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The purpose of this paper is to draw on social exchange theory and heuristic–systematic model to examine how peer-to-peer (P2P) lending firms can enhance their customer acquisition by achieving mobile social media popularity.

Content data collected from multiple sources (websites and mobile applications) were employed to validate the research model.

The mobile social media popularity of P2P lending firms positively influences their customer acquisition. Furthermore, the heuristic cues (i.e. source credibility and content freshness) and the systematic cue (i.e. transaction relevance) potentially affect the firms’ mobile social media popularity.

Mobile social media is not only a platform for firms’ image-building but a critical means of acquiring actual customers. The appropriate use of heuristic–systematic cues in a mobile interface is useful for firms to achieve high user popularity despite the challenges derived from the mobile context.

To achieve higher user popularity in the competitive online world, firms should dedicate greater effort in determining the adequate heuristic–systematic cues designed for the interface of their mobile social media account. The effect of popularity can then help the firms acquire more customers.

This study extends the understanding of social exchange in the context of mobile social media accounts and enriches the knowledge on business value of mobile social media popularity. This paper also contributes to the literature by relating heuristic–systematic cues to firms’ mobile social media popularity.

The helpfulness vote is a type of aggregate user representation that, by measuring the quality of an online review based on certain criteria, can allow readers to find helpful reviews more quickly. Although widely applied in practice, the effectiveness of the voting mechanism is unsatisfactory. This paper uses the heuristic–systematic model and the theory of dynamics of reviews to shed light on the effect of various information cues (product ratings, word count and product attributes in the textual content of reviews) on online reviews’ aggregative voting process. It proposes a conceptual model of seven empirically tested hypotheses.

A dataset of user-generated online hotel reviews (n = 6,099) was automatically extracted from Ctrip.com. In order to measure the variable of product attributes as a systematic cue, the paper uses Chinese word segmentation, a part-of-speech tag and word frequency statistics to analyze online textual content. To verify the seven hypotheses, SPSS 17.0 was used to perform multiple linear regression.

The results show that the aggregative process of helpfulness voting can be divided into two stages, initial and cumulative voting, depending on whether voting is affected by the previous votes. Heuristic (product ratings, word count) and systematic cues (product attributes in the textual content) respectively exert a greater impact on the two stages. Furthermore, the interaction of heuristic and systematic cues plays an important role in both stages, with a stronger impact on the cumulative voting stage and a weaker one on the initial stage.

This paper’s findings can be used to explore improvements to helpfulness voting by aligning it with an individual’s information process strategy, such as by providing more explicating heuristic cues, developing different methods of presenting relevant cues to promote the voting decision at different stages, and specifying the cognitive mechanisms when designing the functions and features of helpfulness voting.

This study explores the aggregative process of helpfulness votes, drawing on the study of the dynamics of online reviews for the first time. It also contributes to the understanding of the influence of various information cues on the process from an information process perspective.

The 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.

This study synthesizes findings from 100 previous empirical works through the application of meta-analysis.

The 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.

The 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.

This study aims to explore the impact of emotional cues in knowledge product descriptions on users’ willingness to gather information. It specifically focuses on how different types of textual emotional cues, including heuristic cues like “emotional titles” and systematic cues like “emotional synopses,” influence users’ information-gathering willingness and examines the mediating role of emotional arousal in this process.

A conceptual model was developed by integrating the heuristic-systematic model with cue utilization theory. The experimental design employed knowledge product descriptions from the “Knowledge Column” section of the Zhihu platform. A controlled experiment was conducted to investigate the effect of varying emotional cues in these descriptions on participants’ willingness to gather information.

The study identified two types of emotional cues – heuristic cues, such as “emotional titles,” and systematic cues, such as “emotional synopses” – that significantly and positively influence users' information-gathering willingness. Additionally, emotional arousal was found to mediate the relationship between emotional cues and users’ willingness to gather information in the context of knowledge payments.

This study confirms that emotional cues in knowledge product descriptions, mediated by emotional arousal, can enhance the information-gathering willingness of knowledge payment users. The research deepens the theoretical exploration of information behavior among online knowledge payment users, providing valuable insights for knowledge producers on effectively leveraging emotional cues to attract potential customers as well as offering guidance for knowledge payment users in their information-gathering practices.

The continued evolution of influencer marketing has created a need to better understand influencer marketing effectiveness. With brands increasingly partnering with influencers, research is yet to provide an integrated perspective examining the critical role of both parties. This study aims to draw on the source credibility model and signaling theory to explain the mechanisms that matter in influencer marketing effectiveness.

The proposed model of influencer marketing effectiveness is analyzed using partial least squares with data from 281 followers of social media influencers.

The authors establish influencer characteristics of popularity and attractiveness as heuristic cues that inform judgments of influencer efficacy. Further, category involvement and altruistic motives for collaboration are shown to moderate followers’ reliance on these heuristic cues. Then, a sequential mediating effect demonstrates the critical roles of the influencer and partner brand in three desired outcomes: enhanced perception of brand authenticity, enhanced brand engagement and positive attitudes toward influencer posts.

Future research should consider other heuristic cues that could inform influencer efficacy judgments and switch the focus toward the partner brand’s impact on such judgments.

A step-by-step visual framework is presented to help marketers and influencers translate these findings into key responsibilities for developing more effective and collaborative partnerships.

Besides presenting an integrated perspective, signaling theory provides an original lens for explaining influencer marketing effectiveness, addressing the need to expand the theoretical boundaries of influencer marketing research. 

Consumer-perceived review attitude determines consumer overall information adoption and is a core part of consumer’s online-shopping. This study aims to focus on factors that could influence consumer review attitude and can be used by marketers to shape individual information perception.

The study used the questionnaire method to collect data from online shoppers and the modelling of structural equations as an empirical approach to analyse the data.

The findings demonstrate that both systematic and heuristic cues impact the reviewer’s credibility and perceived website attitude differently, which, in turn, influence review attitude. Review characteristics, such as factuality, consistency and relevancy, have a positive relationship with reviewer credibility, while only review consistency and relevancy appears to have a relationship with review attitude. Website characteristics such as reputation, familiarity and social interactivity positively influence the website attitude, which positively influences review attitude. Apart from this, review skepticism has a significant negative relationship with review attitude.

This study could help to foster a positive attitude towards online reviews. Digital marketers need to motivate trusted reviewers to post consistent, fact-based reviews. Further improving the overall website reputation and interactivity could bring a positive attitude towards the reviews. Also, digital marketers must filter and avoid contradictory reviews or reviews that have a bipolar message and reviews expressing numerous emotions to enhance review relevance and consistency.

The current study addresses the need to understand the formation of consumer review attitude through both review and website characteristics using heuristic – systematic model. The paper captures the complex process undergone by the consumer to decipher review attitude and thereby extend the understanding of consumer information processing.

As the epidemic of online fake news is causing major concerns in contexts such as politics and public health, the current study aimed to elucidate the effect of certain “heuristic cues,” or key contextual features, which may increase belief in the credibility and the subsequent sharing of online fake news.

This study employed a 2 (news veracity: real vs fake) × 2 (social endorsements: low Facebook “likes” vs high Facebook “likes”) between-subjects experimental design (N = 239).

The analysis revealed that a high number of Facebook “likes” accompanying fake news increased the perceived credibility of the material compared to a low number of “likes.” In addition, the mediation results indicated that increased perceptions of news credibility may create a situation in which readers feel that it is necessary to cognitively elaborate on the information present in the news, and this active processing finally leads to sharing.

The results from this study help explicate what drives increased belief and sharing of fake news and can aid in refining interventions aimed at combating fake news for both communities and organizations.

The current study expands upon existing literature, linking the use of social endorsements to perceived credibility of fake news and information, and sheds light on the causal mechanisms through which people make the decision to share news articles on social media.

This study is based on the heuristic-systematic model (HSM) to dynamically examine the effect of review variance on sales and the boundary conditions that mitigate this effect.

Based on the theoretical domain of HSM, a conceptual model is proposed that analyzes the nonlinear relationship between review variance and sales and the interaction and motivation factors that moderate these relationships. Review data from websites targeting the film industry in the USA and South Korea (Korea) were collected to empirically analyze the authors' hypothesis, and panel regression analysis was used for confirmation.

Moderated by interactive and motivational factors, review variance exhibits an inverse-U-shaped relationship with review variance. Specifically, as an interaction factor, review valence and owned social media (OSM) resulted in positive interaction effects, and as a motivation factor, the number of alternatives exhibited a positive interaction effect with review variance. The effect of review variance was less pronounced in the USA than in Korea.

The study outcomes reveal a nonlinear relationship between review variance and sales, thus supporting the contradictory findings of previous studies. This study contributes to the literature by using the HSM as a theoretical framework to verify various HSM mechanisms using online review data. This exploratory study also contributes to the international marketing literature by showing that the effects of review variance vary across cultures.

The purpose of this study is to find the role of online informediaries on the perspective of price comparison and information aggregator. Specifically, the author wants to explain how the level of product involvement moderates the effect of price dispersion and product information quality on attitude toward product in online informediaries.

The data for this study are obtained from a three‐way factorial experimental research design. Data were collected from 258 college students who have an experience with an online informediary. Combining ANCOVA and regression analysis enables the study of attitude formation and yields encouraging results.

The study finds that high‐involvement consumers focus on systematic cues (e.g. product attributes) in evaluating product quality. However, when they feel that their initial search yields insufficient results, causing them to perceive more product performance risk, they search for additional cues (e.g. price dispersion). Low‐involvement consumers are mainly affected by price dispersion, which is a heuristic cue, and they evaluate the product more favorably under a high (vs low) level of price dispersion.

This paper is one of the first to consider and empirically test a heuristic‐systematic model for attitude toward product in online informediaries. It also uniquely tests the level of price dispersion to discern the important motivating factors.

Listing popularity indicates the public’s interest in a listing on peer-to-peer (P2P) accommodation platforms. Although listing popularity is crucial to the survival and development of the P2P accommodation platform, this issue has received limited attention in the tourism management discipline. Drawing upon the heuristic-systematic model and uncertainty reduction theory, this study aims to examine the impacts of host and property attributes on listing popularity.

The model was empirically validated using a data set of 6,828 listings on a popular P2P accommodation platform called Airbnb. This study chooses a hierarchical regression analysis to perform the model validation.

The findings reveal that host self-disclosure, host reputation and host identity verification are key host attributes in promoting listing popularity. Meanwhile, property visual description, property photo verification and property visual appeal are important property attributes in facilitating listing popularity.

The study adds useful insights on understanding on determinants of listing popularity. Future researchers are recommended to empirically verify the underlying psychological mechanism by which host attributes and property attributes influence listing popularity.

The P2P accommodation platform should promote the listing popularity by taking advantage of the host attributes and providing property attributes.

First, to the best of the authors’ knowledge, this study is one of the few studies to explore the formation of the listing popularity. Second, this study examines how the host and property attributes promote the listing popularity through the heuristic and systematic information processing modes.