Why should I pay? Exploring the determinants influencing smartphone users’ intentions to download paid app

The objectives of this study are to investigate (1) the positive effects of smartphone users’ core self-evaluations (CSEs), online consumer conformity, and the social identity of their emotions, (2) the effects of their positive emotions on their trust, and (3) the effects of their trust on their intention to purchase paid apps and willingly engage in co-production. A questionnaire was employed to examine the relationship between the users’ CSEs, online consumer conformity, and social identity, on the one hand, with their intention to purchase paid apps and willingly engage in co-production on the other hand. The findings were as follows: (1) CSE, online consumer conformity, and social identity positively affected the users’ emotions, (2) positive emotions had a significantly positive effect on user trust, and (3) trust had significantly positive effects on the users’ intention to purchase paid apps.     

Identifying associations between mobile social media users’ perceived values,attitude, satisfaction,and eWOM engagement: The moderating role of affective factors

Recently, the explosive growth of mobile social media technologies has dramatically transformed individuals’ interpersonal interaction, decision-making, and daily lifestyles. The primary objectives of this current article are to investigate the possible influences of perceived values (hedonic and utilitarian) on WeChat users’ affective responses (attitude and satisfaction) and electronic word-of-mouth (eWOM) engagement. This study represents one of the few that utilized customer-perceived value theory and uses and gratifications theory to establish a conceptual framework to determine consumers’ word-of-mouth behaviors in the WeChat setting. Based on a web-based survey of 408 WeChat users, structure equation modeling was implemented to identify and confirm the hypothesized research model. Overall, the results reveal that hedonic value and utilitarian value positively and significantly impact WeChat users’ attitudes and anticipated satisfaction. Additionally, satisfaction has a significant influence on eWOM engagement. Furthermore, utilitarian value is discovered to exert a significant indirect effect through satisfaction on eWOM engagement. The obtained outcomes offer fresh insight into whether and how mobile social media could promote mobile social media users’ attitudes and gratification which subsequently would facilitate indicators of eWOM engagement in contemporary mobile-mediated context.     

Should I scan my face? The influence of perceived value and trust on Chinese users’ intention to use facial recognition payment

While China has seen the widespread adoption of facial recognition payment, concerns over the potential risks impede the further growth of user acceptance. Drawing on the perspectives of perceived value and trust, we developed a research model to explore how the Chinese users’ trade-off between perceived benefits (perceived convenience and perceived novelty) and perceived risks (perceived privacy risk and perceived financial risk) influences their usage intention. Based on survey data from 1,200 Chinese mobile payment users, this study uses structural equation modeling to examine the hypotheses. Our results show that perceived convenience positively influences perceived value, while privacy risk and financial risk negatively influence perceived value and trust. Although perceived novelty has no significant effect on perceived value and trust, perceived value positively influences trust, and both of them have a positive effect on the intention to use. Furthermore, our moderation analysis indicates that the influence of perceived value on the intention to use is stronger among users who consider facial information to be more sensitive. The theoretical implications for research as well as the practical implications for practitioners are also discussed.     

A survey of ‘young social’ and ‘professional’ users of location-based services in the UK

The objective of this study was to assess the response to location-based services (LBS) by three key demographic groups within the United Kingdom. This study took the form of a survey of relevant demographics, attitudes and consumer behaviour undertaken via a web-based survey. Results are based on over 1200 respondents, filtered and segmented into three demographic groups who are typically early adopters of new technology. There were positive attitudes towards a range of LBS, with the major exception being location-based advertising. There were mixed views towards location-based gaming and safety camera information. There were low levels of awareness of many services. The levels of use were typically under 20% for all types of LBS.     

Drone delivery: Factors affecting the public’s attitude and intention to adopt

Drones, or unmanned aerial vehicles (UAVs), show high potential for parcel delivery. Drone delivery may be faster, less expensive, and more eco-friendly than traditional delivery modes such as trucks. Drones are not yet in commercial use, but many companies such as Amazon and Google have done pilot tests, and they will probably become common in the near future. Regardless of what companies decide, however, adoption intention among customers is vague. This study explores the factors affecting attitudes to drone delivery service and intention to adopt among 296 U.S. consumers by online survey. The results demonstrate that the relative advantages of speed and environmental friendliness, along with complexity, performance risk, and privacy risk, affect drone delivery adoption. Personal innovativeness also positively affects adoption intention. Furthermore, the results show that the determinants of drone delivery adoption differ according to the customer’s area of residence.     

Exploring the differences of users’ interaction behaviors on microblog: The moderating role of microblogger’s effort

On microblog, users interact with microbloggers via three behaviors—forward, comment, and like. Prior studies have paid more attention to forward, little research has investigated the differences between these three behaviors. Besides, there is a lack of an integrated theoretical framework that explores whether the same factors have different impacts on the behaviors. This study investigates the differences that users’ interactions behaviors in the presence of the same factors. Building upon elaboration likelihood model (ELM) and text mining, the propose of this study is to systematically explore the relationships among content features (topical relevance, information richness) of post, source features (credibility, social ties and activeness) of microblogger, and users’ interaction behaviors. More importantly, we explore whether such relationships are contingent on microblogger’s effort (material motivation and information originality). A panel data was constructed using a total of 437,533 posts from Sina-Weibo, the largest micro-blogging platform in China. The empirical results show that topical relevance and social ties significantly affect users’ interaction behaviors. Source credibility and source activeness are partially influence the behaviors. additionally, there are positive and negative effects between information richness and the behaviors, indicating that both the bright and dark side of information richness. In addition, the microblogger’s effort moderate the most of the relationships between content features and the three behaviors. These results indicate that there are differences among the three behaviors. Overall, these findings could offer new insights into the deep understanding of the differences among users’ interaction behaviors on microblog.     

Determinants of backers’ funding intention in crowdfunding: Social exchange theory and regulatory focus

Crowdfunding has become a novel and popular financing channel worldwide; however, the success rate of crowdfunding projects on most platforms is less than 50%. Thus, project proponents should not only try to attract more visitors but also understand their funding intention, which is particularly important in increasing the success of fundraising projects. Based on social exchange theory, this study examines the key factors influencing backers’ funding intention. More than 204 experienced backers in Taiwan participated in this study, and structural equation modeling was applied for data analysis. Results show that commitment has a remarkable and positive effect on funding intention. Interestingly, perceived risk was found to be positively associated with funding intention, which challenges the conventional view of perceived risk having a negative effect on usage intention. The moderating effects of regulatory focus and funding amount are also discussed. This study not only indicates the key determinates of backers’ funding intention for management but also explains the potential significance of positive perceived risk in funding intention to the literature.     

VRS-DB: preserve confidentiality of users’ data using encryption approach

We focus on security and privacy problems within a cloud database framework, exploiting the DataBase as a Service (DBaaS). In this framework, an information proprietor drives out its information to a cloud database professional company. The Data-Owner (DO) encrypts the delicate information before transmission at the cloud database professional company end to offer information security. Current encryption ideas, nonetheless, are just halfway homomorphic as all of them intend to enable an explicit kind of calculation, which is accomplished on scrambled information. These current plans can’t be coordinated to solve genuine functional queries that include activities of various types. We propose and evaluate a Verifiable Reliable Secure-DataBase (VRS-DB) framework on shared tables along with many primary operations on scrambled information, which enables information interoperability, and permits an extensive possibility of Structured Query Language (SQL) queries to be prepared by the service provider on the encoded data. We show that our security and privacy idea is protected from two forms of threats and are fundamentally proficient.     

Modeling of piezo actuator’s nonlinear and frequency dependent dynamics

To facilitate on-line identification and implementation of a piezoelectric actuator model for precision machining, this paper describes a hybrid hysteresis model integrating the classical Preisach model and a neural network. The incorporation of a neural network enables on-line model identification from operating data of a piezo (a great contrast to the tedious calibration process required by the classical Preisach model). The model is then extended to describe a piezo actuator’s frequency dependent behavior which is not possible for the classical model. Experimental results confirmed the accuracy of both models and the superiority of the extended one.     

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

The COVID-19 pandemic has caused major global changes both in the areas of healthcare and economics. This pandemic has led, mainly due to conditions related to confinement, to major changes in consumer habits and behaviors. Although there have been several studies on the analysis of customers’ satisfaction through survey-based and online customers’ reviews, the impact of COVID-19 on customers' satisfaction has not been investigated so far. It is important to investigate dimensions of satisfaction from the online customers’ reviews to reveal their preferences on the hotels' services during the COVID-19 outbreak. This study aims to reveal the travelers’ satisfaction in Malaysian hotels during the COVID-19 outbreak through online customers’ reviews. In addition, this study investigates whether service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. Accordingly, we develop a new method through machine learning approaches. The method is developed using text mining, clustering, and prediction learning techniques. We use Latent Dirichlet Allocation (LDA) for big data analysis to identify the voice-of-the-customer, Expectation-Maximization (EM) for clustering, and ANFIS for satisfaction level prediction. In addition, we use Higher-Order Singular Value Decomposition (HOSVD) for missing value imputation. The data was collected from TripAdvisor regarding the travelers’ concerns in the form of online reviews on the COVID-19 outbreak and numerical ratings on hotel services from different perspectives. The results from the analysis of online customers’ reviews revealed that service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. In addition, the results showed that although the customers are always seeking hotels with better performance, they are also concerned with the quality of related services in the COVID-19 outbreak.     

Data centers’ services restoration based on the decision-making of distributed agents

Telecommunication Systems - The increasing number of companies that are migrating their IT infrastructure to cloud environments has been motivated many studies on distributed backup strategies to...     

Determinants of live streamers’ continuance broadcasting intentions on Twitch: A self-determination theory perspective

Empowered by today’s rich tools for a media generation, the rapid development of the Internet, and collaborative production, live streaming services that allow anyone to launch a stream or watch someone else perform over the Internet have gained great popularity. This study endeavored to ascertain the determinants compelling live streamers to continue broadcasting on Twitch, a live streaming video platform. This novel research model used self-determination theory to investigate different motivational forces (i.e., intrinsic and extrinsic) that drive live streamers’ continuance broadcasting intentions. Both intrinsic and extrinsic motivation significantly influenced live streamers’ performance expectancies, but not their perceived website attractiveness. Efforts to influence perceived website attractiveness must be made via performance expectancies. Performance expectancy and perceived website attractiveness subsequently affect streamers’ continuance of broadcasting intentions on Twitch. This study yields important managerial implications for live streaming platforms to improve their service design and understanding of streamers’ behavioral intentions.     

The buffering effect of flow experience on the relationship between overload and social media users’ discontinuance intentions

There is a growing need to understand why users discontinue using social media platforms. Understanding the antecedents of such decisions and the moderators that govern the antecedent effects can help users reach such decisions, and assist service providers in mitigating them. From a theoretical standpoint, there is a need to enrich the theoretical account of social media discontinuance phenomena. To address these issues, we integrate the “stimulus-organism-response” (S-O-R) framework and flow theory. We consequently portray the direct, indirect and moderating roles of flow experience in mitigating discontinuance intentions. We test this model via a survey of 502 WeChat users. The results support the S-O-R model and indicate that social overload, information overload, and communication overload (stimuli) increase the fatigue feelings (organism) of social media users, which, in turn, increase their social media discontinuance intentions (response). By combining the S-O-R perspective with flow theory, we show that flow experience not only help reduce users’ perceptions of fatigue and discontinuance intentions, but also moderate (weaken) the effects of fatigue on discontinuance intentions. Flow experience, therefore, serves as a means to inhibit the formation of social media discontinuance intentions, even when overload and fatigue persist. The present research also has several valuable theoretical and practical implications.     

Millennials’ socio-psychology and blood donation intention developed from social media communications: A survey of university students

Less than 1% of South-Africans donate blood annually. New donors are required, especially from Millennials, who are large in numbers and influential. Being more receptive to social media communications and altruistic, millennials are the hope of safe blood supply. However, the drivers of millennials’ positive attitude and behavioural intentions (BI) towards donating blood need examination. This study used ideas from Social Cognition Theory, Health Belief Model and Theory of Planned Behaviour to examine how social media communications impact blood donation attitudes and behavioural intention through some socio-psychological outcomes among young adult Millennials at a university in South-Africa. Quantitative data was collected from 650 respondents. Structural equation modelling results revealed that social media communications positively impacted awareness, perception, peers, family, and behavioural intention. Motivation, awareness, peers and family positively influenced attitudes, which in turn, predicted blood donation intention. Blood donations agencies and public policy-makers should seek ways to convert Millennials’ positive attitudes and BI into actual blood donation.     

Digital natives’ intention to interact with social media: Value systems and gender

Social media research focuses predominantly on the link between attitude, behaviour and intention, and rarely takes value systems into account. Values are expected, through intervening variables, to affect intention directly or indirectly. Starting from the Theory of Trying, the aim of this study is to investigate how value systems affect digital natives’ intention to interact with social media. By using Fuzzy Set Qualitative Comparative Analysis (fsQCA), an empirical analysis involving data from 116 social media users is carried out to examine how global and domain-specific values, attitude towards trying and gender affect the intention to interact. The results of a configurational analysis show that gender appears to affect many of the configurations leading to the outcome of interest. There are two configurations in which, regardless of gender, global values, domain-specific values and attitude towards trying cause the outcome. The findings indicate that there is no single condition necessary to ensure the outcome, but there are several different configurations of the conditions lead to outcome of interest.     

Understanding the effects of the textual complexity on government communication: Insights from China’s online public service platform

While texts are the primary carriers of information for government decision making, few studies have examined the role of textual complexity in government-citizen communication. Using a variety of natural language processing methods, this paper measured textual complexity from the perspectives of word complexity, logical complexity, and abnormal negative emotion based on the textual data of the 1.15 million online messages left by the citizens to government leaders on China’s online public service platform, and explored its impact on government responses. Based on the Double-hurdle model, this paper found that the government response can be composed of two decision-making processes: response-intention, which indicates whether to respond, and response-level, which represents the extent of response. For response-intention decision-making, the simpler the words and logic of the message, the more likely it is to receive a reply from the government. For response-level decision-making, messages with more complex words and logic received a higher level of government response. Abnormal negative emotion in the message significantly reduced the government’s response intention and response level, and the negative effect of abnormal negative emotion on response intention was much greater than on the response level. This study not only helps to understand how the government makes decisions based on textual information, but also has important value for responsive government construction and equalization of government services.     

Cloud service performance evaluation: status,challenges, and opportunities – a survey from the system modeling perspective

With rapid advancement of Cloud computing and networking technologies, a wide spectrum of Cloud services have been developed by various providers and utilized by numerous organizations as indispensable ingredients of their information systems. Cloud service performance has a significant impact on performance of the future information infrastructure. Thorough evaluation on Cloud service performance is crucial and beneficial to both service providers and consumers; thus forming an active research area. Some key technologies for Cloud computing, such as virtualization and the Service-Oriented Architecture (SOA), bring in special challenges to service performance evaluation. A tremendous amount of effort has been put by the research community to address these challenges and exciting progress has been made. Among the work on Cloud performance analysis, evaluation approaches developed with a system modeling perspective play an important role. However, related works have been reported in different sections of the literature; thus lacking a big picture that shows the latest status of this area. The objectives of this article is to present a survey that reflects the state of the art of Cloud service performance evaluation from the system modeling perspective. This articles also examines open issues and challenges to the surveyed evaluation approaches and identifies possible opportunities for future research in this important field.     

An efficient handover decision in heterogeneous LTE-A networks under the assistance of users’ profile

The increasing demand for wireless networks calls for the use of heterogeneous networks in order to fulfil user requirements. Mobility management is considered one of the important entities for such networks. The handover is one of the main features of mobility management in regard to the long term evolution advanced (LTE-A) system, which depends purely on the hard handover. The vertical handover decision is a significant component of heterogeneous networks; it authorizes the user equipment (UE) to migrate between the two-tier LTE-A wireless networks. Femtocell, or also known as the home-evolved nodeB (HeNB), has turned out to be a promising arrangement, as it enhances the coverage and the quality of service for users on one hand, and offloads the eNB on the other hand. In this paper, an advanced handover technique is presented, in terms of adding new and critical parameters, as well as combining between the present UE trajectory and the HeNB cell location. A polynomial function is used to predict the future UE position while the cosine function along with distance are used for the selection of an appropriate target cell. The proposed algorithm is evaluated and then compared to the present work based on the handover number, number of signaling measurements, packet delay ratio, packet loss ratio, and system throughput. Simulation of the LTE-Sim demonstrates that the proposed algorithm significantly reduces the number of handovers, the transmission measurement number, the packet delay ratio, and the packet loss ratio and increases system throughput.     

Data Service: Characteristics, Market Structure, and the Role of Operator

1　Introduction　Since the development of telecommunication technologymake the operator able to offer data service to subscribers inthe mid 1990s, operators of various countries have madeenormous efforts to develop data service. Currently, the ar gument on 3G ( 3rd Generation, International MobileTelecommunications 2000) focuses on how to find, develop,and popularize application services in data service markettoo. Some researchers propose that even NTT DoCoMo can n…