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The reduced problem of the Navier–Stokes and the continuity equations, in two-dimensional Cartesian coordinates with Eulerian description, for incompressible non-Newtonian fluids, is considered. The Ladyzhenskaya model, with a non-linear velocity dependent stress tensor is adopted, and leads to the governing equation of interest. The reduction is based on a self-similar transformation as demonstrated in existing literature, for two spatial variables and one time variable, resulting in an ODE defined on a semi-infinite domain. In our search for classical solutions, existence and uniqueness will be determined depending on the signs of two parameters with physical interpretation in the equation. Illustrations are included to highlight some of the main results.

Prosocial lending in online crowdfunding has flourished in recent years, and it has become a new way to fundraise for philanthropy. However, there is almost a 70% user attrition rate in crowdfunding. The purpose of this study is to understand what the lender’s lending experience and social connection influence lender retention of online prosocial lending from a self-determination perspective.

Drawing on self-determination theory (SDT), this research utilizes a quantifiable method for factors of the lender's lending experience and social connection. Additionally, the research constructs economic models to explore the impacts of these factors acting as the necessary conditions for basic psychological needs on lender retention, using a large-scale sample of over 380,000 lenders from Kiva.

The results indicate that, from the lender's lending experience aspect, the loan narratives with more profit language in the last lending and the failure of past participation are negatively related to lender retention. Regarding the lender's social connection aspect, their friends or small lending teams are positively related to lender retention, while whether they are invited and lending team size show negative influence. Furthermore, results indicate the moderating effects of the disclosure of lending motivation.

This research explores the mechanism of lender retention of online prosocial lending, providing a self-determination perspective about how previous experience influences long-term lending behavior. The study offers significant implications for the literature on online philanthropy, SDT and user retention of online platforms. At the same time, the study provides an understanding of the effects of different aspects of SDT.

The purpose of this paper is to help enhance the scholarly conversation about the essential nature of the entrepreneurial orientation (EO) construct, its dimensionality and measurement. The authors focus on how EO was defined and measured in various contexts, which is the basis for the proposed five-dimensional EO scale (FDEOS).

Survey was conducted in design industry in China. A pilot test was conducted with 20 Chinese firms. Questionnaires were sent to 1,200 firms. A total of 408 complete and valid questionnaires were received.

It was found that a behavior aspect of EO as a second-order reflective model had a greater degree of agreement among scholarly community. As a result, a new FDEOS was proposed from behavioral perspective. Data were collected from 408 firms of design industry in a big developing country.

While five-dimensional EO construct is a well-recognized concept in the literature on entrepreneurship, little is known about its measurement. The research reported in this paper provides support for this assertion and develops a new scale, FDEOS, that designed to be neutral with regard to industry context and type of organization.

This paper aims to provide a typical example of accounting for the carbon dioxide equivalent (CO₂e) in underdeveloped cities, especially for the Poyang Lake area in China. The accounting can increase public understanding and trust in climate mitigation strategies by showing more detailed data.

The paper uses the “Global Protocol for Community-scale greenhouse gas emission inventories (GPC)” method, a worldwide comparable framework for calculating urban CO₂e emission (CE). The empirical case is an underdeveloped city, Nanchang, in China.

The results show the total CE of Nanchang, containing the electricity CE of Scope 2, grew rapidly from 12.49 Mt in 1994 to 55.00 Mt in 2014, with the only recession caused by the global financial crisis in 2008. The biggest three contributors were industrial energy consumption, transportation and industrial processes, which contributed 44.71-72.06, 4.10-25.07 and 9.07-22.28 per cent, respectively, to the total CE. Almost always, more than 74.41 per cent of Nanchang’s CE was related to coal. When considering only the CEs from coal, oil and gas, these CEs per unit area of Nanchang were always greater than those of China and the world. Similarly, these CEs per gross domestic product of Nanchang were always bigger than those of the world. Thus, based on these conclusions, some specific countermeasures were recommended.

This paper argues that the CO₂e accounting of underdeveloped cities by using the GPC framework should be promoted when designing climate mitigation policies. They can provide more scientific data to justify related countermeasures.

Social loafing in knowledge contribution (namely, knowledge contribution loafing [KCL]) usually happens in group context, especially in the mobile collaboration tasks. KCL shows dynamic features over time. However, most previous studies are based on static assumption, that is, KCL will not change over time. This paper aims to reveal the dynamics of KCL in mobile collaboration and analyze how network centrality influences KCL states considering the current loafing state.

This study is based on empirical study design. Real mobile collaboration behavioral data related to knowledge contribution were collected to investigate the dynamic relationship between network centrality and KCL. In total, 4,127 chat contents were collected through Slack (a mobile collaboration APP). The text data were first analyzed using the text analysis method and then analyzed by a machine learning method called hidden Markov model.

First, the results reveal the inner structure of KCL, showing that it has three states (low, medium and high). Second, it is found that network centrality positively influences individuals involved in medium and high loafing state, while it has a negative influence on individuals with low loafing state.

The limitations are related to the single machine learning method and no subdivision of social network. First, this paper only uses one kind of text classification model (TF-IDF) to divide chat contents, which may not be superior to other classification models. This paper considers the eigenvector centrality, and not further divides the social network into advice network and expressive network.

This study helps companies infer tendency of different KCL and dynamically re-organize a mobile collaborative team for better knowledge contribution.

First, previous studies based on static assumptions regarding KCL as static and the relationship between loafing reducing mechanisms and team members KCL does not change over time. This study relaxes static assumptions and allows KCL to change during the process of collaboration. Second, this study allows the impact of network centrality to be different when members are in different KCL states.

Drawing on the stress and coping theory, conservation of resources (COR) theory and social role theory, this study aims to investigate the impact of social media overload on knowledge withholding behavior and examine the gender differences in social media overload, engendering knowledge withholding.

By hiring a professional online survey company, this study collected valid responses from 325 general social media users. The structural equation modeling (SEM) technique, bootstrapping method and multi-group analysis were used to test the proposed theoretical model.

The empirical results reveal that three types of social media overload positively affect users' knowledge withholding behavior and that emotional exhaustion significantly mediates the above relationships. The multi-group analysis demonstrates that gender differences do exist in the decision-making process of knowledge withholding; for example, females are more likely than males to become emotionally exhausted from social media overload, while males are more likely than females to engage in knowledge withholding behavior in the case of emotional exhaustion.

This study contributes to the existing body of knowledge by examining the relationship between social media overload and knowledge withholding, verifying the mediating role of emotional exhaustion as the key mechanism linking them, and narrowing the research gap of lacking gender differences research in knowledge withholding literature.

The purpose of this paper is to provide a theoretical foundation for improving the selective laser melting (SLM) surface roughness. To improve the part’s surface quality during SLM process, the upper surface roughness of SLM parts was theoretically studied and the influencing factors were analyzed through experiments.

The characteristics of single track were first investigated, and based on the analysis of single track, theoretical value of the upper surface roughness would be calculated. Two groups of cubic sample were fabricated to validate SLM parts’ surface roughness, the Ra and relative density of all the cubic parts was measured, and the difference between theoretical calculation and experiment results was studied. Then, the effect of laser energy density on surface roughness was studied. At last, the SLM part’s surface was improved by laser re-melting method. At the end of this paper, the curved surface roughness was discussed briefly.

The SLM upper surface roughness is affected by the width of track, scan space and the thickness of powder layer. Measured surface roughness Ra value was about 50 per cent greater than the theoretical value. The laser energy density has a great influence on the SLM fabrication quality. Different laser energy density corresponds to different fabricating characteristics. This study divided the SLM fabrication into not completely melting zone, balling zone in low energy density, successfully fabricating zone and excessive melting zone. The laser surface re-melting (LSR) process can improve the surface roughness of SLM parts greatly without considering the fabricating time and stress accumulation.

The upper surface roughness of SLM parts was theoretically studied, and the influencing factors were analyzed together; also, the LSR process was proven to be effective to improve the surface quality. This study provides a theoretical foundation to improve the surface quality of SLM parts to promote the popularization and application of metal additive manufacturing technology.

The purpose of this study is to review the literature on digital content management (DCM) published between 2001 and 2021, as well as to provide insights and research directions for the future.

This study followed the systematic literature review framework PRISMA for reviewing existing literature on DCM. The PRISMA checklist helps the researcher in refining the reporting of the review paper. Data was collected from Scopus and Web of Science (WoS) databases. A total of 136 documents were selected for analysis from Scopus and WoS.

Based on current papers, this study attempted to discuss some key DCM trends and themes. Seven themes have been identified in the literature: virtual reality and its implications on DCM; personal DCM; microservices based DCM; model for DCM; DCM using Bluetooth Low Emergency technology; DCM software; and DCM codification. This study identifies influential authors, top contributing countries, top contributing institutions, most cited papers, most common title words and contributions by fields.

The findings of this study, as well as future research projects, open the path for more research and contributions to the field.

Based on the knowledge-based view, this study investigates how firms' information technology (IT) capability broadens and deepens their knowledge base, which consequently improves digital innovation. By further drawing on the institutional theory perspective, this study examines how the relationships between IT capability and knowledge base are moderated by the institutional environments in which the firm operates.

This paper uses 170 samples of Chinese firms and an empirical test conducted by the authors following a hierarchical moderated regression analysis.

The results find that IT capability positively affects knowledge breadth and knowledge depth, which consequently improves digital innovation. Furthermore, the study reveals the negative moderating effects of enforcement inefficiency on IT capability–knowledge breadth relationship, and the negative moderating effects of government support on IT capability–knowledge depth relationship.

This research is one of the earliest attempts to explore the impact of the institutional environment of emerging economies on IT capability. It also clarifies the impact of knowledge breadth and knowledge depth on digital innovation.

“Metaverse” has become a buzzword in the Chinese stock market. However, it remains unclear whether a firm's metaverse-related announcements will elicit positive stock market reactions. Whether and how stakeholder reactions are influenced by a firm's metaverse-related readiness also needs to be further explored. This study aims to discuss the aforementioned objective.

The authors derived a set of factors based on readiness theory and business ecosystem literature and extend them into the context of the metaverse. The authors used a sample of 642 Chinese listed firms in 2021 to investigate the hypotheses through the event study.

The study’s findings show that metaverse coverage induces a positive stock market reaction, but it is subject to three moderating effects. The authors introduce the novel concepts of IT readiness, ecosystem readiness and digital infrastructure readiness as the moderators. Stakeholders perceive metaverse announcements as overhyped, and stock prices do not fluctuate significantly after a metaverse announcement when the listed firms are not ready to embrace the metaverse.

This study is one of the first that introduces the event study method into the metaverse research, and it reveals that different levels of readiness influence stakeholders' evaluations and reactions to corporate metaverse coverage. This provides empirical evidence on metaverse development in China from the stock market's perspective.