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This paper aims to clarify voltage sourced converter’s (VSC’s) influence rules on the alternating current (AC) short-circuit current and identify the key factors, so as to propose the short-circuit current suppression strategy.

This paper investigates the key factors which impact the short-circuit current supplied by the VSC based on the equivalent current source model. This study shows that the phase of the VSC equivalent current source is mainly affected by the type of fault, whereas the amplitude is mainly decided by the control mode, the amplitude limiter and the electrical distance. Based on the above influence mechanism, the dynamic limiter with short-circuit current limiting function is designed. The theoretical analysis is verified by simulations on PSCAD.

The short-circuit current feeding from VSC is closely related to the control mode and control parameters of the VSC, fault type at AC side and the electrical distance of the fault point. The proposed dynamic limiter can make VSC absorb more reactive power to suppress the short-circuit current.

The dynamic limiter proposed in this paper is limited to suppress three-phase short-circuit fault current. The future work will focus more on improving and extending the dynamic limiter to the fault current suppression application in other fault scenarios.

The research results provide a reference for the design of protection system.

The key influence factors are conducive to put forward the measures to suppress the fault current, eliminate the risk of short-circuit current exceeding the standard and reduce the difficulty of protection design.

The purpose of this study is to develop luminescence sensors for the detection of nitroaromatic compounds (NACs) and metal ions to protect human health and prevent environmental pollution.

The composition and morphology of Eu-metal-organic frameworks (MOF) (1) were well characterized by powder X-ray diffraction, elemental analyses, Fourier-transform infrared spectroscopy, thermogravimetric analysis, X-ray photoelectron spectroscopy and scanning electron microscopy. The emission spectrum displays that 1 has significant characteristic emission bands of Eu(III) ions. The authors further investigated the fluorescence sensing performances of 1 to NACs and metal ions.

The results show that Eu-MOF (1) exhibits significant fluorescence quenching effect toward p-nitroaniline and Fe³⁺ ions with good stability and recyclability. This means that 1 can be used as a multifunctional sensing material for the detection of p-nitroaniline and Fe³⁺ ions.

The authors have successfully synthesized a fluorescence Eu-based sensing material under hydrothermal conditions. In addition, the fluorescence property and sensing performances for detecting NACs and metal ions were studied. The results suggest that 1 has highly selective fluorescence quenching toward p-nitroaniline and Fe³⁺ ions with not only high sensitivity and selectivity but also excellent stability and recyclability. Furthermore, this study has confirmed that the multifunctional MOF material is very useful in environment pollutants’ detection and monitoring.

The purpose of this study is to focus on numerical simulation investigations of deformation analysis of asymmetric break-down rolling of a hollow steel, which seriously affects the service life of the final product.

The 3D rigid-plastic thermo-mechanical coupled finite element method (FEM) for a large strain was used to analyze metal deformation in the deformation zone for asymmetric rolling with different roller diameters.

The distribution of stress, strain and dimension accuracy for different diameters was obtained. The results show that the additional shear strain which is different from the normal compression deformation is generated in an asymmetric rolling process. The higher the ratio between upper and lower diameters, the greater the additional shear deformation.

Asymmetric rolling is an important factor affecting the dimensional accuracy of the hollow steel. This study can provide a theoretical basis for developing a reasonable rolling process of the hollow steel.

This study aims to focus on numerical simulation investigations of phase transformation during cooling of 55SiMnMo steel, which is commonly applied to improve mechanical properties.

A mathematical model based on the finite element method (FEM) and the phase transformation kinetics model has been proposed to predict microstructure changes during continuous cooling of 55SiMnMo steel. This model can be employed to analyze the variation of austenite, special upper bainite and lump-like composite structure with cooling time at different cooling rates.

According to the continuous cooling experiments, when the cooling rate is lower than 0.1°C/s, the special upper bainite is the only transformation product which decreases with increasing cooling rate; when the cooling rate is above 0.5°C/s, the transformation products include special upper bainite and lump-like composite structure. Meanwhile, the results of continuous cooling experiment verified the correctness of this finite element model.

This model has a great value for proper controlling of the cooling process which can improve the quality of hollow drill steel and increase the service life of the final product.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

The paper examines whether the hybrid strategy can generate high performance and what hybrid strategy configurations are more conducive to high performance.

This paper explores the complex causal relationships between six strategic elements (marketing, growth, R&D, capital, efficiency, stability) and firm performance. From a configurational approach, the authors utilize necessary condition analysis, time-series qualitative comparative analysis, and typical case extraction techniques to analyze 944 balanced panel data from 118 Chinese ICT firms during 2013–2020.

Chinese ICT sector firms do not rely on pure strategies (prospector or defender) to achieve high performance. The hybrid strategy is conducive to high performance. Only specific hybrid strategy configurations, including stable growth, innovative efficiency, and two-way player types, could enable firms to perform well. Six strategic elements do not constitute a necessary condition for high performance.

This paper proposed an integrated qualitative comparative analysis scheme, proved the effectiveness of the hybrid strategy on firm performance, and revealed how hybrid strategy configurations generate high performance.

This paper extends the current understanding of the retrenchment-–turnaround relationship in declined companies by introducing a compensation gap view. It argues that the effectiveness of the retrenchment strategy is contingent on reducing the executive-employee compensation gap in the turnaround process.

Drawing from a two-stage turnaround model and insights from the literature on executive-employee compensation gap, we develop and test a theoretical model that explains how five attributes, which refer to executive-employee compensation gap, asset retrenchment, cost retrenchment, ownership and size, affect the outcome of the organizational turnaround. This paper uses the fuzzy-set qualitative comparative analysis (fsQCA) method and based on the samples of 112 listed companies that experience the decline between 2005 and 2013.

This paper concludes two valid causal paths and finds that small companies with small executive-employee compensation gap have a higher likelihood of successful turnaround when they implement cost or asset retrenchment actions. As for large state-owned companies, they should reduce the costs and maintain a small executive-employee compensation gap. An excessive compensation gap can be problematic, which could impair the organizational ability to cope with adversity and decline.

First, this paper taps the vital role of employees in the turnaround process besides the mainstream “organizational decline-layoffs” logic, which hints a new human resource management strategy when organizations are facing decline. Second, this paper reveals the theoretical linkage between pay dispersion, internal stakeholder and organizational resilience. Third, as a methodological contribution, we introduce fsQCA, overcoming the shortcomings of turnaround strategy research with case and regression analysis and breaking through the paradigm of “specific factor-turnaround.”

Organizational turnaround is a systematic process that constitutes multiple factors together. When organizations take the asset retrenchment to stop bleeding, reducing the executive-employee compensation gap will help enhance employee's cognition of organizational values and strategic goals, eliminate feelings of exploitation in retrenchment implementation and thus effectively promote turnaround. This paper also provides a basis for executive compensation restrictions and re-examines pay dispersion and economic inequality.

This study sheds some light on the importance of the executive-employee compensation gap in retrenchment strategy and contributes to both organizational turnaround and pay dispersion theories. Also, it reveals the theoretical linkage between internal stakeholders, organizational resilience and long-term orientation.

Customer knowledge from social media can become an important organizational asset. The purpose of this paper is to identify useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers from social media data and facilitate social media-based customer knowledge management.

The authors conducted a case study to analyze people’s online discussion on Twitter regarding laptop brands and manufacturers. After collecting relevant tweets using Twitter search APIs, the authors applied statistical analysis, text mining and sentiment analysis techniques to analyze the social media data set and visualize relevant insights and patterns in order to identify customer knowledge.

The paper identifies useful insights and knowledge from customers and knowledge about customers from social media data. Furthermore, the paper shows how the authors can use knowledge from customers and knowledge about customers to help companies develop knowledge for customers.

This is an original social media analytics study that discusses how to transform large-scale social media data into useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers.

Online customer reviews could shed light into their experience, opinions, feelings, and concerns. To gain valuable knowledge about customers, it becomes increasingly important for businesses to collect, monitor, analyze, summarize, and visualize online customer reviews posted on social media platforms such as online forums. However, analyzing social media data is challenging due to the vast increase of social media data. The purpose of this paper is to present an approach of using natural language preprocessing, text mining and sentiment analysis techniques to analyze online customer reviews related to various hotels through a case study.

This paper presents a tested approach of using natural language preprocessing, text mining, and sentiment analysis techniques to analyze online textual content. The value of the proposed approach was demonstrated through a case study using online hotel reviews.

The study found that the overall review star rating correlates pretty well with the sentiment scores for both the title and the full content of the online customer review. The case study also revealed that both extremely satisfied and extremely dissatisfied hotel customers share a common interest in the five categories: food, location, rooms, service, and staff.

This study analyzed the online reviews from English-speaking hotel customers in China to understand their preferred hotel attributes, main concerns or demands. This study also provides a feasible approach and a case study as an example to help enterprises more effectively apply social media analytics in practice.

To investigate the key sources of competitive advantage gained from e‐business applications by Chinese real estate developers and whether the value chain theory and its related theories can explain this phenomenon.

A key issue in e‐business is how established companies can gain competitive advantage. Despite the interest in e‐business applications, few empirical studies have been carried out to look at how “clicks‐and‐mortar” approaches offer competitive advantages, especially from specific industry perspectives. By using a qualitative case study approach this study addresses this.

The study shows that the value chain framework is useful to identify and categorize possible e‐business application areas. Moreover, this categorization makes identification of key sources of competitive advantage explicit. However, this framework cannot fully explain the success of e‐business applications nor the realization of intended motivations.

Further research is needed to make the value chain model become an easily‐used, practical guideline for e‐business implementation. This study has focussed on one specific industry within China (centre on real estate) so generalisation to other industries is limited at this stage. Similar research in other sectors will go a long way to addressing this.

Offers organizations a theoretical framework which helps to support the identification of appropriate e‐business applications. Furthermore, it closes the gap between strategic direction and subsequent system implementation.

This paper provides empirical evidence of how established organizations gain competitive advantage through their e‐business applications. Furthermore, it offers insight into how value chain theory helps to explain this phenomenon within the context of ongoing changes within the Chinese economy.