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The extrusion-based additive manufacturing method followed by debinding and sintering steps can produce metal parts efficiently at a relatively low cost and material wastage. In this study, 316L stainless-steel metal filled filaments were used to print metal parts using the extrusion-based fused filament fabrication (FFF) approach. The purpose of this study is to assess the effects of common FFF printing parameters on the geometric and mechanical performance of FFF manufactured 316L stainless-steel components.

The microstructural characteristics of the metal filled filament, three-dimensional (3D) printed green parts and final sintered parts were analysed. In addition, the dimensional accuracy of the green parts was evaluated, as well as the hardness, tensile properties, relative density, part shrinkage and the porosity of the sintered samples. Moreover, surface quality in terms of surface roughness after sintering was assessed. Predictive models based on artificial neural networks (ANNs) were used for characterizing dimensional accuracy, shrinkage, surface roughness and density. Additionally, the response surface method based on ANNs was applied to represent the behaviour of these parameters and to identify the optimum 3D printing conditions.

The effects of the FFF process parameters such as build orientation and nozzle diameter were significant. The pore distribution was strongly linked to the build orientation and printing strategy. Furthermore, porosity decreased with increased nozzle diameter, which increased mechanical performance. In contrast, lower nozzle diameters achieved lower roughness values and average deviations. Thus, it should be noted that the modification of process parameters to achieve greater geometrical accuracy weakened mechanical performance.

Near-dense 316L austenitic stainless-steel components using FFF technology were successfully manufactured. This study provides print guidelines and further information regarding the impact of FFF process parameters on the mechanical, microstructural and geometric performance of 3D printed 316L components.

Fused filament fabrication (FFF) technique using metal filled filaments in combination with debinding and sintering steps can be a cost-effective alternative for laser-based powder bed fusion processes. The mechanical behaviour of FFF-metal materials is highly dependent on the processing parameters, filament quality and adjusted post-processing steps. In addition, the microstructural material properties and geometric characteristics are inherent to the manufacturing process. The purpose of this study is to characterize the mechanical and geometric performance of three-dimensional (3-D) printed FFF 316 L metal components manufactured by a low-cost desktop 3-D printer. The debinding and sintering processes are carried out using the BASF catalytic debinding process in combination with the BASF 316LX Ultrafuse filament. Special attention is paid on the effects of build orientation and printing strategy of the FFF-based technology on the tensile and geometric performance of the 3-D printed 316 L metal specimens.

This study uses a toolset of experimental analysis techniques [metallography and scanning electron microcope (SEM)] to characterize the effect of microstructure and defects on the material properties under tensile testing. Shrinkage and the resulting porosity of the 3-D printed 316 L stainless steel sintered samples are also analysed. The deformation behaviour is investigated for three different build orientations. The tensile test curves are further correlated with the damage surface using SEM images and metallographic sections to present grain deformation during the loading progress. Mechanical properties are directly compared to other works in the field and similar additive manufacturing (AM) and Metal Injection Moulding (MIM) manufacturing alternatives from the literature.

It has been shown that the effect of build orientation was of particular significance on the mechanical and geometric performance of FFF-metal 3-D printed samples. In particular, Flat and On-edge samples showed an average increase in tensile performance of 21.7% for the tensile strength, 65.1% for the tensile stiffness and 118.3% for maximum elongation at fracture compared to the Upright samples. Furthermore, it has been able to manufacture near-dense 316 L austenitic stainless steel components using FFF. These properties are comparable to those obtained by other metal conventional processes such as MIM process.

316L austenitic stainless steel components using FFF technology with a porosity lower than 2% were successfully manufactured. The presented study provides more information regarding the dependence of the mechanical, microstructural and geometric properties of FFF 316 L components on the build orientation and printing strategy.

The use and abuse of alcohol is problematic for a person’s social and individual development. Maintenance of abstinence after detoxification programs is difficult for patients who experience a craving, and relapses during the course of the disorder are common. The purpose of this paper is to describe the socio-demographic and clinical features of alcohol-dependent patients by sex and alcohol use status and to analyze the percentage of patients who remained abstinent after 10 months of psychological treatment.

In total, 50 alcohol-dependent patients were enrolled (34 men and 16 women). The patients attended a psychological treatment program at a therapeutic community, Projecte Home Balears, Spain. This paper used the European Addiction Severity Index to collect socio-demographic data and data on alcohol and other drugs and the Trait Meta-Mood Scale-24 to measure emotional management.

Significant differences were observed in occupation (χ² = 9.9; p = 0.007) and duration of alcohol use (U = 137.000; p = 0.005) by sex and hospitalizations during the previous months (χ² = 15.477; p = 0.009) and type of chronic disorder (χ² = 7.6; p = 0.022) and duration (in months) of the longest period of abstinence after treatment in facilities (U = 219.500; p = 0.097) by alcohol use status. The survival analysis showed that 25% of relapses happened after 4.5 months of treatment; at 7.3 months, 50% of the sample remained abstinent.

Women had used alcohol for longer since age at onset than men. Furthermore, after 7.3 months of intensive therapy, 50% of alcohol-dependent patients were abstinent.

This paper aims to increase the understanding of luxury brands’ branded content strategies concerning follower's engagement generated or not by happiness and well-being feelings spread in their branded content.

This study sample was composed of three of the most relevant luxury brands nowadays: Manolo Blahnik, Loewe, y Balenciaga. To address this research, an exploratory-correlational quantitative methodology was chosen; hypotheses were contrasted using ANOVA analysis with the SPSS software. Although the study can be considered quantitative, the first step of qualitative analysis was applied for content analysis with NVivo QSR software, categorizing all posts (N = 192) into three categories.

The dissemination of branded content and corporate social responsibility, despite being different in each case, show in general an interaction and affective commitment with their stakeholders. In the specific case of Manolo Blahnik and Loewe, they have prioritized their content, in the context of the pandemic, in posts related to social welfare, happiness, mental and physical health care. There are significant differences in the interaction with their audience, which respond very favorably to both “Happiness” and “Health and safety” content.

This study reveals how corporate social responsibility can be achieved using efficient communications in social networks. In this way, the perception of the image of the sector and the reputation can be improved – both sectoral and organizational – which unquestionably translates into economic gains for the brands.

Given the importance of chatbots in customer service in tourism, this paper aims to understand the drivers that predispose regular consumers of restaurant recommendation chatbots to continue using them.

A total of 386 regular consumers of a chatbot via WhatsApp restaurant recommender responded to an online questionnaire (inspired by scales found in the literature on technology adoption). Structural equation modeling was used to test the hypotheses.

Significant predictors of intention to continue using these chatbots included “effort expectancy (EE),” “hedonic motivation (HM),” “price value (PV)” and “habit (HT).” Specifically, HT still has a long way to go in terms of its performance, and it will be possible to work on it. Furthermore, two variables, EE and HM, act as a bottleneck when it comes to explaining this recurrent usage intention. Factors such as “performance expectancy (PE),” “facilitating conditions (FC)” and “social influence (SI)” did not influence “behavioral intention (BI).” Likewise, the moderating variables, age and gender, are not significant. Finally, the predictive capability of the model is demonstrated. The study findings will enable the development of effective strategies to foster consumer loyalty to this new technology in the restaurant industry.

This study contributes, building on the suitability of the unified theory of acceptance and use of technology 2 model, to explain users’ intention to continue using chatbot tourism services in the context of an information search for an unplanned and varied purchase decision, namely, restaurant recommendation services. To the best of the authors’ knowledge, this is the first analysis of tourist’s intention to reuse a real and fully functional chatbot via mobile instant messaging.

鉴于聊天机器人在旅游客户服务中的重要性, 本研究旨在了解驱动消费者持续使用WhatsApp餐厅推荐聊天机器人的因素。

共收集386名WhatsApp餐厅推荐聊天机器人的常规用户在线问卷数据（问卷设计参考技术采纳相关文献中的量表）。研究采用结构方程模型（SEM）验证假设。

影响用户持续使用意图的显著预测因素包括“努力期望（EE）”、“享乐动机（HM）”、“价格价值（PV）”和“习惯（HT）”。其中, “习惯（HT）”表现仍有提升空间, 而“努力期望（EE）”和“享乐动机（HM）”是解释持续使用意图的瓶颈因素。此外, “绩效期望（PE）”、“促进条件（FC）”和“社会影响（SI）”对“行为意图（BI）”无显著影响。性别和年龄等调节变量同样不显著。研究结果验证了模型的预测能力, 能够为餐厅行业制定有效策略以增强消费者对这一新技术的忠诚度提供指导。

本研究基于UTAUT2模型, 首次分析了消费者在餐厅推荐服务中持续使用移动即时通讯（MIM）聊天机器人的意图, 为探索非计划性和多样化购买决策背景下的信息搜索服务提供了新见解。

Media and academic attention on Airbnb focuses on user experiences, implications for traditional accommodation establishments and negative sociocultural impacts. The purpose of this paper is to explore the views of Barcelona residents who have been impacted by the proliferation of Airbnb rentals.

A qualitative approach was adopted, involving semi-structured interviews with residents of Barcelona.

It highlights the problem of unregistered Airbnb rentals throughout the city, carrying implications for the gentrification of neighbourhoods, the displacement of local residents and anti-social guest behaviour. This study points to a consequent rise in anti-tourist feeling. It also reveals that the authentic experience promised by the sharing economy is illusory.

This paper presents a model that highlights a clash between the vaunted benefits of the sharing economy for hosts and tourists and the negative implications for a city’s residents.

The COVID-19 pandemic has significantly impacted global tourism, with international travel bearing the burden of restrictions. Domestic tourism has also faced substantial challenges. This paper aims to analyse the impact of the COVID-19 pandemic on domestic tourism in Spain, focusing on travel from Madrid (the country’s capital) to other tourist destinations.

Mobile phone data has been used to study the evolution of tourist trips over the summers of 2019, 2020 and 2021. Regression models are used to explain the number of visitors at destinations.

The pandemic not only caused a drastic drop in tourist flows but also disrupted the overall pattern of the domestic flow system. Winning destinations were typically areas in proximity to Madrid and less densely populated destinations, while urban destinations were major losers. The preferences of domestic tourists varied notably by income group, but the decrease in trip volumes showed only marginal differences.

The paper demonstrates the potential of mobile phone data analysis to study the uneven impact of external shocks, such as the COVID-19 pandemic, on tourist destinations. This approach considers spatial resilience heterogeneity within regions or provinces. By incorporating income information, the analysis introduces a social dimension to highly detailed spatial data, surpassing traditional studies conducted at the regional or national levels.

COVID-19大流行对全球旅游业产生了重大影响，国际旅行受到了限制的影响最为严重。国内旅游也面临着重大挑战。本文分析了COVID-19大流行对西班牙国内旅游的影响，重点关注从马德里（该国首都）到其他旅游目的地的旅行。

本研究使用移动电话数据研究了2019年、2020年和2021年夏季旅游出行的演变。采用回归模型解释了各目的地游客数量。

大流行不仅导致了旅游流量急剧下降，还扰乱了国内流动系统的总体模式。获胜的目的地通常是马德里附近的地区和人口较稀少的目的地，而城市目的地是主要的输家。国内游客的偏好在收入群体之间有明显差异，但旅行量的减少只显示出边际差异。

本文展示了使用移动电话数据分析研究外部冲击（如COVID-19大流行）对旅游目的地的不均匀影响的潜力。该方法考虑了区域或省份内的空间弹性异质性。通过整合收入信息，该分析为高度详细的空间数据引入了社会维度，超越了传统在区域或国家水平进行的研究。