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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.

With the outbreak of the COVID-19 pandemic, online assessment has become the dominant mode of examination in higher education institutions. However, there are contradictory findings on how students perceive online assessment and its impact on their academic performance. Thus, the purpose of this study is to evaluate the potential impact of online assessment on students' academic performance.

This study proposes a research model based on the task–technology fit theory and empirically validates the model using a survey from students in the UK. In addition, the study conducted four experiments based on paper-based and online assessments and analysed the data using paired sample t test and structural equation modelling.

The findings show that the use of online assessment has a positive impact on students' academic performance. Similarly, the results from the experiment also indicate that students perform better using online assessments than paper-based assessments.

The findings provide crucial evidence needed to shape policy towards institutionalising online assessment. In addition, the findings provide assurance to students, academics, administrators and policymakers that carefully designed online assessments can improve students' academic performance. Moreover, the study also provides important insights for curriculum redesign towards transitioning to online assessment in higher education institutions.

This study advances research by offering a more nuanced understanding of online assessment on students' academic performance since the majority of previous studies have offered contradictory findings. In addition, the study moves beyond existing research by complementing assessment results with the views of students in evaluating the impact of online assessment on their academic performance. Second, the study develops and validates a research model that explains how the fits between technology and assessment tasks influence students' academic performance. Lastly, the study provides evidence to support the wide use of online assessment in higher education.

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.

The crowdfunding concept and activities have recently been the focus of attention of many researchers and practitioners over different business contexts. However, there is a dearth of literature considering the main aspects of e-equity crowdfunding activities and their impact on the innovation performance for entrepreneurial business. Therefore, this study aims to explore how entrepreneurs' engagement in e-crowdfunding activities could enhance both knowledge acquisition and innovation performance.

The conceptual model will be proposed based on three main theoretical perspectives: relationship marketing orientation (RMO); Kirzner's alertness theory; and the DeLone and McLean model of information systems. The data of the current study were collected using an online questionnaire from a sample of 500 entrepreneurs who have actively engaged in e-crowdfunding in Saudi Arabia.

The statistical results of structural equation modelling (SEM) approved the impacting role of RMO, entrepreneurial alertness, system quality and service quality on the entrepreneurs' engagement in e-equity crowdfunding, which in turn, predicts both knowledge acquisition and innovation performance.

There are several limitations which could be addressed in future studies, for example, this study has only considered one form of crowdfunding (equity based crowdfunding) and due to its nature these findings would not be easily generalized to other kinds of crowdfunding (i.e. donation-based crowdfunding; rewards-based crowdfunding; and debt-based crowdfunding). Future studies could consider these kinds of crowdfunding activities.

This study has contributed to the understanding of e-equity crowdfunding in several aspects. For example, this study presents results that assist both researchers and practitioners in the Middle East and Saudi Arabia to develop an in-depth knowledge of e-equity crowdfunding by considering new dimensions such as RMO and information system success factors.

This study empirically investigates how ambidextrous innovations and their balancing affect the supply chain financing performance (SCFP) of small and medium-sized enterprises (SMEs), based on signaling theory. Moreover, this study explores the moderating effect of the breadth and depth of digital technology deployment on the relationship between ambidextrous innovations and the SCFP of SMEs.

A mixed-methods design is used, including a qualitative study and a quantitative study. Qualitative data have been collected from six multi-cases in different industries. Questionnaire data have been collected from 259 SMEs in China, and a multiple regression model is used to verify the research hypotheses.

The findings indicate that, in supply chain financing, both exploitative innovation and exploratory innovation are helpful in improving the SCFP of SMEs. For resource-constrained SMEs, a relative balance between exploitative innovation and exploratory innovation can help improve SCFP. The breadth of digital technology deployment can strengthen the relationship between exploitative innovation and SCFP, while the depth of digital technology deployment can weaken the relationship between exploratory innovation and SCFP. In addition, increasing the depth of digital technology deployment strengthens the positive correlation between the relative balance of ambidextrous innovations and SCFP.

To effectively obtain supply chain financing, SMEs can either concentrate their limited resources on a single type of innovation or use relative balance strategies to simultaneously pursue two innovations. In addition, in the process of obtaining supply chain financing by ambidextrous innovations, SMEs should appropriately deploy digital technologies.

This study first deconstructs the impact mechanism of ambidextrous innovation capabilities on SCFP based on signaling theory, and then discusses the balancing effect of ambidextrous innovations on SCFP in the cases of resource-constrained SMEs. This study also goes further and finds the negative moderating effect of digital technology deployment in the process of supply chain financing.

This study aims to investigate the engagement gap between Metaverse and in-person travel, the influence of Metaverse tourism on tourists and the industry and the challenges and responses associated with Metaverse technology. The study presents practical cases and highlights the implications of this research for practice, society and future research.

This study uses a literature review to explore concerns about Metaverse technology in tourism. It analyzes the difference between in-person travel and Metaverse tourism, the impact on tourists and the industry and challenges and responses to Metaverse. The review shows a rising trend in Metaverse tourism research.

These findings suggest differences between Metaverse tourism and in-person travel. By providing personalized travel options, social interaction, immersive experiences and soliciting visitor feedback, it is possible to enhance the tourist experience. Additionally, the study highlights the opportunities and challenges that Metaverse tourism presents to the tourism industry. The study provides practical cases in the tourism industry and implications for practice, society and future research.

The study’s implications for Metaverse tourism are practical, societal and future research-related. Metaverse technology can enhance the tourist experience through personalized options, social interaction, immersive experiences and feedback. This inclusivity can promote social equity and cultural exchange. Further research is needed to explore the social effects of Metaverse tourism and its long-term impacts on local communities, economies and the environment.

This study contributes by exploring the impact of Metaverse tourism, supporting academic research and practice. It fills a knowledge gap by analyzing the application of Metaverse technology in tourism, providing insights for researchers and practitioners. It offers practical guidance by identifying opportunities and challenges in Metaverse tourism, fostering industry innovation. Additionally, it informs policymakers about the impact of Metaverse tourism on development.

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.

The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

This paper takes Chinese A-share listed companies from 2007 to 2021 as research samples to investigate the influence of supplier concentration on debt maturity structure and its mechanism. It further analyzes whether the relationship between the two is different in the case of different monetary policies, collateral assets, and total debt. The research conclusion is of practical significance for enterprises to construct a balanced debt maturity structure and prevent financial risks.

This paper adopts the empirical research method. The data came from the CSMAR database, which eliminated ST and *ST and companies with missing data, resulting in a sample of 20,328. Stata16 was used for statistical analysis.

There is an inverted U-shaped relationship between supplier concentration and debt maturity structure, and market position and trade credit play an intermediary role. In the case of tight monetary policy, fewer collateral assets, and higher total debt, the inverse U-shaped relationship is more significant.

This paper examines the relationship between supplier concentration and debt maturity structure from a non-linear perspective for the first time, providing theoretical support for enterprises to form a reasonable debt structure, and deepening the theoretical cognition of the relationship between supplier concentration and corporate debt maturity structure.