Understanding consumers’ continuance intention towards mobile advertising: a theoretical framework and empirical study

While issues regarding mobile advertising have captured the interest and attention of both practitioners and academics, in practice success stories are rare. An understanding of the continuance intention to use such services can provide insights into failed mobile marketing campaigns, and help to improve the implementation of future ones. Therefore, it is important to examine the underlying drivers of loyalty with regard to mobile advertising. This study uses the expectation–confirmation model in conjunction with the perspectives of value and trust to derive an integrated model to better understand the motivations behind consumers’ continued use of mobile advertising. We conducted an empirical study consisting of an online survey of 508 consumers who had experience with mobile advertising. The results show that perceived value, perceived usefulness, and satisfaction all directly influence continuance intention. Furthermore, consumer satisfaction has a crucial intervening role in the relationships that perceived value, perceived usefulness, and confirmation have with continuance intention. The theoretical and practical implications of the findings are discussed. One key limitation of this research is that the majority of respondents were students, although this group is the chief user of mobile advertising. Future research could be extended to consider other drivers of loyalty in this context, such as cultural differences and personal behavioural characteristics.     

Valuation of online social networks taking into account users’ interconnectedness

Online social networks have been gaining increasing economic importance in light of the rising number of their users. Numerous recent acquisitions priced at enormous amounts have illustrated this development and revealed the need for adequate business valuation models. The value of an online social network is largely determined by the value of its users, the relationships between these users, and the resulting network effects. Therefore, the interconnectedness of a user within the network has to be considered explicitly to get a reasonable estimate for its economic value. Established standard business valuation models, however, do not account for these aspects sufficiently. Thus, we propose an economic model for the valuation of online social networks, which takes into account the users’ interconnectedness within the network. Furthermore, we analyze different centrality measures, which can be used to quantify users’ interconnectedness in online social networks and propose a measure which is based on the PageRank-algorithm. Finally, the practical application of the model is illustrated by an example of the European online social network XING.com.     

Understanding undergraduates’ problems from determinants of Facebook continuance intention

As social networks’ popularity has increased, so have the attendant problems. The purpose of this study is to identify the important problems by exploring the determinants of Facebook continuance intention from a negative perspective. A questionnaire survey and interview method is used to provide a deep understanding of both the problems and their causes. The research hypotheses are empirically evaluated using the responses from a field survey of 555 undergraduates. The results indicate that previous usage behaviour is the most important determinate of continuance intention. There is a positive causal relationship between perceived privacy self-protection and usage behaviour. In addition to a common privacy issue, this study discovers some problems such as underestimating the potential risks, having misconceptions and lacking legal and information security knowledge. Moreover, this study presents a diagnostic system that administrators can use to detect students’ key problems and understand the reasons behind students’ behaviour.     

Analyzing users’ activity in online social networks over time through a multi-agent framework

The number of people and organizations using online social networks as a new way of communication is continually increasing. Messages that users write in networks and their interactions with other users leave a digital trace that is recorded. In order to understand what is going on in these virtual environments, it is necessary systems that collect, process, and analyze the information generated. The majority of existing tools analyze information related to an online event once it has finished or in a specific point of time (i.e., without considering an in-depth analysis of the evolution of users’ activity during the event). They focus on an analysis based on statistics about the quantity of information generated in an event. In this article, we present a multi-agent system that automates the process of gathering data from users’ activity in social networks and performs an in-depth analysis of the evolution of social behavior at different levels of granularity in online events based on network theory metrics. We evaluated its functionality analyzing users’ activity in events on Twitter.     

Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study – A case of China

Although mobile purchase is convenient in the age of mobile commerce, many consumers still do not utilize mobile purchase to its full potential. From the mobile vendor’s perspective, retaining current customers and facilitating their continued purchase are crucial to create profitability and achieve a sustainable development. An understanding of the continuance intention towards mobile purchase can provide insights into mobile vendors’ marketing campaigns. Therefore, it is important to examine the determinants that impact continuance intentions of consumers for mobile purchase. Drawing upon information success model, flow theory and trust, this study proposed and empirically tested an integrated model to better understand the determinants of consumers’ continued intention to purchase on mobile sites. Empirical data from 462 users who had experience with mobile purchase were tested against the proposed research model by using structural equation modelling (SEM). The results indicated that information quality, and privacy and security concerns are the main factors affecting trust, whereas service quality is the main factor affecting flow. System quality, and privacy and security concerns affect satisfaction. Trust affects flow, which in turn affects satisfaction. These three factors together affect continued intention towards mobile purchase. The findings of this study provide several important implications for mobile commerce research and practice.     

Determinants of users’ intention to adopt m-commerce: an empirical analysis

The fast-growing penetration of mobile devices and recent advances in mobile technologies have led to the development of increasingly sophisticated services such as m-shopping for goods or services and m-payment. However, although the number of mobile subscribers is increasing, levels of actual m-commerce activities in many cases remain low. Determining what influences users’ intention to use m-commerce is therefore of growing importance. The purpose of this study was to investigate possible factors. To this aim, we developed a conceptual user adoption model based on technology acceptance model variables and on specific factors such as social influence, personal innovativeness, customization, and individual mobility. The empirical results show that social influence and customization significantly affect perceived usefulness; mobility, customization, and personal innovativeness significantly affect perceived ease of use; and perceived usefulness and perceived ease of use have a direct positive effect on behavioral intention.     

Understanding the determinants of users’ subjective well-being in social networking sites: an integration of social capital theory and social presence theory

In order to understand the factors affecting users’ well-being perception derived from social networking sites usage, this study integrates the perspectives of social presence theory and social capital theory to develop a research model. Data were collected from 305 users of Facebook in Taiwan to test the model. The findings reveal that structural capital, relational capital, and cognitive capital exert significant influences on subjective well-being. The results also reveal that structural capital and cognitive capital have positive influence on relational capital, while structural capital influences cognitive capital significantly. The results, on the other hand, show that awareness and affective social presence are the antecedents of structural capital, whereas cognitive social presence and affective social presence influence cognitive capital significantly. Finally, affective social presence is associated with relational capital positively. Theoretical and practical implications are discussed.     

Understanding online consumers’ purchase intentions: a contribution from social network theory

There is a dynamic and interconnected international setting shaped by the power of the Internet and social media. To gain more consumers, understand their behaviours and needs, and maintain closest relationships with them, businesses should understand how consumers behave in social media and how they vary in their purchase intentions. In the scope of the study, we integrate the social network theory and the theory of planned behaviour to analyse online consumers’ purchase intentions and to investigate their structural positions by analysing their friendships in social networks. We target Twitter users to conduct analysis due to Twitter's popularity in use, market penetration, and opportunity to work with open-source data. This study contributes to a better theoretical understanding of online consumers’ purchase intentions by integrating multiple theoretical perspectives. It expands the literature by considering both online consumers’ friendship network in Twitter and their individual online purchasing intentions. The study also guides e-marketers to design proper strategies for potential and current consumers and target the right sets of people in the social networks.     

Determinants of students’ continuance intention to use blogs to learn: an empirical investigation

This study examines factors influencing students’ continuance intention to use blogs to learn in an undergraduate-level course. The research uses constructs from relevant theoretical frameworks, including the technology acceptance model, social cognitive theory, innovation diffusion theory, and expectation–confirmation model. A survey administered to 108 university students in a Canadian university was analysed using the partial least squares technique. The results show that perceived usefulness and perceived compatibility have positive effects on students’ attitudes towards blog use; perceived ease of use did not. Perceived compatibility, perceived self-efficacy, and perceived support for enhancing social ties with blogs have significant effects on the positive impacts of learning with such tools. Attitude and positive impacts of learning with blogs influence satisfaction with blog use. Both attitude and satisfaction are determinants of students’ continuance intention to use blogs to learn. Satisfaction with blog use is the main predictor of continued use intention.     

The role of perceived e-health literacy in users’ continuance intention to use mobile healthcare applications: an exploratory empirical study in China

ABSTRACT

In recent years, mobile healthcare applications (MHAs) have boomed, providing several new kinds of health services and methods of information transmission. However, MHA vendors face a significant challenge in attracting users to adopt software continuously. Some recent studies recognized users’ perceived e-health literacy (PEHL) as a critical factor in continuance intention, but its influence was still unclear. In this paper, based on the elaboration likelihood model (ELM), we investigated how the users’ PEHL affects their continuance intention when adopting MHAs. We distributed convenience sample questionnaires by Wechat (similar to WhatsApp) in China, where hundreds of MHAs can be downloaded, and 273 valid samples were collected. The result shows that ELM works well in this model, with six of the eight hypotheses supported. The moderating effect of PEHL is largely significant for the peripheral route but not significant for the central route. The most interesting finding is that, with regard to continuance adoption, PEHL has a positive relationship with users’ satisfaction. Possible reasons are discussed, such as there could be a moderator on this relationship. Limitations, future studies and implications for theory, practice and policy are also given.     

Exploring users’ switching intention and behavior on social networking sites: Linear and nonlinear perspectives

The increasing integration of computers and networks into society has profoundly affected our lives in recent years. In Taiwan, use of SNSs – especially Facebook – has become the main action for the Internet users; accordingly, a number of scholars have explored people's intention to use, or actual use of, SNSs. However, few studies have investigated how and why users stop using one SNS and begin using another from the linear perspective. The findings are incomplete for the human behaviors which are complex and nonlinear systems. The purpose of this study is therefore to explore the relationship between SNS users’ switching intention and switching behavior based on structural equation modeling (SEM) and cusp catastrophe model (CCM). The key factors for the switching intentions and behaviors of SNS users were examined through empirical research, and a structural model was established. The model, which involved habits as a mediating factor, was used to conduct a qualitative and quantitative analysis on the switching behaviors of SNS users from a nonlinear perspective. This model will provide a new method for future researchers to analyze nonlinear behaviors as well as a dynamic decision support model for service providers to improve their business operation.     

Exploiting users’ social relations to forward data in opportunistic networks: The HiBOp solution

Opportunistic networks, in which nodes opportunistically exploit any pair-wise contact to identify next hops towards the destination, are one of the most interesting technologies to support the pervasive networking vision. Opportunistic networks allow content sharing between mobile users without requiring any pre-existing Internet infrastructure, and tolerate partitions, long disconnections, and topology instability in general. In this paper we propose a context-aware framework for routing and forwarding in opportunistic networks. The framework is general, and able to host various flavors of context-aware routing. In this work we also present a particular protocol, HiBOp, which, by exploiting the framework, learns and represents through context information, the users’ behavior and their social relations, and uses this knowledge to drive the forwarding process. The comparison of HiBOp with reference to alternative solutions shows that a context-aware approach based on users’ social relations turns out to be a very efficient solution for forwarding in opportunistic networks. We show performance improvements over the reference solutions both in terms of resource utilization and in terms of user perceived QoS.     

Using social networks to distort users’ profiles generated by web search engines

The Internet is one of the most important sources of knowledge in the present time. It offers a huge volume of information which grows dramatically every day. Web search engines (e.g. Google, Yahoo…) are widely used to find specific data among that information. However, these useful tools also represent a privacy threat for the users: the web search engines profile them by storing and analyzing all the searches that they have previously submitted. To address this privacy threat, current solutions propose new mechanisms that introduce a high cost in terms of computation and communication. In this paper, we propose a new scheme designed to protect the privacy of the users from a web search engine that tries to profile them. Our system uses social networks to provide a distorted user profile to the web search engine. The proposed protocol submits standard queries to the web search engine; thus it does not require any change in the server side. In addition to that, this scheme does not require the server to collaborate with the users. Our protocol improves the existing solutions in terms of query delay. Besides, the distorted profiles still allow the users to get a proper service from the web search engines.     

The impact of online community position on online game continuance intention: Do game knowledge and community size matter?

This study attempts to investigate how a player's position in an online gaming community leads to his or her continuance intention toward a Massive Multiplayer Online Game (MMOG) from the perspective of social capital theory. Using subjective and objective data collected from 340 players in a representative MMOG, our results reveal that community position significantly affects community trust and perceived social value, which in turn positively influence MMOG continuance intention. Furthermore, this study provides support for the moderating effects of game knowledge and community size on the proposed model. This study concludes with research limitations and theoretical and managerial implications.     

Understanding users’ continuous content contribution behaviours on microblogs: an integrated perspective of uses and gratification theory and social influence theory

ABSTRACT

Microblogs are revolutionising the way users produce, consume and distribute short content. The continuous content contributions of users are crucial for the sustainable development of microblogs. Knowledge regarding this user behaviour is scarce. Based on the uses and gratifications theory (U&G) and the social influence theory (SIT), this paper proposes an integrated research model with the aim of understanding the factors that affect users’ continuous content contribution behaviours (CCCB) on microblogs. The data were collected from 379 microblog users in China. The empirical results indicate that perceived gratification had a positive but surprisingly trivial effect on continuous content contribution behaviours. Social influence had a strong and significantly positive effect on users’ CCCB, it also had a positive moderating effect on the relationship between perceived gratification and CCCB. Users’ perceived gratification was positively affected by the antecedents of self-expression, anticipated extrinsic rewards and anticipated reciprocity but negatively affected by privacy concerns. The platform attributes of microblogs (i.e. accessibility and interactivity) also influenced users’ perceived gratification. This research contributes to social media research with regards to the theory of users’ CCCB.     

Understanding users’ dynamic behavior in a free trial of IT services: A three-stage model

A free trial of an information technology service (ITS) provides users an opportunity to obtain direct usage experience without purchase commitment, which can significantly reduce their uncertainty about the utility and quality of the ITS and promote their intention of final purchasing. Previous studies of user behavior in a free trial of ITS have mainly focused on either the adoption intention in the pre-trial stage or purchase intention in the post-trial stage. There is a lack of study investigating the trial stage that facilitates the transition and connection between these two separately studied stages. In this study, we view free trial as a motivated learning process and propose a Three-Stage Model (TSM) based on the learning motivation theory and reference-dependent theory to investigate users’ free trial behavior dynamics in moving from motivation to trial, making efforts to gain trial experience, and finally making a further purchase decision after the trial. We collected 377 users’ free trial experience to test our TSM using partial least squares-based structural equation modeling. Our results indicate that the perceived trial benefit and social influence strongly motivate user’s willingness to trial and that the utility experience and flow experience gained through trial effort leads to a willingness to accept and ultimately affect user’s willingness to pay through the mediation effect of expected additional value and price justification. Our study contributes to the theory that explains the dynamics of user decision-making behavior in the context of a free trial of ITS.     

Predicting the influence of users’ posted information for eWOM advertising in social networks

Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users’ posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post’s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.     

Understanding the intentions of users to ‘stick’ to social networking sites: a case study in Taiwan

Social networking sites (SNSs) are the most popular social platforms for developing personal networks. They provide multiple interactive functions for users to create and use large social networks. To determine why people exhibit ‘stickiness’ to SNSs, this study uses the uses and gratifications theory as an underlying structure and builds the research model with factors of motivational needs and interactivity. Our results showed that social needs, information needs, human–message interaction, and human–human interaction are crucial factors that affect the ‘stickiness’ of users to SNSs. The implications of these findings are presented in this paper.     

Understanding online customer repurchasing intention and the mediating role of trust – an empirical investigation in two developed countries

Although e-commerce adoption and customers’ initial purchasing behavior have been well studied in the literature, repeat purchase intention and its antecedents remain understudied. This study proposes a model to understand the extent to which trust mediates the effects of vendor-specific factors on customers’ intention to repurchase from an online vendor. The model was tested and validated in two different country settings. We found that trust fully mediates the relationships between perceived reputation, perceived capability of order fulfillment, and repurchasing intention, and partially mediates the relationship between perceived website quality and repurchasing intention in both countries. Moreover, multi-group analysis reveals no significant between-country differences of the model with regards to the antecedents and outcomes of trust, except the effect of reputation on trust. Academic and practical implications and future research are discussed.     

Enhancing students’ knowledge building through utilising social interactions in an online learning environment

ABSTRACT

In the new “open world” of information, educational systems should involve students in constructing new knowledge of value to a community out of fragmentary information. The already proposed Knowledge Building (KB) approaches typically support only a few general-purpose activities due to the constraints of the utilised web-based environments. To organise and facilitate students’ KB during course activities, this study incorporated services provided by DoosMooc social learning environment into a knowledge transformation model. This approach is completely adapted to an educational context and allows time for iterations, helping students to both contribute to social KB processes and take collective responsibility for improving their understanding of authentic problems. The features provided by the introduced environment support and assess students’ KB activities and facilitate processes of creating, representing, organising, and reviewing different types of knowledge artefacts. The results of a semester-long experiment indicate that the approach and the corresponding instructional design thereof could successfully organise students’ KB activities and facilitate the required interactions. This study reports the impacts of parameters such as learner expertise and quality of shared knowledge on the planned KB processes, and investigates the relationships between students' KB activities and learning achievements.