Heuristic-systematic Model Research Articles

Moral Comments in Social Media: Analyzing the Role of Ideology-Matching Moral Framing and Impression Motivation in the Persuasive Effect of User Comments on YouTube

ABSTRACT This research explores how users form attitudes when they are presented with online videos and moral comments from their fellow audience. Based on the Heuristic-Systematic Model (HSM) and Moral Foundations Theory (MFT), the study aims to find out how different moral foundations represented in user comments interact with the motivational state, the political orientation, and the moral beliefs of the viewer. In two pre-registered experiments (N = 314 and N = 1015), the inclusion of moral arguments within comments below a YouTube video (harm vs. authority), their valence (positive vs. negative) and the participants’ motivational states (high vs. low impression motivation) were varied. While Experiment 1 revealed no significant effects regarding the persuasive effect of user comments and accompanying moral arguments, Experiment 2 showed a more general effect of comment valence on viewers’ attitude formation. These results help to specify the conditions under which user comments may lead individuals to construct their attitude in a way that fits the perceived majority opinion.

Do Heuristic Cues Affect Misinformation Sharing? Evidence From a Meta-Analysis

Information overload in online environments leads individuals to be more likely to rely on heuristic cues to make decisions about (mis)information sharing. Drawing on dual-process models of information processing, namely the heuristic–systematic model and the elaboration likelihood model, we conducted a meta-analysis of 31 individual studies to examine the combined effects of five major heuristic cues on misinformation sharing. The results revealed that the affective heuristic of anxiety exerted the strongest impact on misinformation sharing ( r = .343), followed by three cognitive heuristics: the self-confirmation heuristic ( r = .249), endorsement heuristic ( r = .125), and fact-checking heuristic ( r = -.115)—but not the authority heuristic. The endorsement misinformation receives, consistency between misinformation and individuals’ prior attitudes or beliefs, anxiety people feel, and absence of fact-checking labels all make people more likely to share misinformation. Moderation analyses also highlight the importance of considering contextual and cultural factors in future research.

“You’re fired”: the influence of heuristic-systematic processing in communication and termination decisions in organizational environments

PurposeDecisions regarding the termination of organizational members are not only common but also represent difficult actions for managers. Despite their importance and frequency, managers often make or avoid them based on incomplete or faulty decision-making criteria. Previous research suggests that decision-makers are subject to internal influences that play significant roles in their decision-making.Design/methodology/approachUsing a controlled between-groups experimental design, this study, guided by the heuristic-systematic model, tested to what extent decision-makers rely on heuristic cues versus the systematic processing of more relevant information when making termination decisions.FindingsFindings suggest the order in which information is presented influences participants’ decision-making and influences the information-processing structure.Practical implicationsFindings suggest practical considerations for managers, management trainees and others who engage in termination decisions as to potential influencing factors.Originality/valueThis research adds to the understanding of the decision-making process in organizational contexts.

AI in the spotlight: The impact of artificial intelligence disclosure on user engagement in short-form videos

This paper aims to investigate how AI disclosure affects user engagement intention. We try to comprehensively explore the fundamental mechanisms behind AI disclosure and user engagement, along with the boundary conditions that impact the relationship. Based on the heuristic-systematic model, this study built a moderated mediation model and conducted an online experiment on “Credamo” platform. The 479 valid experimental data of the study were analyzed by partial least squares structural equation modeling (PLS-SEM). The results indicate that AI disclosure has a direct, positive impact on user engagement intention, while it could also diminish user engagement intention by lowering users' perceived content quality. However, the negative impact on perceived content quality can be mitigated by improving users’ perceived AI capabilities. This study expands the research focus of AI disclosure and the practical application of heuristic-systematic model, which provides theoretical insights to the artificial intelligence related literature. In addition, we put forward to informed practical recommendations for video content creators and publishers in creating content and promoting user interaction.

Ethical AI in Financial Inclusion: The Role of Algorithmic Fairness on User Satisfaction and Recommendation

This study investigates the impact of artificial intelligence (AI) on financial inclusion satisfaction and recommendation, with a focus on the ethical dimensions and perceived algorithmic fairness. Drawing upon organizational justice theory and the heuristic–systematic model, we examine how algorithm transparency, accountability, and legitimacy influence users’ perceptions of fairness and, subsequently, their satisfaction with and likelihood to recommend AI-driven financial inclusion services. Through a survey-based quantitative analysis of 675 users in China, our results reveal that perceived algorithmic fairness acts as a significant mediating factor between the ethical attributes of AI systems and the user responses. Specifically, higher levels of transparency, accountability, and legitimacy enhance users’ perceptions of fairness, which, in turn, significantly increases both their satisfaction with AI-facilitated financial inclusion services and their likelihood to recommend them. This research contributes to the literature on AI ethics by empirically demonstrating the critical role of transparent, accountable, and legitimate AI practices in fostering positive user outcomes. Moreover, it addresses a significant gap in the understanding of the ethical implications of AI in financial inclusion contexts, offering valuable insights for both researchers and practitioners in this rapidly evolving field.

The more followers the better? The impact of food influencers on consumer behaviour in the social media context

PurposeThe study explores the impact of food influencers on consumer behaviour in the social media context. It assesses the interplay between the number of followers an influencer has and the type of content this influencer communicates to the audience. Doing so, the research contributes to the strategic refinement of influencer marketing practices, especially in the food industry.Design/methodology/approachThe study employed an experimental between-subject design 2 (influencer type: micro vs macro) x 2 (content type: informational vs entertaining). It recruited 197 Prolific participants (45.7% female, Mage = 45.076), testing their perceptions towards the influencer and the endorsed product in the social media post.FindingsThere was a significant interaction between influencer type and content type on consumers’ attitudes towards and their willingness to buy the advertised product. Specifically, the notion that “the more followers, the better” may only be applicable when consumers peruse the content for entertainment purposes, whereas while they read it for information purposes, a micro influencer (with hundreds to thousands of followers) may have as much impact on consumer behaviour as a macro influencer (with hundreds of thousands to a million followers).Originality/valueOur findings offer a nuanced understanding into the conventional wisdom that people often follow crowd behaviour. Using the Heuristic-Systematic Model (HSM), we explicate when the number of followers matters and when the content type prevails.

Assessing credibility in eWOM: a meta-analysis using the heuristic-systematic model

PurposeThe current research delves into how different cues in messages (such as argument quality, usefulness and informativeness) and cues related to the source (such as credibility and expertise) contribute to the perceived credibility of electronic word-of-mouth (eWOM). The investigation also explores whether source cues influence the overall impact of message cues.Design/methodology/approachThis study synthesizes findings from 100 previous empirical works through the application of meta-analysis.FindingsThe outcomes affirm the presence of both systematic and heuristic processing, the additive effects of both message and source cues and the bias effects of source cues. Moreover, the study identifies a connection between eWOM credibility and behavioral intention. Expanding on this, the research discovers that users’ tendency to avoid uncertainty moderates the impact of message and source cues on their judgment of eWoM credibility.Originality/valueThe research contributes to the eWOM literature by providing a heuristic-systematic model of eWoM credibility judgments. It provides new insights for online sellers, who can benefit from eWoM by fostering potential buyers' behavioral intention to purchase.

How foodstagramming posts influence restaurant visit intention: the mediating role of goal relevance and mimicking desire

PurposeThis study aims to explore the role of social media visual posts (known as foodstagramming) on restaurant visit intention. Drawing on the heuristic–systematic model and normative focus theory, this research introduces a framework that assesses the effects of key foodstagramming attributes – vicarious expression, aesthetic appeal and post popularity – and the mediating roles of goal relevance and mimicking desire, in the process.Design/methodology/approachStructural equation modelling was performed to test the proposed model using a sample of tourists (n = 377) and residents (n = 341). Multi-group analysis was performed to compare the differences between these groups.FindingsResults reveal that mimicking desire and goal relevance influence restaurant visit intention; however, mimicking desire has a stronger influence than goal relevance. Little difference was found between the tourist and the resident groups in the proposed relationships, except that vicarious expression positively influences mimicking desire in the tourist group but not in the resident group.Practical implicationsThis study guides restauranteurs and social media influencers (foodstagrammers). It shows that consumers value the textual content and aesthetic appeal of photos over the popularity of a post. It also indicates that vicarious expression is more important for tourists than for residents.Originality/valueThis research advances social media marketing literature by proposing a new information processing framework. To the best of the authors’ knowledge, this study is one of the first studies to explore the impact of visual post attributes on individual decision-making behaviours through socially acceptable norms.

Live streaming product display or social interaction: How do they influence consumer intention and behavior? A heuristic-systematic perspective

The live streaming e-commerce industry is developing rapidly, significantly influencing consumer decision-making processes. Unlike previous studies focusing solely on singular outcomes, this research concurrently examines impulse buying and repurchase intentions. It constructs a theoretical model based on the heuristic-systematic model to validate the effectiveness of two types of marketing signals (product-related signals and interactive signals) in live streaming. Additionally, this study introduces the uniqueness of streamers, products, and performance as moderating variables, aiming to elucidate the mechanisms through which different marketing signals in live streaming affect consumer cognition, impulse buying, and repurchase intentions. Through the collection and analysis of 468 survey responses, this research reveals that viewer-streamer interactive signals and viewer-viewer interactive signals positively impact the narrowing of psychological distance. Simultaneously, product-related signals positively influence the enhancing of consumer perceived value. Furthermore, three interesting moderating effects are identified. By integrating signal theory and the heuristic-systematic model, this study provides a clear depiction of the pathway through which consumers process marketing signals in live streaming, offering theoretical support and practical insights for streamers, platforms, and businesses.

Improving customer satisfaction in the hotel industry by fusing multi-source user-generated content: An integration method based on the heuristic-systematic model and evidence theory

Improving customer satisfaction in the hotel industry by fusing multi-source user-generated content: An integration method based on the heuristic-systematic model and evidence theory

The Influence of Cognitive and Emotional Factors on Social Media Users' Information-Sharing Behaviours during Crises: The Moderating Role of the Construal Level and the Mediating Role of the Emotional Response.

Understanding the intricate dynamics of social media users' information-sharing behaviours during crises is essential for effective public opinion management. While various scholarly efforts have attempted to uncover the factors influencing information sharing through different lenses, the underlying mechanisms remain elusive. Building upon the heuristic-systematic model (HSM) and construal level theory (CLT), this study explores the complex mechanisms that govern social media users' information-sharing behaviours. The results indicate that both cognition and emotion play crucial roles in shaping users' information-sharing behaviours, with systematic cues having the most significant impact on information-sharing behaviours. In terms of heuristic cues, positive emotions are more influential on information-sharing behaviours than primary cognition and negative emotions. Furthermore, spatial distance emerges as a key moderator, influencing individuals' levels of engagement in information sharing. Emotion also acts as a mediator, connecting cognition to information sharing. This study provides insights into the sophisticated mechanisms of information sharing during crises, offering valuable implications for emergency management agencies to utilise social media for targeted public opinion guidance.

Influence of Severity and Susceptibility Information Content on Users’ Psychological Response in Emergencies—The Moderating Effect of Regulatory Focus

Information content is crucial for public opinion governance, yet its psychological mechanisms remain unclear. This paper endeavors to bridge this knowledge gap by examining the influence of information content on users’ psychological responses. Drawing insights from the heuristic-systematic model (HSM) and regulatory focus theory, we constructed a novel cognitive and emotional response model. Regression analysis reveals that susceptibility strongly influences primary cognitive responses, while severity affects secondary ones. Susceptibility has a stronger impact on emotional responses than severity. Promotion-focus users are less influenced by severity and susceptibility than prevention-focus users. These results offer valuable insights for emergency management strategies and enhance individuals’ resilience in coping with the psychological toll of emergencies.

The media-psychological model of environmental risk perception

The article presents the results of a theoretical analysis on the topic of media-psychological aspects of the perception of environmental risks and the presentation of the author's media psychological model of the impact of media messages on the perception of environmental risks. The presented model examines the processes and stages involved in the initial encounter with environmental risk messages in the media and the further outcomes of their processing which can manifest in information-seeking behaviour. According to the presented model, changes in risk perception are considered a series of stages initiated by attention to information and can continue when information-seeking behaviour is triggered. The main models relied on by the author of this study are the Limited Capacity Model of Motivated Mediated Message Processing to describe media message processing and the Risk Information Search and Processing Model to describe aspects of information-seeking behaviour. Several additional communication models dedicated to the consideration of information behaviour and processing of media messages were also used to describe the processes of mass media influence on the perception of environmental risks. Thus, dual models of information processing and persuasive communication are also considered, including the Heuristic-Systematic Model and the Elaboration Likelihood Model, as well as additional theories examining information-seeking behaviour: the Theory of Motivated Information Management and the Planned Risk Information Seeking Model

Examining the influence of source factors and content characteristics of influencers' post on consumer engagement and purchase intention: A moderated analysis

The current research investigates the impact of fashion influencers on consumer engagement and purchase intention. Guided by the heuristic systematic model (HSM), this paper identifies heuristic and systematic factors of an influencer's post that contributes to consumer engagement and purchase intention. Data collected from 471 respondents was studied through path analysis. The results reveal that consumer engagement mediates between source credibility, content characteristics and purchase intention. Furthermore, the findings indicate that product involvement moderates the relationship between source factors, content characteristics and consumer engagement. The study adds to the extant literature and provides managerial insights for the fashion industry by suggesting ways to choose the right influencer and build stronger relationships with consumers.

Exploring the journey of influencers in shaping social media engagement success

This study unfolds nuanced insights into the diverse dimensions dictating the success of social media influencers. Analyzing more than 210,000 social media posts and utilizing the Heuristic-Systematic Model of Information Processing (HSM), this study explores diverse factors, including individual appearance characteristics, depth of persuasive power, and various influencer types. The findings of this study shed light on the distinct impacts of varying influencer archetypes, such as celebrities and micro-celebrities, on user engagement and reveal the nuanced moderating effects of these archetypes on the relationships intertwined with personal attributes, persuasive potency, and influencer success. The proposed model advocates that influencers who leverage more profound, systematic processing strategies, marked by detailed information analysis and conveyance, are poised to experience elevated user engagement compared to counterparts employing heuristic modalities, distinguished by practical mental shortcuts and superficial examinations. This elucidation accentuates the imperative of harmonizing heuristic and systematic methodologies for emerging influencers and brands aspiring to optimize user engagement and efficaciously mold consumer behavior. This paper encapsulates a comprehensive exploration of the dynamic landscapes of influencer marketing via the HSM prism, delivering profound insights and practical ramifications for scholars, marketers, and influencers aiming to navigate and exploit the intricate networks of influential determinants in the ever-evolving digital marketing domain.

Understanding the impact of national culture differences on customers’ online social shopping behaviours

The growth of social media (SM) has contributed to the retail industry. Academics and professionals are specifically intrigued by how the fusion of SM might address the issue of establishing a relationship between consumers and sellers. By integrating insights drawn from the Informational Social Influence Theory (ISIT) and the Heuristic-Systematic Model (HSM), our study developed a model to comprehend factors affecting customers' online social shopping behaviours across various cultural environments. Our study utilised SEM/PLS to analyse data collected from 2305 respondents in four different countries. Findings revealed that the ISIT can be used to understand customers’ online social shopping behaviours. Our study indicated that normative social influence (NSI), informational social influence (ISI), utilitarian value (UTV), perceived member familiarity (PMF), and perceived information quality (PIQ) are key drivers of customers social behaviours in the developed societies, while hedonic value (HDV), perceived member closeness (PMC), perceived member similarity (PMS), and perceived member expertise (PME) are key drivers of customers social behaviour in the developing societies. The results demonstrated that a “one-size fits-all” paradigm is inadequate to capture the heterogeneity of customers social behaviour through various cultures. The theoretical and managerial implications were demonstrated.

Conflicted and Relevant: Systematic Processing of Information on PFAS Contamination

ABSTRACT Per- and polyfluoroalkyl substances (PFAS) contamination is an emerging environmental and public health crisis. Thus, it is crucial to understand public risk perception and communication behaviors surrounding this issue. Guided by the heuristic-systematic model of information processing, this study explores the impact of conflicting information and personal relevance on information insufficiency and information processing. Through an online experiment, 1,062 U.S. adults were randomly assigned to one of four conditions as part of a 2 (information type: conflicting vs. consistent) × 2 (personal relevance: high vs. low) between-subjects factorial design. Both main effect and interaction effect were detected. Specifically, information insufficiency was highest among participants in the high personal relevance and consistent information condition. Personal relevance also had a main effect on information processing. Conflicting information indirectly elevated information processing through increased information insufficiency, but only when personal relevance was low. These findings suggest the importance of providing consistent and personally relevant information related to the risk of PFAS contamination.

Impact of misinformation from generative AI on user information processing: How people understand misinformation from generative AI

This study examines the impact of artificial intelligence (AI) on the ways in which users process and respond to misinformation in generative artificial intelligence (GenAI) contexts. Drawing on the heuristic–systematic model and the concept of diagnosticity, our approach examines a cognitive model for processing misinformation in GenAI. The study’s findings revealed that users with a high-heuristic processing mechanism, which affects positive diagnostic perception, were more likely to proactively discern misinformation than users with low-heuristic processing and low-perceived diagnosticity. When exposed to misinformation from GenAI, users’ perceived diagnosticity of misinformation can be accurately predicted by the ways in which they perform heuristic systematic evaluations. With this focus on misinformation processing, this study provides theoretical insights and relevant recommendations for firms to be more resilient in protecting users from the detrimental impacts of misinformation.

Debiasing misinformation: how do people diagnose health recommendations from AI?

PurposeThis study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.Design/methodology/approachWe proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.FindingsThe effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.Research limitations/implicationsWhen exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.Practical implicationsPerceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.Social implicationsAlthough there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.Originality/valueThe mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167

Promoting university brand through student co-creation behaviors: the role of online brand posts

PurposeThis study investigates the role of social media brand posts on customer response and whether said impacts foster engagement in brand co-creation behaviors, especially in the higher education sector. The study further explores the moderating role of a university's reputation in strengthening the effects on student response and co-creation behaviors.Design/methodology/approachThe authors conducted this research by using the dual processes of the heuristic–systematic model to understand the effects of brand post‐characteristics on student’s responses and behaviors. A dataset obtained from a survey of 755 students was employed to estimate the proposed research model.FindingsThe results illustrated two key characteristics of brand posts, namely argument quality (systematic processing) and quantity of posts (heuristic processing), positively affect cognitive and affective responses, thus encouraging students to co-create value for a university brand. Moreover, our study also found that university reputation plays a significant moderating role in strengthening the relationship between recipients’ responses and co-creation behavior.Originality/valueOnline brand posts not only enable institutions to exchange brand information but also allow students to contribute their own resources to co-create brand value. Thus, the study findings can help brand managers successfully implement co-branding efforts and foster students in the co-creation process.