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The purpose of this paper is to design an automatic press-fit instrument to realize precision assembly and connection quality assessment of a small interference fitting parts, armature.

In this paper, an automatic press-fit instrument was developed for the technical problems of reliable clamping and positioning of the armature, automatic measurement and adjustment of the attitude and evaluation of the connection quality. To compensate for the installation error of the equipment, corresponding calibration method was proposed for each module of the instrument. Assembly strategies of axial displacement and perpendicularity were also proposed to ensure the assembly accuracy. A theoretical model was built to calculate the resistant force generated by the non-contact regions and then combined with the thick-walled cylinder theory to predict the press-fit curve.

The calibration method and assembly strategy proposed in this paper enable the press-fit instrument to achieve good alignment and assembly accuracy. A reasonable range of press-fit curve obtained from theoretical model can achieve the connection quality assessment.

This instrument has been used in an armature assembly project. The practical results show that this instrument can assemble the armature components with complex structures automatically, accurately, in high-efficiency and in high quality.

This paper provides a technical method to improve the assembly quality of small precision interference fitting parts and provides certain methodological guidelines for precision peg-in-hole assembly.

This paper aims to explore the matching effect of hospitality brand image (cool vs non-cool) and service agents (Artificial intelligence [AI] vs human staff) on brand attitude, with a focus on assessing the role of feeling right as a mediator and service failure as a moderator.

This paper tested the hypotheses through three experiments and a Supplementary Material experiment, which collectively involved 835 participants.

The results indicated that the adoption of AI by cool brands can foster the right feeling and enhance consumers’ positive brand attitudes. In contrast, employing human staff did not lead to improved brand attitudes toward non-cool brands. Furthermore, the study found that service failure moderated the matching effect between service agents and cool brand images on brand attitude. The matching effect was observed under successful service conditions, but it disappeared when service failure occurred.

The findings offer practical guidance for hospitality companies in choosing service agents based on brand image. Cool brands can swiftly transition to AI, reinforcing their modern, cutting-edge image. Traditional brands may delay AI adoption or integrate it strategically with human staff.

To the best of the authors’ knowledge, this paper represents one of the first studies to address the issue of selecting the optimal service agent based on hospitality brand image. More importantly, it introduces the concept of a cool hospitality brand image as a boundary condition in the framework of AI research, providing novel insights into consumers’ ambivalent responses to AI observed in previous studies.

The purpose of this study is to empirically examine the effects of the numerical cues (NC) used in online review comments on perceived review helpfulness and the underlying psychological mechanisms.

An experimental design approach was employed to investigate the proposed research questions. Two experiments were conducted to test the hypotheses. Mplus 7 and Stata 14.0 were used for data analysis.

Empirical findings support the positive correlation between the presence of NC in online review comments and perceived review helpfulness across different product categories. This relationship is mediated by two psychological responses of consumers: cognitive elaboration and credibility perception.

This research adds to the existing literature by focusing on the value of NC in online review comments and how they can enhance perceived review helpfulness. Some practical implications are also addressed. For example, marketers can encourage consumers to post reviews that contain quantitative information to facilitate their target markets' comprehension of a product or brand.

Building on the previous literature, the work adds incremental knowledge on the role NC in online review comments play in affecting consumers' perceptions. In addition, the research uncovers the underlying psychological responses that mediate the relationship between NC in review comments and perceived review helpfulness.

The purpose of this paper is to construct an integrated theoretical framework of firm resilience, and examine the relationship between resource reconfiguration, firm resilience, disruption impact, profit growth, innovation and environmental uncertainty in the context of COVID-19.

A survey was distributed to 220 companies and a total of 207 respondents returned the survey. chief executive officer (CEO) and chief financial officer (CFO) of each company participants in the survey. The hypotheses are tested using structural equation modeling (SEM) technique.

The results showed that firm resilience can be stimulated through the reconstruction of existing resources, and environmental uncertainty played a moderating role in this process; in turn, the improvement of firm resilience enabled companies to reduce the impact of disruptions, achieve profit growth and promote innovation.

This study provides practical implications for how business management shapes firm resilience and promotes organization recovery and development.

This study expands the literature of firm resilience by providing an integrated theoretical framework of firm resilience. Firstly, based on the perspective of dynamic capabilities, this study reveals that resource reconfiguration plays a key role in shaping firm resilience. Secondly, this study enriches the boundary research on firm resilience by incorporating environmental uncertainty into the research framework. Thirdly, this study validates the impact of firm resilience on disruption impact, profit growth and innovation of companies, providing sufficient empirical evidence for the outcomes of firm resilience.

Reviews the latest management developments across the globe and pinpoints practical implications from cutting‐edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Those who say branding is “only a name” are missing the point. An effective, recognizable brand can be a wondrous thing. But there are hazards ahead for marketers seeking to make their product brand immediately recognized – and trusted – in a global economy.

Provides strategic insights and practical thinking that have influenced some of the world's leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy‐to digest format.

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

With frequent floods occurring, and the fast economic development in China, attention must be paid to flood prevention, water supply, and forecasting precision. In particular, mid‐ and long‐term runoff prediction is being paid more and more attention by researchers, and it is also the most difficult problem to solve. The purpose of this paper is to apply chaos phase space theory to forecast river run off.

Because the hydrologic system is a complicated huge system, there exist high non‐linear characteristics in the space‐time change of hydrologic factors. According to theory of chaotic phase space, the paper established four models of the single‐point, multi‐point, lineal, and three‐parameter D(m,τ,k) models, they have stronger non‐linear mapping function and much more information in the time series than traditional ways.

The results of calculation show that the models are highly effective and worthy of popularization and application. It is reasonable and superior to use these models in mid‐ and long‐term hydrologic prediction.

The method cannot reduce or eliminate the un‐prediction parts caused by the inner random factors, such as the noise information of the observed data.

The models are applied in the long‐term runoff prediction of Baishan reservoir.

The new approach of hydrology forecasting due to the theory of chaotic phase space. The paper is aimed at hydrology forecasting researches and engineers, especially those who dealt with the mid‐ and long‐term prediction.

This chapter investigates the impact of the COVID-19 pandemic on economic stimulus policies. Based on data from 156 economies, empirical results show that in the medium term, cumulative effect of COVID-19 pandemic is positively correlated with the economic stimulus policies but not in the short term. Heterogeneity tests show that while economic policies are used in developed economies more often, restrictive measures in developing countries are likely used as a substitution; deaths have a positive impact on economic stimulus policies but confirmed cases not. The results suggest that the pandemic may reinforce economic inequality due to potential stimulus policy capabilities, requiring international coordination and assistance to low-and-middle income countries in various aspects.

This paper aims to study the oxidation kinetics of the nanocrystalline Al ultrathin films. The influence of structure and composition evolution during thermal oxidation will be observed. The reason for the change in the oxidation activation energy on increasing the oxidation temperature will be discussed.

Al thin films are deposited on the silicon wafers as substrates by vacuumed thermal evaporation under the base pressure of 2 × 10⁻⁴ Pa, where the substrates are not heated. A crystalline quartz sensor is used to monitor the film thickness. The film thickness varies in the range from 30 to 100 nm. To keep the silicon substrate from oxidation during thermal oxidation of the Al film, a 50-nm gold film was deposited on the back side of silicon substrate. Isothermal oxidation studies of the Al film were carried out in air to assess the oxidation kinetics at 400-600°C.

The activation energy is positive and low for the low temperature oxidation, but it becomes apparently negative at higher temperatures. The oxide grains are nano-sized, and γ-Al₂O₃ crystals are formed at above 500°C. In light of the model by Davies, the grain boundary diffusion is believed to be the reason for the logarithmic oxidation rate rule. The negative activation energy at higher temperatures is apparent, which comes from the decline of diffusion paths due to the formation of the γ-Al₂O₃ crystals.

It is found that the oxidation kinetics of nanocrystalline Al thin films in air at 400-600°C follows the logarithmic law, and this logarithmic oxidation rate law is related to the grain boundary diffusion. The negative activation energies in the higher temperature range can be attributed to the formation of γ-Al₂O₃ crystal.

The study tests a model that considers online brand trust in different nonbrand-owned touchpoints as a multifactorial construct constituted by: social network influencers, bloggers, online retail platforms and brand-related user generated content. Furthermore, it examines the influences that offline and online brand trust exert on consumer buying intention.

A convenience sample of 3,335 total individuals participated in the survey. Structural equation modelling was used to test the hypotheses.

Online brand trust is significantly influenced by trust in all investigated nonbrand-owned touchpoints. Both offline and online brand trust positively influence buying intention.

Whereas brand trust is considered a multidimensional construct that includes both cognitive and affective aspects, in addition to individuals' personality traits, the present study only investigated the rational dimension of the brand trust paradigm. Moreover, this study examined the influence of brand trust on consumers' buying intention and not overt behavior. In addition, even though the extant literature suggests that the relation between trust and behavioral outcomes may vary across cultures, no test of the possible influences that culture exerted on brand trust and BInt was run. Finally, given the convenience sampling method used in this research, statistically significant surveys would provide a more solid basis for the investigated phenomenon, and they would enable an appropriate generalization of the findings.

To build brand trust and favour buying intention, marketers should monitor and influence the online touchpoints that are partially under or totally out of their control, and reconceive and manage physical stores.

This paper contributes to the stream of literature on online brand trust by proving that it is a multifactorial construct resulting from trust in different non-proprietary online entities and pointing out the prevalent role that physical stores play in shaping consumer buying intention. It also indicates that a trust transfer effect takes place between different online information sources and offline outlets.