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A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

We take a state-stewardship view on corporate governance and executive compensation in economies with strong political involvement, where state-appointed managers act as responsible “stewards” rather than “agents” of the state.

We test this view on China and find that Chinese managers are remunerated not for maximizing equity value but for increasing the value of state-owned assets.

Managerial compensation depends on political connections and prestige, and on the firms’ contribution to political goals. These effects were attenuated since the market-oriented governance reform.

Economic reform without reforming the human resources policies at the executive level enables the autocratic state to exert political power on corporate decision making, so as to ensure that firms’ business activities fulfill the state’s political objectives.

As a powerful social elite, the state-steward managers in China have the same interests as the state (the government), namely extracting rents that should adhere to the nation (which stands for the society at large or the collective private citizens).

As China has been a communist country with a single ruling party for decades, the ideas of socialism still have a strong impact on how companies are run. The legitimacy of the elite’s privileged rights over private sectors is central to our question.

Chinese executive compensation stimulates not only the maximization of shareholder value but also the preservation of the state’s interests.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

This paper centers on the exploration of Chinese conflict management styles in the context of international joint ventures in the People's Republic of China (PRC). Based on interviews conducted with directing managers in U.S.‐Chinese joint ventures and seminars held in China on conflict management in such ventures, major characteristics of Chinese conflict management styles are discussed. Influenced by the traditional Chinese values, norms, and philosophies, Chinese managers in joint ventures tend to adopt contingent, long‐term, contextual, and holistic approaches to conflict resolution.

In this paper, a kind of an oil groove structure which could improve the transmission torque of an oil film was designed, i.e. the width and depth of oil groove gradually decrease with the increase in the radius.

Effects of the structural parameters of the oil groove on the hydro-viscous drive (HVD) characteristics with variable rotational speed were investigated by means of numerical calculation.

Research results show that with the decrease of the width and depth of the oil groove at the outer diameter, transmission torque increases, while the temperature is almost unchanged. Keeping the effective area unchanged, comparing the transmitted torque under the oil groove angle θ₂ = 0.5° and θ₂ = 4.5°, the former was almost 200 per cent of the latter; the torque transmitted with h₂ = 0.05 mm was almost 150 per cent of that with h₂ = 0.2 mm.

In this paper, the authors analyze the friction surface of the friction plate between the oil groove, oil distribution and oil film transfer torque from the oil groove structure parameters and found methods to improve the transmission torque. For the first time, the influence of the structural parameters of oil groove on the characteristics of HVD was studied under the condition of variable rotational speed, and a better method to improve the transmission torque was proposed.

Budget hotels are becoming an emerging industry for convenience and affordability, where consumer sentiments are of paramount importance. Tourism has become increasingly dependent on social media and online platforms to gather travel-related information, purchase travel products, food, lodging, etc., and share views and experiences. The user-generated data helps companies make informed decisions through predictive and behavioural analytics.

Design/Methodology/Approach: This study uses text mining, deep learning, and machine learning techniques for data collection and sentiment analysis based on 117,151 online reviews of the customers posted on the TripAdvisor website from May 2004 to May 2019 from 197 hotels of five prominent budget hotel groups spread across India using Feedforward Neural Network along with Keras package and Softmax activation function.

Findings: The word-of-mouth turns into electronic word-of-mouth through social networking sites, with easy access to information that enables customers to pick a budget hotel. We identified 20 widely used words that most customers use in their reviews, which can help managers optimise operational efficiency by boosting consumer acceptability, satisfaction, positive experiences, and overcoming negative consumer perceptions.

Practical Implications: The analysis of the review patterns is based on real-time data, which is helpful to understand the customer’s requirements, particularly for budget hotels.

Originality/Value: We analysed TripAdvisor reviews posted over the last 16 years, excluding the Corona period due to industry crises. The findings reverberate in consonance with the performance improvement theory, which states feed-forward a neural network enhances organisational, process, and individual-level performance in the hospitality industry based on customer reviews.

This study aims to benchmark Chinese TEFL academics’ research productivities, as a way to identify and, subsequently, address research productivity issues. This study investigated 182 Chinese TEFL academics’ research outputs and perceptions about research across three Chinese higher education institutions using a literature‐based survey. ANOVA, t‐tests and descriptive statistics were used to analyse data from and between the three institutions. Findings indicated that more than 70 per cent of the TEFL academics had produced no research in 10 of the 12 research output fields during 2004‐2008. The English Language and Literature Department in the national university outperformed all other departments at the three institutes for most of the research output categories. While a majority of the participants seemed to hold positive perceptions about research, t‐tests and ANOVA indicated that their research perceptions were significantly different across institutes and departments. Developing TEFL research capacity requires tertiary institutions to provide research‐learning opportunities.

This study aims to examine the current state of the research activities of scholars in the hospitality and tourism field by analyzing the first 20 years of the new millennium.

Longitudinal analyses using 14,229 journal articles as data source were realized by adopting BibExcel, Gephi and VOSviewer network analysis software packages.

This study provides a comprehensive overview of the hospitality and tourism research based on authorship and social network analysis, with patterns of prolific authors compared over four distinct periods.

The hospitality and tourism academic society is clearly illustrated by tracing academic publication activities across 20 years in the new millennium. In addition, this study provides a guide for scholars to search for multidisciplinary collaboration opportunities. Government agencies and non-governmental organisations can also benefit from this study by identifying appropriate review panel members when making decisions about hospitality- and tourism-related proposals.

To the best of authors’ knowledge, this study is the first to use bibliometric analysis in assessing research published in leading hospitality and tourism journals across the four breakout periods in the new millennium.