This paper presents the quality factor improvement of the micromachined suspended inductors and their usage in a fully integrated 0.18-μm CMOS microwave amplifier. Removing the lossy silicon substrate underneath the spiral inductors by adopting post-CMOS compatible microelectromechanical system (MEMS) technology allows construction of suspended structures with a high Q-factor. Although micromachining technology has had a remarkable impact on industries in recent years, it is still challenging to design fully integrated CMOS-MEMS active circuits at microwave frequencies. To evaluate the performance improvement of 0.18-μm CMOS microwave amplifiers by using micromachined suspended inductors, two amplifiers in the 24-GHz industrial, scientific, and medical band were designed and fabricated with and without the MEMS process for comparison. At 0.85-V low supply voltage, the measured peak gain of the microwave amplifier can be significantly increased from 12.3 to 13.7dB due to the high Q-factor suspended inductors. In addition, the measured noise figure of the 24-GHz microwave amplifier is effectively improved from 5.8 to 5.0dB. Theories for predicting the gain and noise figure improvement are also presented, and the mechanisms are validated by experiments. Also, a proposed simplified double-π micromachined inductor model considering the skin effect is introduced and characterized.

As an important tool for loading, unloading, and distributing palletized goods, forklifts are widely used in different links of industrial production process. However, due to the rapid increase in the types and quantities of goods, item statistics have become a major bottleneck in production. Based on machine vision, the paper proposes a method to count the amount of goods loaded and unloaded within the working time limit to analyze the efficiency of the forklift. The proposed method includes the data preprocessing section and the object detection section. In the data preprocessing section, through operations such as framing and clustering the collected video data and using the improved image hash algorithm to remove similar images, a new dataset of forklift goods was built. In the object detection section, the attention mechanism and the replacement network layer were used to improve the performance of YOLOv5. The experimented results showed that, compared with the original YOLOv5 model, the improved model is lighter in size and faster in detection speed without loss of detection precision, which could also meet the requirements for real-time statistics on the operation efficiency of forklifts.

Purchase intention and decision turn out to be the research hotspots in the field of consumer behavior, whereas the reasons for consumer hesitation before purchase have been scarcely investigated. In order to explore the factors that affect consumers’ online purchase hesitation in the context of e-commerce retail, this study uses the theory of perceived risk to analyze how different dimensions of perceived risk dominated by consumer trust affect consumers’ purchase hesitation at the checkout stage, examines the moderating effect of consumers’ online shopping experience on the influencing process, and builds a test model with moderating variables. In this study, the factors for purchase hesitation are empirically analyzed using the methods of literature analysis and logistic regression based on the real transaction data from Taobao. The results show that seller credit rating, representing seller risk, exerts a significant adverse effect on purchase hesitation, whereas the order amount (i.e. financial risk, and price dispersion, representing product risk) positively affects purchase hesitation. The consumer experience plays a moderating role in the above process. In addition, this article further explores the heterogeneous role of buyer’s device, seller’s platform, and buyer’s gender and excludes some of the interfering factors that lead to involuntary hesitation. JEL Classification: M31, M37

Implementing green transition with high quality has been confirmed as a critical approach to achieve sustainable development worldwide. This study focuses on how “Internet plus” affects the green transition of manufacturing companies. Based on the research sample of A-share-listed manufacturing companies from 2015 to 2020, the study concludes that “Internet plus” can significantly improve green transition, and the reliability of the above results is confirmed through endogeneity analysis and robustness tests. The result of the heterogeneity analysis suggests that “Internet plus” has a more significant promotion effect on state-owned companies, eastern regions, and high-tech industries. The result of the in-depth analysis indicates that “Internet plus” can contribute to green transition by boosting green innovation. In addition, environmental regulation and sewage fee-to-tax have significant positive effects in regulating the above relationships, further confirming that the enactment of the Environmental Protection Tax increases the regulating effect. This study provides a new theoretical framework for the intrinsic mechanism of “Internet plus” affecting the green transition of manufacturing companies.

With the development of artificial intelligence and machine learning technology, online shopping is increasingly becoming the mainstream shopping method. It is challenging to investigate the correlation between price dispersion and bargaining. In accordance with the assimilation‐contrast theory, this study theorizes about the influence of price dispersion on consumers’ bargaining power and it aims to analyze the moderating role of online shopping experience of consumers. Therefore, this paper develops a discrete price model to measure the dispersion of product prices in the marketplace. Cluster analysis was subsequently conducted to preliminary explore the association between price dispersion and bargaining. With the construction of a multiple regression model, the phenomena found by the cluster analysis are further analyzed. The results indicate that the bargaining power of consumers increases with the increase of the price dispersion level. At high levels of the price dispersion, high‐experienced consumers exhibit greater bargaining power than low‐experienced consumers. At low levels of price dispersion, low‐experienced consumers have higher bargaining power than high‐experienced consumers. Finally, we demonstrate the validity and robustness of the study results by grouping regressions and replacing four measures of price dispersion.