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Testing several approaches for implied volatility modeling and forecasting.

Comparative empirical study with four traded options.

Non-parametric higher-order spline is better than parametric stochastic volatility inspired (SVI) in China.

Our results imply that even though popular on Wall Street, SVI seems not to be utilized by traders and market-makers in China.

Traders may consider higher-order spline as a better method for implied volatility modeling and forecasting.

Propose to model and forecast implied volatility via the fifth-order spline interpolation as a first; initiates studies of the empirical performance of SVI and the fifth-order spline models in implied volatility modeling and forecasting.

This paper aims to propose a novel model and calibration method to improve the absolute positioning accuracy of a robotic drilling system with secondary encoders and additional axis.

The enhanced rigid-flexible coupling model is developed by considering both kinematic parameters and link flexibility. The kinematic errors of the robot and the additional axis are considered with a model containing 27 parameters. The elastic deformation errors of the robot under self-weight of links and end-effector are estimated with a flexible link model. For calibration, an effective comprehensive calibration method is developed by further considering the coordinate systems parameters of the drilling system and using a two-step process constrained Levenberg–Marquardt identification method.

Experiments are performed on the robotic drilling system that contains a KUKA KR500 R2830 industrial robot and an additional lifting axis with a laser tracker. The results show that the maximum error and mean error are reduced to 0.311 and 0.136 mm, respectively, which verify the effectiveness of the model and the calibration method.

A novel enhanced rigid-flexible coupling model and a practical comprehensive calibration method are proposed and verified. The experiments results indicate that the absolute positioning accuracy of the system in a large workspace is greatly improved, which is conducive to the application of industrial robots in the field of aerospace assembly.

This study examines the interdependent relationships between green supply chain management (GSCM), carbon neutrality capability (CNC), digital transformation (DT) and firm performance (FP) among enterprises listed on the Chinese stock market. The primary objective is to provide a scholarly examination that may help these organisations to enhance their GSCM practices significantly.

Drawing on data from mainland Chinese publicly listed firms over the period from 2014 to 2021, this study posits and methodically evaluates four hypotheses: (1) GSCM practices are positively associated with an increase in CNC; (2) GSCM practices have a beneficial impact on FP; (3) DT moderates the GSCM–FP relationship and (4) CNC mediates the effect of GSCM on FP.

Contrary to initial assumptions, the findings suggest that GSCM practices may initially have a negative impact on FP. However, a concerted focus on CNC has the potential to convert this negative trajectory into a positive influence on FP. The findings further identify that DT has a significant moderating effect on the GSCM–FP relationship.

The findings of this study enrich the academic discourse concerning the symbiotic effects of GSCM, CNC and DT on FP. By systematically analysing these dynamics, the study underscores the critical importance of CNC and DT in the successful application of GSCM practices, thus offering valuable contributions to the literature on sustainable corporate operations.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

This study aims to explore the effect of digitalization on the promotion of enterprise R&D cooperation, and it analyzes the microimpact mechanism and boundary conditions of enterprise digitalization on enterprise R&D cooperation.

Based on survey data sourced from the World Bank Enterprise Surveys of the business environment of Chinese enterprises in 2012, this study applies multiple regression methods to test theoretical hypotheses.

Enterprise digitalization positively affects the breadth and intensity of enterprise R&D cooperation. Employees’ digital literacy plays an intermediary role between enterprise digitalization and enterprise R&D cooperation. The subordinate attributes of enterprises weaken the positive relationship between enterprise digitalization and the breadth and intensity of enterprise R&D cooperation. The shareholding of state-owned enterprises reinforces the positive relationship between digitalization and the intensity of enterprise R&D cooperation. However, such shareholding shows no significant regulatory effect on digitalization and the breadth of enterprise R&D cooperation.

Focusing on the digital transformation of the enterprise, this study discusses its impact mechanism on enterprise R&D cooperation, including the impact on the intensity and breadth of R&D cooperation. The study further examines the regulatory effect of organizational inertia on enterprise digital and R&D cooperation from two aspects: resource rigidity and routine rigidity. It emphasizes the significance of the digital literacy of employees in enterprise digitalization and discusses the micromechanism of enterprise digitalization and enterprise R&D cooperation.