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This study aims to analyze the relationship between corporate social responsibility (CSR) and quality of accounting report, especially on earnings management (EM). In addition, potential moderators of this relationship are examined.

After a comprehensive study of potential mechanisms, the authors obtain plenty of empirical results to open the black box of the link between CSR and EM. Meta-analysis is applied on 51 studies from 35 papers. Further analysis is also carried out to determine the moderating effects, such as the cultural and sample selection differences in these papers.

CSR is negatively associated with EM. In addition, this effect is moderated by cultural difference, CSR measurement, and year of sample selection.

Two patterns of the hypothesis between CSR and EM are confirmed based on agency cost theory, a theoretical shift of corporate ethics based on organizational moral perspective. Several useful suggestions are also provided for future studies on the empirical model and sample selection. Further research is necessary to clarify the agency cost behind the two theoretical patterns.

CSR is not a tool for firms to market but rather a strategy to ensure their consistency with moral principles, indicating that management should pay more attention to the potential damage of the incongruence between CSR and accounting reporting quality. CSR reporting quality remains an important issue for legislature to guarantee continued firm operations.

To the best of the authors’ knowledge, this study is the first to analyze the CSR and EM link using a meta-analysis and to consider its underlying mechanism under the global environment. Previous method design and sample selection are reviewed to provide reference for future studies.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.

This paper aims to present a new design for removable partial dentures (RPDs) for partially edentulous patients to improve the efficiency and quality of RPD manufacturing. Additive and subtractive manufacturing technologies and zirconium silicate micro-ceramic bonding in the aesthetic zone are used herein.

A case was presented. First, RPD digital definitive casts were acquired, and then digital frameworks with crown retainers and digital crowns were obtained by computer-aided design (CAD). The titanium alloy frameworks and resin crowns were fabricated by three-dimensional (3D) printing and computer-aided manufacturing (CAM) processes, respectively. The crowns adhered to the crown retainers. Ceramage bonding was used to reform the gingival anatomy in the aesthetic zone during the fabrication of the RPDs. The finished RPDs were assessed by a clinician and delivered to the patient.

The RPDs were conventionally assessed by a clinician, were deemed to be accurate and satisfied both the patient and clinician.

This novel method provides a way to fabricate RPDs with a combination of additive and subtractive manufacturing technologies. The design of the framework was different from that of a conventional framework because it contained the crown retainers, and the traditional base retainer no longer existed. Ceramage bonding was used to replicate the gingival anatomy in the aesthetic zone. The new RPDs provided accuracy and were less time-consuming to produce than those produced with the traditional method. The new method enables the digital manufacturing of nearly the entire RPDs.

Recommending suitable doctors to patients on healthcare consultation platforms is important to both the patients and the platforms. Although doctor recommendation methods have been proposed, they failed to explain recommendations and address the data sparsity problem, i.e. most patients on the platforms are new and provide little information except disease descriptions. This research aims to develop an interpretable doctor recommendation method based on knowledge graph and interpretable deep learning techniques to fill the research gaps.

This research proposes an advanced doctor recommendation method that leverages a health knowledge graph to overcome the data sparsity problem and uses deep learning techniques to generate accurate and interpretable recommendations. The proposed method extracts interactive features from the knowledge graph to indicate implicit interactions between patients and doctors and identifies individual features that signal the doctors' service quality. Then, the authors feed the features into a deep neural network with layer-wise relevance propagation to generate readily usable and interpretable recommendation results.

The proposed method produces more accurate recommendations than diverse baseline methods and can provide interpretations for the recommendations.

This study proposes a novel doctor recommendation method. Experimental results demonstrate the effectiveness and robustness of the method in generating accurate and interpretable recommendations. The research provides a practical solution and some managerial implications to online platforms that confront information overload and transparency issues.

Ti6Al4V alloy patient-customized implants (PCI) are often fabricated using laser powder bed fusion (LPBF) and annealed to enhance the microstructural, physical and mechanical properties. This study aims to demonstrate the effects of annealing on the physio-mechanical properties to select optimal process parameters.

Test samples were fabricated using the Taguchi L9 approach by varying parameters such as laser power (LP), laser velocity (LV) and hatch distance (HD) to three levels. Physical and mechanical test results were used to optimize the parameters for fabricating as-built and annealed implants separately using Grey relational analysis. An optimized parameter set was used for fabricating biological test samples, followed by animal testing to validate the qualified parameters.

Two optimized sets of process parameters (LP = 100 W, LV = 500 mm/s and HD = 0.08 mm; and LP = 300 W, LV = 1,350 mm/s and HD = 0.08 mm) are suggested suitable for implant fabrication regardless of the inclusion of annealing in the manufacturing process. The absence of any necrosis or reaction on the local tissues after nine weeks validated the suitability of the parameter set for implants.

To help PCI manufacturers in parameter selection and to exclude annealing from the manufacturing process for faster implant delivery.

To the best of the authors’ knowledge, this is probably a first attempt that suggests LPBF parameters that are independent of inclusion of annealing in implant fabrication process.

To present a custom design and fabrication method for a novel hemi‐knee joint substitute composed of titanium alloy and porous bioceramics based on rapid prototyping (RP) and rapid tooling (RT) techniques.

The three‐dimensional (3D) freeform model of a femur bone was reconstructed based on computerized tomography images via reverse engineering and the 3D reconstruction accuracy was evaluated. The negative image of artificial bone was designed with interconnected microstructures (250‐300 μm). The epoxy resin mould of a hemi‐knee joint and the negative pattern of an artificial bone were fabricated on Stereolithography apparatus. Based on these moulds, a titanium‐alloy hemi‐knee joint and a porous‐bioceramic artificial bone were created by quick casting and powder sintering (known as RT) techniques, respectively. After assembling, a composite hemi‐knee joint substitute was obtained.

The 3D reconstructed freeform model of the femur bone conformed to the original anatomy within a maximum deviation 0.206 mm. The sintered artificial bone had interconnected micropores (250 μm) and microchannels (300 μm). After implanting in vivo, the composite hemi‐knee joint substitute matched well with the surrounding tissues and bones with sufficient mechanical strength.

Further in‐vivo research is needed to provide the evidence for tissue growth into the ceramic structures and long‐term viability and stability of the implant.

This method enhances the versatility of using RP in the fabrication of tissue‐engineered substitutes, especially when individual matching is considered. Although this paper took a customized hemi‐knee joint substitute as an example, it is capable of fabricating other artificial substitutes with a variety of biomaterials.