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Online review bias research has predominantly focused on self-selection biases on the user’s side. By collecting online reviews from multiple platforms and examining their biases in the unique digital environment of “Chinanet,” this paper aims to shed new light on the multiple sources of biases embedded in online reviews and potential interactions among users, technical platforms and the broader social–cultural norms.

In the first study, online restaurant reviews were collected from Dianping.com, one of China's largest review platforms. Their distribution and underlying biases were examined via comparisons with offline reviews collected from on-site surveys. In the second study, user and platform ratings were collected from three additional major online review platforms – Koubei, Meituan and Ele.me – and compared for possible indications of biases in platform's review aggregation.

The results revealed a distinct exponential-curved distribution of Chinese users’ online reviews, suggesting a deviation from previous findings based on Western user data. The lack of online “moaning” on Chinese review platforms points to the social–cultural complexity of Chinese consumer behavior and online environment that goes beyond self-selection at the individual user level. The results also documented a prevalent usage of customized aggregation methods by review service providers in China, implicating an additional layer of biases introduced by technical platforms.

Using an online–offline design and multi-platform data sets, this paper elucidates online review biases among Chinese users, the world's largest and understudied (in terms of review biases) online user group. The results provide insights into the unique social–cultural cyber norm in China's digital environment and bring to light the multilayered nature of online review biases at the intersection of users, platforms and culture.

This study investigates the heterogeneous impact of R&D capital market distortions (CMDs) on the quantity and quality of innovation in Chinese firms by exploring key pathways from a dual-arbitrage perspective.

Using data from Chinese A-share listed companies (2015–2021), we employ a multidimensional fixed effects model to validate the research hypotheses. Under the Systems of National Accounts (SNA, 2008) framework, we use the Bureau of Economic Analysis method to estimate enterprise R&D capital stock and the Cobb-Douglas production function to estimate R&D CMDs.

Results show that R&D CMDs drive firms toward strategic innovation, emphasizing quantity over quality. Policy arbitrage, including policy catering and rent-seeking, emerges as a pivotal mechanism under R&D CMDs, encouraging firms to prioritize quantity over quality in innovation. High-technology firms and those in the decline stage are more inclined to spearhead strategic innovation within the context of R&D CMDs.

These findings help policymakers promote high-quality innovation in Chinese enterprises by enhancing patent review mechanisms and shifting policies from quantity-driven to quality-oriented goals.

This study enriches the research on factor market distortions and innovation in emerging markets from the perspective of R&D CMDs, based on the “emerging + transitional” comprehensive framework. Unlike previous studies, which generally use enterprise R&D expenditure flow data, we apply the theory of R&D capitalization accounting to the micro-enterprise level under the SNA (2008) framework, enhancing the accuracy of R&D CMD estimations.

Switching to green energy is a crucial step in achieving carbon neutrality. This study aims to explore what motivates people to use green energy and how much more people are willing to pay for green energy.

Grounded on the value–attitude–intention hierarchy, this study proposes that environmental consciousness as a human value influences attitudes including attitude toward environmental issues and attitude toward ecosocial benefits while attitudes, information and knowledge about green energy and quality and price of green energy influence people’s intention to use green energy. Data were collected from 342 Chinese adults.

Results showed that environmental consciousness significantly and positively influenced attitudes while attitude toward environmental issues had the greatest effect on people’s intention to use green energy, followed by quality and price of green energy. About 44% respondents were willing to pay 2.5% to <5% more money for green energy.

This study extended the use of value–attitude–intention hierarchy to investigate what motivates people to use green energy. Specifically, this study demonstrated that quality and price, and knowledge and information also significantly shaped people’s intention to use green energy significantly.

The purpose of this study is to undertake an evaluation of the resilient capacity of the infrastructure systems in the city of Wuhan. This evaluation focuses on the ability of the infrastructure to cope with extreme weather from multiple dimensions and to propose effective interventions against such risks.

This research draws on a review and synthesis of the theory of resilience and adopts the literature induction method to build an evaluation index for five urban systems, namely: roads; water supply and drainage; energy and power; urban disaster reduction; and communications. Index data from the period of 1990–2019 are combined with the views of experts from Wuhan and analyzed using principal component analysis (PCA) to calculate the weightings of the five urban systems. A fuzzy comprehensive evaluation method is then used to investigate the resilient capacity of these five urban infrastructure systems in the city.

Generally, the results show that the resilience of the infrastructure systems in Wuhan are at a high level. Based on the results, the communications and roads systems are found to have higher levels of resilience, while the disaster mitigation system is found to have a relatively low level of resilience. Recommendations are suggested to help improve resilience and prioritize investments in the development of the city's infrastructure systems.

The development of these specific indicators and quantitative requirements have not been studied in detail, so a more comprehensive, systematic evaluation of quantitative indicators and methods of urban infrastructure resilience is still required. In addition, the research on the resilience of urban infrastructure under extreme weather is still in its infancy, and it is essential to further increase the quantitative assessment of the resilience of urban infrastructure under construction. This will also be indispensable information in the subsequent implementation of a resilient planning process.

This research builds a rigorous and reliable evaluation model that avoids any subjective bias in the results and represents a new approach to evaluate the resilience of the infrastructure systems in the city of Wuhan, which could be applied to other cities.

China has, apparently, more trade union members than the rest of the world put together, but the unions are subservient to the Party-state. The theme of the paper is the gap between rhetoric and reality. Issues analysed include union structure, membership, representation, and the interaction between unions and the Party-state. We suggest that Chinese unions inhabit an Alice in Wonderland dream world and that they are virtually impotent when it comes to representing workers. Because the Party-state recognises that such frailty may lead to instability it has passed new laws promoting collective contracts and established new tripartite institutions to mediate and arbitrate disputes. While such laws are welcome they are largely hollow: collective contracts are very different from collective bargaining and the incidence of cases dealt with by the tripartite institutions is tiny. Much supporting evidence is presented drawing on detailed case studies undertaken in Hainan Province (the largest and one of the oldest special economic zones) in 2004 and 2005. The need for more effective representation is appreciated by some All China Federation of Trade Unions (ACFTU) officials, but it seems a long way off, so unions in China will continue to echo the White Queen: “The rule is, jam tomorrow and jam yesterday – but never jam today” and, alas, tomorrow never comes.

This study’s goal was to identify how several markets have developed over time and what determinants have influenced this process, based on adaptive markets hypothesis (AMH). In this regard, the authors consider that agents are driven by the seeking for abnormal returns to stay “alive” and their environment could somehow modify their decision-making processes, as well as influence the degree of efficiency of the market.

The authors collected the daily closing-of-the-market index from 50 countries, between 1990 and 2022. The sample includes emerging countries, developed countries and frontier markets. Then, the authors ran multilevel modeling using Hurst exponent as an informational efficiency metric estimated by two different moving windows: 500 and 1,250 observations (approximately 2 and 5 years).

The results indicate that the efficiency of the markets is not constant over time. The authors also have identified that markets follow a cyclical pattern of efficiency/inefficiency, and they are currently in a period of convergence to efficiency, possibly explained by the increase in computational capacity and speed of the available information to agents. In addition, this study identified that country characteristics are associated with market efficiency, considering institutional factors.

Studies of this nature contribute to the literature, considering the importance of better comprehension of market efficiency dynamics and their determinants, specially observing other theories on the relationship between information and markets (like AMH), which work with other investor assumptions than those used by efficient market hypothesis.

The purpose of this study is to explore how to select a suitable supply chain collaboration paradigm (SCCP) based on the intelligent manufacturing model (IMM) of enterprises.

Given the fit between internal collaboration and external collaboration, we propose a model to select a suitable SCCP based on two-sided matching between SCCPs and IMMs. In this decision problem, we invited five university scholars and seven related consultants to evaluate SCCPs and IMMs based on the regret theory, which is used to obtain the perceived utility and matching results. The evaluation values are comfortably expressed through probabilistic linguistic term sets (PLTSs). Also, we set the lowest acceptance threshold to improve the accuracy of matching results.

The findings indicate that the characteristics of IMMs can significantly influence the selection of SCCPs, and an SCCP is not suitable for all IMMs. Interestingly, the study findings suggest that the selection of SCCP is diverse and multi-optional under the constraints of IMMs.

Existing studies have explored supply chain collaboration (SCC) in Industry 4.0 to improve supply chain performance, but less attention has been paid to the impact of the match between SCCPs and IMMs on supply chain performance. And even fewer studies have addressed how to select a suitable SCCP in different IMMs. This study provides a unique contribution to the practice of SCC and expands the understanding of supply chain management in Industry 4.0.

The study aims to examine the green finance customers' post-usage continuance behavior based on an extended social support theory (SST). Remarkably, this study explores five indirect predictors of green finance continuance behavior (GFCB) (i.e. environmental consciousness (EC), green bank marketing initiatives (GBMI), informational supports, emotional supports (EST) and psychological reactance) and a mediator (i.e. customer satisfaction).

In this study data were collected from 362 respondents from Bangladesh using a purposive sampling method with a structured self-administrative questionnaire and analyzed by partial least square structural equation and modeling using SMART PLS 3.0 software.

The results depict that the five predictors, i.e. information supports (ß = 0.367, t-statistics = 2.463, p < 0.001), EST (ß = 0.206, t-statistics = 2.315, p < 0.000), EC (ß = 0.324, t-statistics = 3.484, p < 0.000), GBMI (ß = 0.288, t-statistics = 2.028, p < 0.000), psychological reactance (ß = 0.126, t-statistics = 0.969, p < 0.052) influence GFCB while satisfaction is predicted by four predictors except psychological reactance (ß = 0.126, t-statistics = 0.969, p < 0.052). In addition, customer satisfaction (ß = 0.638, t-statistics = 6.317, p < 0.005) also has an impact on continuance behavior. Besides, the study understood that four predictors indirectly influence GFCB through satisfaction except psychological reactance ((ß = 0.080, t-statistics = 964, z = 0.958p < 0.338). Finally, the coefficient of determinations (R2) indicates that the five predictors explained 65.3% of changes in satisfaction, whereas 72.8% of changes are described by the five predictors and customer satisfactions.

Finally, this study highlights the social and managerial implications for the implementers of the green finance industry. It is recommended to emphasize green finance practice as it plays a crucial role in promoting environmental protection, ensuring social equity and driving economic growth. The green banking service providers, industry analysts, green consumers and respective government authorities can generalize green finance activities as an essential aspect of sustainable development to equalize the economic growth with a view to protecting environmental collapse and promoting renewable energy, energy efficiency, sustainable agriculture and other environmentally friendly activities.

The study will enormously contribute to the existing literature validating the proposed holistic framework applying SST along with EC, GBMI and psychological reactance in green finance continuance behavior.

The purpose of this paper is to explore the factors affecting the intention of social networking sites (SNS) users to comply with government policy during the COVID-19 pandemic.

Based on the theory of appraisal and coping, the research model is tested using survey data collected from 326 SNS users. Structural equation modeling is used to test the research model.

The results show that social support has a positive effect on outbreak self-efficacy but has no significant effect on perceived avoidability. Government information transparency positively affects outbreak self-efficacy and perceived avoidability. Outbreak self-efficacy and perceived avoidability have a strong positive impact on policy compliance intention through problem-focused coping.

The results suggest that both government and policymakers could deliver reliable pandemic information to the citizens via social media.

This study brings novel insights into citizen coping behavior, showing that policy compliance intention is driven by the ability to cope with problems. Moreover, this study enhances the theoretical understanding of the role of social support, outbreak self-efficacy and problem-focused coping.

This paper aims to conduct an experimental and theoretical investigation into fuel pre-delivery effects for a heavy fuel crankcase scavenged spark ignition two-stroke cycle engine for unmanned aerial vehicle application.

One-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline and fuels.

The experimental research has shown performance improvements using fuel preheating via use of auxiliary transfer port fuel injection. Computational simulation has allowed comparisons with auxiliary transfer port injection and direct in-cylinder injection to be made.

While some heavy fuel engines are now available for unmanned aerial vehicles the best solution to meet the military equipment single fuel policy remains an area of evolving research. The findings within this study show possibilities for fuel pre-treatment.

One-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline fuels.