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This study aims to reveal the factors that drive researchers to share data and to provide reference for promoting open scientific data.

Based on the theory of social capital and the theory of planned behaviour, hypotheses were proposed and the model was developed. The authors acquired 479 valid samples of Chinese researchers through questionnaires and conducted an empirical analysis via AMOS 23.0.

Attitudes towards data sharing are significantly and positively correlated with trust, reciprocity and social interaction, but not with a shared vision; willingness to share data is significantly and positively correlated with attitudes and perceived behavioural control, but not with subjective norms; furthermore, data quality, which performed the function of a moderating variable, was found to play a facilitating role in the above correlations. Based on the findings, suggestions for relevant entities were specified.

The study developed and validated an integrated theoretical framework, clarified the mechanism by which social capital and planned behaviour affect willingness to share data, hoping to provide reference and empirical support for subsequent studies as well as new ideas for data management and sharing.

Extant research has paid considerable attention to the effects of enterprise social media (ESM) on employees' work attitudes and outcomes, yet the authors know little about the influence of job demands arising from the implementation of ESM. Drawing on resource allocation theory, the purpose of this study is to unravel how ESM-related job demands influence employee outcomes.

This study conducts a two-wave time-lagged survey of 223 employees from 53 teams in 14 financial service firms in China to test the conceptual model.

The findings of this paper indicate that ESM-related job demands have indirect effects on employee outcomes (i.e. job satisfaction and work–family conflict), and emotional exhaustion plays an intermediary role in these relationships. Specifically, ESM-related job demands have a U-shaped effect on emotional exhaustion.

This study combines job demands with ESM research and clarifies the mechanism behind how ESM-related job demands at different intensity affect employee outcomes from a new perspective. Moreover, this study’s findings suggest several beneficial courses of action for managers to take advantage of ESM.

This paper aims to research the corrosion behavior of the metal under the disbonded coatings interfered with AC through electrochemical method.

The corrosion behavior of the metal under disbond coating interfered with alternate stray current (AC) was studied by electrochemical methods using the rectangular coating disbonded simulator. The obtained data from electrode potential test, electrochemical impedance spectroscopy (EIS) and polarization curves in simulated soil solution indicated that under the natural corrosion condition, the self-corrosion potential and the corrosion current density of the metal at different depths under disbond coating had obviously changed if there was AC interference.

The self-corrosion potential of the metal at the same depths under disbond coating shifted negatively with the rising of the AC voltage. Under the condition of cathode polarization, there was still obvious potential gradient with the extension of the deep peeling of the coating gap, and the corrosion current density of the test points was minimum, and the protection effect was best when the cathode protection potential was −1.0 V. When the metal was applied with over-protection, the corrosion rate of the metal increased as AC stray current flowing through it increased.

This paper used the rectangular aperture device to study the corrosion behavior of X80 steel under the disbonded coatings through electrochemical methods when the AC stray current interference voltage was 0V, 1V, 5V or 10V and the protection potential was 0V, −0.9V, −1.0V, −1.2V or −1.3V, respectively. There is great significance to the safe operation and long-term service of pipeline steel in soil environment.

Influence diagrams (IDs) have been widely applied as a form of knowledge expression and a decision analysis tool in the management and engineering fields. Relationship measurements and expectation values are computed depending on probability distributions in traditional IDs, however, most information systems in the real world are nondeterministic, and data in information tables can be interval valued, multiple valued and even incomplete. Consequently, conventional numeric models of IDs are not suitable for information processing with respect to imprecise data whose boundaries are uncertain. The paper aims to discuss these issues.

The grey system theory and rough sets have proved to be effective tools in the data processing of uncertain information systems, approximate knowledge acquisition and representation are also the objectives in intelligent reasoning and decision analysis. Hence, this study proposes a new mathematical model by combining grey rough sets with IDs, and approximate measurements are used instead of probability distribution, an implicational relationship is utilized instead of an indiscernible relationship, and all of the features of the proposed approach contribute to deal with uncertain problems.

The focus of this paper is to provide a more comprehensive framework for approximate knowledge representation and intelligent decision analysis in uncertain information systems and an example of decision support in product management systems with the new approach is illustrated.

Collaboration of IDs and grey rough sets is first proposed, which provides a new mathematical and graphical tool for approximate reasoning and intelligent decision analysis within interval-valued information systems.

The aim is to present in this paper an effective strategy in dealing with a semi‐infinite interval by using a suitable mapping that transforms a semi‐infinite interval to a finite interval.

The authors introduce a new orthogonal system of rational functions induced by general Jacobi polynomials with the parameters alpha and beta. It is more flexible in applications. In particular, alpha and beta could be regulated, so that the systems are mutually orthogonal in certain weighted Hilbert spaces.

This approach is applied for solving a non‐linear system two‐point boundary value problem (BVP) on semi‐infinite interval, describing the flow and diffusion of chemically reactive species over a nonlinearly stretching sheet immersed in a porous medium. The new approach reduces the solution of a problem to the solution of a system of algebraic equations.

The paper presents an effective strategy in dealing with a semi‐infinite interval by using a suitable mapping that transforms a semi‐infinite interval to a finite interval.

In order to reduce logistics transportation costs and respond to low-carbon economy, the purpose of this paper is to study the more practical and common simultaneous pickup and delivery vehicle routing problem, which considers the carbon tax policy. A low-carbon simultaneous pickup and delivery vehicle routing problem model is constructed with the minimum total costs as the objective function.

This study develops a mathematical optimization model with the minimum total costs, including the carbon emissions costs as the objective function. An adaptive genetic hill-climbing algorithm is designed to solve the model.

First, the effectiveness of the algorithm is verified by numerical experiments. Second, the research results prove that carbon tax mechanism can effectively reduce carbon emissions within effective carbon tax interval. Finally, the research results also show that, under the carbon tax mechanism, the effect of vehicle speed on total costs will become more obvious with the increase of carbon tax.

This paper only considers the weight of the cargo, but it does not consider the volume of the cargo.

Few studies focus on environmental issues in the simultaneous pickup and delivery problem. Thus, this paper constructs a green path optimization model, combining the carbon tax mechanism for the problem. This paper further analyzes the impact of carbon tax value on total costs and carbon emission; at the same time, the effect of vehicle speed on total cost is also analyzed.

This study aims to explore the influence of information presentation conditions on the flow experience of digital reading for high school students.

Firstly, a survey determines the preferred reading medium and the types of texts that high school students frequently read. Secondly, Experiment 1 focuses on the effects of the text type and reading medium on flow experience and reading comprehension. Finally, Experiment 2 addresses a narrative text presented on a smartphone, and discusses the influence of advance organizer, presentation format and page layout on flow experience and reading comprehension.

In digital reading, the narrative text has a stronger flow experience than explanatory text; the flow experience of reading narration on smartphones is more evident than on computers. The advance organizer and text combined with pictures are more conducive to a flow experience when a smartphone is used as a reading medium. From the perspective of reading comprehension, scrolling is more suitable for reading text combined with pictures and paging best suits pure text.

Through experimental methods, this study reveals the influence of information presentation conditions on the digital reading flow experience, which is a meaningful and innovative topic. The findings can provide more enlightenment and reference for the design and promotion of digital resources and digital reading by teenagers.

The M&A literature lacks coherence and consistency when explaining the role of CEO power in influencing post-acquisition firm performance in both theoretical and empirical terms. This study uses meta-analytic techniques to quantitatively synthesize and evaluate the impact of 11 CEO power constructs (CEO duality; compensation; ownership; founder CEO; acquisition experience; functional area experience; outside directorship; elite education; CEO celebrity; age; and tenure) on acquiring firms’ post-acquisition performance. Results of 85 independent studies show that CEO ownership, functional area experience, and tenure are significantly positive predictors for better acquisition performance. At the same time, CEO duality and CEO elite education are significantly negative predictors of different measures of acquisition performance. These findings indicate the importance of integrating different theories to enhance our understanding of the nature of strategic leadership in acquisition performance.

This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive review of the predominant research organisations and countries, key themes and favoured research methodologies pertinent to this subject.

The authors extracted data on social media trending topics from the Web of Science Core Collection database, spanning from 2009 to 2022. A total of 1,504 publications were subjected to bibliometric analysis, utilising the VOSviewer tool. The study analytical process encompassed co-occurrence, co-authorship, citation analysis, field mapping, bibliographic coupling and co-citation analysis.

Interest in social media research, particularly on trending topics during the COVID-19 pandemic, remains high despite signs of the pandemic stabilising globally. The study predominantly addresses misinformation and public health communication, with notable focus on interactions between governments and the public. Recent studies have concentrated on analysing Twitter user data through text mining, sentiment analysis and topic modelling. The authors also identify key leading organisations, countries and journals that are central to this research area.

Diverging from the narrow focus of previous literature reviews on social media, which are often confined to particular fields or sectors, this study offers a broad view of social media's role, emphasising trending topics. The authors demonstrate a significant link between social media trends and public events, such as the COVID-19 pandemic. The paper discusses research priorities that emerged during the pandemic and outlines potential methodologies for future studies, advocating for a greater emphasis on qualitative approaches.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2023-0194.

Merton’s model of capital market equilibrium under incomplete information predicts that contemporaneous stock returns are positively related to investor recognition and that future stock returns are negatively related to investor recognition. The purpose of this paper is to empirically investigate whether Merton’s theory holds true for the Chinese stock market.

This paper proposes the degree of shareholder base growth (SBG) as a proxy for investor recognition and examines the relationship between investor recognition and stock returns through a univariate analysis and Fama-Macbeth cross-sectional regressions based on A-Share listed firms.

The results show that investor recognition is nonlinearly and positively related to contemporaneous stock returns and is negatively related to future stock returns in contrast to the conclusions of Merton’s theory. A long-short trading strategy that involves buying stocks with the lowest SBG rate and that sells stocks with the highest SBG rate will earn an average monthly return of 3.615 percent.

Though Merton’s theory is not fully reflected in the Chinese stock market, investor recognition is considered an important risk factor in the Chinese stock market.

No works have yet investigated the validity of Merton’s “investor cognition hypothesis” in relation to the Chinese stock market. This paper strives to fill this gap.