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This paper presents results from the testing and benchmarking of a slip cast 316 stainless steel injection moulding tool. A brief out line of the slip casting process and the test cavity geometry is given as well as a discussion of some of the commercial alternative methods of forming injection moulding cavities. The calculations for the slip cast test cavity cost and lead time are given and comparisons between slip casting tool formation and alternative methods are made. The paper concludes that the slip casting method has potential in replacing some of the other tooling methods.

In view of the “staircase or stepped effect” in the present commercial rapid prototyping (RP) systems, a new approach is proposed, and is currently under development to produce true stepless parts. The new RP system is a combination of five‐axis motion control technology and precision milling. The system consists of three linear and two rotary axes, which enable the milling tool to be orientated for tangent cutting. Because of the complexity of the five‐axis configuration, ensuring high accuracy and precision is both important and difficult. This paper presents an open‐loop motion compensation algorithm, which enables the machine tool to move more accurately to a given position and orientation than its physical setup allows. Experimental procedures to measure the geometrical errors in the system setup are also presented in this paper.

To investigate the “staircase effect”, which is one of the most significant manifestations of part inaccuracy in liquid‐based rapid prototyping (RP) processes, on multi‐layer RP parts made using a thick layer deposition and photo‐curing process in a stepless rapid prototyping (SRP) system.

The building of a five‐layer part is simulated layer by layer using a finite element method based on an incremental elastic model, to analyze the staircase effect due to shrinkage induced by polymerization and temperature variation. The influence of various factors such as layer thickness and intensity of incident UV light is studied. The results were verified experimentally.

Results show that the staircase amount increases 20 percent and 300 percent with light intensity increasing from 65 to 145 mW/cm² and layer thickness increasing from 0.2 to 2.0 mm, respectively. It is also found that the overall staircase is below 100 μm, which suggests that the SRP process improves surface quality greatly compared to other RP systems, and can provide enough accuracy for fabricating functional parts.

The results apply only to the material used in the work: an acrylate‐based photopolymer resin, C123, produced by Tianjin Chemical Co., China. Also, the thickness of the layers is fixed at 6 mm.

Provides a method to analyze the origin and amount of the staircase effect, upon which to better control the surface finish of RP parts. New materials and different layer thicknesses can be investigated using the same method.

Apart from the above practical implication, this paper establishes the parameters that influence the shrinkage of the material used in SRP.

Strengthening the combination of technology and finance can significantly promote the development of economy and society. Urbanization is a crucial standard to measure the economic and social development of a country and region, and urban regional planning based on science and technology finance has always been the focus of both domestic and foreign research institutions. Thus, this paper takes Mianyang, the first city of science and technology, as the object of research, and from the angle of the development process of Mianyang, investigates the three stages of the construction and development of this science and technology city. This study analyzes the characteristics of regional planning of Mianyang City and sums up the idea of relying on the old city to build another new district, which boosts the development of science and technology as well as the economy. From two specific angles (i.e., urban spatial function region planning and urban and rural planning), this paper thoroughly studies a multiscale planning scheme of Mianyang’s urban area in recent years by researching the local policy, system, finance, and society. Empirical measurement proves that reasonable planning and construction of the science and technology city Mianyang can accelerate the development process of the western region, effectively promoting the economic development of the surrounding areas of Sichuan and remarkably improving the overall quality of the regional economy of both Chongqing and Sichuan Provinces.

The widespread use of artificial intelligence (AI) technology in the hospitality industry has triggered concerns among frontline service employees about their future careers, namely, AI awareness. This study aims to explore whether AI awareness influences frontline service employees’ silence through psychological contract breach and whether this process is contingent on frontline service employees’ moral identity, drawing on social exchange theory and moral identity theory.

The data were collected from 355 frontline service employees in Chinese hotels using a two-wave survey. SPSS macro PROCESS Model 58 was used to test the proposed hypotheses.

AI awareness increases frontline service employees’ silence by prompting psychological contract breach. This process is moderated by frontline service employees’ moral identity. Specifically, moral identity mitigates the effect of psychological contract breach on silence.

Organizations and managers should pay attention to the impact of AI on frontline service employees and take measures to help them better adapt to the rapidly changing work environment. In particular, it helps reduce frontline service employees’ silence by fostering positive attitudes toward AI, maintaining their psychological contracts and developing their moral identities.

This study enriches the research on the outcomes of AI awareness by directing our attention to frontline service employees’ silence. Moreover, this study not only explores the responses to AI awareness that frontline service employees make as “economic persons” but also examine whether they, as “moral persons,” regulate their responses contingent on their moral identity under the impact of AI. Exploring frontline service employees’ dual identities helps bring this research closer to the realities of managerial practice, thereby contributing to a better understanding and management of their complex responses to AI shocks.

This paper aims to explore the effect of different government subsidy decisions and the differences between the consequences of these decisions when supply chain members engage in cooperative green innovation through cost-sharing arrangements.

This paper investigates the optimal decisions for green supply chains under two types of subsidies, including subsidies for green innovation research and development (R&D) costs and subsidies for consumers, by integrating game theory with numerical simulation.

The optimal R&D cost-sharing ratio is found to be 2/3 for manufacturers and 1/3 for retailers. Under any subsidy policy, the supply chain can achieve maximum total profit. When the supply chain adopts the optimal R&D cost-sharing ratio, subsidies for green innovation R&D costs prove to be the most effective in increasing the supply chain’s profit. However, from the perspective of total social welfare, the analysis reveals that government subsidies to consumers are more beneficial for promoting overall social welfare.

Previous studies on green supply chain decisions have primarily focused on either government subsidies or corporate cost sharing in isolation. In contrast, this study combines both government subsidies and cost sharing within a unified framework for a more comprehensive analysis. Additionally, this paper examines the impact of government subsidies on supply chain cost-sharing decisions and their effect on overall social welfare while considering the presence of cost sharing and using the combination of theoretical modeling and simulation analysis.

This paper aims to present a novel approach of image super-resolution based on deep–shallow cascaded convolutional neural networks for reconstructing a clear and high-resolution (HR) remote sensing image from a low-resolution (LR) input.

The proposed approach directly learns the residuals and mapping between simulated LR and their corresponding HR remote sensing images based on deep and shallow end-to-end convolutional networks instead of assuming any specific restored models. Extra max-pooling and up-sampling are used to achieve a multiscale space by concatenating low- and high-level feature maps, and an HR image is generated by combining LR input and the residual image. This model ensures a strong response to spatially local input patterns by using a large filter and cascaded small filters. The authors adopt a strategy based on epochs to update the learning rate for boosting convergence speed.

The proposed deep network is trained to reconstruct high-quality images for low-quality inputs through a simulated dataset, which is generated with Set5, Set14, Berkeley Segmentation Data set and remote sensing images. Experimental results demonstrate that this model considerably enhances remote sensing images in terms of spatial detail and spectral fidelity and outperforms state-of-the-art SR methods in terms of peak signal-to-noise ratio, structural similarity and visual assessment.

The proposed method can reconstruct an HR remote sensing image from an LR input and significantly improve the quality of remote sensing images in terms of spatial detail and fidelity.

Based on upper echelons theory and social contagion theory, this study aims to explore how to translate leader sustainability orientation (LSO) into green supply chain integration (GSCI) by green entrepreneurial orientation (GEO), as well as the moderating effects of four dimensions of organizational learning capability (OLC).

This study conducts hierarchical regression analysis using multi-sourced survey data collected in 264 Chinese companies to examine hypotheses.

The results indicate that LSO has positive influences on green supplier and customer integration. Furthermore, GEO partially mediates the impacts of LSO on green supplier and customer integration. Managerial commitment positively moderates the impact of LSO on GEO, while other dimensions such as systems perspective, openness and experimentation and knowledge transfer and integration have non-significant moderating effects.

This study enriches the existing research on internal drivers of GSCI and contributes to the understanding of the direct impact of LSO and mediating effects of GEO. This study extends social contagion theory boundaries by investigating the moderating effects of OLC on the relationship between LSO and GEO.

In the new retail era, the supply chain synergy produced by quality integration has become the new direction of service supply chain research. The purpose of this paper is to study how to promote the sustainable development of the retail service supply chain (RSSC) by comparing and analyzing the optimal quality behavior, optimal returns, and the combination of conditions and strategies of the participating members of the RSSC.

From the perspective of quality function development and service quality concern, this paper considers RSSC as a two-level supply chain structure composed of functional service provider and retail service integrator. In this paper, a dynamic optimization model of quality input-cooperation-coordination of RSSC is proposed under two quality cooperation modes of decentralization and integration. This paper adopts the differential game method to compare and analyze the optimal quality behavior, optimal income, forming conditions and strategic combination of the participating members of the RSSC in different situations.

(1) Compared with quality dispersion, quality integration has more significant Pareto improvement effect on quality behavior and optimal revenue of RSSC. (2) In the case of quality integration, the optimal revenue obtained by the service sharing model is generally better than that obtained by the retail alliance collaboration model. (3) Benefit distribution ratio and quality cost allocation determine the optimal quality behavior of participating members of the RSSC, and also become the key factors for participating members to choose the collaborative mode in the case of quality integration.

Based on the quality function development of RSSC, this paper introduces the concept of steady service quality, and discusses the relationship between the quality cooperation stability and the mode selection of RSSC. This provides a theoretical basis for how to build a RSSC with efficient operation and stable quality.