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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.

The literature on cohabitation intimates a clear line between marriage and cohabitation where the latter lacks a formal or legal backing. This understanding overlooks contextual issues which complicate definitions of cohabitation. With evidence from historical and contemporary literature on cohabitation among the Asante of Ghana, this chapter argues that traditional social practices coupled with the plurality of legal frameworks governing marriage in Ghana, leads to subjective constructions and interpretations of cohabiting unions. Consequently, there are situations where one form of partnership would qualify as marriage, whilst the same would be considered a cohabiting union in other circumstances. Again, the sense in which cohabitation functions as a prelude, an alternative or equivalent to marriage among the Asante differs significantly from what pertains in other societies. The chapter, therefore, calls into question the oversimplified meanings of cohabitation often based on the assumption of a dualistic relationship between marriage and cohabitation. The chapter concludes that the definition of cohabitation among the Asante and some sections of the Ghanaian public is fluid and not as clearly defined as it is in other parts of the world, especially the Global North. Given this reality, rather than generalized interpretations of cohabitation, researchers need to consider the contextual differences and understandings of cohabitation in their studies.

The increased usage of smartphones has made mobile payment services (MPS) popular among millennials, but it is uncertain if this shift in behavior is temporary due to situational factors like the pandemic or a long-term trend due to technological advances. This study uses the diffusion of innovation (DOI) literature to assess an integrated model including smartphone addiction, technology-related and consumer-related factors that influence consumers' intention to use MPS. It also explores the interplay of situational variables and smartphone addiction in shaping this relationship.

The authors base the conceptual model on the theory of rational addiction and the theory of optimal flow. This model is then empirically validated through data collected from seven hundred users of MPS in India. Research hypotheses are tested using structural equation modeling and multi-group analysis.

The study finds that smartphone addiction has a positive impact on millennials' perceived advantages, compatibility, trialability and observability of MPS but does not significantly affect their perceived complexity or risk. The results also suggest that the relationship between smartphone addiction and MPS is moderated by situational factors. In low-priority situations, smartphone addiction strengthens millennials' perceptions and intentions to use MPS, while in high-priority situations, situational factors overshadow the impact of smartphone addiction.

The findings of the study enable organizations to capitalize on smartphone addiction-driven MPS adoption behavior to sustain long-term usage behavior by appropriately understanding the context/situation which drives MPS adoption.

Consumers worldwide are increasingly adopting mobile payments. However, despite its global popularity, this innovation did not diffuse among American consumers extensively. As of 2019, less than 30% of smartphone users in the USA engaged in mobile payments. The purpose of this paper is to investigate drivers of mobile payment adoption in the USA and to explore the mediating factors of consumers’ attitudes toward mobile payments.

Data were collected through Amazon M-Turk in the USA with 222 final respondents. Participants received an incentive to participate in this study. The measurement and structural models were evaluated by the component-based partial least squares (PLS) approach using Smart-PLS 3 software.

The study shows several factors affecting consumers’ attitudes toward mobile payments. Specifically, relative advantage, compatibility, observability, perceived security and convenience influence attitudes toward mobile payments and, consequently, behavioral intent to use mobile payment technology. This investigation contributes to the ongoing inquiry on the adoption of mobile payment technology in the USA. It offers specific insights for managers on how to increase mobile payment adoption. The study establishes a modified diffusion of innovations (DOI) model of consumer attitudes toward the use of mobile payments.

The objective of this study is to focus mainly on consumers in the USA, and it limits the generalizability of this study.

This study contributes to the current research on mobile payment adoption. Based on theoretical considerations, the authors derived a research model specifying critical drivers of an individual’s intentions to use mobile payments. Specifically, we establish a modified DOI-based model of consumer attitudes towards mobile payments. It shows several contributing factors affecting consumers’ attitudes toward mobile payments. The paper has important managerial implications aimed at the increase of the diffusion of mobile payments in the USA.

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.

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.

This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.

The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.

The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

This study investigates whether and how the service quality of artificial intelligence (AI) chatbots affects customer loyalty to an organization.

Based on the sequential chain model of service quality loyalty, this study first classifies AI chatbot service quality into nine attributes and then develops a research model to explore the internal mechanism of how AI chatbot service quality affects customer loyalty. The analysis of survey data from 459 respondents provided insights into the interrelationships among AI chatbot service quality attributes, perceived value, cognitive and affective trust, satisfaction and customer loyalty.

The results show that AI chatbot service quality positively affects customer loyalty through perceived value, cognitive trust, affective trust and satisfaction.

This study captures the attributes of the service quality of AI chatbots and reveals the significant influence of service quality on customer loyalty. This study develops research on service quality in the information system (IS) field and extends the sequential chain model of quality loyalty to the context of AI services. The findings not only help an organization find a way to improve customers' perceived value, trust, satisfaction and loyalty but also provide guidance in the development, adoption, and post-adoption stages of AI chatbots.

Because the success of m-payment services depends on the enablers and barriers that affect user satisfaction, the present research explores the effects of perceived value and sacrifices on users' satisfaction with m-payment services. The predicted relationships among perceived value, perceived sacrifices, users' satisfaction, continuance intention, word-of-mouth (WOM), shopping effectiveness, quality of life (QOL) and stickiness were established based on the mobile technology acceptance model (MTAM) and the value-based adoption model (VAM).

A representative data sample of 430 Egyptian banking clients was analyzed to test the hypotheses using partial least squares-structural equation modeling (PLS-SEM).

The findings revealed that all perceived value constructs significantly positively affect users' satisfaction. Moreover, all perceived sacrifice constructs significantly negatively affect users' satisfaction. Users' satisfaction, in turn, has a significant positive effect on continuance intention, WOM, shopping effectiveness, QOL and stickiness with m-payment services.

This is the first study to examine several levels of m-payment outcomes, including m-payment, consumer and bank outcomes, based on the integration of MTAM and VAM models.

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.