with both cognitive and emotional trust. The interaction between emotional and cognitive trust is affirmed, with trust significantly fostering user adoption intention of chatbots. Moreover, this study tests the moderating effect of sample characteristics (culture, IT penetration), chatbot features (text-driven vs. voice-driven, task-oriented vs. conversation-oriented), and usage industry. Theoretical contributions and practical implications are also derived toward the end.
Artificial Intelligence (AI) is increasingly being viewed as critical for organizational decision-making and the long-term competitiveness of firms, demanding upskilling in human-AI interaction and delegation. While trust, informed by estimated AI accuracy, is critical for such collaboration, inconsistencies between these estimates and the actual performance of AI systems often occur, potentially leading to negative outcomes. However, the effect of this inconsistency between estimated accuracy and actual performance on human-AI collaboration is not well understood in current literature. Grounded in signaling theory and expectancy violation theory, this study presents a 2 x 2 between-subjects online experiment with the aim of examining the effects of estimated accuracy and actual performance on several dependent variables. The study's results show that while estimated accuracy strongly influences humans' cognitive trust, the inconsistency between estimated accuracy and the actual performance of AI systems leads to misplaced trust, with humans over-trusting low-performing AI systems or distrusting high-performing ones. Such misplaced trust reduces human-AI collaboration performance by weakening the complementarity between humans and AI. These findings contribute to current understanding of the sources and consequences of human trust in AI systems and provide practical guidance for firms wanting to improve human-AI collaborative performance.
