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Based on the dynamic capability theory, our study tries to explore the mediator mechanism of service supply chain dynamic capability between market orientation and service innovation performance, as well as the boundary conditions in which service supply chain dynamic capability plays a role, in order to reveal the key elements and their mechanisms for manufacturing enterprises to improve service performance.

With a total of 317 valid questionnaires, structural equation modeling (SEM) was used to test the research model and hypotheses.

The empirical results confirm that the three types of service supply chain dynamic capability (environment insight capability, resource integration capability and resource reconfiguration capability) can partially mediate the relationship between firm market orientation (responsive and proactive market orientations) and service innovation performance. In addition, supply chain collaboration has different types of moderator effects on the relationship between the three types of service supply chain dynamic capability and service innovation performance.

This research discovers that market orientation and dynamic capability are the key factors leading to high service performance and reveals the mediating role of service supply chain dynamic capability between market orientation and service innovation performance. Moreover, this research explores the moderating role of supply chain collaboration in service supply chain resource reconfiguration capability and service innovation performance.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI.

Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM.

Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices.

Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM.

Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.

The purpose of this study is to investigate the influence mechanism of different interface component surface textures on the ultrasonic motor (USM) output performance.

The energy transmission mechanism of the traveling-wave ultrasonic motor 60 (TRUM-60) was numerically and experimentally investigated by fabricating dimple textures with different feature types on the friction material and the stator.

Textured friction material can increase the contact range effectively, and thus, can improve the friction characteristics of the interface and the output performance of the TRUM-60. The experimental results verified the expected influence mechanism and demonstrated that the use of either a textured friction material or stator has a very different effect on USM output performance. A textured PI-based friction material improved the TRUM-60 output performance, resulting in a maximum energy conversion efficiency of 57.11%. However, a textured stator degraded the TRUM-60 output performance, resulting in a minimum energy conversion efficiency of only 44.92%.

The results of this study provide a theoretical foundation for improved USM designs with textured interfaces.

The purpose of this paper is to investigate whether ex ante board connections and director retention result in agency costs to target company shareholders in the form of reduced payment in mergers and acquisitions transaction.

The authors employ detailed data of ex ante board connection and director retention in the mergers and acquisition in the UK from 1999 to 2015. Ex ante board connections are measured as proportion of target and acquirer companies’ directors worked on the same board at any time prior to the takeover, while director retention is measured as proportion of target companies’ directors remains on board after the takeover is completed. For mergers and acquisition payment characteristics, the authors examine takeover premium, cash payment percentage and offer price adjustment.

The authors find that ex ante board connections and director retention lead to reduced offer prices and lower proportions of cash payment. Notably, when there is no connection and target directors are not retained, the authors find that the bidding companies increase their final offer by £14m more than in other scenarios. The authors also document strong evidence that ex ante board connections lead to a higher probability of director retention.

The paper highlights that ex ante board connections and director retention will lead to a significant cost on target company shareholders. The authors recommend that a more detailed set of information on ex ante board connections and intended target board retention should be disclosed.

This study aims to prepare a low-formaldehyde and environmentally friendly glucose-lignin-based phenolic resin.

The authors directly used lignin to substitute formaldehyde to prepare lignin-based phenolic resin (LPF) with urea as formaldehyde absorbent. To improve the performance of the adhesive, the biobased glucose was introduced and the modified glucose-LPF (GLPF) was obtained.

The results showed that when the replacing amount of lignin to formaldehyde reached 15 Wt.%, the physical properties of the prepared LPF met the Chinese national standard, and the bonding strength increased by 21.9%, from 0.75 to 0.96 MPa, compared with PF. The addition of glucose boost the performance of wood adhesive, for example, the free phenol content of the obtained GLPF was significantly reduced by 79.11%, from 5.60% to 1.17%, the bonding strength (1.19 MPa) of GLPF increased by 19.3% in comparison to LPF and the curing temperature of GLPF decreased by 13.08%.

The low-formaldehyde and environmentally friendly GLPF has higher bonding strength and lower curing temperature, which is profitable to industrial application.

The prepared GLPF has lower free formaldehyde and formaldehyde emission, which is cost-effective and beneficial to human health.

The joint work of lignin and glucose provides the wood adhesive with increased bonding strength, decreased free phenol content and reduced curing temperature.

This paper aims to investigate the effect of frictional materials and surface texture on the energy conversion efficiency and the mechanical output performance of the ultrasonic motor (USM).

A newly designed testing system was set up to measure the mechanical output performance of the USM. The influence of different frictional materials on the output performance of the USM was studied under the same assembly process and parameters. The surface texture was fabricated by laser ablation processing. The effects of surface texture and input parameters on the energy conversion efficiency and mechanical output performance of the USM were studied.

The results show that polyimide (PI) composites as frictional material can significantly improve the output performance of the USM compared to polytetrafluoroethylene (PTFE) composites. When the pre-load is 240 N, the energy conversion efficiency of the USM using textured PI composites as frictional material can reach 41.93 per cent, increased by 29.21 per cent compared to PTFE composites, and the effective output range of the USM is increased to 0.7-1.1 N m. Besides, the pre-load and surface texture have a great influence on the output performance of the USM.

PI composites can improve the mechanical output performance of the USM. Surface texture can also improve the interface tribological properties and the energy conversion efficiency based on the advanced frictional materials, which will contribute to the increment of the output performance of the USM under the same input conditions.

Dyadic interactions are significant for human life. Most body sensor networks-based research studies focus on daily actions, but few works have been done to recognize affective actions during interactions. The purpose of this paper is to analyze and recognize affective actions collected from dyadic interactions.

A framework that combines hidden Markov models (HMMs) and k-nearest neighbor (kNN) using Fisher kernel learning is presented in this paper. Furthermore, different features are considered according to the interaction situations (positive situation and negative situation).

Three experiments are conducted in this paper. Experimental results demonstrate that the proposed Fisher kernel learning-based framework outperforms methods using Fisher kernel-based approach, using only HMMs and kNN.

The research may help to facilitate nonverbal communication. Moreover, it is important to equip social robots and animated agents with affective communication abilities.

The presented framework may gain strengths from both generative and discriminative models. Further, different features are considered based on the interaction situations.

Aiming at improving the mechanical efficiency, the applicability and the working life of high water-based hydraulic motor (HWBHM) under working conditions at low speed and high pressure, the friction performance of different matching materials for piston slipper – crankshaft pair with high water-based hydraulic fluid (HWBHF) under working conditions at low speed and high pressure – were studied.

The friction experiments for different materials (316L, 316L with surface coating OVINO – tetrahedral amorphous carbon [TAC; 316L-TAC] – 316L with surface coating OVINO-graphite intercalated compound [GIC; 316L-GIC] and polyetheretherketone [PEEK] reinforced with 30 per cent carbon fiber [PEEK-30CF]) under HWBHF lubrication were implemented on a pin-disk friction abrasion machine to determine the variations of coefficient of friction (CoF) and wear rate for each matching materials. In addition, the roughness and the morphology of worn surface of different matching materials were quantitatively characterized.

The study revealed that material combinations have different friction performances. Test results showed that the abrasion of matching type stainless steel (SS) and SS is rather serious, and the method of surface coating could improve the friction performance of SS when friction with other materials. For matching type of SS with surface treatment (SS-ST) and SS-ST, 316L-GIC and 316L-GIC have relatively stable CoF, and the wear rate was smaller than other matching materials, while 316L-TAC and 316L-TAC has the smaller CoF than that of 316L-GIC. Matching materials 316L-GIC with PEEK-30CF of matching type SS-ST and PEEK-30CF has more stable COF and better wear resistance than those of other matching materials.

This research has laid a foundation for the improvement of service life and working efficiency of friction pair in HWBHM under working conditions at low speed and high pressure.

The purpose of this paper is to review the major systemic educational reforms that China has undertaken over the past three decades and analyze the reasons behind their different degrees of success.

Two running themes are identified among various reforms on the Chinese educational system: decentralization and marketization. The authors explore the driving forces behind these reforms and discuss whether the reforms were successful or not.

In conclusion, the authors highlight four takeaway lessons of Chinese educational reforms.

This is an original discussion of educational reforms in China in the contexts of decentralization and marketization.