Search results

With the rapid development of the financial market, stock index futures have been the one of important financial instruments. Predicting stock index futures accurately can bring considerable benefits for investors. However, traditional models do not perform well in stock index futures forecasting. This study put forward a novel hybrid model to improve the predictive accuracy of stock index futures.

This study put forward a multivariate deep learning framework based on extreme gradient boosting (XGBoost) for stock index futures price forecasting. First, the original sequences were decomposed into several sub-sequences by variational mode decomposition (VMD), and these sub-sequences were reconstructed by sample entropy (SE). Second, the gradient boosting decision tree (GBDT) was used to rank the feature importance of influential factors, and the top influential factors were chosen for further prediction. Next, reconstructed sequence and the multiple factors screened were input into the bidirectional gate recurring unit (BiGRU) for modeling. Finally, XGBoost was used to integrate the modeling results.

For the sake of examining the robustness of the proposed model, CSI 500 stock index futures, NASDAQ 100 index futures, FTSE 100 index futures and CAC 40 index futures are selected as sample data. The empirical consequences demonstrate that the proposed model can serve as an effective tool for stock index futures prediction. In other words, the proposed model can improve the accuracy of stock index futures.

In this paper, an innovative hybrid model is proposed to enhance the predictive accuracy of stock index futures. Meanwhile, this method can be applied in other financial products prediction to achieve better forecasting results.

The Napster case has drawn enormous attention to digital intellectual property right problems of online file swapping. These peer‐to‐peer network technologies represent a powerful new paradigm for networking. In this paper, we try to figure out the intellectual property right problems of peer‐to‐peer network, in order to deal with potential digital piracy to avoid similar litigation. If libraries can embrace peer‐to‐peer technologies into their own services, they will possibly develop new service models, or improve existing ones.

The purpose of this paper is to examine the effects of bank ownership structure and ownership concentration on credit risk.

Using panel data on a sample of 88 Chinese commercial banks, with 826 observations over a period of 2003–2018, this study has applied system generalised method of moments regression to examine the impact of bank ownership structure and ownership concentration on credit risk. This study has used two measures of credit risk, which are non-performing loan ratio (NPLR) and loan loss provision ratio (LLPR).

The results show that ownership type (both government and private ownership) exerts a positive and significant impact on credit risk. Measuring ownership concentration using Herfindahl–Hirchmann Index, the results indicate that concentration of ownership in the hands of government has a negative and significant effect on credit risk, whereas private ownership concentration positively impacts credit risk. Overall, the findings suggest that concentration of ownership in government hands reduces risk; however, private ownership concentration exacerbates credit risks. The results are invariant to both measures of credit risk, before and after the financial crisis.

The findings provide useful insight to guide policy decisions in Chinese banks’ lending policies and bank ownership.

Using two ex post measures of credit risk, NPLR and LLPR, and one ownership concentration measure, HHI, this study deepens our understanding on the effectiveness of Chinese banks’ corporate governance reforms on managing credit risks.

The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems.

A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities.

Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services.

This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode.

A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM).

In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing.

The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices.

A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality.

The contradiction of construction land in economically developed regions is becoming more prominent, and the scale of construction land in some large cities is close to the ceiling. Therefore, China implemented the policy of construction land reduction in 2014. The main objective is to optimize the stock of homesteads and then help to realize rural revitalization by transferring land indexes across regions. Shanghai took the lead in implementing the reduction policy in 2014, for which reduction acceptance data are available. Thus, this paper evaluates the impact of homestead reduction on rural economic development based on data from towns in Shanghai.

This paper uses the difference-in-difference (DID) model to analyze the policy effects of homestead reduction on rural residents' income and industrial integration development. Using economic agglomeration (EA) as a mediating variable, the authors explore how homestead reduction (HR) promotes EA to drive rural economic development and analyze the impact of geographic location and government investment.

HR significantly promotes rural economic development and shows a significant cumulative effect. In the long run, HR can improve rural residents' income and promote industrial integration by promoting EA. The positive effect of HR and EA in suburban regions on industrial integration development is gradually increasing. However, the incentive effect on rural residents' income is weakening. The positive mediating effect of EA is significantly higher in regions with low government investment than in regions with high government investment.

This paper contributes to testing the impact of HR policy on rural economic development and can provide a reference for other regions aiming to implement reduction policy.

This paper aims to explore what Chinese doctors have learned in authentic medical practice, what they want to learn, and the dynamics behind their professional learning in working contexts.

The paper uses Narrative Inquiry, qualitative data which were collected by open‐ended face‐to‐face interviews and participative observation. Seven doctors from three hospitals in Shandong province were purposefully invited. Each participant was interviewed at least once, and all interview recordings were transcribed into research texts. The author narrated and re‐narrated stories of one chosen participant named Li Hengyang (pseudonym).

The paper finds that Chinese doctors divided their learning into two kinds: “professional” and “non‐professional”. The intrinsic‐motive‐driven learning of medical knowledge and techniques was attributed to “professional” and the extrinsic‐motive‐driven learning of “other things” was treated as “non‐professional”. The resultant force of intrinsic and extrinsic motives caused a performance disorder, a vague sense of professional identity, and involuntary expressive behaviours. The author finally pointed out that Chinese doctors' professional learning in working contexts is, to some extent, identity‐oriented.

Single theoretical perspective constrained the analysis; future research may use different theoretical perspectives besides Goffman's theatrical performance theory.

The paper presents identity‐oriented learning of Chinese doctors and the dynamics behind it, which have practical implications for Chinese doctors, medical professional educators and national medical policy makers.

Although Chinese doctors' training and education have been explored a lot, their professional learning in working contexts was rarely studied before.

This research adopts a dynamic self-regulation framework to test whether there is a curvilinear relationship between creative self-efficacy and individual creative performance at the within-person level. Furthermore, to establish a boundary condition of the predicted relationship, the authors build a cross-level model and examine how approach motivation and avoidance motivation moderate the complex relationship between creative self-efficacy and individual creative performance.

To obtain results from a within-person analysis, the authors collect multi-source data from 125 technicians who provided monthly reports over an 8-month period.

The authors find evidence of an inverted U-shaped relationship between creative self-efficacy and individual creative performance at the within-person level and differential moderating effects of approach/avoidance motivations.

This study is one of the first to challenge the assumption that creative self-efficacy always has a positive linear relationship with creativity. It provides a more complete view of the complex pattern between creative self-efficacy and creativity at the within-person level.

This study aims to assess international customers’ experiences in the leading hotels of the iconic city of Shanghai.

Leximancer, a qualitative analysis software program, was used to examine over 2,000 reviews appraising Shanghai’s superior hotels. The reviews were posted on Agoda.com.

Overall, the international tourists were actually quite satisfied with the superior Shanghai hotels. This study highlighted the continuing importance of the attentive and professional “staff”, physical attributes of the “hotel”, comfort of the “room”, “location”, proximity to a “shopping” area and co-creation possibilities to deliver some “beautiful” experiences. Segments of the market based on tourists’ origins, travel style and hotel management styles emphasized different expressive and instrumental features. Some strong commonalities were identified. The most satisfied customers, no matter what their backgrounds, were those who were more impressed with the expressive and intangible elements in the hotel, especially their interaction with and the service qualities of the hotels’ professional and attentive staff.

The work offers a potential range of insights and emphases for individual properties in Shanghai and other locations to help market and co-create experiences in their properties in distinctive ways.

The work is framed within the wider theoretical concerns of extending the meaning of co-creation in the experience economy. The work argues that co-creation is not limited to the on-site experience but rather that post-visit appraisals through user-generated contents constitute an extended form of interaction which may assist in understanding the full trajectory of the hotel experience.