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This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It evaluates the current state of the art, addressing both low- and high-temperature sensors, and explores the potential applications across various fields. The study also identifies challenges and highlights emerging trends that may shape the future of this technology.

This study systematically examines existing literature on TTS, categorizing the materials and fabrication methods used. The study compares the performance metrics of different materials, addresses the challenges encountered in thin-film sensors and reviews the case studies to identify successful applications. Emerging trends and future directions are also analyzed.

This study finds that TTS are integral to various advanced technologies, particularly in high-performance and specialized applications. However, their development is constrained by challenges such as limited operational range, material degradation, fabrication complexities and long-term stability. The integration of nanostructured materials and the advancement of wireless, self-powered and multifunctional sensors are poised to drive significant advancements in this field.

This study offers a unique perspective by bridging the gap between material science and application engineering in TTS. By critically analyzing both established and emerging technologies, the study provides valuable insights into the current state of the field and proposes pathways for future innovation in terms of interdisciplinary approaches. The focus on emerging trends and multifunctional applications sets this review apart from existing literature.

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.

People’s economic behaviors are often embedded in their social networks. Based on social embeddedness theory, this study investigates how customers’ social network embeddedness (structural and relational embeddedness) affects their online referral intentions through four studies.

This study adopted a vignette experimental design and used both offline and online channels to collect data. The respondents were undergraduate students and consumers, covering different age groups and occupation types. We used the ANOVA and bootstrap methods of SPSS to conduct data processing and hypothesis testing.

We found that when fewer (vs more) people in a customer’s social network participated in reward referral programs (RRPs), the customer’s online referral intention was also lower because of higher perceived social costs and lower perceived control. However, when the tie strength, reciprocity and normative influence between customers and people who have participated in RRPs were high, customers’ online referral intention also increased, ignoring the influence of participants’ network size. In these relationships, perceived social costs and perceived control played important mediating roles.

The results provide practical implications for enterprises to develop efficient RRPs in the context of the increasing popularity of the mobile Internet and intelligent terminals.

This study offers insights into the influence mechanism of social network embeddedness on referral likelihood, contributing to the field of RRPs and social embeddedness theory.

Intellectual experiences focus on users’ information processing and critical thinking toward stimuli. The deployment of humanoid service robots as novel stimuli in tourism and hospitality has influenced users’ perceptions and may affect their intellectual engagement. This paper aims to connect four contemporary theoretical concepts: the service robot acceptance model, technological fear, the uncanny valley theory and the stereotype content model, to investigate users’ perceptions and intellectual experiences toward humanoid service robots.

Scale development procedures were conducted: literature review, checking face and content validity, factorizing items and dimensions, achieving construct and criterion validity and testing predictive validity.

Through literature review and free-response tasks, 43 measurement items were generated. Next, 1,006 samples from two cross-cultural groups refined the scale. Finally, a reliable and valid scale with four dimensions measuring users’ perceptions of humanoid service robots was determined.

Humanoid service robots should be designed to enhance functionality and innovativeness while minimizing stiffness, inflexibility, unsafety and danger to improve users’ intellectual engagement.

This study provides a novel examination of users’ intellectual experiences toward humanoid service robots by connecting four contemporary theories of users’ perceptions. This study enriches human–robot experience through an integrated perspective and presents a rigorous examination of the scale’s psychometric properties. A reliable and valid scale for measuring users’ perceptions toward humanoid service robots fills the gaps and serves as an effective predictor of intellectual experience in human–robot literature.

Purpose/Objective: The shadow economy problem comes from the need for governments to increase their revenues, while citizens expect better social protection schemes such as universal basic income, increased spending for social security, and better living standards, including a sustainable and green environment. Our study analyses a complex and multifaced relationship between the shadow economy and the environment.

Design/Methodology/Approach: The analysis refers to the shadow economy (% in GDP) and three environmental proxies (Agriculture Methane Emissions, Methane Emissions for the Energy Sector, and Tax on Pollution) for the EU countries over the 2009–2019 period. Firstly, we describe the evolution of the indicators, and then we observe the correlation between the indicators. The last stage considers simple linear regression models, with shadow economy as the independent variable and environmental proxies as dependent variables.

Significance/Implications/Conclusions: Our research found that the evolution of the shadow economy is on a downtrend, considering that the fight against corruption developed after the 2009 financial crisis and especially after the Euro crisis 2014. Countries such as Romania, Bulgaria, Italy, Portugal, and Spain have the highest shadow economy due to their political electorate’s constant mismanagement and low credibility. On the contrary, countries such as Hungary, Estonia, and Lithuania have a low shadow economy.

Limitations: The reliance on limited data and the models applied.

Future Research: Future studies could expand the analysis by incorporating additional indicators, considering other econometric models, and incorporating more comprehensive and up-to-date data.

Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features for multimodal information effectively. To address these limitations, this study proposes a novel multimodal sarcasm detection model based on the directed graph isomorphism network with sentiment enhancement and multimodal fusion (DGIN-SE-MF).

The approach extracts image and text features through vision transformer and BERT, respectively. To deeply integrate the extracted features, the author develops a text-guided multi-head attention fusion mechanism module. Subsequently, a directed graph is constructed through SE and the multimodal factorized bilinear pooling method to integrate image features into the graph. The DGIN then fuses the image and text features, using a weighted attention mechanism to generate the final representation.

The model is validated on three datasets: English, Chinese and an Indonesian–English dataset. The results demonstrate that the proposed model consistently outperforms other baseline models, particularly on the Chinese and English sarcasm datasets, achieving F1 scores of 88.75 % and 83.10 %, respectively.

The proposed model addresses the inadequacies of previous methods by effectively integrating emotional cues and image features into sarcasm detection. To the best of the authors’ knowledge, this is the first work to leverage a DGIN-SE-MF for this task, leading to significant improvements in detection performance across different languages.

This paper aims to explore the effect of service robots on employees’ customer service performance and service-oriented organizational citizenship behavior through psychological need satisfaction and role stress. Moreover, this paper examines the moderating role of service robots’ autonomy.

Data collected from managers and employees at hotels in South Korea were used to test the aforementioned association. In this paper, partial least squares structural equation modeling was performed to test the hypotheses.

Service robots enhance service employee performance through employees’ psychological need satisfaction, which can decrease service employee performance through role stress. As hypothesized, service robots’ autonomy is the moderator on these associations.

This study shows that using service robots does not always lead to positive employee performance. Therefore, managers should find ways to mitigate the role stress and enhance perceived robot autonomy.

This study offers a balanced perspective of the personal benefits and costs of the use of service robots by developing a dual-path model that unpacks the energizing and draining mechanisms underlying the double-edged effects of working with service robots on employees’ psychological strain and employees’ psychological needs.

Drawing on the pleasure-arousal-dominance (PAD) emotion model, the emotional states of consumers embedded in online reviews can be described through three dimensions, that is, pleasure, arousal and dominance, rather than only the one-dimensional positive and negative polarity, as in previous studies. Therefore, this study aims to explore the effect of online review emotion on perceived review helpfulness based on these three basic emotional dimensions.

A lexicon-based method is developed to analyze PAD emotions of online reviews from JD.com. The zero-inflated negative binomial regression is utilized to empirically validate the study hypothesis. The authors examine the influence of pleasure, arousal, dominance, emotion diversity and emotion deviation on review helpfulness, as well as the moderating effect of product type on the relationship between all independent variables and online review helpfulness.

The study results show that the pleasure emotion impairs the helpfulness of online reviews, while the arousal and dominance emotions have a positive impact. Moreover, the authors find that compared with search products, the effects of pleasure, arousal and dominance on perceived helpfulness are strengthened for experience products. However, the emotional diversity and emotional deviation have opposite effects on the helpfulness of search products and experience products. Additionally, the results show that dominance emotion plays a more important role in the interaction effect.

The empirical findings confirm the applicability of PAD in the online review context and extend the existing knowledge of the influence of review emotion on helpfulness. A feasible scheme for extracting PAD variables from Chinese text is developed. The study findings also have significant implications for reviewers, merchants and platform managers of e-commerce websites.

Drawing on conservation of resources (COR) theory, this research aims to advance the current understanding of leader boundary spanning by examining its effect on task performance, psychological mechanism and boundary conditions.

The empirical data were gathered by a paper-and-pencil survey from 155 employee-supervisor dyads working in various industries.

Our results indicated that leader boundary spanning is positively related to task performance, mediated by employees’ enhanced self-efficacy. Moreover, the results indicated that the positive effect of leader boundary spanning on task performance via enhanced self-efficacy is strengthened when the level of abusive supervision is low or when the level of an employee’s emotional exhaustion is high.

Organizations should find a way to facilitate leaders to engage in boundary spanning behaviors since a leader’s boundary spanning behavior enhances task performance through employee’s self-efficacy. Additionally, it is crucial to establish policies and provide training sessions to reduce the occurrence of abusive supervision in the workplace.

This study gives insights into the current literature by uncovering whether, how and under what circumstances boundary spanning leaders exert influences on task performance via employees’ self-efficacy. Our results showed that the positive effect of leader boundary spanning is likely to be strengthened when boundary spanners do not abuse their employees or when employees are in need of additional resources.

This paper aims to investigate the suppression of end-point vibrations in industrial robot systems that exhibit joint flexibility and are subject to external disturbances.

The real-time position tracking error is effectively decomposed by using feedforward control based on a dynamic model. Various proportional-derivative controllers and adapted versions are used to compute real-time compensation torque for different position tracking errors. This approach aims to simultaneously achieve rapid response and stability in the control system, resulting in reduced end vibration in the industrial robot.

Experiments were conducted in torque compensation on a 6R industrial robot platform. Compared to the dynamic model calculate torque feedforward compensation method, the maximum reduction of the root mean square of the position error of each joint reached 77% and the minimum reduction was 36.2%. This enhancement improves the trajectory tracking accuracy and effectively suppresses the end-effector vibration.

An improved torque feedforward compensation method is proposed and verified. According to the experimental results, the method can effectively suppress vibration and further improve the trajectory tracking accuracy.