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The uncertainty of consumers' perceived value makes online education enterprises face great challenge in developing the pricing strategy. So the purpose of this paper is to research the pricing strategies of online education products by considering knowledge consumers' characteristics.

Considering consumer matching degree and price comparison, this study establishes the utility functions of consumers in normal sales period and discount selling period. On this basis, the research builds pricing models of the online education enterprise under the strategy of price undertaking and intertemporal pricing strategy. It further discusses the impact of consumer matching degree, consumer price sensitivity and different types of consumers on the product price and profit of online education enterprises, and reveals the optimal pricing strategy of the enterprise.

Consumer matching degree and price sensitivity coefficient have positive effects on product price and enterprise profit, but they have different effects on product demand; there are differences in the perceived value of the three types of consumers, and matching consumers are the optimal consumer group; the intertemporal pricing strategy is better than the strategy of price undertaking only when the price sensitivity coefficient is greater than a critical value.

This study enriches the literature on the pricing model of online education products and owns a practical significance to guide the online enterprise to make marketing strategies to increase profit.

Although researchers have demonstrated a keen interest in knowledge collaboration in online encyclopedias, previous studies have seldom explored the dynamic interrelations in online encyclopedias over time that involve the iteratively melding of individual cognitive system and knowledge collaboration system. Therefore, this paper aims to reveal the structure and dynamics of knowledge collaboration in online encyclopedias from a perspective of system dynamics (SD).

This paper proposes a general activity system of knowledge collaboration in online encyclopedias based on Engeström’s activity theory. According to the SD methodology proposed by Forrester, this study develops a holistic SD model by identifying interactions of knowledge collaboration factors based on behavioral theories; validating the SD model by structural tests and behavior tests involving historical data of English Wikipedia; and conducting simulation to capture the interactive dynamics of the salient factors of knowledge collaboration.

According to the SD methodology, this study develops and validates an SD model to explore interesting dynamic interrelations among core factors (contributors, conflicts, discussions, entries quantity and entries quality) that are neglected by previous research. The results show that there is a significant negative feedback relationship between inactive contributors and entries quality, between contributors and conflicts and between edit conflicts and entries quality. There is a complicated nonlinear feedback relationship between active contributors and entries quality, and between edit conflicts and discussions.

Different from prior empirical studies that normally investigate the unidirectional linear relationships among prominent factors of knowledge collaboration in online encyclopedias from a static perspective, this study captures a dynamic picture of their interrelations by unfolding their behavior patterns over time. The main contribution of this study is to develop a holistic SD model and to reveal and elaborate on the complex dynamics involved online encyclopedias based on activity theory.

The purpose of this paper is to research the price strategies of online knowledge payment product by considering network externality in the C2C sharing economy.

Considering the characteristics of online knowledge goods and the social network externality of consumers, this study establishes a consumer utility function. On this basis, a multistage game pricing model of online knowledge products is established based on three kinds of network price strategies under a completely competitive market structure. It also analyzes the influence of consumer social network structure and consumer utility on online knowledge product pricing and producer profit, as well as the influence of consumer quantity and discount rate on pricing strategy.

The consumer social network and consumer utility affect the pricing of online knowledge product under different price strategies. In the growth period of the platform, adopting the price discrimination strategy, the profit of producers is significantly higher than that of other price strategies, and producers should choose effective price strategies for reasonable pricing in combination with their own sales objectives.

This study enriches the literature on the pricing model of online knowledge payment product and owns a practical significance to guide the knowledge producers’ marketing strategies to increase profit.

The 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.

This 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.

Deploying 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.

This 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.

This paper aims to establish an organizational learning system model based on both western and Chinese management thoughts.

The approach is a conceptual model which is based on research within the field.

The model consists of nine interrelated organizational learning sub‐systems including “discovering”, “innovating”, “selecting”, “executing”, “transferring”, “reflecting”, “acquiring knowledge from environment”, “contributing knowledge to environment”, and “building organizational memory” ones. The evidences in some famous Chinese traditional cultural classics (including Great Learning, Doctrine of the Mean, The Analects of Confucius, Book of Change, Tao‐Te‐Ching, The Art of War and Chuan‐Xi‐Lu) that support the rationale of the model are described and analyzed.

Several propositions are developed and it is hoped that the model is applicable in both eastern and western business environments.

reverser considered in this paper uses the natural blockage concept, with only the fan duct flow being reversed. This paper focuses on the study of the aerodynamic performance of the cascade within a cold stream thrust reverser. Aerodynamic simulations are carried out using realistic operating conditions, for idealized cascade models representing three design options. The aim of this work is to investigate whether the aerodynamic performance of the thrust reverser cascade has been improved while minimizing weight of the cascade. In addition, t1his is the first attempt of us to considering noise reduction during design of the thrust reverse. The numerical simulations show that despite a reduction in total reverse thrust for the weight reduced designs, the supersonic flow regime, which existed in the original design, was eliminated after changing vane configurations made with the 5% and 10% weight reductions. The aerodynamic performance around the cascade and in the fan duct within the thrust reverser has been improved. Moreover, the acoustic characteristics of the thrust reverser are improved too. The total reverse thrust is not significantly affected with the modified cascade.

The purpose of this paper is to determine a set of routes for multiple salesmen starting at and turning back to the home depots. The objective of the algorithm is to be efficient and to minimize the total cost of all salesmen.

The new method first generates a SModel, then deletes all redundant edges in the model and reorganizes isolated paths. According to the given statistics, about 16.5 percent of the nodes have a degree greater than 2 in the SModel, which means that there must be redundant edges in the model. The authors refer to those edges connected to nodes with a degree greater than 2 as redundant candidate edges. By deleting redundant edges, the original graph is simplified to a great extent, then related operation is adopted to generate expected result.

A simple model is used to simplify the original graphs by deleting redundant edges. Based on the simplified results, two strategies are proposed to determine primal edges linking with home depot. Simulations are carried out to illustrate the performance of the proposed method.

Although new method can efficiently solve the variance of multiple traveling salesmen problem (MTSP) with multiple salesmen open path, it does not consider the workload balance. To a great extent, the total course time of this variance of MTSP is decided by the last achieved salesman's time cost.

This method can be used to simulate many everyday applications such as transportation logistics, job planning, vehicle scheduling, and so on. The main applications include print press scheduling, crew scheduling, school bus routing, mission planning, and the design of global navigation satellite surveying system networks. Moreover, it can be used to solve the problem of multiple traveling robots, and can be considered as a relaxation of the vehicle routing problem (VRP) with the capacity restrictions removed.

This paper proposes a new method to solve a heterogeneous MTSP with multiple depots and open paths. A simple model (SModel) is introduced to implement it. The model can transform a complicated graph into a simplified one. Based on the model, the subsequent workings of the new method involve merely linking paths together. Based on SModel, the greatest advantage of the new method is that it can find a global solution efficiently.

A total of 478 Americans participated in an online survey. Each participant was asked to answer questions about a company randomly assigned from one of 36 companies representing six industries.

This study aims to explain how corporate social responsibility (CSR) and negative corporate ability (CA) associations lead to negative word-of-mouth (WOM) intentions in non-crisis situations. Specifically, this study investigates the mediating roles of revenge and avoidance motives in the relationship between negative CSR and CA associations and the intention to generate negative WOM.

The findings indicate that negative CSR associations have a greater effect on WOM than negative CA associations. Moreover, negative CSR associations stimulate the revenge motive, resulting in stronger intentions to spread negative information, while negative CA associations lead to the avoidance motive, resulting in weaker intentions to spread negative information.

Unlike most previous studies that focused on crises, this study examines how negative CA and CSR associations influence negative WOM in non-crisis situations, shedding light on the roles of motives including the revenge and avoidance. The research fills a gap in the existing literature by demonstrating that negative CSR associations have a greater impact on negative WOM intentions than negative CA associations in non-crisis situations.

In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.