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The purpose of this paper is to describe the policy and trends in rural education in China over the past 40 years; and also discuss a number of challenges that are faced by China’s rural school system.

The authors use secondary data on policies and trends over the past 40 years for preschool, primary/junior high school, and high school.

The trends over the past 40 years in all areas of rural schooling have been continually upward and strong. While only a low share of rural children attended preschool in the 1980s, by 2014 more than 90 percent of rural children were attending. The biggest achievement in compulsory education is that the rise in the number of primary students that finish grade 6 and matriculate to junior high school. There also was a steep rise of those going to and completing high school. While the successes in upscaling rural education are absolutely unprecedented, there are still challenges.

This is descriptive analysis and there is not causal link established between policies and rural schooling outcomes.

The authors illustrate one of the most rapid rises of rural education in history and match the achievements up with the policy efforts of the government. The authors also explore policy priorities that will be needed in the coming years to raise the quality of schooling.

This is the first paper that documents both the policies and the empirical trends of the success that China has created in building rural education from preschool to high school during the first 40 years of reform (1978-2018). The paper also documents – drawing on the literature and the own research – the achievements and challenges that China still face in the coming years, including issues of gender, urbanization, early childhood education and health and nutrition of students.

This paper provides a thorough examination of Socios.com, a blockchain platform that integrates token sales with the fan experience in the sports industry. The study focuses on three key aspects: the performance, bubble phenomenon and dynamics of fan tokens. The author aims to address important questions that may concern potential supporters and investors. Might sports fans incur financial losses due to their team loyalty? Is the fan token market just a passing trend? Are fan tokens driven by the behaviour of the cryptocurrency market?

This analysis aims to involve several methodologies. The author evaluates the short- and long-term performance of fan tokens by computing first-day and buy-and-hold (abnormal) returns. The author also employs the Phillips, Shi, and Yu's (PSY) real-time bubble detection method to investigate the presence of bubble phenomenon in the fan token market segment. Finally, the author examines the potential dependences between fan tokens, Chiliz and the cryptocurrency market (represented by the CCi30 index) using both Pearson/Kendall correlations and the wavelet coherence approach.

The study presents three notable contributions to the existing literature. First, the author demonstrates that investing in fan tokens to support one's favourite sports teams can lead to financial losses, whereas traders can potentially outperform the market by investing in Chiliz. Second, the author states that fan tokens were a short-lived trend, as evidenced by their decline in value after the bubble burst in 2021. Third, the findings indicate that the fan token market was influenced by the cryptocurrency market and Chiliz during periods of market downturns.

To the best of author’s knowledge, this is the first paper to conduct a comprehensive analysis of the performance, bubble phenomenon and dynamics of the token market fan segment, along with the exclusive on-platform currency, Chiliz.

This paper aims to consider each strategy of the particle swarm optimization (PSO) as a unit in data envelopment analysis (DEA) and uses the minimax mixed-integer linear programming DEA approach to find the most suitable inertia weight strategy. A total of 15 inertia weight strategies were empirically examined in a suite of 42 benchmark problems in the view of DEA.

PSO is very sensitive to inertia weight strategies, and therefore, an important amount of research attempts has been concentrated on these strategies. There is no research into the determination of the most suitable inertia weight strategy; however, there are a large number of comparisons related to the inertia weight strategies. DEA is one of the performance evaluation methods, and its models classify the set of strategies into two distinct sets as efficient and inefficient. However, only one of the strategies should be used in the PSO algorithm. Some effective models were proposed to find the most efficient strategy.

The experimental studies demonstrate that an approach is a useful tool in the determination of the most suitable strategy. Besides, if the author encounters a new complex problem whose properties are known, it will help the author to choose the best strategy.

A heavy oil thermal cracking three lumps model for the simplification of the reaction system was used because it is an important complicated chemical process. In addition, the soil water retention curve (SWRC) plays an important role in diverse facets of agricultural engineering. As the SWRC can be regarded as a nonlinear function between the water content and the soil water potential, Van Genuchten model is proposed to describe this function. To determinate these model parameters, an optimization problem is formulated, which minimizes the difference between the measured and modeled data.

In this paper, the PSO algorithm is integrated with minimax mixed-integer linear programming to find the most suitable inertia weight strategy. In this way, the best strategy could be chosen for a new more complex problem.

The purpose of this paper is to rigorously determine the tensile properties of a selective laser sintering (SLS) material. Emphasis was placed on the anisotropy and inhomogeneity of the material, the repeatability of the SLS process, and the effect of age (actually moisture absorption) on the material properties.

Two builds of 144 dogbone tensile specimens each were tested, with 18 specimens stored for 43 days in a non‐desiccated environment before testing. Specimens were distributed throughout the build volume and aligned with the apparatus' principal axes. Tensile properties were treated statistically, using the t‐test to determine the differences between various samples.

The material was transversely isotropic in Young's modulus and strain to failure, and generally orthotropic in ultimate tensile strength. The material was inhomogeneous throughout the build volume and affected by age, with a 57 per cent reduction in University of Technology after 43 days (the changes in properties were suggested to be due to moisture absorption). Properties varied by up to 25 per cent from build‐to‐build with no change in nominal process parameters.

It was not possible to confirm the “ageing” effect was caused by moisture absorption, and further work is suggested in this area. The causes of inhomogeneity and the effect of re‐coater action should also be studied further.

This is the most complete study of an SLS material's mechanical properties to date. The statistical analyses used further allow increased confidence in the conclusions drawn. This is also the only study to use cross‐fill scanning to produce specimens, and, therefore, isolate the effect of the re‐coater action.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

In today's world, retailers must embrace technological devices to provide fluid, convenient and complete customer experiences. Therefore, combining the offline and online spaces into a single strategy becomes essential, representing a significant opportunity for retailers to improve customer experience. Therefore, this study aims to explore and compare the importance of digital elements in an omnichannel experience by companies in the luxury and non-luxury segments.

The research offers a model to explore and compare the omnichannel strategies that brands use, considering six dimensions that cover recent technological advances, thus offering a complete experience to their customers. A multiple case study was selected based on a sample of six international companies from two different price segments (luxury and non-luxury).

The data collected allowed the authors to verify the presence of some dimensions, even though some had little evidence. Nevertheless, the dimensions connectivity, innovativeness and flexibility (only in luxury segment companies) were not present. Overall, and even though they present just little evidence, the results showed that retailers for the luxury segment invest more in delivering digital experiences within omnichannel strategies than the non-luxury ones.

This study improves the existing knowledge of omnichannel retailing. By analysing and comparing the omnichannel experiences, companies can identify areas for improvement and enhance the overall customer journey. Additionally, the model allows managers to compare and re-evaluate their omnichannel strategies with other competitors to gain competitiveness in an ever-evolving market.

The purpose of this paper is to understand the effect of two types of reciprocity (restricted reciprocity and generalized reciprocity) on customers’ trust in social commerce (s-commerce) and trust performance (purchase intention and word-of-mouth intention). Furthermore, this study examines how individual and contextual moderators (personal shopping experience and community shared language) could impact the trust development process.

This study adopted a survey method and obtained data from 287 users in a customer-to-customer (C2C) s-commerce platform. Structural equation modeling was used to examine the research hypotheses.

The results demonstrate that two types of reciprocity positively affect trust in s-commerce. Customers’ trust performance is significantly affected by trust in s-commerce. Additionally, shopping experience in s-commerce is found to positively moderate the relationship between restricted reciprocity and trust in s-commerce.

The findings help to understand the nature and role of reciprocity in influencing trust and trust-related behaviors in the context of C2C s-commerce. The research also helps to explore the individual and contextual moderators that impact the effect of reciprocity on trust development.

The results offer a comprehensive view of trust building strategies for s-commerce practitioners, including shoppers, vendors and managers of s-commerce platforms.

This study is among the first few research studies that offers a theory-based conceptualization of reciprocity in C2C s-commerce and provides empirical support for the impact of reciprocity on customers’ trust in C2C s-commerce. In addition, this study devises a broader view of reciprocity based on restricted and generalized exchange principle to represent the interaction of vendor–shopper and shopper–shopper, respectively.

Hoping to uncover the physical principles of the vibration of the functionally graded material (FGM) microplate, by which the authors can make contributions to the design and manufacturing process in factories like micro-electro-mechanical system (MEMS) and other industries.

The authors design a method by establishing a reasonable mathematical model of the physical microplate composed of a porous FGM.

The authors discover that the porosity, the distributions of porosity, the power law of the FGM and the length-to-thickness ratio all affect the natural frequency of the vibration of the microplate, but in different ways.

Originally proposed a model of the micro FGM plate considering the different distributions of the porosity and scale effect and analyzed the vibration frequency of it.

Many companies have now built brand fan pages (BFPs) on social media platforms to connect with their existing and potential customers. Nevertheless, the inability to retain existing followers would severely threaten the survival of BFPs and the effectiveness of a company's social media strategies. Drawing upon Furneaux and Wade's discontinuance framework, our study develops a research model to understand the BFP user's intention to discontinue following a BFP.

An empirical study was conducted through an online survey of Chinese social media users. The proposed model was tested by analyzing the collected data using the partial least squares structural equation modeling (PLS-SEM) approach.

The results reveal that dissatisfaction with information quality, unfollowing costs, trust and alternative attractiveness affect the individual's intention to unfollow a BFP. Notably, unfollowing costs is the most powerful factor to predict followers' propensity to discontinue.

Our study contributes to the understanding of the discontinuance of information systems. Theoretical implications for future social commerce research as well as practical suggestions for BFP operators are also discussed.

The Chinese believe that “man will conquer the sky” and “fighting with the sky brings endless joy”. Considering that disaster assessment can be regarded as a two-person, zero-sum game problem between nature and human beings, this paper proposes a multi-attribute decision-making method based on game theory and grey theory in a single-value neutrosophic set environment. Due to the complexity and uncertainty of the decision-making environment, the method builds a decision matrix based on single-valued neutrosophic numbers.

First, the authors use the single-value neutrosophic information entropy to calculate the attribute weights and the weighted decision matrix. Second, the optimal mixed strategy method based on linear programming solves the optimal mixed strategy for both sides of the game so that the expected payoff matrix can be obtained. Finally, grey correlation analysis is used to obtain the closeness coefficient of each alternative based on the expectation payoff matrix to identify the ranking result of the alternative.

An example is used to verify the effectiveness of the proposed method, and its rationality is verified through a comprehensive comparison and analysis of the various aspects.

The proposed decision-making method can be applied to typhoon disaster assessment. Such assessment results can provide intelligent decision support to the relevant disaster management departments, thereby reducing the negative impact of typhoon disasters on society, stabilizing society and improving people's happiness. Further, the method can be used for decision-making, recommendation and evaluation in other fields.

The proposed method uses single-value neutrosophic numbers to solve the information representation problem of decision-making in a complex environment. Under a new perspective, game theory is used to handle the decision matrix, while grey relational analysis converts inexact numbers to exact numbers for comparison and sorting. Thus, the proposed method can be used to make reasonable decisions while preserving information to the extent possible.