Knowledge Payment Research Articles

Enhancing consumer satisfaction in the online knowledge payment context: the effects of warmth and competence

Enhancing consumer satisfaction in the online knowledge payment context: the effects of warmth and competence

Research on Knowledge Payment Product Supply Chain Governance Based on Blockchain: An Evolutionary Game Model

ABSTRACTBlockchain provides a new opportunity to govern the dilemmas in the knowledge payment product supply chain. This paper introduces blockchain into the evolutionary game to explore the behavioral strategies of knowledge providers, platforms, and consumers and to analyze in depth the influence of initial willingness and blockchain‐related factors by the system dynamics. The analysis shows that (1) improving the tripartite initial willingness is conducive to accelerating the process of supply chain governance and making the system reach an ideal state: knowledge providers choose compliance creation, platforms adopt blockchain, and consumers buy authorized product; (2) there are specific thresholds for the blockchain adoption cost and the premium of product brought by blockchain, only when the cost and premium are lower than the thresholds, the system evolves towards the ideal state; (3) when blockchain is adopted, it can effectively inhibit knowledge providers' illegal creation behavior and consumers' piracy behavior by increasing the punishments of platforms on knowledge providers and consumers. The results provide guidance to implement effective governance and the orderly development of knowledge payment industry.

STUDY ON THE INFLUENCE OF CUSTOMER PERCEIVED VALUE ON REPEATED PURCHASE BEHAVIOR OF KNOWLEDGE PAYMENT IN ONLINE SHOPPING ENVIRONMENT: AN EMPIRICAL ANALYSIS BASED ON ONLINE EDUCATION PLATFORM

Nowadays, with the rapid development of information technology, numerous platforms and groups have entered the field of knowledge payment, thereby initiating a new trend. Despite the recognition of some users, there is still a low purchase or repeat purchase behavior, and many companies face a low fan conversion rate and a scarcity of loyal fans. Therefore, this paper aims to explore the impact of perceived value on consumers' repeated purchase behavior of knowledge so as to propose constructive suggestions for the development of the knowledge payment industry. We introduce customer recognition and brand effect as mediating and moderating variables in this study, and construct an analytical model for knowledge-based repeat purchase behavior on an online education platform. We find that each dimension of perceived value completely mediates the influence on the mediating variable "sense of identity", with the exception of the educational function value, which only partially mediates the influence. Enhancing the brand effect strengthens the relationship between each dimension and consumers' repeated purchase intention, thereby verifying the existence of the moderating effect. However, the social value dimension's influence did not significantly change, making it impossible to verify its moderating effect.

Buyer-initiated knowledge payment facilitates free knowledge contribution in knowledge-sharing platforms: an integration of relational signaling theory and attribution theory

PurposeThe model of pay-for-knowledge incentivizes individuals with financial rewards for sharing their expertise, facilitating a transactional exchange between knowledge providers (sellers) and seekers (buyers). While this model is effective in promoting paid contributions, its influence on free knowledge exchanges remains ambiguous, creating uncertainty about its overall impact on platform knowledge ecosystems. This study aims to explore the mechanim of how knowledge payment influences free knowledge contribution. Based on relational signaling theory, this study posits that a buyer’s payment for knowledge acts as a positive relational signal in the buyer–seller relationship and examines how the signaling effect varies across different social contexts through attribution theory.Design/methodology/approachThis paper empirically tests the hypotheses by analyzing a data set comprising 630 instances from 359 unique knowledge sellers on Zhihu, a prominent knowledge-sharing platform in China. This paper use zero-inflated negative binomial models to conduct this analysis.FindingsThe findings reveal that when buyers pay for knowledge, this action positively influences sellers to contribute knowledge for free. However, the strength of this influence is moderated by the platform’s social functions: appreciation feedback tends to weaken this effect, while social network ties enhance it.Originality/valuePrior research has predominantly focused on the financial incentives of pay-for-knowledge and its spillover effects on unpaid users’ activities. This study shifts the focus to the social dimensions of pay-for-knowledge, arguing that buyer-initiated knowledge payments signal buyers’ commitment to foster reciprocal relationships with sellers. It expands the literature on the relationship between knowledge payment and contribution, moving beyond financial incentives to include social factors, thus enriching our understanding of the interplay between paid and free knowledge activities. Additionally, the empirical evidence supports the efficacy of pay-for-knowledge in promoting both free and paid contributions within knowledge-sharing platforms.

Promoting sales of knowledge products on knowledge payment platforms: A large-scale study with a machine learning approach

With the digital transformation of the global economy, a new mode of knowledge service has emerged on open innovation platforms such as those for the sharing economy. This mode is the paid knowledge-sharing service, where knowledge providers share knowledge with only those who have paid for it. Since an individual customer's purchases are influenced by others around them, we adopted social influence theory to explain sales of such services on paid knowledge-sharing platforms. A machine learning approach was applied to analyze 27,223 text reviews from the Zhihu Live platform (a well-known and large-scale open knowledge community in China). Hierarchical regression models were built to verify twelve proposed hypotheses about the knowledge providers, knowledge quality, interaction quality, and ratings. The results confirm the positive effect on sales of responsiveness (a dimension of interaction quality), and the negative effect on sales of free provider-driven knowledge contributions.In summary, this study provides a comprehensive framework for antecedent factors of sales of knowledge-sharing services. By introducing to knowledge management notions from the field of e-commerce (e.g., price, quality), this study broadens the understanding of the free-to-paid phenomenon on knowledge-sharing platforms.

Understanding Guilin Tourism Major Students Toward Financial Management Knowledge Courses In The Era Of Knowledge Payment

Understanding Guilin Tourism Major Students Toward Financial Management Knowledge Courses In The Era Of Knowledge Payment

Why to purchase health knowledge on online platforms? A two-phased SEM-ANN approach

ABSTRACT Previous research on online health knowledge payment has mainly focused on the health consultation context and knowledge contributors-related characteristics. However, less attention has been given to the roles of health knowledge itself and the underlying platforms. Based on the perceived value theory and S-O-R framework, this study investigated how health knowledge and platform characteristics influence consumers’ purchase intention. Through a survey of 432 Chinese respondents, we employed a multi-analytical approach, combining structural equation modelling (SEM) with artificial neural network (ANN) techniques. SEM results indicate that knowledge personalisation, platform information quality, and platform service quality positively influence both utilitarian and hedonic values, subsequently affecting purchase intention. Furthermore, our findings support the partial mediation role of perceived value. ANN results highlight platform information quality as the most influential stimulus factor. Our study broadens the research scope of online health knowledge payment and offers theoretical and practical insights for its further advancement.

What drives users’ knowledge payment behaviour? The moderating role of knowledge expertise and social identity

ABSTRACT Previous research on user payment behaviour in online community has predominantly focused on the pre-paid mode, with limited understanding of the antecedents influencing user payment behaviour in the post-paid mode. Drawing upon the dual-process theory and social identity theory, this study uses the text mining method based on the attention mechanism and the social network method to explore the influence of the quality of knowledge products and the credibility of contributors, focusing on the role of knowledge expertise and social identity. Using 247,013 replies to 32,373 questions from 3,631 seekers on Xueqiu.com (one of the most popular post-paid online Q&A communities in China), our empirical results found that informativeness, relevance of knowledge products, contributor honour, and experience significantly positively influence user payment behaviour, while timeliness of knowledge products exhibits a significant negative impact on user payment behaviour. Furthermore, contributor social interaction has a significant negative impact on user payment behaviour, contrary to the direction observed in the pre-paid mode. Moreover, the findings show that knowledge expertise and social identity have significant moderating effects in this process. This study provides assistance in developing diverse payment modes for knowledge platforms, and suggests insights for users to contribute knowledge more effectively.

Identification and Evolutionary Analysis of User Collusion Behavior in Blockchain Online Social Media

Blockchain technology has given rise to a series of new blockchain online social medias (BOSMs), of which Steemit is representative. Such communities are based on a token reward system and attempt to engross users in the knowledge activities of the community through knowledge payment. Studies have found that the reward system of such communities has been abused (e.g., collusion for profit), but few studies have performed an in-depth analysis for this phenomenon. Consequently, real data for Steemit are used as a case study herein to examine the collusion of users in BOSMs. Two user collusion behaviors (group-voting and vote-buying) are defined and measured. On this basis, an identification and evolutionary survival analysis of the two collusion behaviors are conducted for colluding users and colluding groups, and the behavior patterns of user collusion under the token system are deconstructed. The results of this study improve stakeholders’ understanding of user participation behavior in new online communities, and serve as a reference for decision-making in community governance and token design.

Research on the Development and Innovative Strategy of Knowledge Payment Platform in the Internet Era

The widespread adoption of knowledge-based payment systems and numerous online knowledge-based paid items is made possible by the quick development of knowledge information and networking technology. Paid columns were quickly introduced by platforms like Himalaya FM, Zhihu, and Qingting FM, while pay-for- knowledge businesses like Fenda, iGet, and Qianliao quickly went live online. Users rapidly increased, and it was assumed that the knowledge payment progressive trend had been met. This paper aims to examine the emergence of edge computing into the mobile information system into the presence and inevitability of the knowledge payment platform, evaluate the advantages, challenges, and pathways for knowledge payment platform optimization, and try to provide a conceptual suggestion for aiding in its advancement. During data analysis, the independence of the polynomial characteristics was evaluated using Pearson's chi- squared tests. A brand-new meta-heuristic optimizer dubbed Harris Hawks optimization is inspired by how Harris hawks seek food in the wild. According to the experimental results, 98 of the survey's respondents—or 19.1% of all respondents—were under the age of 18; 201 were between the ages of 18 and 29; 142 were between the ages of 30 and 39; and 73 were over 40, or 14.2% of all respondents. The findings indicate a younger age distribution for the sample, with the concentration being highest among those between the ages of 18 and 29, then 30 to 39. The mobile information system edge-based knowledge payment platform has successfully undergone continuous use behavior analysis.

Impacts of information asymmetry on users' payment rates: evidence from trading data of Chinese knowledge payment platform

PurposeThis paper aims to clarify the impact of information asymmetry on users' payment rates and examine the role of perceived uncertainty (PU) and acceptable price (AP) in the relationship between information asymmetry and users' payment rates.Design/methodology/approachTo test the influences of information asymmetry on users' payment rates, this paper collects 18,489 transaction data from the Chinese knowledge payment platform Zhihu with a Python crawler. This paper constructs a mediation model to define the relationship between information asymmetry and users' payment rates by introducing PU and AP as the mediators.FindingsInformation asymmetry negatively affects users' payment rates. In addition, PU and AP mediate the information asymmetry in users' payment rates bond.Research limitations/implicationsThis study only explores the mediators of the information asymmetry users’ payment rates bond, ignoring the effect of potential moderators, which would be an important direction for future research.Practical implicationsThe findings of this paper suggest that information communication is essential in knowledge market transactions. Knowledge providers, as well as knowledge platforms, should enhance information exchange with consumers in order to increase product sales.Social implicationsThis paper provides a new perspective for understanding how information asymmetry affects users' payment rates and helps to guide suppliers to improve product quality. The research framework of this paper is universal to a certain extent.Originality/valueThis paper is one of the first to propose using PU and AP to construct a mediation model to study the information asymmetry between users' payment rates relationship. It provides a new perspective for understanding the channel of information asymmetry in customer behavior.

Dynamic pricing strategies for multi‐type knowledge payment products: A system dynamics approach

AbstractWith the emergence of knowledge economy, knowledge payment has become an essential means of knowledge circulation. This study employs a system dynamics approach and integrates signal theory and customer value perception to investigate the dynamic pricing strategies for various knowledge payment products from the perspective of knowledge producers. First, this study analyzes the categories of knowledge payment products and proposes a theoretical research framework for designing dynamic pricing strategies for different products categories. Second, this study identifies the key factors that impact the profitability of knowledge payment platforms and construct a system dynamics model of product pricing strategies for knowledge payment platforms; next, three typical knowledge payment products on Zhihu Live are chosen as research objects, and system dynamics equations are constructed to simulate the profitability changes of different types of products in different periods. Finally, the results of simulation and sensitivity analysis are combined to select dynamic pricing strategies for different products types. This study offers an innovative exploration of multi‐stage pricing strategies for different types of knowledge payment products, which fills the gap in existing research and provides more scientific suggestions for knowledge producers and consumers in terms of knowledge transactions.

Pricing strategy of knowledge payment products considering copyright supervision in the blockchain technology era

PurposeThe purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.Design/methodology/approachThis study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.FindingsDeploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.Originality/valueThis study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.

An interval-valued intuitionistic fuzzy group decision-making method for evaluating online knowledge payment products

Increased demand for knowledge, evolving consumer attitudes, and the convenient online transaction opportunities provided by Internet technology have led to the rapid rise and growth of online knowledge payment. At present, studies on the online knowledge payment industry mainly focus on exploring the influencing factors of users' willingness to pay for online knowledge payment products (OKPPs), and there are fewer studies on the evaluation and rating methods of OKPPs. To address this problem, this paper proposes an improved group decision-making method based on consensus adjustment and prospect theory to realize the evaluation of OKPPs from the perspective of consumer experience value. The method uses interval-valued intuitionistic fuzzy numbers to process evaluation information, selects leading users (LUs) as decision makers, and identifies four evaluation criteria based on consumer experience value, which are functional value, self-fulfillment value, hedonic value, and emotional value. The proposed group decision-making method in this paper takes into account the consensus problem of LUs’ opinions, proposes a consensus adjustment method, and uses prospect theory to incorporate the psychological factors of LUs into the group decision-making process. Finally, the effectiveness and advantages of the method proposed in this paper are verified using an example and a comparison with existing methods. This research will provide methodological reference for knowledge payment platforms (KPPs) to select high quality OKPPs, and will also urge knowledge producers (KPs) to create OKPPs that can bring higher experience value to knowledge consumers (KCs). At the same time, this research makes possible the co-creation of knowledge between KPs and KCs, and enriches and develops the relevant research on the online knowledge payment industry.

Research on the Existing Problems and Future Outlook of Knowledge Payment

With the development of science and technology, network information technology has influenced and gradually realized economic sharing. To some extent, it promotes the arrival of knowledge payment, making payment platforms such as Himalaya App and Zhihu occur in the public view. The occurrence of knowledge payment improves the utilization rate of knowledge and reduces the problems of improper use and waste of knowledge. However, with the rapid development of knowledge payment, it also faces many problems, such as the imperfect legal system, imperfect technical means, and people's weak consciousness of knowledge payment. Based on this, this paper summarizes the existing problems of knowledge payment. In addition, we put forward real-time strategies, including perfecting the laws and regulations, improving scientific and technological means, and strengthening the publicity of knowledge payment.

A Study on the Business Model Optimization Strategy of Knowledge Payment Platform: The Example of Zhihu

The rapid development of the Internet has contributed to the continued advancement of the knowledge payment industry. Currently, knowledge payment platforms, as the core force of the knowledge payment market, guide the continuous changes in the direction of content production, enterprise operation and consumer demand in the knowledge payment industry. However, research on knowledge payment platforms in academia is still in its infancy, and in particular, there is a paucity of research that systematically examines the characteristics of successful knowledge payment platforms and strategies to address the problems of business models from the perspective of business models as a whole. Therefore, a systematic and thorough understanding of the essence and richness of the business models of knowledge payment platforms is crucial to an in-depth understanding and grasp of the development rules of the knowledge payment industry.This article focuses on the business models of Internet knowledge payment platforms and their optimisation strategies. Take Zhihu as an example using a case study approach and the perspective of value networks, this paper constructs a business model based on value networks and conducts specific research and analysis on the eight elements of the business model to explore the essence of the business model of knowledge payment platforms and its optimisation strategies under the collaborative competition model, which is equally important in the Internet era. Evidence from this case study finds that value network is the main form of operation of the business model of platform-based enterprises, and the platform achieves the business closure of value acquisition and value maintenance through the engine driven by value proposition and value co-creation.The study reveals that competition and cooperation are equally important business concepts and the whole process of cross-enterprise value co-creation in the Internet era, which complements the research perspective of business model optimization strategy research focusing on competition and provides certain reference significance for the business model optimization of platform-based enterprises.The contribution of this paper is to provide a new perspective for the study of business model optimization strategies. This article is sorting out business model optimization strategies. On the basis of relevant literature, the original theoretical research perspective of enterprise management focusing on competition rather than cooperation is supplemented，From the perspective of “value network”, combined with the theoretical basis of Yuanlei’s business model, a business model based on value network is proposed Model. On this basis, take the knowledge payment industry as the exploration field, and take the typical knowledge payment platform Zhihu platform. In order to study the case, by revealing the key factors for the success of the business model of Zhihu platform, verify the new business model theory Explanations of enterprise practice. Through research, it is found that the theoretical model of the new business model better explains the Internet knowledge. The essence of the business model of the payment platform is a complete value co-creation closed-loop structure, which also reveals the Internet knowledge.

Study of Online Continuous Learning Behavior of College Students in the Context of Knowledge Payment

With the rapid development of information technology in the education industry, the number of users of online learning platforms is showing an in the current era of the Internet, online learning platforms have become the preferred learning tools for many college students. Compared with traditional learning modes, online learning has advantages such as abundant learning resources, random learning locations, flexible learning times, and personalized learning. Compared with traditional learning modes, online learning has advantages such as abundant learning resources, random learning locations, flexible learning times, and personalized learning content. However, at the same time, the online learning of college students also exhibits negative learning behaviors and habits such as high dropout rates, low participation, and difficulty in deep learning. Based on the theory of planned behavior, this paper expands, introduces expectation, and provides an overview of online learning. This paper expands, introduces expectation confirmation factors and economic factors, and obtains a survey report through the analysis of second-hand Based on the theory of planned behavior, this paper expands, introduces expectation confirmation factors and economic factors, and obtains a survey report through the analysis of second-hand data research, face-to-face interviews, and telephone interviews. It also summarizes the continuous influencing factors that affect college' online paid knowledge learning from the aspects of information quality, perceived usefulness, social factors, and expectation perception. The research results are helpful for improving the quality of online courses, Enhancing the value of online learning, enhancing the satisfaction of The research results are helpful for improving the quality of online courses, Enhancing the value of online learning, enhancing the satisfaction of college students with online learning, and promoting the healthy development of knowledge payment platforms have important reference significance.

Decisions of Knowledge Payment Product Supply Chain Considering Government Subsidies and Anti-Piracy Efforts: Based on China’s Knowledge Payment Market

Knowledge payment is an emerging business mode that has developed in the era of social media. With the impact of Internet technology, the knowledge payment market is rapidly expanding, especially in China. However, piracy leads to more intense competition and affects the profits of knowledge providers and knowledge payment platforms. Government policies combined with the anti-piracy measures of these platforms have become effective methods to combat piracy. This paper investigates the impact of government subsidies and anti-piracy efforts on a knowledge provider’s and platform’s optimal decisions. We develop a two-stage knowledge payment product supply chain with a knowledge provider and a knowledge payment platform. The platform in the leader position of the supply chain has anti-piracy efforts and the government subsidizes the platform. Stackelberg game models are constructed and compared to examine the equilibrium solution in relation to three modes (no government subsidies and no anti-piracy efforts; only anti-piracy efforts; and both government subsidies and anti-piracy efforts). Our analysis shows that (1) both government subsidies and anti-piracy efforts increase the quality level and unit quality signing bonus of the knowledge payment product. Meanwhile, the product’s retail price increases with anti-piracy efforts but decreases within a certain subsidy range. (2) The knowledge provider’s profit always increases with the anti-piracy effort level, while the platform’s profit is an inverted U-shaped relationship with the anti-piracy effort level. (3) Government subsidy behavior can always increase a knowledge provider’s profit but may not necessarily increase the platform’s profit. Moreover, there exists a certain threshold: when subsidies are lower (higher) than this threshold, it is more beneficial to the knowledge provider (platform). In addition, we also find that the method of high subsidies combined with a low anti-piracy effort level benefits both parties and that the subsidized party will be more sensitive. The results will provide knowledge providers and platforms with new market management insights from the perspective of government subsidies and anti-piracy efforts and guide them to make optimal decisions.

What factors determine users' knowledge payment decisions? A mixed-method study.

Methods for obtaining valuable knowledge from the vast amount of mixed-quality information have become a top priority for knowledge demanders. As an online knowledge-sharing channel, the socialized question and answer (Q&A) platform provides important support services for knowledge payment. Based on the personal psychological dimensions of users and social capital theory, this paper aims to study the behavior mechanisms of knowledge payment users and examine the significant factors affecting user payment. Our research was conducted in two steps: a qualitative study to find these factors and a research model based on a quantitative study for testing the hypothesis. The results show that the three dimensions of individual psychology are not all positively correlated with cognitive and structural capital. Our results fill a gap in the literature on the formation of social capital in the knowledge payment environment by showing how individual psychological dimensions affect cognitive and structural capital differently. Thus, this study offers effective countermeasures for knowledge producers on social Q&A platforms to better amass their social capital. This research also makes practical recommendations for social Q&A platforms to strengthen the knowledge payment model.

Research on the Operation Strategy of Xinpai College in the Era of Knowledge Payment

Research on the Operation Strategy of Xinpai College in the Era of Knowledge Payment