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The purpose of this paper is to review, critique and develop a research agenda for the Elaboration Likelihood Model (ELM). The model was introduced by Petty and Cacioppo over three decades ago and has been modified, revised and extended. Given modern communication contexts, it is appropriate to question the model’s validity and relevance.

The authors develop a conceptual approach, based on a fully comprehensive and extensive review and critique of ELM and its development since its inception.

This paper focuses on major issues concerning the ELM. These include model assumptions and its descriptive nature; continuum questions, multi-channel processing and mediating variables before turning to the need to replicate the ELM and to offer recommendations for its future development.

This paper offers a series of questions in terms of research implications. These include whether ELM could or should be replicated, its extension, a greater conceptualization of argument quality, an explanation of movement along the continuum and between central and peripheral routes to persuasion, or to use new methodologies and technologies to help better understanding consume thinking and behaviour? All these relate to the current need to explore the relevance of ELM in a more modern context.

It is time to question the validity and relevance of the ELM. The diversity of on- and off-line media options and the variants of consumer choice raise significant issues.

While the ELM model continues to be widely cited and taught as one of the major cornerstones of persuasion, questions are raised concerning its relevance and validity in 21st century communication contexts.

The purpose of this study is to unpack the knowledge structure of the elaboration likelihood model (ELM), examine its applications in various domains and propose future research directions using bibliometric analysis.

The study involves the bibliometric analysis of 279 articles retrieved from Scopus using VOSviewer and Biblioshiny. The authors used trend topic analysis, bibliographic coupling, cluster analysis and content analysis as the analytical methods.

The study revealed the most influential authors, journals, articles and countries in the domain. The keyword analyses showed that initially, the model was used in the field of “persuasion” and “persuasive communication”; however, in the past five years, it has been widely adopted in different areas such as “crowdsourcing,” “decision support systems” and “information systems.” Bibliographic coupling combined with content analysis resulted in seven clusters: ELM in marketing communications, ELM in information system research, ELM in the service context, ELM in advertising research, ELM and electronic word-of-mouth, ELM and trust in the online context and ELM in other contexts.

The study provides a bibliometric analysis of the ELM, offers useful future research directions to the scholars of different domains and highlights implications for managers.

This study aims at building a framework for the electronic word-of-mouth (eWOM) response under the social media environment. The elaboration likelihood model was adopted to explain how message source credibility and message appeal jointly influence the eWOM response process, while source credibility provides a central route and message appeal plays a peripheral route for information processing.

This study used a scenario design to test the decision behavior in the Facebook environment through message content manipulation. A convenience sampling method was adopted in this study. We collected 203 valid questionnaires and tested this research model with LISREL 8.8. This study used a two-stage structural equation modeling data analysis method with LISREL 8.8, by which the measurement model was assessed through confirmatory factor analysis for the reliability and validity of the research model, and the causal relationship among factors was assessed through exploratory factor analysis .

The results showed that 53% variance of eWOM responses could be explained by message source credibility and emotional message appeal from the elaboration likelihood model perspective. Message source credibility plays a central role in the social media environment. The model was further tested with a demographic profile analysis for both gender and age. It is found that a female user is influenced by both source credibility and emotional appeal, but a male user is only influenced by message source credibility. The mature age group is more responsive to eWOM messages.

The sample might not represent all social networking sites (SNS) users. The participants represent a small segment of the Facebook population around the globe. Secondly, this research design could be improved by using more recreational messages to test the effects of message appeal and message source credibility. Thirdly, the mobile phone is a type of physical product rather than an experiential product. Future studies could try to identify the same eWOM determinants with different SNS functions, for example, the inbox message function. Similarly, Facebook users are allowed to use both text and pictures to disseminate promotional messages.

This study provides an insight for SNS administrators regarding the determinants of driving more customer responses toward a message. Message source credibility and message appeal are identified as the antecedents for eWOM responses in SNS. Companies could make use of this finding to improve their marketing communication strategy in SNS. The finding can inform administrators of the importance of focusing on both customers’ psychological state and message attributes during the dissemination of promotional messages to improve the efficiency of the promotional effort. Companies aimed at receiving different types of eWOM responses in SNS may need to consider other factors for creating their promotional messages.

Previous studies have mainly identified factors influencing eWOM responses from the people-centered variables such as personal traits and social relationships. This study proposes that the eWOM response is a dual information processing process that can be explained by the ELM. When a user processes information in SNS, he follows both the central route and the peripheral route (i.e. source credibility and message appeal) which can influence the eWOM response. It is the first time that the source credibility is investigated as the central route in ELM model.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

This chapter provides a comprehensive review of several social-cognitive models that have been lately applied in public health and donation contexts. The current review included the elaboration likelihood model (ELM), the prototype willingness model (PWM), and the organ donation model (ODM). This review also details and discusses the main strengths and limitations of these models. Importantly, this review helps to identify the gap of the current social marketing and health-care literature. In particular, this chapter provides a solid theoretical foundation and has initiated further pathways for future researchers who are interested in the fields of public health and social change literature, organ donation context, as well as social-cognitive decision-making models. The significance of this review is defined by advancing public health practitioners, social marketing communicators, and educationalists, evidencing how conceptual models can inform and guide the research.

The purpose of this theoretical paper is to introduce a conceptual model to investigate e-learning persuasion through gamification elements using the social psychology theory of elaboration likelihood model (ELM).

The author systematically reviewed several theoretical and empirical papers which applied the ELM in various settings. Based on the literature, the author identified six research prepositions which facilitate to investigate e-learning persuasion through gamification.

This study contributes to the existing literature by identifying an ELM-based conceptual model which can be used to empirically investigate the e-learning persuasion using gamification elements. Accordingly, the central route persuasion could be conducted through argument quality, demographic differences and technology context facilitated through gamification elements. The peripheral route persuasion could be conducted through variables such as source credibility, social presence and message content.

This study contributes important findings to the e-learning research by introducing a conceptual model–based on the social psychology theory of ELM. Thereby, this study introduces a method for the future researchers, to investigate the e-learning persuasion using gamification elements. Further, future researchers can use this model to investigate the e-learning persuasion through gamification in different contexts including primary, secondary and tertiary educational levels.

To the best of the author’s knowledge, this study can be considered as the first theoretical paper which developed an ELM-based conceptual model to investigate the e-learning persuasion through gamification in education context.

The purpose of this research is to contribute to the understanding of how customer contact persons influence attitudinal and behavioral loyalty in three different customer groups, who differ in terms of their motivation and ability to understand stock market information. The mutual fund product is one of last century's big success stories. Consumers invest a lot of money in complex financial products that they do not understand. Therefore, they need professional advice to make decisions.

The study is based on a nationally representative random sample of mutual fund owners. The elaboration likelihood (EL) model predicts that high, moderate, and low elaborators are different. Three such customer groups were therefore analyzed.

A path model shows that customer contact persons influence attitudinal and behavioral loyalty and that the impact is higher for high elaborators (higher knowledge and motivation to process stock market information) than for low elaborators. This suggests that the role of the contact person differs for different customer groups, i.e. the notion of multiple roles for variables.

Future studies of complex services should acknowledge that different groups of consumers with different needs, preferences, and behaviors have different needs and preferences, and that they react differently

Customer contact persons must be rewarded for delivering value to customers. Unless they do, they will loose their unique opportunity to influence customers' decisions. They must adapt their communication to different customer groups, and acknowledge that the perception of what is valuable advice may differ.

This paper demonstrates that a very simple and easy to use model can show the value of customer contact persons. All linkages in the model are tested, which is not done in prior research. In addition, different groups of consumers have different needs, preferences, and behaviors, a fact that is almost never acknowledged in prior research.

The elaboration likelihood model (ELM) provides a general framework for understanding the basic processes underlying the effectiveness of persuasion. The purpose of this paper is to utilize the ELM to understand the basic processes underlying the effectiveness of persuasion to use digital libraries for getting information.

The survey data collection was conducted in one comprehensive university. The partial least squares structured equation modelling was employed to verify the research model.

Source credibility and reputation have positive effects on information usefulness which further significantly impacts digital library usage for getting information. The effect of information quality on information usefulness is overpowered by reputation. Information need positively moderates the effect of information quality on information usefulness and negatively moderates the effect of reputation on information usefulness.

Digital libraries enormously influence the way how individuals gather information over the world. However, the important status of digital libraries as conventional information sources in practice invites appreciation by more and more people. The authors believe the findings of this study provide useful insights for facilitating digital libraries to be fully accessed and utilized.

This study explores the effects of the central route (information quality) and the peripheral route (source credibility and reputation) on digital library usage for getting information by extending the ELM with information need as a motivation variable, presenting a new lens for digital library research and practice alike.

As a new communication paradigm, social networking sites (SNS) have boosted information diffusion and viral marketing. Prior researchers have identified various factors affecting information dissemination on SNS. However, they often focus on limited factors and there is a lack of an integrated theoretical framework that explains aspects of relevant factors. Besides, the research on the impacts of relationships on individual retweeting behavior is still controversial. The purpose of this paper is to propose a theoretical framework to systematically investigate the determinants of individual dissemination behavior on SNS based on the elaboration likelihood model (ELM). Moreover, the authors also examine the relative importance of those relevant factors.

The authors randomly selected 1,250 members of Twitter and crawled posts published by each member since he/she created the Twitter account using Twitter API. The authors processed the data to create panel data and tested hypotheses with the panel logit model.

Factors both on the central route and on the peripheral route of ELM have positive impacts on individual dissemination behavior. Among them, information receiver-related factor and relationships-related factors are the most influential. Contrastingly, source-related factors are the least influential. Furthermore, the authors find that social tie strength mediates almost 50 percent of the effect of value homophily on individual dissemination behavior.

The authors are the first to directly apply ELM to examine individual dissemination behavior on SNS. By integrating factors into the two information processing routes, They incorporate relevant factors into the model and systematically analyze their impacts on individual retweeting behavior on SNS. The research offers at least one explanation for the contradictory findings about the effect of homophily on individual sharing behavior in previous research. The authors propose new variables that gauge topical relevance and interpersonal value homophily on SNS.

Aiming to address the problem in which practitioners mindlessly prioritise the reputation of social media influencers (SMIs) over ensuring proper congruence between the influencers themselves and content marketing strategies, this study develops a conceptual framework that adopts an elaboration likelihood model and attachment theory to ascertain the effects of SMIs, live content marketing and their congruency on impulsive buying (IB).

Through collecting cross-sectional data from 608 valid replies, this study adopts an integrated method that combines partial least squares structural equation modeling (PLS-SEM), artificial neural network (ANN) and fuzzy-set qualitative comparative analysis (fsQCA) to analyse.

The results reveal that the credibility and relevance of live content, the empathy and professionalism of SMIs, and their congruence are critical antecedents of consumers' attachments to live content and SMIs, thus triggering their attachment to endorsement and IB.

In knowledge, this study benefits the scope of the elaboration likelihood model and attachment theory and enriches live streaming commerce literature. In method, an integrated analytical method is used to cope with complex structural relationships in non-linear patterns and predictions, as well as examine the complex causal configurations. In practice, this study facilitates practitioners to further ascertain what attributes in live content and SMIs can foster customer's emotional attachments in choosing endorsers and developing endorsement strategies, thus driving their IB.