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Given the growing preference for internet celebrity restaurants, it is crucial to explore how internet celebrity restaurants can maintain customer loyalty. Therefore, this study aims to examine the connections between brand cognition [emotion value, brand symbol (BS) and brand experience (BE)], brand resonance (BR) and revisit intention.

In this paper, the authors use a theoretical model to test the relationship between cognition and intention. A total of 366 volunteers were recruited to participate in this research. Hypothesis testing and a moderated mediation model were used to measure the results.

BR acts as a mediator in the interaction between emotion value, BS, experience and repurchase intention (RI). Surprisingly, the authors also discover that electronic word-of-mouth (e-WOM) acceptance negatively modifies the relationship between brand cognition and BR. Internet exposure (IE) helps consumers perceive BE and BSs more favorably.

Managers should be aware of how internet celebrity BR is built. Specifically, they can use cultural or emotional elements to maintain relationships with consumers. Furthermore, to lessen the negative consequences of e-WOM, managers should work to maintain positive WOM consistency.

The research advances our knowledge of RI in internet celebrity restaurants settings. This study pioneers an investigation of how brand cognition is related to RI through BR’s mediating effect. It enriches this research perspective of the emerging restaurant literature. By analyzing the boundary impact of internet transmission on resonance, it also advances the literature.

The purpose of this paper is to improve the robustness of the traditional Bhattacharyya metric for the effect of histogram quantization in the histogram-based visual tracking. However, the traditional Bhattacharyya metric neglects the correlation of crossing-bin and is not robust for the effect of histogram quantization.

In this paper, the authors propose a visual tracking method via crossing-bin histogram Bhattacharyya similarity in the particle filter.

A crossing-bin matrix is introduced into the traditional Bhattacharyya similarity for measuring the reference histogram and the candidate histogram, and the basic tasks of measure such as maximum similarity of self and the triangle inequality are proven. The authors use the proposed measure in the particle filter visual tracking framework and address a model update strategy based on the crossing-bin histogram Bhattacharyya similarity to improve the robustness of visual tracking.

In the experiments using the famous challenging benchmark sequences, precision of the proposed method increases by 12.8 per cent comparing the traditional Bhattacharyya similarity and the cost time decreases by 38 times comparing the incremental Bhattacharyya similarity. The experimental results show that the proposed method can track the object robustly and rapidly under illumination change and occlusion.

This chapter discusses key training challenges that organizations need to confront with the objective of building a robust human resource management system. Given the dynamics of the current business environment, training and development has become an indispensable function in global organizations. Building an effective human capital that contributes to continual organizational growth has become the established norm to survive in a competitive business landscape. However, the training and development function is often rendered ineffective, on account of various bottlenecks existing in the organization. Addressing these bottlenecks is quintessential in ensuring the creation of a performance-driven human capital. The goal of this chapter is to draw attention to the training impediments that hinder organizational growth and to diagnose the underlying causes for the same. This chapter concludes with recommendations that organizational decision-makers can leverage in their quest to strengthen the human capital, by utilizing their training and development infrastructure optimally.

Robot vision is a fundamental device for human–robot interaction and robot complex tasks. In this paper, the authors aim to use Kinect and propose a feature graph fusion (FGF) for robot recognition.

The feature fusion utilizes red green blue (RGB) and depth information to construct fused feature from Kinect. FGF involves multi-Jaccard similarity to compute a robust graph and word embedding method to enhance the recognition results.

The authors also collect DUT RGB-Depth (RGB-D) face data set and a benchmark data set to evaluate the effectiveness and efficiency of this method. The experimental results illustrate that FGF is robust and effective to face and object data sets in robot applications.

The authors first utilize Jaccard similarity to construct a graph of RGB and depth images, which indicates the similarity of pair-wise images. Then, fusion feature of RGB and depth images can be computed by the Extended Jaccard Graph using word embedding method. The FGF can get better performance and efficiency in RGB-D sensor for robots.

The purpose of this study is to present the state of the art for fiber Bragg grating (FBG) acceleration sensing technologies from two aspects: the principle of the measurement dimension and the principle of the sensing configuration. Some commercial sensors have also been introduced and future work in this field has also been discussed. This paper could provide an important reference for the research community.

This review is to present the state of the art for FBG acceleration sensing technologies from two aspects: the principle of the measurement dimension (one-dimension and multi-dimension) and the principle of the sensing configuration (beam type, radial vibration type, axial vibration type and other composite structures).

The current research on developing FBG acceleration sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of a new information detection method. This paper hypothesizes that in the future, the following research trends will be strengthened: common single-mode fiber grating of the low cost and high utilization rate; high sensitivity and strength special fiber grating; multi-core fiber grating for measuring single-parameter multi-dimensional information or multi-parameter information; demodulating equipment of low cost, small volume and high sampling frequency.

The principle of the measurement dimension and principle of the sensing configuration for FBG acceleration sensors have been introduced, which could provide an important reference for the research community.

Balancing exploration and exploitation is a strategic challenge for technology-based companies striving to successfully implement ambidexterity in rapidly changing markets. This study aims to look at the extent in which corporate universities can be instrumental in the cross-functional deployment of the resources, capabilities and experience needed to achieve organizational ambidexterity.

This study is the result of a single case study of ZTE University in China. Data from archives, direct observations, and semi-open interviews have been triangulated and analyzed with pattern matching technique.

This study analyzed the development of capabilities allowing the strategic combinations of exploration and exploitation, and to clearly witness how the corporate university was dynamically linked with those development.

The empirical results offer new insights on the most relevant capabilities for technology-based companies and notably those that are more likely to be exploited through a corporate university.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

This study is intended to investigate the current status of corporate universities in China. It aims to explore the processes and practices of corporate universities in China, and discover the issues and challenges involved in building and running a corporate university in China.

The heads of 11 well‐known corporate universities in China were interviewed. In addition, documentary data were also collected to triangulate with the interview data.

Compared with best practice corporate universities worldwide, the 11 corporate universities in this study have done well in three aspects, namely, learning initiatives support strategy and business goals, strong top management support, and leaders as teachers in management training programs. What needs improvement is the lack of a training evaluation mechanism.

The findings of this study provide a reference point for, and insights into, the processes and practices associated with corporate universities, and afford an opportunity to gain a better understanding of the issues and challenges involved in building and running a corporate university in China.

This study represents one of the first attempts to understand how a corporate university model works in the Chinese context. As such, it helps enrich the literature of corporate universities.

It is now well-established that good water quality is associated with economic prosperity, reduced incidence on public health and the good functioning of the various ecosystems found in our environment. Water contamination is mostly related to both diffused (agricultural lands and geologic rock degradations) and point sources of pollution. Mauritius has many water resources which depend solely on precipitation for their replenishment. Water parameters which are of relevance include total dissolved solids (TDS), temperature, pH, electrical conductivity, turbidity, dissolved oxygen, dissolved and particulate organic carbon and major cations and anions. The traditional methods of analysis for these parameters are mostly using electrical and optical methods (probes and sensors in the field), while chemical titrations, Flame AAS and High-Performance Liquid Chromatography techniques are carried out in the laboratory. Image Classification techniques using neural networks can also be used to detect the presence of contaminants in water. In addition to basic water quality parameters, the field sensors range have been extended to cover important major ions and can now be integrated with Artificial Intelligence (AI)-based models for the prediction of variations in water quality to better protect human health and the environment, reduce operation costs of water and wastewater treatment plant unit processes.

Due to its fast growth, cross-border e-commerce (CBEC) is becoming a popular internationalization model, especially in those destination markets with impressive e-commerce development like China. However, CBEC also brings new logistics challenges and uncertainty. This paper aims to understand how companies cope with logistics uncertainty in this field and whether the different types of uncertainty influence the risk management strategies adopted to face them.

A survey targeting online exporters to China and third-party forwarding logistics service providers (3PFLs) is conducted. A structural equation model (SEM) analysis is performed to test the possible relationship between the adopted risk management strategies and the types of uncertainty. The type, industry and size of the company, as well as the distance between the company's home country and China, are used as control variables in the study. Survey results are enriched via interviews with some of the respondents.

The risk management strategies adopted are dependent on the type of logistics uncertainty that the companies face and, to a minor extent, on the industry the company operates in. Conversely, no significant influence is exerted by other types of control factors, i.e. home country, company size or company type.

The paper investigates logistics uncertainty and risk management approaches in the novel context of CBEC. A systematic review of relevant sources of uncertainty is offered to help both scholars and practitioners understand the current complexities of CBEC. From a theoretical perspective, the paper models the investigated concepts in light of the contingency approach. From a practical perspective, results can be of interest since the list of proposed items can support risk identification and evaluation while the interviews with managers can provide insights on risk management practices.