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Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

Drawing on conservation of resources theory, this study aims to develop a resource-based model depicting a decreased level of psychological resourcefulness – relational energy, as a novel explanatory mechanism that accounts for the harm of abusive supervision, and we further investigate the role of leader humor as a boundary condition.

We applied multilevel path analysis to test our hypotheses with three-time-point survey data collected from 226 supervisor-employee dyads in a telecommunication company in China across six months.

Our results show that abusive supervision is negatively related to employee relational energy, leading to a subsequent decline in employee job performance. The predictions of the depleting effects get alleviated by leader humor.

This study foregrounds the importance of employee relationship management in the workplace and reveals that some abusive supervisors may manage to sustain employee performance and relational energy by using humor in their interactions, which necessitates immediate intervention.

These findings offer novel insights into the deleterious impact of abusive supervision by demonstrating the critical role of relational energy in dyadic interactions. We also reveal the potential dark side of leader humor in the context of abuse in the workplace.

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

In recent decades, emerging market multinational enterprises (EMNEs) have predominantly adopted a big step internationalization strategy to expand their business overseas. This study aims to examine the effect of big step internationalization on the speed of subsequent foreign direct investment (FDI) expansion for EMNEs. The authors also investigate the potential boundary conditions.

The authors use the random effects generalized least squares (GLS) regression following a hierarchical approach to analyze the panel data set conducted by a sample of publicly listed Chinese firms from 2001 to 2012.

The findings indicate that implementing big step internationalization in the initial stages accelerates the speed of subsequent FDI expansion. Notably, the authors find that this effect is more pronounced for firms that opt for acquisitions as the entry mode in their first big step internationalization and possess a board of directors with strong political connections to their home country’s government. In contrast, the board of director’s international experience negatively moderates this effect.

This study provides insights into our scholarly and practical understanding of EMNEs’ big step internationalization and subsequent FDI expansion speed, which offers important implications for firms’ decision-makers and policymakers.

This study extends the internationalization theory, broadens the international business literature on the consequences of big step internationalization and deepens the theoretical and practical understanding of foreign expansion strategies in EMNEs.

Despite extensive research on the detrimental work-related impact of customer mistreatment, there has been limited investigation into the outcomes that encompass both positive and negative connotations (i.e. unethical pro-organizational behavior [UPB]). This study aims to test whether, how and when daily customer mistreatment leads to hospitality employees’ daily UPB.

This study conducted a two-phase daily diary study. In the first phase, participants completed measures of their sense of power and provided demographic information. During the subsequent two-week period, participants completed questionnaires twice daily. The analysis included data from 87 hospitality employees, with 781 surveys remaining. This study performed multilevel analyses using Monte–Carlo simulations.

This study revealed that hospitality employees experiencing daily customer mistreatment exhibited heightened perceptions of status threats, resulting in increased daily UPB. The moderating effects of employees’ sense of power were found to be significant in both direct and indirect relationships.

Hospitality managers should recognize that customer mistreatment can threaten employees’ social status and result in daily UPB. To protect employees, implementing daily training programs is essential. Moreover, hotels and managers should provide HR management/recognition programs and empowerment initiatives to boost employees’ sense of power and counteract the harmful effects of customer mistreatment on their status.

This study makes contributions to the existing literature on customer mistreatment by establishing a positive relationship between daily customer mistreatment and daily UPB through the mechanism of status threat. Furthermore, thise study highlights the importance of enhancing hospitality employees’ sense of power as a protective factor against the negative consequences of customer mistreatment.

The purpose of this paper is to study the following two issues regarding blockchain crowdsourcing. First, to design smart contracts with lower consumption to meet the needs of blockchain crowdsourcing services and also need to design better interaction modes to further reduce the cost of blockchain crowdsourcing services. Second, to design an effective privacy protection mechanism to protect user privacy while still providing high-quality crowdsourcing services for location-sensitive multiskilled mobile space crowdsourcing scenarios and blockchain exposure issues.

This paper proposes a blockchain-based privacy-preserving crowdsourcing model for multiskill mobile spaces. The model in this paper uses the zero-knowledge proof method to make the requester believe that the user is within a certain location without the user providing specific location information, thereby protecting the user’s location information and other privacy. In addition, through off-chain calculation and on-chain verification methods, gas consumption is also optimized.

This study deployed the model on Ethereum for testing. This study found that the privacy protection is feasible and the gas optimization is obvious.

This study designed a mobile space crowdsourcing based on a zero-knowledge proof privacy protection mechanism and optimized gas consumption.

This study aims to propose a research model integrating technology acceptance model 3 (TAM3) constructs and human aspects of humanoid service robots (HSRs), measured by the Godspeed questionnaire series and tested across two hotel properties in Japan and the USA.

Potential participants were approached randomly by email invitation. A final sample size of 395 across two hotels, one in Japan and the other in the USA, was obtained, and the data were analysed using structural equation modelling.

The results confirm that perceived usefulness, driven by subjective norms and output quality, and perceived ease of use, driven by perceived enjoyment and absence of anxiety, are the immediate direct determinants of users’ re-patronage intentions for HSRs. Results also showed that users prefer anthropomorphism, perceived intelligence and the safety of an HSR for reusing it.

The findings have practical implications for the hospitality industry, suggesting multiple attributes of an HSRs that managers need to consider before deploying them in their properties.

The current study proposes an integrated model determining factors that affect the re-patronage of HSRs in hotels.

The purpose of this study is to design and process the optimal V-shaped microstructure for 7075 aluminum alloy and reveal its wear resistance mechanism and performance.

The hydrodynamic pressure lubrication models of the nontextured, V-shaped, circular and square microtextures are established. The corresponding oil film pressure distributions are explored. The friction and wear experiments are conducted on a rotating device. The effects of the microstructure shapes and sizes on the wear mechanisms are investigated via the friction coefficients and surface morphologies.

In comparison, the V-shaped microtexture has the largest oil film carrying capacity and the lowest friction coefficient. The wear mechanism of the V-shaped microtexture is dominated by abrasive and adhesive wear. The V-shaped microtexture has excellent wear resistance under a side length of 300 µm, an interval of 300 µm and a depth of 20 µm.

This study is conductive to the design of wear-resistant surfaces for friction components.

The adoption of mobile payment remains low in certain regions, highlighting the need to identify the factors that enable and inhibit its adoption. This study aims to address this gap by investigating the role of information security, loss aversion and the moderating influence of the herd effect on Inertia and behavioral intentions in the adoption of mobile payment systems.

A structural equation model was developed and tested with 332 valid questionnaires to examine the proposed hypotheses.

The empirical results reveal that information security plays a significant role as an enabler, while loss aversion acts as an inhibitor of mobile payment adoption. Furthermore, the study uncovers the moderating influence of the herd effect on the relationship between Inertia and behavioral intentions.

This study was conducted in a specific region and may not be generalizable to other regions. Future studies could expand the sample size and scope to enhance the external validity of the findings.

This study offers practical implications for mobile payment service providers. Understanding the key enabling and inhibiting factors identified in this study can guide providers in designing and improving their services. Strengthening information security measures can help build trust among potential adopters, while offering incentives can mitigate the impact of loss aversion and encourage early adoption.

The findings of this study have social implications as they contribute to promoting the adoption of mobile payment systems. Increased adoption can enhance financial inclusion and stimulate economic development.

This study provides novel insights into the enabling and inhibiting factors of mobile payment adoption and highlights the moderating role of the herd effect. By shedding light on the influence of social norms on individual behavior in the context of mobile payment adoption, this study contributes to the existing literature and advances our understanding of this phenomenon.

This study aims to investigate low-carbon footprint travel choices, considering both destination attributes and climate change perceptions, and examine the impacts of nudging (a communication tool to alter individuals’ choices in a predictable way) on tourists’ preferences for carbon mitigation in destinations.

A discrete choice experiment questionnaire was administered to a sample of 958 Hong Kong respondents. Hybrid choice modeling was used to examine the respondents’ preferences for destination attributes and to explain preference heterogeneity using tourists’ climate change perceptions. The respondents’ willingness to pay for the destination attributes was also calculated to measure the monetary value of the attributes.

Destination type, carbon emissions and travel cost had significant effects on tourists’ choices of destination. Nudging increased tourists’ preference for low-carbon footprint choices. Tourists with higher climate change perceptions were more likely than others to select low-carbon destinations with carbon offset projects.

The findings of this study provide an impetus for destination management organizations to support local carbon offset projects, implement policies that mitigate carbon emissions and develop sustainable tourism to fulfill tourists’ demand for low-carbon footprint travel choices. Based on the findings, policymakers could promote sustainable tourism by publishing relevant climate change information on social media.

This study addressed a gap in the literature on tourist travel choice by considering carbon emission-related attributes and climate change perceptions and by confirming the role of nudging in increasing the choice of low-carbon destinations.