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Although previous research has recognized the pivotal role of mobile social media in knowledge sharing among project members, little is known about what factors affect knowledge sharing in mobile social media groups (MSMGs). Against this background, using normative social influence theory, this study attempts to explore factors influencing knowledge sharing in MSMGs.

Data from 205 Chinese construction project members are collected and used for analysis. Ordinary least squares regression by Stata 16 is used to test the proposed hypotheses.

Concerning role norms, gender difference in knowledge sharing behavior (KSB) is found, while it is not the case for knowledge quality (KQ). Work experience is found to positively affect KQ, but shows no influence on KSB. As for group norms, the inverted-U relationship between number of members and KSB is partially supported. In addition, organizational norms generally exhibit the greatest influence on both KSB and KQ among the three forms of norms.

This study deepens the understanding of knowledge sharing factors in mobile social media environments and affords practical implications for how to make full use of social media for knowledge management within construction project teams.

Despite the documented benefits of voice behavior for projects, little is known about antecedents of voice behavior in the project context, especially construction projects. Against this background, adopting a multi-team system perspective, this study attempts to investigate antecedents of team voice behavior from a contextual view.

This study identifies and examines six factors that influence team voice behavior. Specifically, project urgency, project temporality, and project complexity are identified from the project nature perspective. Satisfaction, trust, and commitment are generated from the relationship quality approach. Then, data from completed construction projects in China was collected to verify the effectiveness of these factors. Besides, the partial least squares structural equation modeling (PLS-SEM) technique was used in this study.

All six factors are found to be significant predictors of promotive team voice behavior. For prohibitive team voice behavior, only project complexity and project commitment make significant effects. Further, the differential effects of these factors on two types of voice behavior are revealed.

This study contributes to the literature on voice behavior in the project context, especially construction projects consisting of multiple teams. Also, this research enriches our knowledge on antecedents of team voice behavior in construction projects and thus affords practical implications to foster voice behavior.

EU countries, including those in Central and Eastern Europe, seem to have increasingly similar economies, allowing for the study of real convergence as a process of equalising income levels (measured by GDP per capita). Studies of income convergence in the European Union also have a regional dimension and often focus on convergence at the NUTS2 or NUTS3 regional level. The level of development and income in Polish regions differ significantly. The regional policy implemented at the national and EU level focuses on reducing these differences.

The main aim of the chapter is to analyse the income convergence process among regions in Poland and verify the effectiveness of regional policy implemented at the national and EU level.

The study uses Barro type regression for panel data, log t convergence test, and club clustering algorithm introduced by Phillips and Sul to identify patterns of club convergence in Polish regions. The data used for the study is the Local Data Bank provided by Statistics Poland, which includes gross domestic product per capita at the NUTS-3 level for 73 Polish regions over the period of 2000–2020.

The results of the study indicate a very weak convergence process for all Polish NUTS-3 regions and suggest a club convergence. The club convergence is characterised by regions with similar income levels clustering together. The regional distribution of clubs is similar to the regional distribution of income. The study's findings provide important insights into the effectiveness of regional policy in Poland and suggest that policymakers need to focus on policies that promote catch-up growth in less developed regions. The study also highlights the importance of supporting the most developed regions in the country as they can play a crucial role in driving the country's economic growth and prosperity.

The purpose of this study is to explore the impact of asymmetric trust on construction project management performance in China's construction industry. Moreover, the authors explore the mediating role of two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) in explaining the association between asymmetric trust and project management performance.

A theoretical model based on the research hypotheses proposed in this study was developed and a questionnaire survey was conducted with 271 professionals. The data collected was analyzed by the structural equation modeling (SEM) technique.

The results of this study indicate that there is a significant and negative association between asymmetric trust and project management performance. Moreover, two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) have different degrees of impact on improving project management performance. In addition, tacit knowledge sharing is a mediator between asymmetric trust and project management performance.

The data used in this study is from Chinese scenarios, so the research conclusions and application effects based on this are bound to have certain regional limitations. Besides, there are many factors that affect project management performance improving, and the relationships among them are so complex. The theoretical model proposed in this study may not be fully considered. Therefore, follow-up researchers can consider bringing more suitable variables into their researches, so that the theoretical researches can be more in line with the actual project management practice, and the specific mechanism for improving project management performance can be explained more deeply.

This research's value is as follows: Firstly, this paper contributes to the trust and relational governance literature by expanding the research perspective of mutual trust to asymmetric trust. Specially, this research designs a measurement scale for asymmetric trust and then reveals the impact mechanism of it on project management performance, which will certainly promote research paradigm change of trust. Secondly, this research is beneficial to knowledge sharing literature in the construction management field by expanding the research scope of knowledge sharing from a cross-organizational perspective.

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.

This study aims to solve the realistic dilemma between the importance of entrepreneurship and the high rate of entrepreneurial failure, and to point out the direction of subsequent research.

The paper takes the form of a literature review.

Entrepreneurial activities involve multiple dimensions. Entrepreneurs or entrepreneurial teams will be affected by multiple factors when starting a business, and sufficient attention should be paid to both the factors within the group and the factors outside the group such as institutional quality and market competition. High entrepreneurial failure rate is an essential characteristic of entrepreneurial activities, while solving this problem requires entrepreneurs to maintain passion, clarify their own motivation, improve their learning abilities and adopt appropriate entrepreneurial strategies to improve entrepreneurial performance. Meanwhile, it also urgent to build entrepreneurial teams with common goals, heterogeneous knowledge structure, outstanding learning ability, solid mutual trust, strong social influence and social capital. Successful entrepreneurship should adhere to the perspective of openness and cooperation. It should not only actively strengthen international cooperation but also fully adapt to the country’s system and culture. Sustainable growth of entrepreneurial enterprises requires not only stable commercial revenue but also responsibility to society, which in turn leads to a good reputation and high social recognition.

The authors hope this review can provide some insightful viewpoints for deepening the theoretical system of entrepreneurship, improving the success rate of entrepreneurship and promoting the sustainable growth of enterprises.

Further research can be carried out on the promotion of business growth by entrepreneurship at the micro level in the following aspects: analyze functional mechanism between innovation and entrepreneurship; entrepreneurship research by integrating multiple institutional contexts and cultural traditions; consider the changes in emerging technologies on entrepreneurial activities; diversified mechanism between entrepreneurship education and business growth.

The tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.

To tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.

The proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.

(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

Online influencers are increasingly used by brands around the globe to establish brand communication. This study aims to investigate the characteristics of social media content in terms of presentation style and brand communication among online influencers in China. The authors identified how characteristics of social media posts influence young consumers’ engagement with the posts.

The authors analyzed 1,779 posts from the Sina Weibo accounts of ten top-ranked online influencers by combining traditional content analysis with Web data crawling of audience engagement with social media posts.

Online influencers in China more frequently used photos than videos to communicate with their social media audience. Altogether 8% and 6% of posts carried information about promotion and event, respectively. Posts with promotional incentives as well as event information were more likely to engage audiences. Altogether 22% of the sampled social media posts mentioned brands. Posts with brand information, however, were less likely to engage audiences. Furthermore, having long text is more effective than photos/images in generating likes from social media audiences.

Combining content analysis of social media posts and engagement analytics obtained via Web data crawling, this study is, to the best of the authors’ knowledge, one of the first empirical studies to analyze influencer marketing and young consumers’ reactions to social media in China.

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.

This study aims to investigate the influence and impact mechanism of capital tax incentives on firm innovation.

This study employs the difference-in-differences (DID) method, in conjunction with the exogenous impact of accelerated depreciation (AD) pilot policy. This study selects Chinese listed companies from 2010 to 2017 as the research sample.

Firstly, AD exerts a substantial positive effect on the quantity and quality of the innovation output of firms, and the positive impact results primarily from heightened investment in fixed assets, particularly, machinery and equipment. Secondly, the influence of the policy is pronounced in non-state-owned enterprises, mature enterprises, less capital-intensive enterprises and non-high-tech industries, which all exhibit strong innovation incentives. Lastly, the tax incentive policy significantly stimulates firm innovation in the short term, but its long-term impact on innovation incentives lacks statistical significance.

This study highlights the significance of capital tax incentives in facilitating the innovation process in firms.