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Drawing upon social cognitive theory, this study aims to investigate the potential predictors and consequences of social media health-misinformation seeking behavior during the coronavirus (COVID-19) pandemic.

Using a sample of 230 international students studying at Wuhan University and Beijing Language and Cultural University, China, this study employs structural equation modeling to analyze the collected data.

The results indicate that personal factors such as lack of health information literacy, environmental factors, information overload and social media peer influence have a significant effect on behavior, namely social media health-misinformation seeking behavior, which further influences outcomes, namely social media users' anxiety during the COVID-19 pandemic. In addition, both lack of health information literacy and social media peer influence have significant and direct effects on social media users' anxiety. However, the direct effect of information overload on social media users' anxiety is insignificant.

First, this study contributes to the literature on the individuals' social media health-misinformation seeking behavior, its precursors and its consequences, specifically on their mental healthcare during a pandemic situation. Second, this research is one of the pioneer studies that extend social cognitive theory to the context of social media health-misinformation seeking behavior and users' anxiety relationship.

This research aims to establish a comprehensive approach that integrates the aspects to describe how knowledge is focused, developed, reassigned, and implemented to increase project effectiveness. This study examines the interaction of social factors that influences tacit knowledge sharing, absorptive capacity, and project site performance.

The data were collected from Chinese project-based organizations and examined using structural equation modeling (SEM) to test the model and evaluate the hypothesis.

The findings reveal that good knowledge governance and tacit knowledge sharing are essential prerequisites to boost the project’s absorptive capability. Furthermore, social dynamics favorably modify the link between absorptive capacity, tacit knowledge sharing, and project results. The findings are supportive of the proposed model in general.

This research addresses the critical issue of project knowledge management systems and presents a comprehensive framework that broadens the technical and interpretative bounds of current models designed to achieve project success.

This study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.

To achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.

The results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.

This study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.

To effectively implement knowledge management, one prerequisite is to understand and implement the knowledge management enablers in the sense of optimal institutional efficiency. This paper aims to analyze and measure the significant enablers in overseeing knowledge management in the construction sector.

The mixed-method technique was used to achieve the objective of this study and involved the application of detailed questions to project engineers and project managers within leading construction engineering companies, provided by the Institution of Engineering and Technology Ghana. In total, 150 questionnaires were collected and analyzed using the Statistical Package for Social Sciences v. 26.

The study confirms that the knowledge management enablers such as employees knowledge, motivations, effective decisions and strategic planning are some of the important ways in which construction professionals can achieve different strategic goals in many processes and concluded that the progress of the next generation knowledge management strategy will be based on content sharing, decision-making and by promoting the free flow of ideas.

The study offers perspectives into knowledge management enablers and recommends key performance factors, championed by Ghanaian construction contractors for institutional knowledge capture.

Creativity and productivity are important factors for corporate and government institutions in the COVID-19 era. As a result, there is an urgent need to ensure that construction projects can recover adequately to survive potential surges or even potential epidemics. Therefore, this study aims to explore social capital by examining the effect/impact of knowledge creation on construction performance in the COVID-19 era.

A simple random sampling approach focused on Ghanaian construction firms was used. Completed responses were obtained and analyzed from employees who had tasks on sites. SmartPLS 3.3.3 and Statistical Package for Social Sciences v. 26 was used.

One key finding from this research was that construction firms with solid social capital built by their management staff are more connected and have better adaptive systems than firms with low capital. A company’s development programs must concentrate not only on the development of targeted or selective know-how and professional abilities but also on capacity creating, collaboration and knowledge creation and sharing among its employees.

Using this study’s findings, construction professionals can develop successful solutions to the COVID-19 epidemic and future emergencies. Additionally, the comprehensive exposition of the implications, constraints and preventive methods in this study may enable scholars to discover current gaps in the literature and investigate other elements of the pandemic’s influence on the construction industry.

Traditional case-adaptation methods have poor accuracy, low efficiency and limited applicability, which cannot meet the needs of knowledge users. To address the shortcomings of the existing research in the industry, this paper proposes a case-adaptation optimization algorithm to support the effective application of tacit knowledge resources.

The attribute simplification algorithm based on the forward search strategy in the neighborhood decision information system is implemented to realize the vertical dimensionality reduction of the case base, and the fuzzy C-mean (FCM) clustering algorithm based on the simulated annealing genetic algorithm (SAGA) is implemented to compress the case base horizontally with multiple decision classes. Then, the subspace K-nearest neighbors (KNN) algorithm is used to induce the decision rules for the set of adapted cases to complete the optimization of the adaptation model.

The findings suggest the rapid enrichment of data, information and tacit knowledge in the field of practice has led to low efficiency and low utilization of knowledge dissemination, and this algorithm can effectively alleviate the problems of users falling into “knowledge disorientation” in the era of the knowledge economy.

This study provides a model with case knowledge that meets users’ needs, thereby effectively improving the application of the tacit knowledge in the explicit case base and the problem-solving efficiency of knowledge users.

The adaptation model can serve as a stable and efficient prediction model to make predictions for the effects of the many logistics and e-commerce enterprises' plans.

This study designs a multi-decision class case-adaptation optimization study based on forward attribute selection strategy-neighborhood rough sets (FASS-NRS) and simulated annealing genetic algorithm-fuzzy C-means (SAGA-FCM) for tacit knowledgeable exogenous cases. By effectively organizing and adjusting tacit knowledge resources, knowledge service organizations can maintain their competitive advantages. The algorithm models established in this study develop theoretical directions for a multi-decision class case-adaptation optimization study of tacit knowledge.

Continuous knowledge contribution behaviors (CKCB) are critical for the healthy development of online medical communities (OMCs). However, it is unclear that if and how contributors' prior actions and the responses they received from the community influence the nature of their future contributions. Drawing upon the Information Systems Continuance theory and Service Feedback theory, the purpose of the study is to examine the impact of knowledge contribution performance (KCP) on doctors' CKCB. Evaluation of social motivation, financial incentive and the moderating influence of expertise level (EL) provided further insight into the pathways that motivate various forms of CKCB.

In order to better understand the CKCB of physicians in OMCs, the authors divided it into two categories: A_CKCB (active CKCB) and P_CKCB (passive CKCB). Information Systems Continuance theory and Service Feedback theory are adapted and integrated with empirical findings from previous research on OMCs to develop a model of CKCB. This study used ordinary least squares (OLS) regression to test hypotheses in the preexisting research model based on data collected from a Chinese OMC platform.

The results show that KCP helps develop several facets of CKCB. According to the findings, doctors' CKCB improved dramatically after receiving feedback from A_CKCB and P_CKCB, but feedback from peers did not promote CKCB. This study found that financial rewards only have a significant positive effect on P_CKCB, and that the level of expertise has a negative effect on the effect. The findings also demonstrated that doctors' level of expertise moderates the relationship between fA_CKCB (a comprehensive evaluation of doctors' A_CKCB) and A_CKCB.

Future studies should look at the role of self-efficacy as a mediator and attitudes as a moderator in the link between KCP and various forms of CKCB. This will help authors figure out how important KCP is for physicians' CKCB. And future research should use more than one way to gather data to prove the above roles.

This study makes a significant contribution to understanding the association between CKCB and KCP by highlighting the significance of distinguishing between the various forms of CKCB and their underlying causes.

This research has advanced both the theory and practice of OMCs' user management by illuminating the central role of KCP in this context.

This study aims to deal with the case adaptation problem associated with continuous data by providing a non-zero base solution for knowledge users in solving a given situation.

Firstly, the neighbourhood transformation of the initial case base and the view similarity between the problem and the existing cases will be examined. Multiple cases with perspective similarity or above a predefined threshold will be used as the adaption cases. Secondly, on the decision rule set of the decision space, the deterministic decision model of the corresponding distance between the problem and the set of lower approximate objects under each choice class of the adaptation set is applied to extract the decision rule set of the case condition space. Finally, the solution elements of the problem will be reconstructed using the rule set and the values of the problem's conditional elements.

The findings suggest that the classic knowledge matching approach reveals the user with the most similar knowledge/cases but relatively low satisfaction. This also revealed a non-zero adaptation based on human–computer interaction, which has the difficulties of solid subjectivity and low adaptation efficiency.

In this study the multi-case inductive adaptation of the problem to be solved is carried out by analyzing and extracting the law of the effect of the centralized conditions on the decision-making of the adaptation. The adaption process is more rigorous with less subjective influence better reliability and higher application value. The approach described in this research can directly change the original data set which is more beneficial to enhancing problem-solving accuracy while broadening the application area of the adaptation mechanism.

The examination of the calculation cases confirms the innovation of this study in comparison to the traditional method of matching cases with tacit knowledge extrapolation.

The algorithm models established in this study develop theoretical directions for a multi-case induction adaptation study of tacit knowledge.

This study designs a multi-case induction adaptation scheme by combining NRS and CBR for implicitly knowledgeable exogenous cases. A game-theoretic combinatorial assignment method is applied to calculate the case view and the view similarity based on the threshold screening.

The effective and efficient implementation of daily work activities necessitates tacit knowledge sharing, boosting firm productivity. However, the link between tacit knowledge sharing within a company and its effects on organizational performance is unclear, so the purpose of this study is to examine the impact of sharing tacit knowledge on the success of a company.

Construction managers and senior managers were the study’s target participants. The correlation matrix was used to assess the significant correlation between study frameworks and the statistical approach of multiple regression was also used to test the hypotheses using statistical package for social sciences (SPSS) v.26.

The findings suggest that companies will be more willing and capable of making decisions based on experience when knowledge systems are used successfully. Furthermore, new organizational knowledge and particular evaluation procedures, such as anxiety and conflict resolution preparation, personal relationship and training improvement, mediation and task clarity, are explained, which can aid in success.

The study contributes to construction companies’ perception of knowledge sharing and recommends organizations to build capacity to encourage, improve engagement and review to maintain the dissemination of knowledge.

The study aims to explore the impact of tacit knowledge sharing (TKS) factors and its consequences in the form of technological innovation capabilities (TICs) within Pakistani software small–medium enterprises (SSMEs).

Drawing upon the social exchange theory (SET), the study used a quantitative approach and structural equation modeling (SEM) to test hypotheses with 220 valid data collected from 23 Pakistani software SSMEs.

The peer influence (PI) has positive and significant effect on collaborative culture (CC), willingness to share tacit knowledge (WSTK) and TICs. Organizational trust (OT) has a positive and significant impact on CC and TIC. Whereas, CC possessed positive and significant effect on WSTK and insignificant on TIC. Furthermore, WSTK has positive and significant effect on TIC. Finally, WSTK partially mediates the relationship between PI and TIC whereas WSTK fully mediates the relationship between CC and TIC.

The study enriches the research on knowledge sharing and TIC. This research investigates the precursors of tacit knowledge-sharing willingness and their consequences in software SMEs; future studies need to examine tacit knowledge-seeking willingness and its consequences not only in software enterprises but also in other industrial sectors. Besides, it needs to evaluate types of innovative capabilities in software SMEs.

The study suggested that the practitioners need to strengthen TKS in the form employees’ updated skills and expertise which ultimately fosters software enterprise’s innovative capabilities to attain competitive advantages in a specific industry.

This research is one of the few studies to examine the potential antecedents of WSTK and their final effects within software SMEs in the form of TICs. As currently it is observed, an incredible increase of skills oriented innovations in firms particularly in the software domain and IT industry. Therefore, this study emphasizes how PI, OT and WSTK positively affect TIC of Pakistani software SMEs. However, the study could be considered as a guideline for the academia and practitioners who attempt to strengthen the technological innovations capabilities in software SMEs.