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The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.

The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.

A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.

This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

The study investigated the effect of marketing communications’ dimensions on brand loyalty in the banking sector.

The study adopted the quantitative research approach which relied on the explanatory design due to the nature of the hypotheses tested. The convenience sampling technique was used to pull 377 customers of a branch of a commercial bank in Ghana. Furthermore, the PLS-SEM technique was deployed to assess the measurement model and test the research hypotheses.

Results show that the following dimensions of marketing communications are significant predictors of brand loyalty: direct marketing, public relations and sales promotion. The exception is advertising, which had an inverse relation with brand loyalty.

The results provide significant pointers to banks’ management that they should deploy a variety of marketing communication channels other than intensive advertising to reach and persuade customers.

The study illustrates the latest effort to extensively provide insights into how commercial banks could leverage marketing communication tools to sustain loyalty in an emerging economy that is intensively competitive.

This study aims to explicate consumers’ intentions to use online food delivery systems (OFDS) subscription services. The study revisited the unified theory of acceptance and use of technology.

A typical methodology that involved a confirmatory factor analysis, followed by structural equation modeling, was used to test the hypotheses using a sample of 573 OFDS users from the USA.

The results revealed that social influence has the most significant impact on consumers’ intentions to use OFDS subscription services, while effort expectancy and perceived security have relatively lower impacts on consumers’ intentions to use OFDS subscription services. In addition, the study revealed the role of compatibility and convenience orientation in shaping consumers’ OFDS system perceptions (e.g. performance and effort expectancy).

The results provide several theoretical and managerial implications and open new avenues for future research. The study advances the literature by validating the set of antecedents of important core perceptions (e.g. performance expectancy and effort expectancy). The study also provides implications for two types of practitioners, such as OFDS and restaurants.

To the best of the authors’ knowledge, this is the first study to examine consumers’ intentions to use OFDS subscription services. This study is also the first to examine key factors influencing consumers’ intentions to use OFDS subscription services.

本研究旨在阐明消费者使用在线订餐（OFDS） 订阅服务的意图。该研究重新审视了 Unified Theory of Acceptance and Use of Technology 理论（UTAUT2）。

本研究采用典型的量化研究方法, 包括确认性因子分析和结构方程建模, 并使用来自美国的573名OFDS用户的样本来测试假设。

结果显示, 社会影响对消费者使用OFDS订阅服务的意图具有最显著的作用, 而努力期望和感知安全对消费者使用OFDS订阅服务的意图影响较小。此外, 研究揭示了兼容性和便利性取向在塑造消费者对OFDS系统感知（例如, 性能和努力期望）方面的作用。

研究结果提供了多方面的理论和管理启示, 并为未来研究开辟了新的途径。本研究通过验证重要核心感知（例如, 性能期望和努力期望）的前因完善了相关文献。另外, 本研究还为OFDS和餐厅等两类从业者提供了重要启示。

本研究是第一个调查了消费者使用OFDS订阅服务意图的研究, 也是首次研究了影响消费者使用OFDS订阅服务意图的形成因素。