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Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

In the extant research on online knowledge communities (OKCs), little attention has been paid to the influence of membership fluidity on the coevolution of the social and knowledge systems. This article aims to fill this gap.

Based on the attraction-selection-attrition (ASA) framework, this paper constructs a simulation model to study the coevolution of these two systems under different levels of membership fluidity.

By analyzing the evolution of these systems with the vector autoregression (VAR) method, we find that social and knowledge systems become more orderly as the coevolution progresses. Furthermore, in communities with low membership fluidity, the microlevel of the social system (i.e. users) drives the coevolution, whereas in communities with high membership fluidity, the microlevel of the knowledge system (i.e. users' views) drives the coevolution.

This paper extends the application of the ASA framework and enriches the literature on membership fluidity of online communities and the literature on driving factors for coevolution of the social and knowledge systems in OKCs. On a practical level, our work suggests that community administrators should adopt different strategies for different membership fluidity to efficiently promote the coevolution of the social and knowledge systems in OKCs.

This study used an integrated model that incorporates the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB) to empirically investigate how eco-gamification stimulates users' sustainability knowledge and, consequently, their pro-sustainable intentions through the mediating roles of sustainable knowledge and psychological and social norms. Thus, the study aims to examine users'’ experiences with the JouleBug app, which is designed to encourage users to complete at least one daily green task.

After a trial period of two weeks, a total of 360 participants completed the post-game survey during the research process.

The findings from the structural equation modeling and data analysis indicated a good fit for the model. The findings demonstrate that usefulness, ease of use and enjoyment of eco-gamification enrich users' sustainability knowledge, which, in turn, strongly influences their pro-sustainable intentions. According to the findings, the three factors of TPB have a significant impact on users' pro-sustainability intentions. Both sustainable knowledge and social cues play mediating roles in such relationships.

This study advocates that eco-gamification can be used as a platform to modify tourists’ pro-sustainability intentions in emerging tourism and technology destinations such as Egypt. Hence, this study offers significant information to tourism planners and other stakeholders on tourists’ behavioural intentions.

This study examined the effectiveness of an integrated model of TAM and TBP in predicting tourists’ intentions to use eco-gamification to improve the sustainability of tourist destinations.

本研究采用结合技术接受模型（TAM）和计划行为理论（TPB）的综合模型, 旨在探究生态游戏化如何提升用户对可持续性的认知, 从而影响他们支持环保行为的意愿。通过研究可持续性知识以及心理和社会规范在其中的中介作用来实现这一目标。因此, 本研究调查了用户使用JouleBug应用程序的体验, 该应用程序旨在鼓励用户每天完成至少一个环保任务。

在为期两周的试验期后, 共有360名参与者在研究过程中完成了后测问卷调查。

通过结构方程模型和数据分析, 研究结果表明模型拟合良好。研究发现, 生态游戏化的实用性、易用性和乐趣能够丰富用户的可持续性知识, 从而强烈影响他们支持可持续性的意愿。研究结果还显示, 计划行为理论（TPB）的三个因素对用户的支持可持续性意愿有显著影响。可持续性知识和社会提示在这些关系中发挥着中介作用。

本研究主张, 生态游戏化可以作为一个平台, 用于引导游客在埃及等新兴旅游和科技目的地中支持可持续性的意愿。因此, 该研究为旅游规划者和其他利益相关者提供了有关游客行为意向的重要信息。

本研究考察了TAM和TPB综合模型在预测游客使用生态游戏化改善旅游目的地可持续性意愿方面的有效性。

Este estudio utilizó un modelo integrado que combina el Modelo de Aceptación Tecnológica (TAM) y la Teoría del Comportamiento Planificado (TPB) para investigar cómo la eco-gamificación aumenta el conocimiento de los usuarios sobre la sostenibilidad y, en consecuencia, sus intenciones para actuar favorablemente en el medio ambiente. Esto se logró analizando cómo el conocimiento sostenible y las normas psicológicas y sociales actuaban como mediadores. Para ello, la investigación examina las experiencias de los usuarios con la aplicación JouleBug, diseñada para fomentar que los usuarios realicen al menos una tarea verde diaria.

Tras un período de prueba de dos semanas, un total de 360 participantes completaron la encuesta posterior al juego durante el proceso de investigación.

Los resultados del modelo de ecuaciones estructurales y análisis de datos indicaron un buen ajuste del modelo. Los resultaros evidencian que la utilidad, facilidad de uso y disfrute de la eco-gamificación enriquecen el conocimiento de sostenibilidad de los usuarios y, a su vez, influye significativamente en sus intenciones pro-sostenibilidad. Conforme a los resultados, los tres factores de la TPB tienen un impacto significativo en las intenciones pro-sostenibilidad de los usuarios. Tanto el conocimiento sostenible como las señales sociales desempeñan roles mediadores en estas relaciones.

Este estudio aboga por el uso de la eco-gamificación como una plataforma para modificar las intenciones pro-sostenibilidad de los turistas en destinos emergentes de turismo y tecnología, como Egipto. Por tanto, esta investigación proporciona información significativa para los planificadores de turismo y otros interesados en las intenciones conductuales de los turistas.

Este estudio examinó la eficacia de un modelo integrado de TAM y TPB para predecir las intenciones de los turistas de utilizar la eco-gamificación para mejorar la sostenibilidad de los destinos turísticos.

Recent studies on search-as-learning (SAL) have recognized the significance of identifying users' learning needs as they evolve for acquiring knowledge during the search process. In this study, the authors clarify the extent to which search behaviors reflect the learning outcome and foster the users' knowledge of Chinese art.

The authors conducted an exploratory-sequential mixed-methods approach using simulated work task situations to collect empirical data. The authors used two types of simulated learning tasks for topics related to painting and antique knowledge. A lot of 25 users participated in this evaluation of digital archives (DAs) at the National Palace Museum (NPM) in Taiwan. For each set of topics, a close-ended task related to lower-level learning goals and an open-ended task related to higher-level learning goals.

The learning criteria reflect changes in the users' knowledge structure, revealing the SAL process. Furthermore, users achieved better task performance on the higher-level creative-learning task, which suggests that they met more learning criteria, exhibited a greater variety of search patterns when exploring the topics via interaction with various sources. Finally, there is a close relationship between creative-learning tasks, prior knowledge, keyword search actions and learning outcomes.

The authors discuss implications with respect to the design of DAs in practice and contributions to the body of SAL knowledge in DAs of online museums. For future reference, the authors provide implications for the development of learning measures from the perspective of user search behavior with associated learning outcomes in the context of DAs.

This study employed self-determination theory (SDT) and the “Motivational affordance–Psychological outcomes–Behavioral outcomes” framework to investigate the relationship between gamification features and knowledge-sharing behavior in online communities.

A theoretical model was tested with 281 Chinese users from an online social question and answer (Q&A) community. Partial least square structural equation modeling was applied to analyze the data.

The empirical results revealed that competence mediated the effects of immersion and achievement-related gamification features on knowledge sharing. Moreover, relatedness mediated the effects of immersion, achievement and social-related gamification features on knowledge sharing.

This study was conducted on a Chinese Q&A platform, and the results may not be generalizable to other cultures or service providers with different goals.

The study's findings indicate that gamification could serve as an effective toolkit for incentivizing and promoting knowledge sharing in online communities. The findings thus provide strategic insights for administrators of online communities seeking to leverage gamification designs to encourage user participation in knowledge-sharing activities.

Research on the role of gamification in promoting knowledge sharing has been limited in scope and has focused on tourism comment communities. Little evidence exists on the effect of gamification within social Q&A communities. Further, the finding of gamification's positive role in motivating knowledge sharing indicates the need for the knowledge-sharing field to focus on contextual factors.

The current study aims to investigate the factors that impact the feedback received on answers to questions in social Q&A communities and whether the expertise-required question influences the role of these factors on the feedback.

To understand the antecedents and consequences that influence the feedback received on answers to online community questions, the elaboration likelihood model (ELM) is applied in this study. The authors use web data crawling methods and a combination of quantitative analyses. The data for this study came from Zhihu; in total, 353,775 responses were obtained to 1,531 questions, ranging from 49 to 23,681 responses per question. Each answer received 0 to 113,892 likes and 0 to 6,250 comments.

The answers' cognitive and emotional components and the answerer's influence positively affect user feedback behavior. In addition, the expertise-required question moderates the effects of the answer's cognitive component and emotional component on the user feedback, moderating the effects of the answerer's influence on the user approval feedback.

This study builds upon a limited yet growing body of literature on a theme of great relevance to scholars, practitioners and social media users concerning the effects of the connotation of answers (i.e. their cognitive and emotional components) and the answerer's influence on user feedback (i.e. approval and collaborative feedback) in social Q&A communities. The authors further consider the moderating role of the domain expertise required by the question (expertise-required question). The ELM model is applied to explore the relationships between questions, answers and feedback. The findings of this study add a new perspective to the research on user feedback and have implications for the management of social Q&A communities.

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.

In the hybrid knowledge-sharing platform where paid and nonpaid (“free”) knowledge activities coexist, users’ free knowledge contribution may be influenced by financial factors. From the perspective of opportunity cost, this study investigates the direct effect of how the amount of monetary income from users’ contribution to paid knowledge activities influences their free knowledge contribution behavior in the future. Further, this study aims to verify the interaction effect of financial and nonfinancial factors (i.e. the experience of free knowledge contribution and social recognition) on free knowledge contribution.

Objective data was collected from a hybrid knowledge-sharing platform in China and then analyzed by using zero-inflated negative binomial regression model.

Results show that the amount of monetary income that knowledge suppliers gain from paid knowledge contribution negatively influences their free knowledge contribution. Experience of free knowledge contribution strengthens the negatively main effect, while social recognition has the weakening moderating role.

Although some studies have explored and verified the positive spillover effect of financial incentives on free knowledge contribution, the quantity dimension is ignored. This study examines the hindering influence of the quantity of monetary income from the perspective of opportunity cost. By taking the characteristic of knowledge suppliers and platforms as moderators, this study deepens the understanding of the influence of monetary income on free knowledge contribution in the hybrid knowledge-sharing platform.