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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.

This research explores the impacts of content-generating devices (mobile phones versus personal computers) and content features (social content and achievement content) on consumer engagement with marketer-generated content (MGC) on social media. It also examines these factors' interaction effects on consumer engagement.

The study analyzed MGC that 210 companies had posted to Sina Weibo over three years, testing the study’s proposed model with negative binomial regression analysis.

The study's results show that MGC generated via mobile phones attracts more consumer engagement than MGC generated via personal computers. MGC with more social features attracts more consumer engagement, whereas MGC with more achievement features reduces consumer engagement. The authors also found that MGC with more social features generated via mobile phones and MGC with more achievement features generated via personal computers lead to more consumer engagement due to the congruency of the construal level of psychological distance.

This research enriches the literature by exploring the effects of content-generating devices and content features on consumer engagement in the MGC context, which extends the research on consumer engagement with social media from the context of user-generated content to the MGC.

This chapter examines China’s corporate governance and accounting environment that shapes the adoption of internationally acceptable principles and standards. Specifically, it examines international influences, including supranational organizations; foreign investors and international accounting firms; domestic institutional influences, including the political system, economic system, legal system, and cultural system; and accounting infrastructure. China’s convergence is driven by desired efficiency of the corporate sector and legitimacy of participating in the global market. Influenced heavily by international forces in the context of globalization, corporate governance and accounting practices are increasingly becoming in line with internationally acceptable standards and codes. While convergence assists China in obtaining legitimacy, improving efficiency is likely to be adversely affected given that corporate governance and accounting in China operate in an environment that differs considerably from those of Anglo-American countries. An examination of the corporate governance and accounting environment in China suggests heavy government involvement within underdeveloped institutions. While the Chinese government has made impressive progress in developing the corporate governance and accounting environment for the market economy, China’s unique institutional setting is likely to affect how the imported concepts are interpreted and implemented.

The purpose of this paper is to review English-language publications about school principalship in China published between 1998 and 2013 and to present an overview of the authorship, topics, methodologies and key findings of these publications.

The methodology includes an exhaustive review of journal articles and book chapters about Chinese school principalship published in the English language. In total, 39 articles and 17 book chapters are identified for the 1998-2013 period. Qualitative analysis is conducted to determine the basic patterns of authorship, topics, methods and key findings. The changes or continuities in these patterns during the study period are also discerned.

The paper identifies several continuous and discontinuous patterns in each of the review categories and provides a better understanding of on-going research into the practice of school principalship in China. The results also suggest areas that require deeper exploration.

This paper explores the landscape of school principalship in China as reflected in the international literature and indicates the ways that this landscape has changed or remained the same over the years. As such, the paper contributes to the thin knowledge base concerning school principalship in China and sheds light on the enduring local-global tension in the evolution of education systems.

This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster popularity moderates social interaction-oriented content's effect on the two different behaviors in live-streaming commerce.

A research model was proposed and empirically tested using a panel data set collected from 537 live streams via Douyin (the Chinese version of TikTok), one of the most popular live broadcast platforms in China. A fixed-effects negative binomial regression model was used to examine the proposed research model.

This study's results show that social interaction-oriented content in broadcasters' live speech has an inverted U-shaped relationship with broadcast viewers' purchasing behavior and shares a positive linear relationship with viewers' gift-giving behavior. Furthermore, broadcaster popularity significantly moderates the effect of social interaction-oriented content on viewers' purchasing and gift-giving behaviors.

This research enriches the literature on live-streaming commerce by investigating how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' product-purchasing and gift-giving behaviors from the perspective of broadcast viewers' attention. Moreover, this study provides some practical guidelines for developing live speech content in the live-streaming commerce context.

This study investigates the impact of supply chain governance (SCG, which includes relational governance and contractual governance) on supply chain resilience (SCR) using the information processing theory. Moreover, the study also examines the mediating role of information processing capability and the moderating role of digital technology (DT) deployment.

A total of 288 questionnaires were collected from the Chinese manufacturing industry, and hierarchical regression was used to empirically test the proposed model.

This study reveals that SCG positively impacts SCR. Moreover, information processing capability plays a mediating role between SCG and SCR. Furthermore, the breadth of DT deployment positively moderates the effect of relational governance on information processing capability, and the depth of DT deployment positively moderates the effects of both relational governance and contractual governance on information processing capability.

This study offers a novel perspective that helps to understand the importance of the supply chain-wide information acquired by SCG in respect of improving SCR. Furthermore, this article extends the application of information processing theory by providing empirical evidence of the mediating role of information processing capability and elucidating the moderating role of DT deployment.

This study aims to examine how job satisfaction (JS) affects two types of knowledge sharing (KS), in-role KS and extra-role KS. It also investigates the mediating effect of knowledge sharing self-efficacy (KSSE) and the moderating effect of team collaborative culture (TCC) between JS and two types of KS.

This study applies attribution theory to develop a cross-level model and validate it through paired data collected from 322 information technology professionals nested within 80 teams. Hierarchical linear modeling is used to test the hypotheses.

JS positively influences in-role and extra-role KS via KSSE and TCC positively moderates the relationship between JS and extra-role KS.

This study is one of the first to investigate the mechanism underlying the influence of JS on two types of KS. It also identifies the mediating and moderating effects of this mechanism.

This paper aims to propose a precise turbulence model for automobile aerodynamics simulation, which can predict flow separation and reattachment phenomena more accurately.

As the results of wake flow simulation with commonly used turbulence models are unsatisfactory, by introducing a nonlinear Reynolds stress term and combining the detached Eddy simulation (DES) model, this paper proposes a nonlinear-low-Reynolds number (LRN)/DES turbulence model. The turbulence model is verified in a backward-facing step case and applied in the flow field analysis of the Ahmed model. Several widely applied turbulence models are compared with the nonlinear-LRN/DES model and the experimental data of the above cases.

Compared with the experimental data and several turbulence models, the nonlinear-LRN/DES model gives better agreement with the experiment and can predict the automobile wake flow structures and aerodynamic characteristics more accurately.

The nonlinear-LRN/DES model proposed in this paper suffers from separation delays when simulating the separation flows above the rear slant of the Ahmed body. Therefore, more factors need to be considered to further improve the accuracy of the model.

This paper proposes a turbulence model that can more accurately simulate the wake flow field structure of automobiles, which is valuable for improving the calculation accuracy of the aerodynamic characteristics of automobiles.

Based on the nonlinear eddy viscosity method and the scale resolved simulation, a nonlinear-LRN/DES turbulence model including the nonlinear Reynolds stress terms for separation and reattachment prediction, as well as the wake vortex structure prediction is first proposed.

This research aims to use meta-analytical structural equation modeling to look into how hospitality employees use technology at work. It further investigates if the relationship between the constructs of the technology acceptance model (TAM) is moderated by job level (supervisory versus non-supervisory) and different cultures (eastern versus western).

In total, 140 relationships from 30 empirical studies (N = 6,728) were used in this study’s data analysis in accordance with the preferred reporting items for systematic reviews and meta-analysis.

The findings demonstrated that perceived usefulness had a greater influence on “user attitudes” and “acceptance intention” than perceived ease of use. This study also identified that the effect sizes of relationships among TAM constructs appeared to be greater for supervisory employees or in eastern cultures than for those in non-supervisory roles or western cultures.

The findings provide valuable information for practitioners to increase the adoption of employee technology. Practitioners need to focus on the identification of hospitality employee attitudes, social norms and perceived ease of use. Moreover, hospitality practitioners should be cautious when promoting the adoption of new technologies to employees, as those at different levels may respond differently.

This is the very first empirical investigation to meta-analyze the predictive power of the TAM in the context of hospitality staff technology adoption at the workplace. The findings also demonstrated differences in the predictive power of TAM constructs according to job level and cultural differences.