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Informal learning networks are critical to response to calls for practitioners to reskill and upskill in off-site construction projects. With the transition to the coronavirus disease 2019 (COVID-19) pandemic, social media-enabled online knowledge communities play an increasingly important role in acquiring and disseminating off-site construction knowledge. Proximity has been identified as a key factor in facilitating interactive learning, yet which type of proximity is effective in promoting online and offline knowledge exchange remains unclear. This study takes a relational view to explore the proximity-related antecedents of online and offline learning networks in off-site construction projects, while also examining the subtle differences in the networks' structural patterns.

Five types of proximity (physical, organizational, social, cognitive and personal) between projects members are conceptualized in the theoretical model. Drawing on social foci theory and homophily theory, the research hypotheses are proposed. To test these hypotheses, empirical case studies were conducted on two off-site construction projects during the COVID-19 pandemic. Valid relational data provided by 99 and 145 project members were collected using semi-structured interviews and sociometric questionnaires. Subsequently, multivariate exponential random graph models were developed.

The results show a discrepancy arise in the structural patterns between online and offline learning networks. Offline learning is found to be more strongly influenced by proximity factors than online learning. Specifically, physical, organizational and social proximity are found to be significant predictors of offline knowledge exchange. Cognitive proximity has a negative relationship with offline knowledge exchange but is positively related to online knowledge exchange. Regarding personal proximity, the study found that the homophily effect of hierarchical status merely emerges in offline learning networks. Online knowledge communities amplify the receiver effect of tenure. Furthermore, there appears to be a complementary relationship between online and offline learning networks.

Proximity offers a novel relational perspective for understanding the formation of knowledge exchange connections. This study enriches the literature on informal learning within project teams by revealing how different types of proximity shape learning networks across different channels in off-site construction projects.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

To promote the success of peer-to-peer accommodation, this study examines the effects of online host–guest interaction as well as the interaction's boundary conditions of listing price and reputation on listing popularity.

Using 330,686 data collected from Airbnb in the United States of America, the authors provide empirical evidence to answer whether social-oriented self-presentation and response rate influence listing popularity from the perspective of social exchange theory (SET). In addition, the authors investigate how these two kinds of online host–guest interactions work with listing price and reputation to influence listing popularity.

The results reveal the positive association between online host–guest interaction and listing popularity. Notably, the authors find that listing price strengthens but listing reputation weakens the positive effects of online host–guest interactions on listing popularity in peer-to-peer accommodation.

This study is the first attempt to adopt SET to explain the importance of online host–guest interactions in influencing listing popularity as well as examine the moderating role of listing price and reputation on the above relationship.

This study aims to explore the factors that affect online knowledge sharing among the scientific performance of academics at the University of Mosul, Republic of Iraq.

Data were collected by using a random sample by means of an electronic questionnaire distributed to 211 academics at the University of Mosul via online platforms. Structural equation modeling was used to test hypotheses using AMOS 24 software.

The results showed that collaboration, perceived flexibility and willingness to share had a significant effect on online knowledge sharing behavior and that which in turn had an effect on the academic performance of respondents, while the results showed no influence of knowledge self-efficacy and communication on the behavior of online knowledge sharing.

In this research, the effects of five factors on online knowledge sharing behavior were studied, in addition to the effect of the latter on academic performance. The research did not study the effect of the participants’ personal characteristics on the behavior of knowledge sharing online, which could be an area of future investigation. The study was limited to online knowledge sharing for academics working in public universities, and the authors suggest conducting a future study from the perspective of medical staff working in hospitals and its impact on their performance.

Based on the findings of the current study, this study suggests that the academic staff at the University of Mosul and similar universities pay attention to scientific cooperation between researchers and teaching staff, by creating online groups to carry out joint research projects that contribute to sharing knowledge among participants through social media in general and scientific platforms in particular. Establishing a scientific research portal could serve this well for example.

Most previous studies have focused on areas related to knowledge sharing in higher education institutions from the traditional perspective and therefore studies that examine the factors affecting online knowledge sharing among academics are limited, so this study fills this gap. This paper focuses on identifying the scientific benefits for academics through knowledge exchange and the use of electronic platforms at the University of Mosul. The study is expected to contribute to enhance the exchange of knowledge online between academics in similar universities in Asia and Africa due to the convergence of cultures and the nature of the work of these universities, as well as the possibility of generalization due to the research’s use of the deductive method.

While spontaneous and voluntary knowledge contribution in online communities promotes value co-creation, dysfunctional knowledge behaviors hamper the effectiveness and development of such communities. The study conceptualizes physicians' proactive knowledge sharing and knowledge withholding behaviors in physician-driven online health communities (OHCs) and integrates the theories of role identity as well as communal and exchange relationships to understand the root causes and motivations behind these two types of knowledge behaviors.

The authors collected survey data from 166 users from one of the largest physician-driven OHCs in China and applied the covariance-based structural equation modeling approach to test the hypotheses.

The findings suggest that (1) physicians' professional role identity had a positive indirect effect on proactive knowledge sharing behaviors through communal motivation, and work pressure weakened this indirect effect; and (2) professional role identity had a negative indirect impact on knowledge withholding behaviors through exchange motivation.

This study extends proactive knowledge sharing and knowledge withholding behaviors from the organizational management domain to the online environment, exploring the underlying causes and motivations behind both behaviors in the unique context of physician-driven OHCs. The findings offer practical suggestions for the effective management of OHC platforms, as well as policy implications that respond to the workforce shortage of healthcare providers, a crisis that is unfolding globally.

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 analyzes whether farmers' incomes increase as they participate in online groups.

The study analyzed interview data from 673 farming households in three mountainous provinces of northern Vietnam, utilizing the propensity score matching (PSM) method.

The empirical results reveal that farmers participating in online groups, particularly those engaged in 1–3 groups, experience an increase in their income attributed to the three advantages of sharing-accessing-saving (SAS) information. Farming households engaged in online groups earn higher incomes, ranging from equivalent to 25.78 to 26.96 USD, in comparison to those who do not participate. Notably, farmers participating in 1–3 online groups outpace their counterparts in 4–5 groups in terms of income.

This study exclusively focuses on examining farmers' total income derived from all their agricultural activities and does not quantify the specific impact of online group participation on the income generated by each product. Furthermore, it is important to note that the PSM method has the potential to introduce bias due to unobserved factors, such as social networks and local culture. Consequently, future research should prioritize the segmentation of income from individual agricultural products, distinct from the overall income, to gain a more nuanced understanding of each product’s sensitivity to information exchanged in online groups. Simultaneously, accounting for unobserved factors is crucial to obtain unbiased estimates.

This study represents the inaugural exploration into the comparison of farmers' incomes within a novel context – participation in digital-based groups. Furthermore, it extends the inquiry by delving into the correlation between the number of online groups joined and farmers' income. The empirical findings indicate that farmers may benefit the most by limiting their participation to a select few groups that align with their information needs and analytical abilities.

The purpose of this study is to investigate the role of blockchain technology in reducing online fraud among Gen Y and Gen Z.

This study uses a two-phase approach. Firstly, a systematic literature review is conducted to examine various aspects of blockchain technology and cyber security. Secondly, the Technology Adoption Model is used to study the adoption dynamics of blockchain-based platforms for online data exchange among 415 Gen Y and Z users.

The results indicate that efficiency and security, perceived ease of use, perceived usefulness, and trust have a positive effect on behavioral intention and attitude towards use. This is the first study to examine the role of blockchain technology to reduce fraud among Gen Y and Gen Z.

This study provides new insights into the adoption of blockchain-based platforms for online data exchange among Gen Y and Gen Z. The study highlights the critical areas of concern for the adoption of blockchain technology and provides managerial implications for fintech firms, banks, and e-commerce platforms. It is unique in its focus on the potential for blockchain technology to reduce fraud among Gen Y and Gen Z, which has not been previously explored in the literature.