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The purpose of this paper is to explore the evolvement of investors’ behavior in stock market dynamically on the basis of non-cooperative strategy applied by investors in complex networks.

Using modeling and simulation research method, this study designs and conducts a mathematical modeling and its simulation experiment of financial market behavior according to research’s basic norms of complex system theory and methods. Thus the authors acquire needed and credible experimental data.

The conclusions drawn in this paper are as follows. The dynamical evolution of investors’ trading behavior is not only affected by the stock market network structure, but also by the risk dominance degree of certain behavior. The dynamics equilibrium of trading behavior’s evolvement is directly influenced by the risk dominance degree of certain behavior, connectivity degree and the heterogeneity of the stock market networks.

This paper focuses on the dynamical evolvement of investors’ behavior on the basis of the hypothesis that common investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of anti-coordination game in complex network. While the investors’ preference and the beliefs among them are not easy to quantify, that is deterministic or stochastic as the environment changes, and is heterogeneous definitely. Thus, these limitations should be broken through in the future research.

This paper aims to address the dynamical evolvement of investors’ behavior in stock market networks on the principle of non-cooperative represented by anti-coordination game in networks for the first time, considering that investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of differential choosing in every time step. The methodology designed and used in this study is a pioneering and exploratory experiment.

The purpose of this paper is to analyze the operational decisions of a manufacturer who produces multiple products and the government's selection of cap-and-trade and carbon tax regulations.

This paper explores the production decisions of a multi-product manufacturer under cap-and-trade and carbon tax regulations in a cap-dependent carbon trading price setting and compares carbon emission, the manufacturer's profits and social welfare under the two regulations. Game theory and extreme value theory are used to analyze our models.

First, the authors find that the optimal profit of the manufacturer (the optimal cap) increases and then decreases with the cap (the unit carbon emission of product). Second, if the environmental damage coefficient is moderate, the optimal cap of unit environmental damage coefficient is independent of the product carbon emission or other related product parameters. Ultimately, cap-and-trade regulation always generates more carbon emission than carbon tax regulation. And cap-and-trade regulation (carbon tax regulation) can generate more social welfare if the environmental damage coefficient is low (high), and the social welfare under the two regulations is equal to each other, or otherwise.

This paper contributes the prior literature by considering the inverse relationship of the allocated cap and the carbon trading price and discusses the social welfare under cap-and-trade and carbon tax regulations. Some important and new results are found, which can guide the government's implementation of the two regulations.

The purpose of this paper is to introduce an analytic method to calculate the slot leakage reactance of stator bar strands in alternative current machines whose stator windings have multiple bars per layer and using deficient transposition.

Based on the analysis of deficient transposition, the calculation model of mutual slot leakage reactance between any two strands in one bar is established. The subsection integral method is presented to calculate the slot leakage reactance and analytic function is listed. A pump motor used in nuclear power is taken as an example, and the slot self leakage reactance of any strand in its top layer winding and the slot mutual leakage reactance between one strand and other strands in the same bar are calculated depending on the method described above. The slot leakage reactance of all strands in the top layer winding is calculated when different transposition angles are applied in stator bars.

The results show that subsection integral method is effective in calculating the slot leakage reactance of stator bar strands of deficient transposition. The slot leakage reactance distribution of all strands is obtained. The transposition angle has a great impact on the slot leakage reactance distribution of stator bar strands.

This paper presents an available method to calculate the slot leakage reactance of any strands in alternative current machine whose stator windings have multiple bars per layer and using deficient transposition, and discusses the impact of transposition angle on the slot leakage reactance. The conclusion can lay the foundation of the effective calculation of circulating current losses in stator bars with deficient transposition.

This research examines the impact of the National Rural E-commerce Comprehensive Demonstration Project (NRECDP) on poverty reduction and income growth in rural China.

The study develops a theoretical framework, which considers the role of geographical, technological, institutional and cultural factors for the e-commerce poverty alleviation (e-CPA) model. Empirically, this study applies the difference-in-differences (DID) model and the event study approach to evaluate the effectiveness of NRECDP on the basis of large-scale county-level and household-level panel data spanning 2010 to 2020.

The study found that the NRECDP, as a government-led, information and communication technology (ICT)-enabled, market-based program, has led to a significant increase in per capita output of primary industry employees, as well as in the disposable income of rural residents, especially those in national-level poverty-stricken (NP) counties. The interventions of the NRECDP achieved these positive outcomes through transportation and Internet infrastructure improvement, ICT adoption and human capital accumulation in impoverished towns and villages in remote rural areas. These effects are larger in the eastern region of China, followed by the central region, whereas the weakest effects were found in the western region. However, we found little evidence of the NRECDP increasing household developmental expenditure.

The study findings have important practical and policy implications for rural e-commerce development and self-sustained poverty alleviation solutions. The research revealed the significance of government NRECDP interventions for increasing rural income, reducing living costs, and empowering the rural population in its multiple social roles, namely, as consumers, producers, employees and microentrepreneurs. The local cultural context may also play a role in ICT adoption and entrepreneurship cultivation with a downstream effect on the effectiveness of e-CPA practices. Policymakers would need to ensure a supportive entrepreneur-friendly environment for rural e-commerce development and continue implementing progressive policies for poverty alleviation.

This study explores poverty alleviation issues in China by developing for the first time a multi-faceted framework that is subsequently tested by both county-level and household-level large-scale observations. Also, it is the first study to provide nationwide empirical evidence on the effectiveness of e-CPA in narrowing down the spatial and digital divides in China. In addition to the impact of geography, technology and governmental support, this study also sheds light on the role of culture in the adoption and diffusion of digital technologies and as a source of local entrepreneurial opportunities.

This paper aims to study the impact of CEOs' cultural background on corporate innovation. The paper constructs a measure of CEOs' cultural individualism based on their birthplaces and investigates its relationship with firms' patents and citations. The study aims to shed light on the interaction of culture and corporate decisions and focuses on the role of top managers. The paper also investigates the mechanism of how top management can affect corporate innovation output.

The paper constructs the measure of individualism using the westward expansion in US history. To do so, the paper uses the US county-level duration of exposure of the frontier territory in the 19th century and links the counties to CEOs' birthplaces. The paper argues the cultural characteristics of birthplaces can affect a person's later management styles and decisions, hence affecting corporate innovation policies. Using regression and difference-in-differences estimations, the paper explores the relation and causality between cultural individualism and innovation output.

The paper finds that CEO cultural individualism is positively related with the number of patents produced by the firm and the citations received by the firm. Difference-in-differences tests using CEO turnovers support that the relation is causal. The paper also investigates the economic mechanism of how individualistic CEOs achieve such results. It finds that individualistic CEOs tend to hire more talented employees and improve the workplace environment to attract top inventors.

This paper provides firm-level evidence of culture and innovation. Prior studies in this area focus on cross-country evidence and suffer the limitation of confounding factors. Using a county-level measure of individualism and a sample of firms in USA, the paper alleviates the concern and provides evidence with better granularity. This paper also provides a novel mechanism for attracting top inventors, while existing literature tend to focus on risk-taking activities.

The purpose of this paper is to examine the industrial production efficiency, pollution treatment efficiency, total factor energy efficiency and water efficiency in China with the consideration of technological innovation. This study also explores the distribution proportion of technological innovation between industrial production substage and pollution treatment substage.

A nonparametric method, data envelopment analysis (DEA), is used as the model foundation of this study. Specifically, a novel two-stage range-adjusted measure (RAM-DEA) with shared inputs is constructed to analyze the China’s industrial system. In this study, the panel data of 30 provinces from 2008 to 2015 are used.

This study found that although the current environmental regulation reduced the efficiency of industrial production, it could significantly improve the pollution treatment level. However, the lack of pollution treatment capacity was still an obstacle for development of China's industrial system. Compared with the total factor energy efficiency, the total factor water efficiency had more room for improvement. The optimal distribution of technological innovation in the two substages performed little change and the distribution roughly followed the “three-seven principle”.

More attention should be paid to improve the pollution treatment level and total factor water efficiency. And more R&D expenditure should be used in the industrial production substage in the eastern coastal areas, while in the inland areas, more R&D expenditure should be used in the pollution treatment substage.

This study proposed a model to environmental efficiency score with considering interval data under two-stage evaluation structure, which could strengthen the theory and expand the application scope of DEA approach.

With the continuous increase of space activities and insight into space exploration, the velocity of near space hypersonic vehicles becomes higher and higher, which leads to the aerothermodynamic phenomenon getting worse around a vehicle; therefore, the exploration of numerical scheme applicability is essential for hypersonic flow simulations.

The implicit finite volume schemes are derived from axisymmetric Navier–Stokes equations for chemical equilibrium flow and programmed in Fortran. Taking the atmosphere at 30 km as an example, the performance of spatial discretization schemes such as AUSMPW and AUSMPW+ are analyzed in a range of Mach numbers from 17 to 32.

The AUSMPW scheme appears pressure jump near the stagnation if the Mach number is over 18, but AUSMPW+ scheme shows better performance in comparison.

This study will help the aerothermodynamic design in near space hypersonic vehicles.

The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant departments in formulating public opinion control measures for specific time and space contexts.

The spatiotemporal situational awareness framework comprises situational element extraction, situational understanding and situational projection. In situational element extraction, the data on the COVID-19 vaccine, including spatiotemporal tags and text contents, is extracted. In situational understanding, the bidirectional encoder representation from transformers – latent dirichlet allocation (BERT-LDA) and bidirectional encoder representation from transformers – bidirectional long short-term memory (BERT-BiLSTM) are used to discover the topics and emotional labels hidden in opinion texts. In situational projection, the situational evolution characteristics and patterns of online public opinion are uncovered from the perspective of time and space through multiple visualisation techniques.

From the temporal perspective, the evolution of online public opinion is closely related to the developmental dynamics of offline events. In comparison, public views and attitudes are more complex and diversified during the outbreak and diffusion periods. From the spatial perspective, the netizens in hotspot areas with higher discussion volume are more rational and prefer to track the whole process of event development, while the ones in coldspot areas with less discussion volume pay more attention to the expression of personal emotions. From the perspective of intertwined spatiotemporal, there are differences in the focus of attention and emotional state of netizens in different regions and time stages, caused by the specific situations they are in.

The situational awareness framework can shed light on the dynamic evolution of online public opinion from a multidimensional perspective, including temporal, spatial and spatiotemporal perspectives. It enables decision-makers to grasp the psychology and behavioural patterns of the public in different regions and time stages and provide targeted public opinion guidance measures and offline event governance strategies.

The purpose of this paper is to present a tie-breaking procedure for computing performance efficiencies to improve benchmarking and performance evaluation process in a business situation.

The authors propose a unified approach based on data envelopment analysis (DEA) and technique for order of preference by similarity to ideal solution (TOPSIS), to overcome the difficulty of unique ranking in the prevalent benchmarking and performance evaluation processes such as DEA, Super efficiency DEA model, etc., under constant return to scale (CRS) assumption. This model is called as efficiency ranking method using DEA and TOPSIS (ERM-DT). In order to check the consistency of the approach, various input-output combinations (to calculate the efficiencies) have been illustrated. Further, the authors present a case of an Indian Bank to illustrate an application of the proposed approach.

The proposed approach, ERM-DT enables assign a unique rank to decision making units and provides a tie breaking procedure. Results obtained using the proposed approach are statistically compared with those obtained from the CRS DEA approach and super efficiency DEA approach using Friedman’s test.

The proposed model provides an efficiency ranking method based on a score obtained by considering the minimum distance from the best value and maximum distance from the worst value. The proposed methodology is capable of handling negative data and undesirable output variables. This approach is unit invariant and makes the calculations simple. The authors present an application to compute the efficiency of various branches of an Indian bank. The authors hope the proposed method can enhance the decision-making ability of the management in complex situations.

The authors propose an integrated DEA and TOPSIS framework for better benchmarking and performance evaluation. This approach provides a tie-breaking procedure for the efficiencies computed using CRS DEA approach. Ranks are assigned based on score obtained by considering the distance from the worst and the best solution. The proposed approach can be used with non-positive data points and undesirable output variables.