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This paper aims to establish a service efficiency-oriented framework for training design and evaluation as a pivotal service procedure in the workplace to fill the gap between training and organizational performance in a service context.

A semi-structured interview was first employed to confirm the primary indicator for training programs and criteria design as the pivotal factor for operational efficiency. An observation experiment was subsequently conducted to reveal that the training program can be redesigned according to the concrete operation effects and influencing factors for operational efficiency in the workplace.

The proposed service efficiency-oriented training model is suggested to underline and guide the activities for training requirements, training methods, training criteria and training evaluation for the service sector. Training auditing, analyzing and redesigning based on service efficiency could help to integrate service efficiency so that service organizations can readjust their specific training needs and concise the training program in the human resource management practice.

This study only conducted an on-site observational experiment on one of the casinos in Macau. An observational method assessed the conceptual model in the context of table game operations. More quantitative approaches like AI-assisted systems may be employed in the future. The representativeness of the sample is somewhat limited. In addition, the service efficiency-oriented training concept model is an open system that any organization could extend by incorporating more elements in each part that can be developed to meet their human resource management needs. Finally, other service-oriented organizations like airlines and banks can learn from the theoretical model proposed in this article. It is suggested that non-profit organizations would be a better research area.

The finding can provide organizations and practitioners with insights and tools on how to provide and evaluate service efficiency and assess employee performance.

The proposed service efficiency-oriented training model provides a theoretical foundation for training and organizational performance for service organizations.

This study is the first to develop a service efficiency-oriented training framework with training needs, methods, criteria and evaluation. A service industry sample was used to verify the framework in the context of casino game pace and dealer training for table games. Suggestions for a combination of management are provided for casino operators to redesign and evaluate the dealer training program for service improvement.

This paper explores the workplace experiences of aesthetic labour among racially diverse frontline women workers in a fashion retail store.

This qualitative study is based on an ethnographic study, drawing on findings from participant observation and interviews with frontline workers at a fashion retail store in the UK.

This paper explores how the embodiments of aesthetic labour are perpetually produced and commodified through the discipline of management in a fashion retail store. It challenges the notion of phenotypical Whiteness as the beauty standard within fashion retail and demonstrates how embodiments differ according to race. While White women are continuously scrutinised by their appearance, the aesthetic demands for women of colour tend to focus on speech and racialised bodies to provide “authentically” exotic experiences for customers. Additionally, this study highlights how the mobilisation of aesthetic labour can create work humiliation and work alienation.

Despite this study being based on an ethnographic study at one British fashion retailer, this paper seeks to give voices to an underrepresented group by exploring the lived experiences of racially diverse women workers.

This paper contributes to the intersection between aesthetic labour and race from an embodiment perspective, exploring the workplace experiences of racially diverse women workers in fashion retail and how their various forms of embodiment are racialised and commodified.

The highly uncertain and turbulent environments nowadays intensify the paradoxical effects of supply base concentration (SBC) on improving cost efficiency while increasing idiosyncratic risk (IR). Digitalization is regarded as a remedy for this paradox, yet digitization's potentially curative effect has not been empirically tested. Leveraging the lenses of paradox theory and information processing theory (IPT), this study explores how two distinct dimensions of digitalization, i.e. digitalization intensity (DI) and digitalization breadth (DB), reconcile the paradoxical effects of SBC.

Using a panel dataset of 1,238 Chinese manufacturing firms in the period of 2012–2020, this study utilizes fixed-effects regression models to test the proposed hypotheses.

The authors discover that SBC enhances a firm's cost efficiency but induces greater IR. More importantly, there is evidence that DI restrains the amplifying effect of SBC on IR. However, DB weakens the enhancing effect of SBC on cost efficiency and aggravates the SBC's exacerbating effect on IR.

This study advances the understanding of the paradoxical effects of SBC on cost efficiency and IR from a paradox theory perspective. More importantly, to the best of the authors' knowledge, the authors' study is the first to untangle the differential roles of DI and DB in reconciling the paradox of SBC. This study also provides practitioners with nuanced insights into how the practitioners should use appropriate tactics to deploy digital technologies effectively.

The purpose of this paper is to evaluate an English Proficiency (EP) programme and its efficacy with respect to students' academic performance in a university within a multi-lingual context, as the programme had been in effect for some years.

A quasi-experimental approach was used to study the efficacy of an EP programme in a university within a multilingual context. Data across two academic years were used, along with regression discontinuity design.

Results suggest that the EP programme had a significant and positive intervention effect on students' initial semester grade point average. The programme effect size was found to be medium to large.

It might be useful to extend the study for one more year for more concrete conclusions. As the study was anchored upon the structure of the 2016 EP programme, any major curricular/structural change to the programme warrants another study.

This study demonstrated that the implementation of EP programmes in higher education institutions is essential not only for international students who are foreign language speakers of English but also for domestic students in English-speaking countries, especially for bi/multilingual speakers.

Previous studies related to the efficacy of EP within higher education have focused on international students who speak English as an additional/foreign language. Further, most studies have focussed on students' self-reported experiences and have yielded disparate findings. This study contributes to scholarship as it addresses the under-researched area related to domestic students who speak English as the first language in a bi/multi-lingual context.

The purpose of this paper is to explore the role of intellectual capital (IC) in supply chain intelligence integration (SCII) and the interrelationships of the three components of IC (i.e. human capital (HC), structural capital (SC) and relational capital (RC)) in the supply chain context.

This paper conducted an empirical study by using primary data from 389 sample firms. The authors applied structural equation modeling to test the proposed hypotheses.

The results indicate that both HC and RC have direct impact on SCII, whereas SC only influences SCII through RC.

This study evidences that IC is an enabler of SCII. Furthermore, this study reveals the interrelationships of human, structural and RC.

In this study, a highly sensitive and quantitative analysis method using surface-enhanced Raman scattering (SERS)-labeled immunoassay is adopted for bisphenol A bisphenol A (BPA) detection in water samples.

Primarily, an excellent SERS immuno-nanoprobe is prepared, which relays on Au/Ag core-shell nanoparticles tagged 4-mercaptobenzoic acid (4MBA) and labeled with specific antibody against BPA. Second, the coating antigen of 4,4-Bis(4-hydroxyphenol) valeric acid (BVA) coupling poly-L-lysine (PLL) conjugate (BVA-PLL) is fastened on the substrate. Based on competitive immunoassay, the antibody labeled on SERS immuno-nanoprobe will bind with the free BPA and BVA-PLL competitively.

A calibration curve was obtained by plotting the intensity of SERS signal of 4MBA at 1007 cm⁻¹ versus the concentration of BPA. The results indicated that the limit of detection (LOD) for BPA is 1 ng/mL and present a great capacity for higher sensitivity. Furthermore, the method was able to quantitatively detect BPA in water samples, which was validated by high performance liquid chromatography (HPLC).

The method was developed based on competitive immunoassay, and the conjugate (BVA-PLL) was chosen as the coating antigen. Au/Ag core-shell nanoparticles played as the SERS active substrate and were labeled with Raman reporter. The value of this paper is supplying a wide potential for analysis of target analytes in the environmental monitoring and food safety.

The task of internet intrusion detection is to detect anomalous network connections caused by intrusive activities. There have been many intrusion detection schemes proposed, most of which apply both normal and intrusion data to construct classifiers. However, normal data and intrusion data are often seriously imbalanced because intrusive connection data are usually difficult to collect. Internet intrusion detection can be considered as a novelty detection problem, which is the identification of new or unknown data, to which a learning system has not been exposed during training. This paper aims to address this issue.

In this paper, a novelty detection‐based intrusion detection system is proposed by combining the self‐organizing map (SOM) and the kernel auto‐associator (KAA) model proposed earlier by the first author. The KAA model is a generalization of auto‐associative networks by training to recall the inputs through kernel subspace. For anomaly detection, the SOM organizes the prototypes of samples while the KAA provides data description for the normal connection patterns. The hybrid SOM/KAA model can also be applied to classify different types of attacks.

Using the KDD CUP, 1999 dataset, the performance of the proposed scheme in separating normal connection patterns from intrusive connection patterns was compared with some state‐of‐art novelty detection methods, showing marked improvements in terms of the high intrusion detection accuracy and low false positives. Simulations on the classification of attack categories also demonstrate favorable results of the accuracy, which are comparable to the entries from the KDD CUP, 1999 data mining competition.

The hybrid model of SOM and the KAA model can achieve significant results for intrusion detection.

A green innovation strategy is an important step for enterprises to balance economic and environmental. As the executors of strategic decisions, the attitude and capabilities of senior managers determine the effectiveness of implementing green innovation. Therefore, this paper aims to explore the relationship between executive compensation incentives and green innovation.

Based on the data of heavily polluting enterprises listed in China's A-share market from 2015 to 2020, this study constructs an OLS model with fixed effects of time and industry, and uses the mediation three-step method to verify the correlation between executive compensation incentives, innovation openness and green innovation. Meanwhile, the grouping regression was used to test the moderating effect of environmental regulation on executive compensation incentives.

The empirical results show that executive salary incentives promote green innovation and equity incentives inhibit green innovation; the openness breadth partially mediates the relationship between salary incentives, equity incentives and green innovation, while the openness depth only partially mediates the relationship between equity incentives and green innovation; and environmental regulation positively moderates executive incentives.

Due to sample selection and variable measurement, the study lacks certain generality. Therefore, future research needs to further analyze the internal factors affecting green innovation from multiple dimensions.

This study provides a new evidence for analyzing how executive compensation measures affect green innovation, and further enhances the mediating mechanism of open innovation.

This study has significant theoretical implications for examining the intra-firm factors that affect green innovation.

The purpose of this study is to investigate the contingencies of supply chain risk management (SCRM) in manufacturing multinational corporations (MNCs) by exploring the moderating role of international asset dispersion in the performance effect of SCRM, as well as the counteraction effect of supply chain integration (SCI).

Multi-country survey data from a sample of 378 responses collected by the sixth round International Manufacturing Strategy Survey were analyzed. Hierarchical regression analysis was conducted to test the proposed hypotheses.

The results demonstrate that SCRM improves the operational effectiveness of manufacturing MNCs but this performance effect is attenuated by international asset dispersion. Nevertheless, external integration can counteract the negative effect of international asset dispersion and ensure the efficacy of SCRM practices.

The results of this study provide suggestions for supply chain managers of manufacturing MNCs to better conduct SCRM practices under the condition of dispersed international assets. Besides, supply chain managers can leverage external integration to ensure the efficacy of SCRM practices.

Although there are plenty of studies on the relationship between SCRM and operational performance, prior findings are inconsistent. This study sheds light on the SCRM-operational performance relationship by considering how a manufacturing MNC’s international asset dispersion can influence the efficacy of SCRM practices and how SCI can attenuate the negative effect of international asset dispersion.

The present study provides a comprehensive review of the advancements in five active heating modes for cold-proof clothing as of 2021. It aims to evaluate the current state of research for each heating mode and identify their limitations. Further, the study provides insights into the optimization of intelligent temperature control algorithms and design considerations for intelligent cold-proof clothing.

This article presents a classification of active heating systems based on five different heating principles: electric heating system, solar heating system, phase-change material (PCM) heating system, chemical heating system and fluid/air heating system. The systems are analyzed and evaluated in terms of heating principle, research advancement, scientific challenges and application potential in the field of cold-proof clothing.

The rational utilization of active heating modes enhances the thermal efficiency of cold-proof clothing, resulting in enhanced cold-resistance and reduced volume and weight. Despite progress in the development of the five prevalent heating modes, particularly with regard to the improvement and advancement of heating materials, the current integration of heating systems with cold-proof clothing is limited to the torso and limbs, lacking consideration of the thermal physiological requirements of the human body. Additionally, the heating modes of each system tend to be uniform and lack differentiation to meet the varying cold protection needs of various body parts.

The effective application of multiple heating modes helps the human body to maintain a constant body temperature and thermal equilibrium in a cold environment. The research of heating mode is the basis for realizing the temperature control of cold-proof clothing and provides an effective guarantee for the future development of the intelligent algorithms for temperature control of non-uniform heating of body segments.

The integration of multiple heating modes ensures the maintenance of a constant body temperature and thermal balance for the wearer in cold environments. The research of heating modes forms the foundation for the temperature regulation of cold-proof clothing and lays the groundwork for the development of intelligent algorithms for non-uniform heating control of different body segments.

The present article systematically reviews five active heating modes suitable for use in cold-proof clothing and offers guidance for the selection of heating systems in future smart cold-proof clothing. Furthermore, the findings of this research provide a basis for future research on non-uniform heating modes that are aligned with the thermal physiological needs of the human body, thus contributing to the development of cold-proof clothing that is better suited to meet the thermal needs of the human body.