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The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors toward financial technology (fintech) platforms, so extracting the sentimental tendency information has great practical value for the development of fintech platforms. Based on the investor sentiment theory, the paper aims to analyze the relevant social media data and test the influence path of online news evaluation on the stock price fluctuation of fintech platforms.

Taking Oriental Fortune as the research object, this paper selects multiple variables such as stock bar popularity, snowball popularity, news popularity and news sentiment scores collected by UQER and combines the sentiment scores of single daily news into a daily sentiment score. Based on the period from November 1, 2019 to March 31, 2020, during the emergence of the coronavirus disease 2019 (COVID-19) pandemic as the background, the authors conduct the Granger causality test based on the vector autoregressive (VAR) model and analyze the relevant evaluation of Oriental Fortune through the empirical model.

The authors' results show that different online evaluations impact the rise and fall of stock prices differently, while news popularity has the most significant impact. Besides, news sentiment scores on share price fluctuation have a relatively substantial influence. These findings indicate that the authoritative news evaluation can strongly guide investors to make relevant investment behavior operations in the information dissemination process, significantly affecting stock prices.

The research findings of this paper have good inspiration and reference values for investors and financial regulators.

With its continuous development and application in the hotel industry, artificial intelligence (AI) is gradually replacing many jobs traditionally performed by humans. This research aims to understand how this threat and opportunity of substitution affects hotel employees’ behavioral decision-making.

This study uses a structural equation model, ordinary least squares and bootstrapping method to analyze the data collected with a field study and a scenario experiment from star-hotels in Shanghai, Paris and Seoul.

The results discovered that employees’ AI awareness has a positive relationship with their work engagement and AI boycott through two paths. The promoting path involves recovery level, while the hindering path includes job insecurity. In addition, the estimates showed that AI awareness has a great indirect effect on work engagement or AI boycott when innovativeness as a job requirement is high.

The findings offer insights to help hotels optimize the relationship between AI and hotel human workers while providing valuable implications for addressing behavioral dilemmas faced by hotel employees in the era of AI.

By integrating the behavioral decision-making literature with the conservation of resources theory, the study focuses on the dual mechanisms – challenging and hindering – through which AI awareness influences hotel employees’ coping strategies.

The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent findings regarding consumer engagement behavior. To address this knowledge deficit, we contribute to the consumer engagement literature by developing and testing a conceptual model that explores and explains the relationships between the factors that influence continued engagement intention (CEI), a form of behavioral intention.

A literature review was conducted to identify gaps and develop a theoretically informed conceptual model and hypotheses. Survey data from 604 Instagram SMI followers were analyzed using partial least squares structural equation modeling using SmartPLS 3.3.3 to assess the structural model relationships and conduct post hoc analysis.

The findings suggest that it is important to positively influence consumer responses to elicit CEI. Furthermore, homophily attitudes toward SMIs moderate the relationship between SMI experience and CEI.

Brands must work with SMIs to create positive SMI experiences and develop CEI. Furthermore, SMIs should focus on brands that fit their lifestyles to enhance homophily attitudes and forge CEI.

This study contributes to the literature by combining social exchange and flow theories to develop and test a holistic framework for examining CEIs regarding SMIs and brands. The findings show that creating positive SMI experiences benefits brands seeking CEI.

This study aims to examine the effects of economic uncertainty on Shariah stock returns (SR) in Asia-Pacific Economic Cooperation countries. This study also compares the impacts of uncertainty on Shariah and conventional stocks.

A panel vector autoregressive model was used to capture the dynamic relationships between variables. Granger tests, impulse response functions and forecast error variance decomposition are applied to obtain a comprehensive interpretation.

The empirical results indicated that temporary economic uncertainty has a significant adverse impact on Shariah SR. The stability was also observed over time. This study also revealed that Shariah stocks were affected by economic uncertainty, although they were designed to mitigate such effects. In addition, Shariah stocks show lower sensitivity to uncertainty. However, their recovery was slower than that of conventional stocks.

Short-term investors are advised to diversify their portfolios. In the long term, the stability of Shariah SR enables investors to pursue their financial goals. Policymakers are encouraged to improve investor confidence and develop policies to accelerate the recovery of the Sharia stock prices.

This study proves the existence of uncertainty in the Shariah stock market and explores the comparative impact of uncertainty on Shariah and conventional stocks. Furthermore, by incorporating uncertainty as a variable, this study contributes to expanding the efficient market hypothesis, offering a deeper understanding of market behaviour under uncertain conditions.

This study aims to investigate the effect of top management team (TMT) stability on outward foreign direct investment (OFDI) of Chinese firms and the moderating effects of state ownership and managerial ownership on this relationship.

An empirical analysis based on the ordinary least square regression model is conducted using Chinese A-share listed firms that engaged in OFDI from 2008 to 2021.

TMT stability has a positive effect on firms’ OFDI. Moreover, state ownership significantly strengthens the positive relationship between TMT stability and OFDI, while managerial ownership weakens this positive relationship.

The findings help firms to effectively retain TMT talents and promote the smooth internationalization of firms, thereby enhancing their long-term development capabilities and competitive advantages.

This study expands the investigation of the factors influencing OFDI at the micro level of the TMT, providing valuable decision-making insights for firms.

The crowdsourcing software development platforms organize geographically distributed developers to complete various developing tasks, bringing convenience and efficiency to users. However, with the increasing number of both developers and tasks, it becomes more and more challenging to match tasks and suitable developers, especially for imbalanced data. The purpose of this paper is to propose an accurate and diverse recommendation model for crowdsourcing tasks.

A revised circle loss function is applied to achieve a certain adaptive ability, which is critical for imbalanced data, it guarantees diversity by maximizing the target label score and leveraging mathematical approximation to automatically balance the weights. Besides, the authors leverage the capsule network to obtain the semantic feature of tasks’ descriptions, modify the dynamic routing mechanism to better learn users’ preferences and improve the recommendation accuracy.

The comprehensive experiments conducted on real crowdsourcing platform data demonstrate that the proposed Crowd-CapsNet model can achieve high recommendation accuracy with a certain diversity. It improves around 1% accuracy with only 37% training time of the LSFA approach.

This paper proposes Crowd-CapsNet, an adaptive crowdsourcing task recommendation model. A relatively general feature pre-processing method describes crowd-sourcing tasks and the modified capsule network further obtains the semantic features to improve the recommendation accuracy and diversity.

The traditional information phase of value engineering (VE) workshops often involves face-to-face meetings and physical site visits, which can be time-consuming, costly and impractical due to various constraints. This paper introduces a web-based platform integrating BIM and GIS to streamline this phase by systematically gathering, processing and visualizing multi-format information in a virtual environment.

A comprehensive literature review was conducted to analyze the potential of BIM and GIS integration in the VE context. A three-step information structure generation method was employed to outline the information gathering needs during the VE workshops, incorporating a review of multi-source references. A framework including information gathering, processing and visualization was proposed to streamline the information phase with BIM and GIS integration as the core. Subsequently, a web-based prototype platform was developed utilizing the three-layer architecture, with the case study to demonstrate its application. A comprehensive evaluation involving black box testing, user interface testing and focus group discussion was conducted to validate the functionality, usability, potential and limitations.

The platform can support the systematic collection, processing, organization and visualization of multi-format information during the information phase, enable virtual meetings and virtual site visits and facilitate VE participants’ review, understanding and analysis of such information and the documentation of their comments and suggestions. The black box testing validated its functionality, with necessity, effectiveness and convenience confirmed by VE practitioners. Its potential was approved due to clear information structure, web-based virtual review and logical multi-format information organization.

The generalized four-category information structure and proposed three-layer framework streamline the information phase of VE practices. The developed platform allows the VE team to review multi-format information virtually, simultaneously, freely and as many times as necessary.

Recognition of the complexity of job embeddedness in the work environment has grown, highlighting the need for a deeper understanding of the factors that contribute to this phenomenon. This study analyzed how and when job crafting and leisure crafting are linked to job embeddedness by investigating employee resilience as a mediator and employee adaptivity as a moderator.

Data were gathered from 568 Taiwanese hotel employees. The PROCESS macro was used to verify all hypotheses.

Both job crafting and leisure crafting increased job embeddedness. Employee resilience mediated the impacts of job and leisure crafting on job embeddedness. The positive relationship between employee resilience and job embeddedness was stronger when employee adaptivity was high. Employee adaptivity moderated the indirect impacts of job and leisure crafting on job embeddedness through employee resilience.

Hotel managers should foster a workplace culture that encourages employees to engage in job crafting. Additionally, managers can offer employee assistance programs to proactively encourage workers to participate in leisure crafting. Providing training and wellness programs to strengthen employee resilience, along with allocating resources and designing learning programs to enhance employee adaptability, can further promote job embeddedness.

This research contributes to the literature through the construction of a moderated mediation model that explored how and when job and leisure crafting affect job embeddedness.

International trade and its effects on the environment are increasingly discussed both in academia and by policymakers. To counter negative effects of international trade on the environment, so called environmental provisions have been integrated in trade agreements aimed at businesses and economies. However, as both the intent and effectiveness of these provisions are controversial, this paper aims to provide an overview of the current state of research and identified key factors influencing their effectiveness.

The authors conduct a systematic literature review of 44 papers on the effects of environmental provisions in international trade agreements on the environmental performance of businesses, as well as economies from 1992 to mid-2024.

The integration of environmental provisions into trade agreements generally has positive effects on the environment while their effectiveness is influenced by their design and several boundary conditions. Alongside the importance of effective enforcement mechanisms, reputation concerns of businesses and lobbyism are discussed as intermediary factors in the design and impact of environmental provisions.

The insights can benefit policymakers to optimize future environmental provisions and advance the effectiveness of policies aimed at balancing the effects of trade liberalization with environmental protection.

Social sustainability is increasingly relevant for creating more sustainable trade policy while societal mechanisms seem to be an adequate tool to ensure effective enforcement of ecological provisions.

To the best of the authors’ knowledge, this review is the first of its kind to provide a systematic overview of the literature on the effectiveness of environmental provisions that combines the micro-level of businesses and macro-level of economies, although the importance for trade in general and environmental protection, in particular, has been recognized in the academic literature.

This study undertook a systematic literature review of consumers’ information and knowledge sharing (I&KS) in digital scenarios, as it is an expanding thematic area that differs from other consumer behavior and has been underexplored.

Following the PRISMA philosophy, we identified I&KS-related studies in the Scopus database based on a search term chain determined through an exploratory study. Additional inclusion and exclusion criteria were applied, and studies were manually filtered. An input–process–output type model was used to manually review and systematize the literature. Then, a second content analysis was conducted using artificial intelligence (AI) tools.

Based on 51 relevant articles, this study characterized the I&KS research field as multidisciplinary through quantitative methods. Based on an input–process–output consumer behavior model and content analysis, this study systematized existing knowledge and revealed that most knowledge encompassed the influence of personal and psychological consumer characteristics. Additionally, based on AI tools applied to the full texts of the relevant articles, five thematic clusters emerged, largely coinciding with the input–process–output model used. Finally, future research avenues and recommendations for business and organizational practices were identified.

This study fills the gap in consumer studies by systematically reviewing I&KS, a developing field, as no prior research has addressed this topic systematically.