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Endorsement marketing has been widely used to generate consumer attention, interest and purchase decisions among targeted audiences. Internet celebrities who become famous on the Internet are dependent on strategic intimacy to appeal to their followers. Our study aims to examine how multiple exposures to Internet celebrity endorsements influence consumers’ click and purchase decisions in the context of influencer marketing.

Based on a unique and representative dataset, the authors first model consumers’ choices for clicks and purchases with two panel fixed-effect logit models linking clicks and purchases with the frequency of exposure to Internet celebrity endorsement. To further control the endogeneity produced by the intercorrelation between the click and purchase models, the authors also adopt the two-stage Heckman probit structure to jointly estimate the two models using Maximum Likelihood Estimation. Robustness checks confirm the effectiveness of the models.

The results suggest that Internet celebrity endorsement plays a significant role in bringing referral traffic to e-commerce sites but is less helpful in affecting conversion to sales. The impact of repetitive Internet celebrity endorsements on consumers’ click decisions is U-shaped, but the role of Internet celebrities as online retailers will “shape-flip” this relationship to a negative linear relation.

Our study is the first to investigate the repetitive exposure effect of Internet celebrity endorsement. The results show a contradictory pattern with a wear-out effect of repetition in the advertising literature. This is the first study to show how the endorsing self, which is a common business model in influencer marketing, moderates the effectiveness of influencer marketing.

The metaverse has garnered increasing attention from researchers and practitioners, yet numerous firms remain hesitant to invest in it due to ongoing debates about its potential financial benefits. Therefore, it is crucial to analyze how the implementation of metaverse initiatives affects firms’ stock market value – an area that remains underexplored in the existing literature. Additionally, there is a significant lack of research on the contingency factors that shape the stock market reaction, leaving a noticeable gap in managerial guidance on the timing and benefits of investments in the metaverse. To narrow these gaps, we examine whether and when the implementation of metaverse initiatives enhances firms’ stock market value.

Based on 73 metaverse implementation announcements disclosed by Chinese listed firms during January 2021–August 2023, we employ an event study approach to test the hypotheses.

We find that metaverse implementation announcements elicit a positive stock market reaction. Moreover, the stock market reaction is stronger for technology-focused announcements and smaller firms, or when public attention to the metaverse is higher. Nevertheless, firms’ growth prospects do not significantly alter the stock market reaction.

This study extends the nascent literature on the metaverse by applying signaling theory to offer novel insights into the signaling effect of metaverse implementation announcements on stock market value and the boundary conditions under which the effectiveness of the signal varies. Besides, it provides managers with important implications regarding how to tailor the investment and information disclosure strategies of the metaverse to more effectively enhance firms’ stock market value.

With the popularity of social media and, recently, live streaming, internet celebrity endorsements have become a prevalent approach to content marketing for e-commerce sellers. Despite the widespread use of social media and online communities, empirical studies investigating the economic value of user-generated content (UGC) and marketer-generated content (MGC) still lag behind. The purpose of this paper is to contribute both theoretically and practically to capture both first-order effects and second-order effects of internet celebrity endorsements on marketing outcomes in an e-commerce context.

This study conducts a cross-sectional regression to evaluate the economic value of internet celebrity endorsement, and a panel vector autoregressive model is adopted to examine the relationship between celebrities’ and consumers’ content marketing behaviors and e-commerce sales performance. The authors also adopt look-ahead propensity-score matching technique to correct for selection bias.

The empirical results show that the content generation efforts of marketers and the interaction behaviors between marketers and consumers will significantly influence the e-commerce sales, which refers to the first-order effects of internet celebrity endorsement. Moreover, interactions within the fan community exert second-order effects of content marketing on sales performance.

This paper provides new insights for e-commerce retailers to evaluate the economic values of internet celebrity endorsement, a new content marketing practice in e-commerce platform.

This paper aims to study the influence of the different parameters of magnetorheological polishing fluids (MRP fluids) on the surface roughness and material removal rate (MRR) of the workpiece surface in the reciprocating magnetorheological polishing (RMRP) process.

A series of single-factor experiments are performed to evaluate the influence of the concentration of magnetic particles, concentration of abrasive particles and size of abrasive particles on surface processing effects by using the RMRP method. Moreover, the yield stress and viscosity of MRP fluids are studied based on the Bingham plastic model by varying the MRP fluids parameters.

A reasonable parameter of MRP fluids is crucial to the surface roughness and MRR of the workpiece surface, and the optimized parameters are obtained by the single-factor experiments of RMRP. The results are when the concentration of carbonyl iron particles is 40 Vol.%, the concentration of CeO₂ is 5 Vol.% and the size of CeO₂ is 2.5 µm in the MRP fluids, the surface roughness of the workpiece remarkably decreases to 28 nm from the initial 332 nm and the MRR of the workpiece increases to 0.118 mg/min.

In this study, the single-factor experiments for the different parameters of MRP fluids are studied to polish K9 glass by using the RMRP device, and the yield stress and viscosity of MRP fluids are investigated by rheological experiments, which provides reference for a reasonable selection of the MRP fluids parameter in RMRP process.

This paper aims to study the effects of the processing parameters in the reciprocating magnetorheological polishing (RMRP) on abrasive particle trajectory by the simulation analysis, which provides a basis for the machining uniformity of the workpiece.

The principle of the RMRP method is discussed, and a series of simulation analysis of the abrasive particle trajectory are performed to evaluate the effects of the workpiece’s rotational speed, the eccentric wheel’s rotational speed, the eccentricity and the frame gap on abrasive particle trajectory by using the RMRP method.

The processing parameters have a significant influence on the abrasive particle trajectory, and then the machining uniformity of the workpiece is affected. Under certain experimental conditions, the height difference of workpiece measuring points varies between 4 and 11 µm, and the height difference of equal radial measuring points is less than 1.5 µm by optimizing processing parameters.

In this study, the optimal processing parameters can be obtained by the simulation analysis of abrasive particle trajectory, which can replace the experimental methods to obtain the reasonable processing parameters for the machining uniformity of the workpiece. It provides references for the selection of processing parameter values in magnetorheological polishing process.

This paper aims to study the effects of the different processing parameters in the reciprocating magnetorheological polishing (RMRP) on the surface roughness (Ra) and material removal rate (MRR) of the workpiece surface.

The principle of RMRP method is discussed, and a series of the single factor experiments are performed to evaluate the effects of the workpiece’s rotational speed, the reciprocating frequency, the magnetic field strength, the working gap and the processing time on machining results using the RMRP device.

The RMRP method is effective and practical for K9 glass polishing, and the optimized processing parameters are obtained by the single factor experiments of RMRP. The surface roughness of the workpiece is reduced from 332 nm to 28 nm under optimized processing parameters.

In the present study, the RMRP method is proposed, and a system of experiments is carried out using the RMRP device. The RMRP device can improve the surface roughness and MRR of the K9 glass significantly. Furthermore, the test results provide references for reasonable selection of the processing parameters in magnetorheological polishing process.

This paper aims to analyze the significance of machining parameters (workpiece’s rotational speed, magnet coil current and working gap) on final Ra (surface roughness) and material removal rate (MRR) of workpiece in reciprocating magnetorheological polishing (RMRP) process.

The research is planned to analyze, model and predict the optimum machining parameters to anticipate final Ra and MRR by applying response surface methodology (RSM) and multiresponse optimization (desirability function approach). The experiments have been planned by design of experiments (DOE). Analysis of variance (ANOVA) is applied to determine the significances of machining parameters on RMRP performance characteristics.

Response surface plots for final Ra and MRR by RSM show that machining parameters are significant for the responses. The optimum machining parameters obtained are optimized by desirability function approach (DFA), and the optimum parametric combination has been validated by confirmatory experiments. The experimental results of the final Ra and MRR are deviated by 5.12% and 2.31% from the response results under the same optimization conditions, respectively.

In this study, the RMRP responses (final Ra and MRR) are improved at predicted input machining parameters condition obtained by RSM and DFA approach. Furthermore, the research results provide a reference for experimental design and optimization of MRP process.

Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this engineering problem. Without the restriction of skin effect, remote field eddy current (RFEC) overcomes the interference caused by the damping coating. The RFEC, which has potential advantages for detecting the hidden defects of aluminum plate with damping coating, can penetrate the metal plate to detect buried depth defects. This study aims to test how thick the RFEC sensor can penetrate the metal plate to detect the buried defects.

The magnetic field distribution characteristics are analyzed, the magnetic field intensity distribution is calculated, and the structure and parameters of the coil, magnetic circuit and shielding damping are determined through the two- and three-dimensional finite element simulation methods. Optimal excitation frequency is obtained, and the distance between the excitation coil and detection coil is determined by analyzing the relationship between excitation frequency and remote field points.

Simulation and experimental results verify the feasibility of applying the RFEC detection technology in detecting the hidden defects of aluminum alloy plate with damping coating.

In this paper, the RFEC testing model of hidden defects in aluminum plate sample with damping coating is established by using the finite element method.

This study aims to explore the impact of key parameters of brake pads on the dynamic characteristics of the braking system.

This study conducted experimental research based on a friction testing machine with a slider-disc structure. The experiment studied the impact of key parameters of brake pads (rotation speed, pressure, mass, braking radius, etc.) and the braking environment (dry friction, wetness, sand, etc.) on the stability of the braking system. At the same time, a dynamic model of the brake pad braking system was established and compared with experimental results using the mathematical tool of autocorrelation coefficient.

The key parameters of brake pads have a significant impact on the dynamic characteristics of the braking system; under different conditions of brake pad mass, tribological parameters, brake pad radius and braking environment, the chaotic characteristics of the braking friction force signal show a trend of expansion or contraction, which can be suppressed by adjusting the key parameters of brake pads.

This study can provide a reference for optimizing the braking strategy and reducing noise and vibration in brake pad systems.

To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.