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Drawing on social exchange theory, this study aims to investigate the reciprocal relationship between an employee’s knowledge sharing and his or her coworkers’ responses to this focal contributor in terms of knowledge sharing and helping behaviors.

A two-wave online survey collected data from 84 respondents who provided ratings on each member on their team, representing 440 dyadic relationships. Hierarchical linear modeling analyzed the between-subjects and within-subject data simultaneously.

Employees generally reciprocate contributors’ knowledge sharing with an exact act (i.e. knowledge sharing) through the mechanism of peer respect. However, respect generated by knowledge sharing is enhanced only when the knowledge contributor is competent.

Research on how an employee’s knowledge sharing actually influences other members of a team is lacking. This study addresses this gap by examining responses to a team member’s knowledge sharing from a peer’s perspective. It also reveals when knowledge sharing is more pronounced in earning peer respect.

Users' knowledge contribution behaviors are critical for online Q&A communities to thrive. Well-organized question threads in online Q&A communities enable users to clearly read existing answers and their evaluations before contributing. Based on the social comparison and peer influence literature, the authors examine peer influence on the informativeness of knowledge contributions in competitive settings. The authors also consider three levels of moderating factors concerning individuals' perception of competitiveness: question level, thread level and contributor level.

The authors collected data from one of the largest online Q&A communities in China. The hypotheses were validated using hierarchical linear models with cross-classified random effects. The generalized propensity score weighting method was employed for the robustness check.

The authors demonstrate the peer influence due to social comparison concerns among knowledge contribution behaviors in the same question thread. If more prior knowledge contributors choose to contribute long answers in the question thread, the subsequent contributions are more informative. This peer influence is stronger for factual questions and questions with higher popularity of answering but weaker in recommendation-type and well-answered questions and for contributors with higher social status.

This research provides a new cue of peer influence on online UGC contributions in competitive settings initiated by social comparison concerns. Additionally, the authors identify three levels of moderating factors (question level, thread level and contributor level) that are specific to online Q&A settings and are related to a contributor's perception of competitiveness, which affect the direct effect of peer influence on knowledge contributions. Rather than focus on motivation and quality evaluation, the authors concentrate on the specific content of online knowledge contributions. Peer influence here is not based on an actual acquaintance or a following relationship but on answering the same question. The authors also illustrate the competitive peer influence in subjective and personalized behaviors in online UGC communities.

This study aims to propose a model to elevate the financial empowerment of Muslim women by rejuvenating the practice of Mahr in society and facilitating the affordability of men to pay that Mahr amount.

The approach of this study is to offer a model through the interest-free savings-based finance concept. The model comprises four stages; each stage of the model is mathematically formulated and graphically explained to ensure clarity and coherence. To further investigate the issue, the authors use a convenient sampling method to ask a small sample size of respondents (women) from different countries about their financial contribution and empowerment in the family.

This model enables women to turn their exclusive financial right into a source of earning without borrowing from any source or paying interest on the principal amount. Besides, it encourages accelerating men’s obligation to pay the Mahr to the women immediately during the marriage ceremony by facilitating men’s affordability. Almost 45% of respondents state that a woman’s financial contribution exalts her decision-making power and strengthens her financial position in the family.

The authors attempt to revitalize Mahr practice in Muslim society to accelerate the process of receiving a woman’s exclusive financial right and empower a family as a whole through the Mahr model.

Considering the model’s uniqueness, the developed and proposed Mahr model in this research is novel; to the best of the authors’ knowledge, no other study has been conducted and developed such a model using the Mahr concept.

The purpose of this study is to examine the state of the literature on knowledge sharing in open source software (OSS) development communities by examining the existing research and identifying the knowledge gaps and opportunities that can inform areas for future research.

A systematic literature review was conducted of literature published between January 2011 and February 2023. A total of 24 papers were identified and reviewed.

The findings reveal that the literature on knowledge sharing in OSS development communities from developing countries are limited. Additionally, there exists a limited focus on the development of frameworks to support knowledge sharing in OSS communities. The transient nature of OSS development contributors’ results in knowledge loss; thus, knowledge retention needs further investigation.

This study only included papers whose titles, keywords or abstracts included the search keywords “knowledge sharing” and “Open Source Software”. While the keywords were carefully applied, when applying the search, it cannot be ruled that some relevant studies might have been missed. The study was also limited to conferences and journal papers published in English. Despite the limitations, the study provides a systematic review of knowledge sharing in OSS communities and presents findings that can be useful to researchers and practitioners interested in this area.

The study provides a systematic literature review of published papers and identifies themes and future research areas on knowledge sharing in OSS communities. Additionally, this review offers insights into future research avenues for theory, content and context on knowledge sharing in OSS development communities.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

This study examines the extreme quantile connectedness and spillovers between West Texas Intermediate (WTI) crude oil futures and ten Vietnamese stock market sectors. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors employ the extreme quantile connectedness methodology of Ando et al. (2022).

Initial results show that the size of spillovers is higher during bearish markets than bullish markets and under major financial, political, energy and pandemic events. The oil market is a net receiver of spillovers during downward markets and net contributors during upward markets. The banking sector is a net contributor of spillovers, whereas consumer discretionary and consumer staples are net receivers for different quantiles. The role of the remaining sectors as net receivers/contributors is sensitive to the quantiles. Oil has a large spillover effect on the electricity sector for all quantiles. Comparing all crises, oil offers the best hedging effectiveness to the Vietnamese sector during the coronavirus disease 2019 (COVID-19) crisis. Moreover, oil was a cheap hedge asset during oil crises. Finally, oil provides the highest hedging effectiveness for healthcare during the global financial crisis (GFC) and consumer staples during the European debt crisis (EDC), oil crisis and COVID-19.

Acknowledging the presence of heterogeneity in the relation between oil and economic sectors under different market conditions, this study is the first to examine the extreme quantile connectedness between oil and Vietnamese sectors.

This study examines the dualities of digital services – that is, how customers’ favorite everyday digital services can positively and negatively contribute to their well-being. Thus, the study describes the meanings of favorite digital services as part of customers’ everyday lives and the types of well-being to which such services can contribute.

We used a qualitative research approach through semi-structured interviews conducted in 2021 to collect data from 14 young adults (22–31 years old) who actively used digital services in their daily lives.

Our findings revealed that customers’ favorite everyday digital services can contribute to their mental well-being, social well-being, and intellectual well-being. Within these three dimensions of well-being, we identified nine dualities of digital services that describe their positive and negative contributions: (1) digital escapism versus digital disruption, (2) digital relaxation versus digital stress, (3) digital empowerment versus digital subjugation, (4) digital augmentation versus digital emptiness, (5) digital socialization versus digital isolation, (6) digital togetherness versus digital exclusion, (7) digital self-expression versus digital pressure, (8) digital learning versus digital dependence, and (9) digital inspiration versus digital stagnation.

These findings suggest that everyday digital services have the potential to contribute to customer well-being in various aspects – both positively and negatively – accentuating the need for service providers to decipher the impacts of their offerings on well-being. Indeed, understanding the relationship between digital services and customer well-being can help companies tailor their services to customers’ needs. Companies that prioritize customer well-being not only benefit their customers but also create sustainable growth opportunities in the long run. Further, companies can use the derived information in service design to develop marketing strategies that emphasize the positive impacts of their digital services on customer well-being.

Although prior transformative service studies have investigated the well-being of multiple stakeholders, such studies have focused on services related to the physical and healthcare domains. Consequently, the role of everyday digital services as contributors to customer well-being is an under-researched topic. In addition, the concept of well-being and its various dimensions has received limited attention in previous service research. By investigating everyday digital services and their multidimensional contribution to customer well-being, this study broadens the perspective on well-being within TSR and aids in refining a more precise conceptualization.

The aim of the study is to understand the transformative impact of ChatGPT on artificial intelligence (AI) research, its applications, implications, challenges and potential to shape future AI trends. The study also seeks to assess the relevance and quality of research output through citation and bibliographic coupling analysis.

This study employed a comprehensive bibliometric analysis using Biblioshiny and VOSviewer to investigate the research trends, influential entities and leading contributors in the domain of AI, focusing on the ChatGPT model.

The analysis revealed a high prevalence of AI-related terms, indicating a significant interest in and engagement with ChatGPT in AI studies and applications. “Nature” and “Thorp H.H.” emerged as the most cited source and author, respectively, while the USA surfaced as the leading contributor in the field.

While the findings provide a comprehensive overview of the ChatGPT research landscape, it is important to note that the conclusions drawn are only as current as the data used.

The study highlights potential collaboration opportunities and signals areas of research that might benefit from increased focus or diversification. It serves as a valuable resource for researchers, practitioners and policymakers for strategic planning and decision-making in AI research, specifically in relation to ChatGPT.

This study is one of the first to provide a comprehensive bibliometric analysis of the ChatGPT research domain, its multidimensional impact and potential. It offers valuable insights for a range of stakeholders in understanding the current landscape and future directions of ChatGPT in AI.