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Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.

Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.

Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.

This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.

Previous research suggests that perceived risk is an important ingredient in the consumer decision‐making process. The purpose of the present study is to investigate what are the perceived barriers to Internet usage and e‐marketing by both users and non‐users. By understanding these potential obstacles, more efficient marketing strategies will become available that will drive Internet use and e‐commerce. A detailed perceived risks map has been developed using a qualitative research paradigm. We suggest a model with the factors affecting the Internet’s perceived risk elements. The factors are demographic traits and usage behavior characteristics. The model is tested against a sample of 465 employed adults.

With over-the-top (OTT) streaming services rapidly transforming the media industry and saturating the market, the authors' study seeks to enrich the goal-directed behaviour model by exploring how perceived risks and descriptive norms influence OTT consumption.

Survey data from OTT subscribers were collected online to assess their risk behaviours. The 353 responses obtained were analysed with SmartPLS, validating the structural equation modelling (SEM) through structural and measurement model verification.

The authors' findings illustrate that descriptive norm, perceived behavioural control, as well as positive and negative anticipated emotion (NEM) and attitude, contribute positively to the desire to engage with OTT streaming services. Interestingly, the authors' study contradicts common assumptions, revealing that subjective norms do not significantly impact the propensity to utilise OTT services. This counterintuitive finding necessitates a reconsideration of prevalent theories and contributes to a nuanced understanding of OTT adoption determinants.

The data gathering for this study were conducted from the perspective of a single nation. Therefore, caution must be exercised when generalising this study's results.

The practical ramifications of this research are vast, providing OTT service providers and marketers with actionable insights to maximise user engagement and navigate perceived risks related to OTT service adoption and consumption.

This study's exploration of perceived risks and descriptive norms enhances the goal-directed behaviour model's breadth, facilitating a holistic comprehension of the constructs shaping OTT consumption behaviours. It would be the first attempt to combine perceptual, affective and behavioural factors and perceived risks to understand the user's predisposition to engage in OTT streaming services.

The aim of this paper is to analyse the determinants of social networking site loyalty, paying special attention to the roles of user attitude, perceived risk and satisfaction.

The impact of uses and gratifications of social networking sites, attitude, perceived risks and satisfaction on social networking site loyalty is tested through structural equation modelling techniques. The sample consisted of 811 Spanish social networking site users collected through a personal survey. Risk is measured as a formative construct.

Data analysis shows that attitude is a key variable in increasing satisfaction and loyalty towards social networking sites. Sociability and entertainment gratifications and perceived risks (psychological, time loss and social) are the main drivers of user attitude towards social networking sites.

This research enables managers to know what aspects to highlight in their communication strategies to increase social networking site use and positive word‐of‐mouth. The research findings show managers that social networking site content should provide fun and foster user interactions in order to improve user attitude. Practical recommendations to increase social networking site satisfaction and loyalty and guidelines to reduce perceived risk dimensions are also provided.

Despite the importance of social networking sites for companies, only limited work has been done to identify motivators and barriers of social networking site loyalty. This work aims to combine the influence of gratifications provided by social networking sites, perceived risks, attitude and satisfaction in order to construct an improved model for social networking site loyalty formation. Furthermore risk is measured as a formative construct because there is no reason to expect that risk dimensions in social networking site use are correlated.

Bike sharing becomes suddenly hot up in China since the end of 2016. However, few studies have focused on shared bicycle users’ behavior. To fill this research gap, this paper aims to develop an integrated model to investigate factors that affect shared bicycle users’ subjective well-being.

A field survey with 220 shared bicycle users is conducted to test the research model and hypotheses.

The highlights are that perceived value has positive effect on users’ life satisfaction. Specially, it is interesting to find that hedonic value has the greatest impact on users’ life satisfaction, followed by social value and utilitarian value. Perceived risks which including privacy risks, financial risks and functional risks act as a moderating role between perceived value and users’ life satisfaction.

First, the authors clear factors that affect users’ subjective well-being from the perspective of perceived value. The results deepen our understanding about the effect of perceived value on users’ subjective well-being. Second, the current researches have ignored the effect of perceived risks on users’ subjective well-being. The authors filled that gap and found that perceived risks which including privacy risks, financial risks and functional risks act as a moderating role between perceived value and users’ subjective well-being.

Multimedia content that is accessible through mobile devices has a larger size than other types of content (e.g. text, images). This may lead to higher prices for accessing the content via mobile devices, as mobile operators are capping mobile data billing plans in an effort to increase their revenues and prevent congestion. This poses problems for the users that are not willing/do not afford to pay the required price but still want to use multimedia content through the mobile networks. A price reduction for the user, as well as minimising bandwidth consumption can be obtained as a trade-off in multimedia quality. However, as previous research shows, not all people are willing to trade-off quality for a lower price; therefore, there is no straightforward approach to this problem. In this context, the purpose of this paper is to present a model of user willingness to pay for multimedia content quality as a function of the user risk attitude with the aim to provide personalised content depending on the user willingness to trade-off price for multimedia content quality.

A user model was proposed based on a literature review and an existing data set. A stereotypical approach was used where users are divided in two groups: risk averse and risk seekers. An experimental study involving six scenarios was used to validate the findings.

The results of the evaluation show that for the proposed user risk model, risk seekers preferred to pay for multimedia quality, whereas risk adverse users preferred to switch to a lower multimedia quality when monetary cost is involved. However, when the mobile data billing plan had the bandwidth limited, rather than a higher price to be paid when the bundle quantity was exceeded, the risk averse people’s preference for a lower quality still holds, but it does not show that most of the risk seekers prefer to pay for the multimedia quality.

This paper adds to the state of the art by providing a novel way to model the user preferences for multimedia quality based on their attitude towards risk, age, and gender.

Mobile data users, content providers (application service providers, over-the-top providers), mobile network operators (MNOs) and internet service providers (ISPs) could benefit from the results of this research. For mobile data users, the outcome of this research could be beneficial, as they can obtain personalised content based on their needs. From the content providers’ point of view, providing personalised content can lead to more satisfied users. It could also reduce the bandwidth consumption and the traffic to the server and/or proxy. Reducing the bandwidth consumption could lead to the possibility to acquire more customers and hence increase the revenues.

This is among the first studies to assess how the user preference towards multimedia quality if affected by the user attitude towards risk.

Social commerce websites have emerged as new platforms which integrate social media features with traditional commerce aspects to enhance users’ purchasing experience. The purpose of this paper is to examine the role of social factors such as trust toward site members in determining users’ trust and risk evaluations, and the role of social commerce use habit in attenuating users’ rational risk and trust considerations for developing purchase intentions.

Relying on the risk deterrence perspective and rational decision-making models involving trust and habit, this study proposes a set of hypotheses which are tested through analyzing survey data using structural equation modeling techniques.

Results show that commerce risk deters purchasing intentions; trust toward the social commerce website increases users’ purchasing intentions; and trust toward the site members indirectly increases purchasing intentions. Moreover, trust toward site members reduces perceived commerce risk. Findings also show that habit modulates trust and risk effects on use decisions in this context; habit moderates (weakens) the relationships between commerce risk and purchase intentions and between trust toward the social commerce site and purchase intentions.

This study extends theories on decision making in social settings such as in the case of social commerce. It does so by accounting for unique modulating effects of habit in social settings in which social aspects such as trust in other members and risk are unique and important.

Given its growing economic potential and social impact, this study aims to understand the motivations and concerns regarding metaverse usage. It identifies user needs and risks around the metaverse grounded on uses and gratifications theory and perceived risk theory.

The authors analyzed user reviews and rating data from Roblox, a representative modern metaverse platform. They applied BERTopic modeling to extract topics from reviews, identifying key motivations and risk aspects related to metaverse usage. They further constructed an explanatory model to assess how those affect user satisfaction and changes in these effects over time.

This study discovered that gratifications like entertainment, escapism, social interaction and avatar-based self-expression significantly influence user satisfaction in the metaverse. It also highlighted that users find satisfaction in self-expression and self-actualization through creating virtual spaces, items and video content. However, factors such as identity theft, fraud and child safety were identified as potential detriments to satisfaction. These influences fluctuated over time, indicating the dynamic nature of user needs and risk perceptions.

The novelty of this study lies in its dual application of the uses and gratifications theory and perceived risk theory to the metaverse. It provides a novel perspective on user motivations and concerns, shedding light on the distinct elements driving user satisfaction within the metaverse. This study unravels the metaverse’s unique capacity to assimilate features from established digital media while offering a distinctive user-generated experience. This research offers valuable insights for academics and practitioners in digital media and marketing.

This research pioneers the application of both uses and gratifications and perceived risk theories to understand factors influencing metaverse satisfaction. By establishing a comprehensive framework, it explores the metaverse’s unique value as a user-content creation platform, while encompassing existing digital platform characteristics. This study enriches the academic literature on the metaverse and offers invaluable insights for both metaverse platforms and brand marketers.

The purpose of this paper is to build a research model that examines social media privacy concerns (SMPC) in relation to users’ trusting beliefs and risk beliefs.

An instrument with eight constructs (SMPC: collection, SMPC: secondary usage, SMPC: errors, SMPC: improper access, SMPC: control, SMPC: awareness, trusting beliefs and risk beliefs) was developed and administered to subjects from a mid-sized university in the USA. Collected data were analyzed using partial least square structural equation modeling.

The results showed that three of the six SMPC (i.e. secondary usage, improper access and awareness) were negatively and significantly associated with users’ trusting beliefs. In addition, three of the six SMPC (i.e. collection, errors and improper access) were positively and significantly associated with users’ risk beliefs.

Practical implications were aimed at the social media sites to design simple and straightforward privacy policy statements that are easy to understand; to safeguard users’ online privacy behaviors; and to develop mechanisms to protect personal information.

This study enhances the literature by contributing to a generalized knowledge of SMPC of users as they relate to their trusting beliefs and risk beliefs.

This study discusses the effects of diffusion and adopters of mobile banking services (MBSs), perceived risk, brand awareness, and brand image of MBS providers, on attitude toward using MBSs, and on intention to use MBSs. In accordance with sample usage frequency in MBSs, this study subgroups the sample population into several behavioral segments (frequent/infrequent users) to concentrate sample characteristics and the behavioral models.

Data from the 610 valid questionnaires collected in Taiwan were analyzed by SPSS and LISREL. In accordance with sample usage frequency in MBSs, this study subgroups the sample population into several behavioral segments (frequent/infrequent users) to concentrate sample characteristics and the behavioral models.

Analytical results demonstrate that mobile banking users with different behavioral patterns have dissimilar perceptions of innovation benefits and risk. Moreover, brand awareness and brand image of the MBSs provider are crucial exogenous factors associated with attitude and intention to use MBSs. Finally, this study presents several suggestions for researchers, bankers, and marketers.

This study examined MBSs in Taiwan, with an enhanced investigation model includes diffusion of innovation, TPA, second‐order risk sub‐dimensions, and brand effects on attitude and intention. The contributions of this study includes: this is the first study that incorporate brand awareness, and brand image in discussing mobile banking adoption behavior; meanwhile, this study incorporate a five factors risk structure, discussing perceived risk detailed in financial risk, performance risk, time risk, psychological risk, and privacy risk. Furthermore, this study is the first study that has differentiated between different consumer types: frequent and infrequent users. The findings of this study is practical in providing MBS for bankers.