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The case of the Mercedes-Benz Arena in Shanghai, China raises an important issue with respect to transnational venue management corporations embedding and operating in foreign markets. The purpose of this paper is to examine how Anschutz Entertainment Group (AEG) has implemented social embeddedness strategy to influence the management structure and enhance operational performance of the Mercedes-Benz Arena.

A case study approach was chosen to examine the social embeddedness of AEG through the Mercedes-Benz Arena in Shanghai. An in-depth interview was conducted with John Cappo, the President and CEO of AEG China, in April 2016. In addition, the relative news and interviews of leaders from AEG and AEG China over the past ten years was also collected. Qualitative content analysis of the data was conducted through a coding approach. All the materials were coded into three main categories based on three aspects of social embeddedness: local stakeholder relations, reputation and trust-building, cultural and institutional adaptation.

AEG has demonstrated how a transnational venue management corporation can successfully integrate social embeddedness strategy with the management structure and operational procedures of the Mercedes-Benz Arena in three ways. First is through the relationship between AEG and its partners in the joint venture, OPG in terms of the enforcement of the contract, the clear division of responsibilities, and the mutual understanding and use of relationship building. Second is the relationship between AEG and the local government in Shanghai. Third was adapting the structures of AEG to fit within local culture and institutional contexts.

The unique multi-stakeholder relationship inherent to venue management in China raises important questions with respect to transnational venue management corporations operating in foreign markets. The adaptation to the local context, as a moderating factor to the institutional exposure of a venue management company involves more challenging obstacles for non-local firms, compared to firms which are familiar with their institutional context. Understanding the key solutions in building relationships and trust with partners in joint venture and local government, as well as the key methods to adopt in local contexts, have applications across any number of sport industries.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.

The purpose of this paper is to explore the determinants of family business owners’ intrafamily succession intention based on the theory of planned behavior and neo-institutional theory.

National survey data were collected from Chinese private firms in 2010, and a sample of 804 family firms was used to test the hypotheses.

At the micro level, familism, intrafamily succession regulation and family control have positive effects on owners’ intrafamily succession intention. At the macro level, district succession orientation, which is the district prevalence of intrafamily succession practice, has a positive effect on owners’ intrafamily succession intention. Additionally, the district succession orientation weakens the positive effects of intrafamily succession regulation and family control.

The paper contributes to the understanding of family business owners’ intrafamily succession intention from both micro and macro perspectives. Besides, it also contributes to the integration of micro and macro research by examining the interaction effects.

Climate change has aroused widespread concern around the world, which is one of the most complex challenges encountered by human beings. The underlying cause of climate change is the increase of carbon emissions. To reduce carbon emissions, the analysis of the factors affecting this type of emission is of practical significance.

This paper identified five factors affecting carbon emissions using the logarithmic mean Divisia index (LMDI) decomposition model (e.g. per capita carbon emissions, industrial structure, energy intensity, energy structure and per capita GDP). Besides, based on the projection pursuit method, this paper obtained the optimal projection directions of five influencing factors in 30 provinces (except for Tibet). Based on the data from 2000 to 2014, the authors predicted the optimal projection directions in the next six years under the Markov transfer matrix.

The results indicated that per capita GDP was the critical factor for reducing carbon emissions. The industrial structure and population intensified carbon emissions. The energy structure had seldom impacted on carbon emissions. The energy intensity obviously inhibited carbon emissions. The best optimal projection direction of each index in the next six years remained stable. Finally, this paper proposed the policy implications.

This paper provides an insight into the current state and the future changes in carbon emissions.

Dynamic capabilities (DCs) upgrade operational capabilities. However, DC dimensions of sensing, seizing and reconfiguring may combine in different configurations that result in alternative outcomes, depending on the firm's lifecycle stage. The purpose of this research is to explore configurations of DC dimensions during different stages of firms' lifecycles that result in operational marketing and technological capabilities.

Given the limited understanding of how DC dimensions and operational capabilities interact across a firm's lifecycle, the authors employed a multi-method approach to understand whether different configurations of DC dimensions may lead to operational marketing and technological capabilities and how the firm's lifecycle may condition these configurations. The authors first apply PLS path modelling to assess the validity and reliability of the measures. Then, the authors use fuzzy-set qualitative comparative analysis (fsQCA) to analyse micro, small and medium-sized enterprises (SMEs) in different growth stages operating in the creative industry within highly competitive and fast-changing environments.

Results show that several configurations of DC dimensions and competitive intensity influence marketing and technological capabilities. Although several configurations include sensing, seizing and reconfiguring, the findings also point to configurations where not all DC dimensions are present.

Improving operational capabilities does not necessarily imply a simultaneous presence of all three DC dimensions. Especially in the growth stage, managers that face resources shortage may only focus on sensing and seizing dimensions when developing marketing capabilities.

This research focuses on configurations of DC dimensions (instead of configurations of different types of DCs) that generate diverse marketing and technological capabilities development paths. The authors provide several equifinal configurations of DC dimensions that lead to operational marketing and technological capabilities. This study contributes to disentangling DCs and their dimensions across different lifecycle stages.

The purpose of this study is to meta-analytically compare the effect of differentiation strategy formulation on financial and non-financial performance to explore the agency problem.

This study was conducted using a meta-analysis approach and CMA2 software. Hypotheses has been tested using cumulative effect sizes. Then, the cumulative effect sizes if some subsamples are also tested for robustness check by manipulation of circumstances.

Based on the findings, differentiation affects performance dimensions. However, spite of shareholders’ wealth maximization, differentiation has a smaller effect on financial performance (as the proxy of shareholders’ wealth) compared with operational performance. Meanwhile, the robustness test showed that the results in all subcategories has also confirmed, and this supports the results.

The results catch attentions of shareholders to review the elements of management evaluation in the corporate governance system in a way that they focus more on stakeholders’ interests in developing differentiation strategy. Limitations of this study is firstly based on limitations of meta-analysis approach, which provide general results of relevant studies so that the local conditions of each firm should be considered in deploying implications.

Exploring the overall schema of firms (from past to present and in different research conditions) regarding the impact of differentiation strategy on performance has been the originality of this research because of potentials of meta-analysis against past field studies. This originality led to the discovery of the general confusion of firms in the development of differentiation strategy so that it emphasizes operational performance more than financial performance.

Owing to increased energy demands, China has become the world’s top CO2 emitter, with electricity generation accounting for the majority of emissions. Therefore, the Chinese Government aspires to achieve a low-carbon transformation of the electric industry by enhancing its green innovation capacity. However, little attention has been paid to the green development of electric technology. Thus, this paper aims to uncover the spatiotemporal evolution of electric technology in the context of China’s low-carbon transformation through patent analysis.

Using granted green invention patent data for China’s electric industry between 2000 and 2021, this paper conducted an exploratory, spatial autocorrelation and time-varying difference-in-differences (DID) analysis to reveal the landscape of electric technology.

Exploratory analysis shows that the average growth rate of electric technology is 8.1%, with spatial heterogeneity, as there is slower growth in the north and west and faster growth in the south and east. In addition, electric technology shows spatial clustering in local areas. Finally, the time-varying DID analysis provides positive evidence that low-carbon policies improve the green innovation capacity of electric technology.

The different effects of the low-carbon pilot policy (LCPC) on R&D subjects and the LCPC’s effectiveness in enhancing the value of patented technology were not revealed.

This paper reveals the spatiotemporal evolutionary characteristics of electric technology in mainland China. The results can help the Chinese Government clarify how to carry out innovative development in the electric industry as part of the low-carbon transformation and provide a theoretical basis and research direction for newcomers in this field.

This paper aims to understand the influence of cylinder liner temperature on friction power loss of piston skirts and the synergistic effect of cylinder liner temperature on lubrication and heat transfer between piston skirt and cylinder liner.

A method to calculate the influence of cylinder liner temperature on piston skirt lubrication is proposed. The lubrication is calculated by considering the different temperature distribution of the cylinder liner and corresponding piston temperature calculated by a new multilayer thermal resistance model. This model uses the inner surface temperature of the cylinder liner as the starting point, and the starting temperature corresponding to different positions of the piston is calculated using the time integral average. Besides, the transient heat transfer of mixed lubrication is taken into account. Six temperature distribution schemes of cylinder liner are designed.

Six temperature distributions of cylinder liner are designed, and the maximum friction loss is reduced by 34.4% compared with the original engine. The increase in temperature in the second part of the cylinder liner will lead to an increase in friction power loss. The increase of temperature in the third part of the cylinder liner will lead to a decrease in friction power loss. The influence of temperature change in the third part of the cylinder liner on friction power loss is greater than that in the second part.

The influence of different temperature distribution of cylinder liner on the lubrication and friction of piston skirt cylinder liner connection was simulated.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing systems. This paper proposes is a new Fault Tolerant Control (FTC) system to identify the probable fault occurrences in the plant.

A Fault Diagnosis and Isolation (FDI) module has been devised based on the estimated state of system. An Unscented Kalman Filter (UKF) is the main innovation of the FDI module to identify the faults. A Multi-Sensor Data Fusion algorithm is utilized to integrate the UKF output data to enhance fault identification. The UKF employs an augmented state vector to estimate system states and faults simultaneously. A control mechanism is designed to compensate for the undesirable effects of the detected faults.

The performance of the Nonlinear Model Predictive Controller (NMPC) without any fault compensation is compared with the proposed FTC scheme under different fault scenarios. Analysis of the simulation results indicates that the FDI method is able to identify the faults accurately. The proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated.

A significant contribution of the paper is the design of an FTC system by using UKF to estimate faults and enhance the accuracy of data. This is done by applying a data fusion algorithm and controlling the system by the NMPC after eliminating the effects of faults.