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In recent years, personalized recommendations have facilitated easy access to users' personal information and historical interactions, thereby improving recommendation effectiveness. However, due to privacy risk concerns, it is essential to balance the accuracy of personalized recommendations with privacy protection. Accordingly, this paper aims to propose a neural graph collaborative filtering personalized recommendation framework based on federated transfer learning (FTL-NGCF), which achieves high-quality personalized recommendations with privacy protection.

FTL-NGCF uses a third-party server to coordinate local users to train the graph neural networks (GNN) model. Each user client integrates user–item interactions into the embedding and uploads the model parameters to a server. To prevent attacks during communication and thus promote privacy preservation, the authors introduce homomorphic encryption to ensure secure model aggregation between clients and the server.

Experiments on three real data sets (Gowalla, Yelp2018, Amazon-Book) show that FTL-NGCF improves the recommendation performance in terms of recall and NDCG, based on the increased consideration of privacy protection relative to original federated learning methods.

To the best of the authors’ knowledge, no previous research has considered federated transfer learning framework for GNN-based recommendation. It can be extended to other recommended applications while maintaining privacy protection.

The purpose of this paper is to derive a new lubrication model of double involute gears drive and study the effect of the tooth waist order parameters of double involute gears on lubrication performance.

The new lubrication model of double involute gears drive was established according to the meshing characteristics of double involute gears drive and the finite length line contact elastohydrodynamic lubrication theory. Numerical calculation of the lubrication model of gear drive was conducted using the multigrid method.

The results show that the oil film necking phenomenon and the oil film pressure peak emerged at the tooth waist order area and the tooth profile ends, and when compared with involute gear, the lubrication performance at the tooth waist order area is better than that at the tooth profile ends. The effect of tooth waist order parameters on lubrication performance at the tooth waist order area was greater than that at other areas.

This research will promote the application of the double involute gear as soon as possible, and it has the reference value for other types of gears.

This paper examines the impact of corporate digital transformation on employee satisfaction. Therefore, this study extends our understanding of the economic consequences of corporate digital transformation from employees’ perspectives.

The data used to construct our main proxy of employee satisfaction are collected from Kanzhun.com, which provides reviews by rank-and-file employees on their employers. This study uses a large sample of Chinese firms and adopts various empirical methods to examine the impact of digital transformation on employee satisfaction.

We find a significant positive relationship between corporate digital transformation and employee satisfaction. Moreover, we document that the relationship between corporate digital transformation and employee satisfaction is more pronounced in firms with higher labor intensity and in state-owned enterprises (SOE).

One significant limitation is that corporate digital transformation is constructed based on word frequency analysis. This approach may be influenced by variations in corporate disclosure practices and might not accurately capture the true extent of corporate digital transformation. This limitation is not only present in our research but is also pervasive in many other studies that utilize similar methodologies. Therefore, our results should be interpreted with this caveat in mind.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study contributes to the literature on the economic consequences of corporate digital transformation and extends existing research on the determinants of employee satisfaction. Additionally, it provides a novel measurement of employee satisfaction for a large sample of Chinese firms.

In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data. The purpose of this paper is to design a robot system compatible with ultra high frequency (UHF) band passive and active RFID applications and to propose a new anti-collision protocol to improve identification efficiency for active tag data collection.

A new UHF RFID robot system based on a cloud platform is designed and verified. For the active RFID system, a grouping reservation–based anti-collision algorithm is proposed in which an inventory round is divided into reservation period and polling period. The reservation period is divided into multiple sub-slots. Grouped tags complete sub-slot by randomly transmitting a short reservation frame. Then, in the polling period, the reader accesses each tag by polling. When tags’ reply collision occurs, the reader tries to re-query collided tags once, and the pre-reply tags avoid collisions through random back-off and channel activity detection.

The proposed algorithm achieves a maximum theoretical system throughput of about 0.94, and very few tag data frame transmissions overhead. The capture effect and channel activity detection in physical layer can effectively improve system throughput and reduce tag data transmission.

In this paper, the authors design and verify the UHF band passive and active hybrid RFID robot architecture based on cloud collaboration. And, the proposed anti-collision algorithm would improve active tag data collection speed and reduce tag transmission overhead in complex manufacturing environments.

The authors intend to investigate the relations between corporate strategic positioning and environmental information disclosure (EID) behaviors in the context of the circular economy. The authors argue that the development of the circular economy is crucial to address environmental issues and achieve sustainable development, and companies play a vital role in this process as micro-entities. By examining corporate EID behaviors, the authors could understand their adoption of circular practices to a certain extent.

The authors conduct a content analysis of companies' annual fiscal reports, social responsibility reports and environmental reports and develop text-based proxies for both strategic positioning and EID quality to explore the relationship between them.

The authors find that corporate strategic positioning does affect corporate EID behaviors. Specifically, firms that implement a prospector strategy are more likely to engage in high-quality EID. Furthermore, the results suggest that green innovation is one of the mediators through which strategic positioning affects EID. Compared with defenders, prospectors are more likely to engage in green innovation, which, in turn, leads to higher-quality EID and demonstrates a more active approach to the circular economy.

This study contributes to the literature on strategic positioning and corporate EID by providing empirical evidence on the impact of corporate strategic positioning on EID behaviors. Moreover, the study employs a textual analysis approach to measure corporate strategy and EID, which is a relatively new research method in this field.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

This paper aims to examine whether China's grain price support policy has distorted the grain market price.

The time-varying differences-in-differences (DID) model is used to study the impact of support policies on grain prices, and it is combined with the event study method to explore the dynamic effects of price support policy. Panel data model is used to study the effect of the price support policy on price formation for national grain market prices. In addition, we apply the smooth transformation (STR) model to verify whether there is a distortion in the transmission of grain prices among different markets in China and from the international market to China’s market.

China’s grain price support policy plays a significant role in rising grain market prices, weakens the decisive role of the market mechanism in the formation of grain prices, hinders the spatial transmission of market price signals and decreases the effect of price transmission from the world market to China’s market.

In order to ensure both the stability of grain production as well as the market stability, and also to ensure that intervention policies do not distort the food market, the minimum purchase price of grain and market regulation policies should be adjusted as follows: (1) price support policy should be shifted to an income support policy and (2) reasonably determine the scale of reserves and implement a grain minimum purchase price policy in limited areas.

Our findings are relevant for understanding the effect of China's grain price support policies on the implementation regions and the price transmission effect, which provide reference experience for developing countries to implement food price policies.

The purpose of this study is to explore the relationship between ambidextrous leadership and sustainability performance. In addition, this study also discusses how ambidextrous leadership affects sustainability performance through employees' green creativity and green product innovation.

This study obtained research data from a questionnaire survey of 307 manufacturing enterprise leaders in China and used regression and bootstrap analysis to test the research hypotheses.

(1) Ambidextrous leadership positively influences sustainability performance. (2) Employees' green creativity mediates the relationship between ambidextrous leadership and sustainability performance. (3) Green product innovation also mediates the relationship between ambidextrous leadership and sustainability performance. (4) The intermediary chain constructed by employees' green creativity and green product innovation has serial mediation effects on the relationship between ambidextrous leadership and sustainability performance.

This study contributes to the literature on leadership and corporate sustainability by clarifying the relationship between ambidextrous leadership and sustainability performance. Meanwhile, this study reveals the influence mechanism of ambidextrous leadership on sustainability performance by analyzing the serial mediation effects of employees' green creativity and green product innovation.

The construction industry has been recognized for its conservatism and lack of innovation. In order to improve the success rate of construction innovation, the implementation of innovations within the context of construction has been discussed and developed. Literature in this area focuses extensively on construction innovation, and yet does not contain a systematic review. This paper looks to fill this gap by providing a systematic review of construction innovation. The review synthesizes the conclusions and shows the implementation of construction innovation. Collaboration, culture, innovation process, and drivers are identified as critical factors to improve the performance of construction innovation. Finally, the limitations of prior studies in construction innovation are discussed and recommendations made for areas of future study.

This paper aims to explore the mechanism underlying the relationship between abusive supervision differentiation (ASD) and team performance. The moderating roles of inter-team and intra-team competitive climate are also examined.

This research collects data from 419 employees and 71 supervisors from hospitals and financial companies in China. Techniques include descriptive statistics and hierarchical multiple regression are applied to analyze the data.

This research finds that (1) team relationship conflict mediated the relationship between ASD and team performance and (2) intra-team competitive climate strengthened the indirect relationship between ASD and team performance through team relationship conflict.

The results indicate that organizations should take measures to minimize the occurrence of abusive supervision. Team leaders should increase self-control and avoid abusing employees. Furthermore, organizations should establish an open and fair reward and punishment system to avoid cutthroat competition.

This study advances our knowledge of how ASD results in poor team effectiveness. This contributes to the literature by identifying team relationship conflict as a mediating mechanism linking the negative association of ASD with team performance. Additionally, competitive climate enriches the individual-focused team-level model of abusive supervision.