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This paper aims to develop a novel method and apply it to solve multiple definite integrals. The proposed method is constructed based on multiple sets of correlation extreme learning machines (MCELM).

The authors present a novel method for solving multiple definite integrals. By using an extreme learning machine (ELM) to learn the integrand function, the primitive function is analytically derived based on the functional expression of the trained ELM and expressed by another ELM, while the correlations between the two ELMs are established. Solutions of multiple definite integrals can be realized by applying this process repeatedly.

To verify the validity and effectiveness of the proposed method, various examples are selected and its numerical solutions are obtained by using the proposed method. The proposed method has high computational accuracy and efficiency, and the superiority is illustrated by comparing with some other existing methods.

MCELM method is proposed for solving multiple definite integrals. The method can be applied for solving multiple definite integrals appearing in applications, the strong applicability of the method in engineering problems is demonstrated in structural system reliability analysis of a cantilever beam.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

Nowadays some consumers consider themselves as “omnichannels” – they combine both physical and digital channels expecting a seamless shopping experience – since they view their shopping process from a multiple-channel viewpoint. Giving that situation, the aim of this paper is to test the role of consumers’ omnichannel tendency (omni-tendency) in the information processing in the digital channel.

Based on the Elaboration Likelihood Model (ELM), emotions as well as utilitarian and hedonic experiences are proposed to understand consumer attitude towards the digital store. Through a survey, data were collected from 284 digital shoppers. PLS path modelling and PLS-MGA were used to test the research hypotheses.

The results confirm that emotions positively affect the evaluation of the experiences, which in turn improves the attitude towards the digital store. Focusing on the differences among consumers, the findings show that for consumers with low omni-tendency the emotions are key to improve the evaluation of their experiences. Moreover, regarding the attitude, consumers with more omni-tendency follow the central route to process the information; and consumers with less omni-tendency follow the peripheral route.

This paper contributes to the literature in three ways. First, this research includes the study of omni-tendency, as a consumer trait, in the information processing developed in the digital channel, ignored in the literature. Second, this work contributes to information processing theories in digital context confirming, specifically the applicability of ELM into the omnichannel context. This offers support to the application of traditional theories to explain new phenomena. Third, and in line with the previous contribution, this work goes a step further in understanding ELM theory by including other constructs –the omni-tendency and emotions– to explain the information processing in the digital context.

The purpose of this study is to explore the influence of electronic word-of-mouth (eWOM) on outbound tourists’ intention to visit a destination through a dual-process perspective – the central route of argument quality (AQ) and the peripheral route of source credibility (SC). With the pervasion of Web 2.0 and information and communication technology, user-generated content (UGC) has become popular in the online environment, and it affects consumers’ decisions greatly.

A structural model based on Elaboration Likelihood Model (ELM) and theory of planned behavior (TPB) is proposed in this study to explore the influence of eWOM on outbound tourists’ intention to visit a destination. Empirical data were collected among Chinese outbound tourists via an online survey. The data were analyzed using structural equation model with SPSS Amos 22.0.

The research results indicate that tourist’s attitude toward a destination was positively influenced by AQ of eWOM, and intention to recommend the destination before travel was positively influenced by attitude toward destination and SC of destination-related eWOM. Outbound tourists’ intention to visit a destination was positively determined by AQ, attitude toward destination and WOM intention. Several practical and theoretical implications are also discussed in the study.

This study contributed to the understanding of individual’s decision-making through a dual-process perspective. Findings indicate that the dual influence process delineated in theory of ELM is also applicable to explain individual’s decision in complicated information source.

Compensatory consumption focuses on the psychological value of products. Special agricultural products have symbolic and social functions that effectively meet psychological needs and stimulate compensatory consumption behavior. The social commerce context not only enriches consumer experience but also influences consumer purchase decisions. This study constructs a model based on the elaboration likelihood model (ELM) and the stimulus-organism-response (SOR) theory to explore the mechanism of compensatory consumption behavior of special agricultural products in a social commerce context.

This study uses a two-stage method of partial least squares structural equation model (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to analyze 523 valid samples collected through random sampling. PLS-SEM was used to examine the relationships and effects between the variables; fsQCA was used to conduct a cohort analysis between the variables to further reveal the complexity and diversity of compensatory consumption behaviors.

PLS-SEM indicates that product attributes and social affordances influence consumers’ triggering of compensatory consumption behavior for control and belongingness needs. fsQCA shows that there are three different modes, and the satisfaction of belongingness or control needs is a necessary condition for triggering compensatory consumption behavior.

There is limited research on compensatory consumption behavior specifically focused on special agricultural products. This study explores the influencing factors and mechanisms of compensatory consumption behavior related to special agricultural products. The occurrence of compensatory consumption behavior is not only influenced by product attributes but also by the social commerce environment. In marketing strategies, it is important to not only consider product characteristics but also pay attention to consumers’ social and psychological needs.

This paper aims to explore the effectiveness of ethnically targeted ads in developing consumer–brand relationships through an application of social identification theory and elaboration likelihood model among African American consumers in the service sector.

Study 1 used a 2 (service type: hedonic vs utilitarian) × 2 (strength of ethnic identification: high vs low) between-subjects experimental design. Study 2 used the same experimental design, procedure and ads as Study 1.

Taken together, the findings from these two studies demonstrate how ethnically targeted advertising, in conjunction with service type, can influence consumer–brand relationships. The results showed that those with high strength of ethnic identification had more brand love, as well as higher intentions to spread positive word-of-mouth, purchase intention and brand loyalty for hedonic services, but that this effect was not significant for utilitarian services.

The environments in which advertisements appear (e.g. in an in-store display or a magazine advertisement) is important, and consumers’ reactions to targeted ads in various environments should be considered in future research. Future studies should also examine the role of individuals’ personality traits and level of acculturation in determining their relationships with brands.

Across two studies, the authors demonstrated that ethnic ads are more effective for African American individuals with high level of ethnic identification especially for hedonic services.

The purpose of this paper is to explore the factors influencing people’s health knowledge adoption in social media, with an eye toward promoting health information literacy and healthy behavior.

Based on the integration of sense-making theory, social influence theory, information richness theory, fear appeal theory, and ELM (elaboration likelihood method), a health knowledge adoption model is constructed. Taking spondylopathy as an example, high health threat and low health threat experiments and questionnaires are designed to complete the empirical study. In all, 355 effective survey samples are collected and analyzed, leveraging a partial least squares method.

Research results indicate that perceived knowledge quality, perceived knowledge consensus, and perceived source credibility have positive effects on health knowledge adoption via the mediator – trust; knowledge richness contributes to the perception of knowledge quality, source credibility, and knowledge consensus, especially under high health threat; health threat has significant positive moderating effects on the relationship between trust and health knowledge adoption, and the relationship between perceived knowledge quality and trust, with negative moderating effects on the relationships between perceived knowledge consensus, perceived source credibility, and trust.

This paper examines the mediating effecting of trust in the process of health knowledge adoption. Based on the integration of fear appeal theory, social influence theory, sense-making theory, information richness theory and elaboration likelihood model, this study investigates the factors influencing health knowledge adoption in social media from the perspective of a user, and explores the moderating effect of health threat on health knowledge adoption.

How to free the potential power of the capital market while simultaneously protecting the investors is critical in equity-based crowdfunding. To realize these goals, the purpose of this study was to investigate the value of information disclosure and leader-follower mechanism which have been widely adopted by crowdfunding platforms.

Based on the Elaboration Likelihood Model (ELM), a research framework was developed. Then, the authors conducted an in-depth exploratory empirical study of Dajiatou (www.dajiatou.com) which is a typical equity-based crowdfunding service provider in China. Independent-samples t-test and linear regression were used to uncover the value of project information disclosure and the lead investor in terms of fundraising performance improvement.

First, the quality of entrepreneurial team information, especially the ratio of full-time staff, staff number and enterprise business age, significantly improve fundraising performance. Second, entrepreneurs’ behaviors, including project updates and project video, play important roles in crowdfunding. Third, whether or not the project has a lead investor, leader’s credibility information and his/her advocacy behaviors – percentage of their investment, identity certification, investment experience and comments for projects – are important factors affecting fundraising performance.

The authors are one of the firsts to apply ELM to investigate the effects of diverse information on fundraising performance in equity-based crowdfunding. The value of lead investor which has been ignored in prior research was studied through second-hand data.

First, an equity-based crowdfunding platform should request the entrepreneur to disclose project quality-related information with more details. Second, crowdfunding platforms should set a high qualifications level for lead investor, and limit the lead investor’s committed percentage in a specific project.

This paper extended the research in crowdfunding by uncovering the value of information disclosure and lead investor based on ELM theory.

This study examined the differential effects of printed advertisements with luxury and nonluxury brands on consumer brand attitude persuasion using a qualitative experimental approach.

The authors adopted a qualitative experimental approach and the authors conducted two experiments over six months. In the first experiment, participants were asked to view five print advertisements related to five different luxury brands. In the second experiment, the same participants were asked to view another five print advertisements on non-luxury brands. The qualitative thematic differences for each brand were analyzed using NVivo software, employing the theoretical assumptions of Petty and Cacioppo's (1981) elaboration likelihood model (ELM).

In experiments 1 and 2, it was identified that brand experience, personalized brand experience, product quality, product quantity, personal image-conscious, nonpersonal image-conscious, affordability and unaffordability as the main thematic findings leading to consumer attitude persuasion.

The two main contributions are as follows: theoretically, applying a social psychology theory to the advertising industry offers an understanding of the social cognition stages of a human mindset. As a practical implication, this study's findings guide advertising agencies, marketers and salespeople regarding how to design effective print advertisements in a way that persuades consumer attitudes.

Through the theoretical assumptions of Petty and Cacioppo's (1981) ELM, this paper can be considered one of the first studies to combine social psychology and advertising to investigate the differential effects on consumer brand attitude persuasion for luxury and nonluxury brands.

From a distinctiveness theory and elaboration likelihood model (ELM) perspective, this study aims to investigate the determinants, the direct and indirect effects of ethnic identification on brand attachment, brand love and behavioral outcomes. The authors examine two types of products (high- vs low-involvement).

In a survey, participants were randomly assigned to four conditions consisting of two high-involvement (i.e. a smart watch and a car) and two low-involvement (i.e. a soda/soft drink and a shampoo) stimuli. A total of 192 respondents participated in this study; 39% were male, 61% were female and 90% were 18-22 years old.

In line with ELM, the authors offer evidence that ethnic advertising is more effective for low-involvement products targeted at African American consumers. Results also showed that brand attachment partially mediates the effect of ethnic identification with the ad (EthIdenAD) and brand love. In summary, the structural equation modeling (SEM) results support the efficacy of ethnic-targeted ads for developing brand attachment, brand love and behavioral outcomes.

Using ethnically targeted ads to target minority groups may not be sufficient to increase the efficacy of ads. According to distinctiveness theory, African Americans with different levels of ethnic identification will respond differently to ad attitudes, brand attachment, brand love, identification with the model in the ad and varying degrees of belief that the ad was targeted toward them.

This study examines the effect of ethnically targeted advertising on brand love, and behavioral outcomes with the mediation effect of brand attachment and moderation effect of product involvement. The results of this study suggest several theoretical and practical implications for marketing and brand management, including directions for advertising strategy and consumer–brand relationships.