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This study embarks on a comprehensive investigation into the intricate relationship between consumer trust in e-commerce platforms and the adoption of Green Supply Chain Management (GSCM). It delves into a multifaceted analysis of how these dynamics influence the landscape of online shopping, with a specific focus on four critical dimensions: the efficiency of online purchasing processes, the fulfillment of product delivery commitments, the convenience associated with e-platform utilization, and the safeguarding of consumers' personal information.

This research employs sophisticated Structural Equation Modeling (SEM) techniques, facilitated by SPSS and SmartPLS software, to meticulously analyze the amassed data and subject the formulated hypotheses to rigorous testing. The empirical foundation of this study draws from a sample of 377 randomly selected online shoppers, providing a robust basis for its insights.

At its core, this research is squarely focused on unraveling the dynamics of consumer trust within e-commerce platforms and highlighting the pivotal role played by GSCM in making online shopping more ecologically responsible and sustainable. Of paramount importance is the novel dimension introduced by this study the integration of trust in e-commerce platforms, GSCM practices, and the multifarious dimensions of online shopping all within a unified conceptual framework. Trust on e-commerce platforms leads to GSCM. GSCM determines online shopping satisfaction, i.e. efficiency, fulfillment, convenience, and privacy. Finally, GSCM mediates between trust on e-commerce platforms and online shopping satisfaction.

This holistic approach represents a ground-breaking contribution to the existing body of literature. It presents a fresh perspective on the intricate interactions that define the contemporary e-commerce landscape.

This initial research integrates trust in e-commerce platforms, GSCM, and online shopping in a single framework through UTAUT2.

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.

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.

Given innovation's significance, this research examines the link between empowered leadership and frugal innovation. The research also explores how collaborative cultures and organizational commitment mediate empowered leadership's effect on frugal innovation.

Quantitative method is used with the approach of hierarchical regression to test the hypotheses with data obtained from Pakistani small- and medium-sized enterprises (SMEs) through the questionnaire from 288 participants.

The results of this study show that empowered leadership has a considerable impact on the firm's capacity for frugal innovation. Additionally, this study shows that organizational commitment and collaborative culture significantly moderate the association between empowering leadership and frugal innovation.

Future studies should examine mediating factors, including employment experience, education and perceived organizational support, and moderating variables like employee psychological empowerment and leadership styles.

This research advises SMEs in developing nations to utilize frugal innovation since they cannot afford to spend extensively on technologies that add creativity and innovation to goods and services.

This study advances how leadership both directly and indirectly helps organizations strengthen their capacity for frugal innovation through the mediating roles of collaborative culture and organizational commitment.

This article aims to explore the connections between tacit knowledge management and the capacity to create new products and services for stimulating organizational performance.

This research utilizes a questionnaire-based study and 378 questionnaires gathered from different provinces of China between August and October 2022. The SmartPLS technique was used to evaluate the regression and mediation analysis on lower-order and higher-order components of the research hypotheses behind the model.

This investigation's results indicate that the tacit knowledge management process (TKMP) significantly drives product and service innovation and impacts organizational performance (ORP). According to the results, TKMP did not directly influence ORP and product innovation to mediate between Tacit knowledge and organizational performance.

Future research should concentrate on different combinations of influences on innovation and other consequences of introducing innovation into businesses. Moreover, researchers may add moderators to innovation and organizational performance.

This study assists managers in how tacit knowledge management affects organisational performance by examining product/service innovation capabilities. Product innovation also mediates between tacit knowledge and organizational performance. Service innovation improves organizational performance, prioritizing knowledge creation, sharing and retention to increase innovation and organizational success.

This study contributes to the literature on tacit knowledge management, innovation capability and organizational performance by concentrating on the tacit knowledge process and using the resource-based view. This study gives a solid theoretical and practical basis for understanding the component interactions.

This paper aims to investigate how perceived working conditions affect employee performance, including safety compliance and task performance, through employee well-being (i.e. job satisfaction) in the context of the coal mining sector in China.

This paper uses the job demands-resources model to test the relationships between working conditions, including job demands (work pressure as a challenge demand and perceived risks and hazards in the workplace and ineffectiveness of the safety system as hindrance demands), job resources (interpersonal harmony), job satisfaction and performance. This study adopts a two-wave design with a three-month lag to reduce possible common method bias.

Employees who experienced high level of challenge demands, e.g. time pressure workload, reported higher levels of task performance, and this positive relationship seemed to be robust. There is a direct effect of perceived ineffectiveness of the safety system on task performance, while the relationship between perceived risks and hazards and task performance was fully mediated by job satisfaction. Challenge demands, i.e. work pressure, did not impact much on employees’ well-being, and thus job satisfaction did not mediate the relationship between work pressure and performance. Perceived ineffectiveness of the safety system was negatively associated with safety compliance. This result is not surprising since a lack of effective safety system reflects management’s ignorance of workplace safety, which demotivates employees to enact safe behaviors. In contrast, the presence and implementation of an effective safety system would be interpreted by employees as management exhibiting a high level of commitment. Work pressure was positively not negatively related to safety compliance. One possible explanation for this finding is that the effects of work pressure on safety compliance behaviors might be dependent on contextual factors such as safety climate. Interpersonal harmony moderated the relationships between work pressure and employee performance (both safety compliance and task performance) and the relationship between perceived risks and hazards and task performance, but the role of interpersonal harmony appeared more complex. There was no significant correlation between challenging job demands and individual employee performance when there were higher levels of interpersonal harmony. The relationship between perceived risks and hazards, a hindrance job demand and task performance became positive as interpersonal harmony increased but negative as interpersonal harmony decreased.

This paper provides a robust integrative theoretical framework that better explains the various types of job demands and job resources in the working environment of coal mining sector in China and their relationships to employee performance. The findings also offer valuable guidance for managers trying to identify effective ways to enhance employee performance and safety in the workplace.

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.

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 current study aims to ascertain how green entrepreneurial orientation (GEO) affects green innovation performance (GIP) through the mediating mechanism of the knowledge creation process (KCP) and whether or not these associations can be strengthened or hampered by the moderating impacts of resources orchestration capabilities (ROC).

The research used data from managers at various levels in 154 manufacturing enterprises in Pakistan to evaluate the relationships among the constructs using hierarchical regression analysis and moderated mediation approach.

The study indicates that GEO substantially impacts firms' GIP. GEO and GIP's relationship is partially mediated by two KCP dimensions: knowledge integration (KI) and knowledge exchange (KE). Furthermore, ROC amplifies not only the effects of GEO on KE but also the effects of KE on GIP. The moderated mediation results demonstrate that KE has a greater mediating influence on GEO and GIP when ROC is higher.

To better understand GEO's advantages and significance, future studies should look into the possible moderating mechanisms of environmental, organizational culture/green capability in the association between GEO, KCP and GIP.

The research helps expand the field of green entrepreneurship and GIP literature by providing a deeper knowledge of GEO and offering insight into how to boost GI in manufacturing firms.

This research helps fill in knowledge gaps in the field by delving further into the mechanisms by which GEO promotes GIP, both directly and indirectly, via the mediating role of KCP and the moderating impacts of ROC.

The current study focuses on the relationship between total quality management (TQM) and sustainable performance (SP) and examines how TQM practices can facilitate firms' achievement of sustainable performance. Knowledge management (KM), with its four dimensions, i.e. knowledge creation (KCR), knowledge acquisition (KAC), knowledge sharing (KSH) and knowledge application (KAP), is also an essential factor for organizations. Therefore, this study also focuses on the mediating role of KM in the relationship between TQM and sustainable performance.

This study used a survey method to collect data from the managers of 485 manufacturing SMEs working in five major industrial cities in Pakistan. Collected data were analyzed through PLS-SEM with the help of smart-PLS.

The study's findings reveal that TQM practices positively influence the environmental and economic sustainability of the firm. At the same time, there is no evidence that TQM practices positively affect the social sustainability of the firm. Results further elaborate that TQM practices significantly affect all four dimensions of KM. Moreover, KM positively affects the two dimensions of SP, i.e. economic and social sustainability, but surprisingly, the impact of KM on environmental sustainability is not found. Finally, results indicate the significant mediating role of KM between TQM and SP.

This study contributes to bridging research gaps in the literature and advances how TQM, directly and indirectly, helps firms improve sustainable performance via the mediating role of KM.