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Given the popularity of online health communities (OHCs) and medical question-and-answer (Q&A) services, it is increasingly important to understand what constitutes useful answers and user-adopted standards in healthcare domain. However, few studies provide insights into how health information characteristics, provider characteristics and recipient characteristics jointly influence user information adoption decisions. To fill this research gap, this study examines the combined effects of physicians' certainty tone as information characteristics, seniority as provider characteristics and disease severity as recipient characteristics on patients' health information adoption.

Drawing on dual-process theory and information adoption model, an extended information adoption model is established in this study to examine the effect of attitude certainty on patients' health information adoption, and the moderating effects of online seniority and offline seniority, as well as patient motivation level—disease severity. Utilizing logit regression models, the authors empirically tested the hypotheses based on 4,224 Q&A records from a popular Chinese OHC.

The results show that (1) attitude certainty has a significant positive impact on patients' health information adoption, (2) the relationship between attitude certainty and information adoption is negatively moderated by physicians' online seniority, but is positively moderated by offline seniority; (3) there is a negative three-way interaction effect of attitude certainty, online seniority and disease severity on patients' health information adoption.

This study extends the information adoption model to examine the two-way interaction between argument quality and source reliability, as well as the three-way interaction with user motivation level, especially for health information adoption in the healthcare field. These findings also provide direct practical applications for knowledge contributors and OHCs.

Online reviews derived from peer communications have been increasingly viewed as an important approach for consumers to gather pre-purchase information. This study aims to examine factors affecting online reviews adoption in social network communities and then indicates the underlying mechanism of this process based on an extended information adoption model (IAM).

Using the data collected from 242 users of a social network community via an online survey, the proposed model is empirically assessed by partial least squares-based structural equation model (PLS-SEM).

The results show that both perceived diagnosticity and perceived serendipity are drivers of online reviews adoption in social network communities. Meanwhile, community identification is not only an antecedent of diagnosticity and serendipity perceived by community members, but also motivates source credibility which, in turn, positively influences argument quality. Finally, the importance of argument quality and source credibility in reviews adoption process is also presented.

This study extends the IAM and enriches the literature regarding online reviews adoption. It deepens the understanding of serendipitous experiences and community identification in social networking context by addressing their important roles in the authors' extended IAM.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

The aim of this research is to measure the impact of eWOM (electronic word of mouth) and brand celebrity use on the purchasing behavior of sports consumers.

To test the model hypotheses, sports consumers who use social media and have purchased at least one online sports product were selected as the research group. Online survey method was used, and 836 participants were reached. The model was tested with structural equation modeling (SEM) through smart PLS software.

As a result, the quality, credibility and usefulness of the information consumers encounter on online platforms cause them to adopt information about products or services, and then exhibit online purchase behavior. While the attractiveness and trustworthiness of celebrities are seen as important factors affecting consumers' online purchase of sports products, the effect of celebrity expertise was found to be ineffective in this study.

Marketers can develop more effective eWOM strategies by considering consumers' expectations. Businesses that want to implement an effective marketing strategy may prefer celebrities in product promotions or advertisements of their brands.

This research revealed the effect of eWOM and celebrity endorsement on the online purchase behavior of sports consumers in terms of the sports industry. Unlike previous studies, this study examined these variables together on sports consumers and contributed to the development of models.

The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

This study aims to identify the essential elements impacting the adoption of blockchain technology (BCT) in supply chain management (SCM) by integrating the technology acceptance and information system success (ISS) models.

Questionnaire-based data was collected from 236 supply chain professionals from Beijing. The proposed research framework was evaluated using structural equation modeling (SEM) by using SPSS 23 and AMOS 24 software.

The empirical findings specify the positive influence of total quality on perceived usefulness and compatibility. Further, perceived ease of use positively influences perceived usefulness, compatibility and behavioral intention. Moreover, perceived usefulness positively impacts compatibility and behavioral intention. Compatibility positively influences behavioral intention. Finally, technology trust was found to be a significant moderator between perceived usefulness and behavioral intention and between perceived ease of use and adoption intention to use BCT in SCM.

This study empirically develops the second-order construct of total quality, representing the ISS model. Furthermore, this study established how the ISS and technology acceptance models influence behavioral intention through compatibility. Finally, this study confirmed the moderating role of technology trust among perceived ease of use, perceived usefulness and behavioral intention.

This study aims to identify the driving factors that influence blockchain technology adoption in the context of a supply chain (SC), considering three dimensions: technology, transactions and collaboration.

An integrative systematic literature review of previous studies was conducted. Using three main dimensions: technology, transactions and SC collaboration, supported by the unified theory of acceptance and use of technology, transaction cost economics (TCE) and concepts of SC collaboration, the authors categorized factors that contributed to blockchain technology in SC in the extant literature and proposed a theoretical model that covers these three dimensions.

The findings reveal that the information sharing category – related to the SC collaboration dimension – is the category with the greatest number of motivating factors for blockchain adoption in the SC context, followed by performance expectancy and behavioral uncertainty.

The review considers papers published until 2021 obtained from a specific database.

This study focuses on filling the research gap concerning technology adoption as it considers the interconnection formed by two organizations, interorganizational transactions and SC collaboration, using complementary theories to explain the phenomenon.

Large, influential and profitable young adults are being targeted for fast fashion that negatively impacts the environment. The transition from a fast to an environmentally friendly slow fashion is a challenging process and culturally dependent. The process starts with slow fashion idea adoption. Thus, the authors modified an information acceptance model (IACM) to examine information characteristics (idea/information quality, credibility, usefulness, source credibility) and consumer factors (need for idea and attitudes) impacting intentions to adopt the slow fashion idea in Canada, South Africa (individualists) and China (collectivists).

Cross-sectional data were collected from South African (n = 197), Chinese (n = 304) and Canadian (n = 227) young adults (18–35 years old) at universities in metropolitan cities. Partial least squares structural equation modeling was used to analyze the data.

The results show that while most information characteristics and consumer factors are vital for slow fashion attitudes and intention formation, information quality and trust in the sources were a problem in individualistic cultures as opposed to the collectivist culture. This finding confirms the greater tendency of collectivists to trust disseminated information on environmental issues. In all cultures, attitudes impacted idea adoption intentions. On testing IACM, the multigroup analyses showed no significant differences between young adults in the individualistic cultures. Attitudes mediated most relationships and were highly explained by IACM (South Africa, 49.6%; China, 74.5%; and Canada, 64.5%).

In emerging and developed markets, this study informs environmentalists and green fashion brands of information characteristics that can create positive attitudes and slow fashion idea adoption intentions among influential young adults.

This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.

In light of the repercussions of the COVID-19 pandemic, electronic auditing otherwise known as computer-assisted audit tools and techniques (CAATTs) has become inevitable to automate the auditing process worldwide. Accordingly, the purpose of this study is to examine the influence of technological, organizational and environmental (TOE) factors on public sector adoption of CAATTs in developing countries such as Jordan under the COVID-19 pandemic conditions.

This study used 136 usable responses from the managers of internal audit (IA) of the Jordanian public sector entities. The data collected were analyzed using partial least squares-structural equation modeling. The TOE framework has been used in this study to consider a wide set of TOE factors. Then, this study suggests a CAATTs adoption model that incorporates the related technology factors of the diffusion of innovation theory to environmental and organizational factors. Further, this study contributes to the TOE framework by addressing government regulations, audit bodies’ support and audit task complexity as environmental factors affecting CAATTs adoption in the context of the public sector.

The results revealed that for technological factors, only the compatibility affects CAATTs adoption by the IA departments. For organizational factors, organizational readiness, top management support, auditors’ information technology competency and entity size were found to be significant factors. From the environmental factors, both government regulation and audit task complexity influence the CAATTs adoption. Besides, entity size moderates the influence of top management support on the CAATTs adoption in the public sector.

The findings could highlight the significance of the CAATTs adoption in the public sector institutions (by internal auditors) post-COVID-19, taking into consideration the TOE framework’s factors. Also, the findings are significant for the decision-makers and regulators in declaring new legislation for the electronic IA profession in the Jordanian public sector.

It turns out that the CAATTs adoption in the public sector can definitely enhance their ability to achieve the role of IA in preserving public funds and restricting corrupt practices within the public sector.

To the best of the authors’ knowledge, this study is one of the first studies that address the professional audit agency support and audit task complexity as environmental factors, as well as the entity size as an organizational factor, that affect CAATTs adoption in the IA department of the public sector.