Search results

In order to meet the different quality of service (QoS) requirements of vehicle-to-infrastructure (V2I) and multiple vehicle-to-vehicle (V2V) links in vehicle networks, an efficient V2V spectrum access mechanism is proposed in this paper.

A long-short-term-memory-based multi-agent hybrid proximal policy optimization (LSTM-H-PPO) algorithm is proposed, through which the distributed spectrum access and continuous power control of V2V link are realized.

Simulation results show that compared with the baseline algorithm, the proposed algorithm has significant advantages in terms of total system capacity, payload delivery success rate of V2V link and convergence speed.

The LSTM layer uses the time sequence information to estimate the accurate system state, which ensures the choice of V2V spectrum access based on local observation effective. The hybrid PPO framework shares training parameters among agents which speeds up the entire training process. The proposed algorithm adopts the mode of centralized training and distributed execution, so that the agent can achieve the optimal spectrum access based on local observation information with less signaling overhead.

This study aimed to bibliometrically and visually analyze and review hospitality and tourism marketing studies published from 2000–2020.

A total of 3,942 articles collected from the databases of Social Science Citation Index (SSCI) and Science Citation Index Expanded (SCI-E) in the Web of Science (WoS) along with their references were used for analyses. The bibliometric software HistCiteTM and literature measurement visualization tools, VOSviewer and CiteSpace, were employed to analyze the selected articles.

The results of the study demonstrated top influential scholars and institutions, intellectual structure and emerging trends of the study topics, and future research opportunities in the field of hospitality and tourism marketing.

First, academic influence of a scholar was evaluated by citations of his/her publications, which did not take the order of authorship into consideration. Second, this study was restricted to the English language journals. Third, other types of published documents related to the studied field such as review papers were not considered by this research.

In comparison to traditional qualitative analysis such as content analysis, bibliometric analysis is a more objective approach to vividly demonstrate trends and performance of a research field, offers unique insights for its advancement with wider inclusiveness of a larger amount of data.

In recent years, counterproductive knowledge behavior (CKB) and its types have received increasing interest in knowledge management as the degree of knowledge sharing and innovation in enterprises continues to increase. A rapidly growing number of studies have shed light on the important antecedents and consequences of employees’ CKB. However, the various labels, conceptualizations and operationalizations of CKB have fragmented this body of research. This study aims to systematically integrate the effects of the six types of organizational characteristics on CKB and further draws more general conclusions based on the results of previous studies.

Based on a survey of 103 effect values responsible for 52 CKB samples, the authors use the ABC theory to explore the effects of the six types of organizational characteristics on CKB. Moderator analysis were performed to resolve inconsistencies in empirical studies and understand the contexts under which CKB has the strongest or weakest effect.

The results showed that task interdependence and a positive organizational atmosphere, in general, negatively affect employees’ CKB in the moderation analysis. In contrast, workplace discomfort, negative organizational atmosphere, internal competition and time pressure positively and partly affect employees’ CKB. The direction and magnitude of these effects were affected by emotional factors, knowledge personnel types and sample sources. Discussing the theoretical, methodological and practical implications of these findings can offer a guiding framework for future research.

Better control of employees’ CKB is not achieved by adjusting organizational characteristics alone but by combining personal characteristics and mood changes with it to balance organizational characteristics and CKB. Furthermore, the large-sample joint study integrated the conceptual definition of CKB. The multivariate data study provided more reliable conclusions and a solid theoretical foundation for CKB research areas.

The purpose of this paper is to prepare a multifunctional nanocomposite that is slow-release and resistant to seawater corrosion and biofouling corrosion and to explore the synergistic effect between the two corrosion inhibitors.

The morphology, structure and release properties of CAP@HNTs, BTA@HNTs and CAP/BTA@HNTs were investigated by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, specific surface area analysis and UV spectrophotometry. The corrosion resistance and antimicrobial properties were investigated by electrochemical measurements and bioinhibition rate tests, and the synergistic effect between the two corrosion inhibitors was explored by X-ray photoelectron spectroscopy.

The CAP/BTA@HNTs are responsive to acidic environments and have significantly improved antibacterial and corrosion resistance compared with CAP@HNTs and BTA@HNTs. CAP and BTA have a positive synergistic effect on anticorrosion and antifouling.

Two types of inhibitors, anticorrosion and antifouling, were loaded into the same nanocontainer to prepare a slow-releasable and multifunctional nanocomposite with higher resistance to seawater corrosion and biocorrosion and to explore the synergistic effect of CAP and BTA on corrosion resistance.

The purpose of this paper is to explore the facilitating and inhibitory factors on paid app downloading intentions based on an integrated valence theory, considering two social environmental factors and two intermediate variables: perceived value and perceived trust.

This study is based on the integrated valence theory. After collecting users’ data, partial least square analysis is used to examine the main driving and constraining factors for users to download paid apps in Apple mobile devices.

The empirical results show that mediated through perceived value, perceived usefulness and perceived compatibility are the absolute positive factors that affect user’s willingness to purchase apps, whereas perceived cost is the main barrier for users to do so. Social environment where the users are in also plays an important role in their purchase intentions.

This study hopes to offer guidance to paid app developers and general app markets, and to help expand the consumer group, make the purchase experience more efficient and promote the development of paid app market.

The finding not only enriches the adoption theory of mobile apps from the perspective of valence theory, but also provides pricing and functional suggestions for platform suppliers and software developers of paid apps.

Mobile Applications (App) privacy has become a prominent social problem. Compared with privacy concerns, this study examines a relatively novel concept of privacy fatigue and explores its effect on the users’ intention to disclose their personal information via mobile Apps. In addition, the personality traits are proposed as antecedents that will induce the personal perception of privacy fatigue and privacy concerns differently.

Data were collected from 426 respondents. Structure equation modeling was used to test the hypotheses.

The findings describe that App users’ intention toward personal information disclosure is determined by privacy fatigue and privacy concerns, but the former has a greater impact. With minor exceptions, the two factors are also influenced by different personality traits. Specifically, neuroticism has positive effects on privacy fatigue, but agreeableness and extraversion have presented the opposite results on the two variables.

This research is very scarce to examine the joint effects of privacy fatigue, privacy concerns and personality traits on App users’ disclosing intention. In doing so, these results will be of benefit to App providers and platform managers and can be the basis for a variety of follow-up studies.

While previous research just focuses on privacy concerns, this study explores the critical roles of privacy fatigue and opens up a new avenue of emotion-attitude analysis that can further increase the specificity and richness of users’ privacy research. Additionally, implications for personality traits as antecedents in the impact of App users’ privacy emotions and attitudes are discussed.