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1.
Potential for the use of mobile wallet is enormous and it is drawing attention as an alternative mode of payment worldwide. The present research aims to provide important insights into the TAM (Technology Acceptance Model) and UTAUT2 (Unified Theory of Acceptance and Use of Technology) models. This study develops a conceptual model to determine the most significant factors influencing user's intention, perceived satisfaction and recommendation to use mobile wallet. The research model included 206 responses from an online and manual survey in India. Our study tested the moderating effect of innovativeness, stress to use and social influence on user's perceived satisfaction and recommendation to use mobile wallet services. We found that ease of use, usefulness, perceived risk, attitude, to have significant effect on user's intention, which further influenced user's perceived satisfaction and recommendation to use mobile wallet services. We also determined the significant moderating effect of stress to use and social influence on user's perceived satisfaction and recommendation to mobile wallet services. This study provides an integrated framework for academicians to measure the moderating effect of psychological, social and risk factors on technology acceptance. It can also help practitioners by identifying important factors affecting user's decision, which further affects user's perceived satisfaction and recommendation to use mobile wallet services. 相似文献
2.
Spending real money on virtual goods and services has become a popular form of online consumer behavior, particularly among teenagers. This study builds on the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine the role of motivation, social influence, measured with perceived network size as well as user interface and facilitating conditions in predicting the intention to engage in purchasing in social virtual worlds. The research model is tested with data from 1045 users of Habbo Hotel, world's most popular virtual world for teenagers. The results underscore the role of perceived network size and motivational factors in explaining in-world purchase decisions. The study shows that virtual purchasing behavior is substantially influenced by the factors driving usage behavior. Hence, virtual purchasing can be understood as a means to enhance the user experience. For virtual world operators, reinforcing the sense of presence of user's social network offers a means to promote virtual purchasing. 相似文献
3.
《Information processing & management》2023,60(2):103198
The online depression community (ODC) has become a popular resource for people with depression to manage their mental health during the COVID-19 pandemic. This study proposed a novel perspective based on response style theory to investigate whether depression individuals’ distractive and ruminative behaviors in ODC were related to social support received and co-rumination. Furthermore, we explored the influences of social support and co-rumination on suicidal behaviors using panel data set. We collected text data from 22,286 depressed users of a large ODC in China from March 2020 to July 2021, and conducted text mining and econometrics analyses to test our research questions. The results showed that depression users’ online ruminative behaviors had a positive relationship with the co-rumination and had a negative relationship with social support received. Besides, constructive distractive behaviors (i.e., providing social support to others) increased the support users received from others but had a negative relationship with co-rumination. Depression users' future suicidal behaviors are influenced by past received social support and co-rumination. The received social supports and co-rumination have a negative and positive influence on depression users' future suicidal behaviors, respectively. Our results enrich the application of response style theory in online medicine. They provide meaningful insights into behaviors that influence the acquisition of online social support and the incidence of online co-rumination in ODCs. This study helps relevant institutions to conduct more targeted online suicide interventions for depression patients. 相似文献
4.
《Information processing & management》2022,59(2):102797
In event-based social networks (EBSN), group event recommendation has become an important task for groups to quickly find events that they are interested in. Existing methods on group event recommendation either consider just one type of information, explicit or implicit, or separately model the explicit and implicit information. However, these methods often generate a problem of data sparsity or of model vector redundancy. In this paper, we present a Graph Multi-head Attention Network (GMAN) model for group event recommendation that integrates the explicit and implicit information in EBSN. Specifically, we first construct a user-explicit graph based on the user's explicit information, such as gender, age, occupation and the interactions between users and events. Then we build a user-implicit graph based on the user's implicit information, such as friend relationships. The incorporated both explicit and implicit information can effectively describe the user's interests and alleviate the data sparsity problem. Considering that there may be a correlation between the user's explicit and implicit information in EBSN, we take the user's explicit vector representation as the input of the implicit information aggregation when modeling with graph neural networks. This unified user modeling can solve the aforementioned problem of user model vector redundancy and is also suitable for event modeling. Furthermore, we utilize a multi-head attention network to learn richer implicit information vectors of users and events from multiple perspectives. Finally, in order to get a higher level of group vector representation, we use a vanilla attention mechanism to fuse different user vectors in the group. Through experimenting on two real-world Meetup datasets, we demonstrate that GMAN model consistently outperforms state-of-the-art methods on group event recommendation. 相似文献
5.
[目的/意义]本文以用户行为感知视角，研究影响移动社交网络主导型用户与浏览型用户持续使用的因素，为移动社交网络信息服务提供理论基础，并为移动社交网络提供商提出参考与应用借鉴。[方法/过程]分析移动社交网络主导型用户与浏览型用户持续使用意愿影响因素，引入相关变量，构建了基于用户行为感知的移动社交网络信息服务持续使用意愿模型并提出假设，最后通过结构方程模型进行实证分析。[结果/结论]感知有用性、感知易用性、感知娱乐、感知质量等因素均显著影响主导型及浏览型两类用户；服务质量、感知风险、知识获取、个人创新、社会认可、感知信任、感知转换成本等因素对两类用户有不同程度的影响。 相似文献
6.
随着现代网络的发展,登录移动社交平台已经成为大多数人每天的日常,和亲人朋友在社交平台上的交流远远多于面对面的交谈,学习工作上的事情也大多可以用社交软件完成,在这样的大前提下,移动社交平台用户之间的信任关系必然要成为关注的重点。用户信任度可以用来详细检查用户之间所有可能的社交网络关系,本文以新浪微博为例提供了一种计算用户之间信任的方法,通过对用户之间的信任进行分析完成相应的推荐和其他服务。 相似文献
7.
Perceived critical mass and collective intention in social media-supported small group communication
Xiao-Liang Shen Christy M.K. Cheung Matthew K.O. Lee 《International Journal of Information Management》2013
The increasing popularity of Web 2.0 has dramatically changed the way in which people communicate with others in their daily life or work. However, the use of social media is fundamentally different from that of traditional information technologies. Specifically, it requires collective efforts and interdependence between two or more people, and thus the usage behavior is no longer an individual's own decision or plan. Built on critical mass theory and social influence processes, this study tries to make an attempt to understand the determinants of collective intention (we-intention), which represents one's perception of a group of people acting as a unit. Instant messaging, one of the most popular social media platforms, has been chosen for investigation, and findings from a survey showed that perceived critical mass influenced we-intention both directly and indirectly through group norm and social identity. Recognizing the importance and relevance of collective intention will advance current understanding beyond individual intention-based models which are widely adopted in prior IS research. This study may be limited by having not included other alternative social technologies, but we leave this work for future research. 相似文献
8.
Bernard J. Jansen 《Information processing & management》2018,54(2):159-174
With the noted popularity of social networking sites, people increasingly rely on these social networks to address their information needs. Although social question and answering is potentially an important venue seeking information online, it, unfortunately, suffers from a problem of low response rate, with the majority of questions receiving no response. To understand why the response rate of social question and answering is low and hopefully to increase it in the future, this research analyzes extrinsic factors that may influence the response probability of questions posted on Sina Weibo. We propose 17 influential factors from 2 different perspectives: the content of the question, and the characteristics of the questioner. We also train a prediction model to forecast a question's likelihood of being responded based on the proposed features We test our predictive model on more than 60,000 real-world questions posted on Weibo, which generate more than 600,000 responses. Findings show that a Weibo's question answerability is primarily contingent on the questioner versus the question. Our findings indicate that using appreciation emojis can increase a question's response probability, whereas the use of hashtags negatively influences the chances of receiving answers. Our contribution is in providing insights for the design and development of future social question and answering tools, as well as for enhancing social network users’ collaboration in supporting social information seeking activities. 相似文献
9.
The rise of social media has created a new e-commerce platform called social commerce. In social commerce, e-vendors such as Amazon may integrate social media with their traditional e-commerce sites. Based on self-determination theory and social commerce literature, we develop a model illustrating how social commerce features may impact consumer behaviors and facilitate social commerce benefits from the extrinsic motivation perspective. We identify four types of extrinsic motivation including external motivation, introjected motivation, identified motivation, and integrated motivation; and we examine their influences on consumers’ intention to contribute social commerce information, which in turn leads to their subsequent behaviors and increases the perceived benefit of social commerce. We also consider the moderating effect of gender in the formulation of social commerce benefits. Based on longitudinal survey data from Amazon consumers, we find that 1) consumers’ external and identified motivation has a positive impact on intention to contribute social commerce information; 2) consumers’ intention is positively associated with their future behaviors, which in turn facilitate their perceptions of social commerce benefits; and 3) gender moderates the impact of behavior on social commerce benefits. 相似文献
10.
《Information processing & management》2023,60(3):103256
Music has a close relationship with people's emotion and mental status. Music recommendation has both economic and social benefits. Unfortunately, most existing music recommendation methods were constructed based on genre features (e.g., style and album), which cannot meet the emotional needs of listeners. Furthermore, the “filter bubble” effect may make the situation even worse, when a user seeks music for emotional support. In this study, we designed a novel emotion-based personalized music recommendation framework to meet users’ emotional needs and help improve their mental status. In our framework, we designed a LSTM-based model to select the most suitable music based on users’ mood in previous period and current emotion stimulus. A care factor was used to adjust the results so that users’ mental status could be improved by the recommendation. The empirical experiments and user study showed that the recommendations of our novel framework are precise and helpful for users. 相似文献
11.
《Information processing & management》2023,60(2):103190
Computational social science has become a branch of social science that uses computationally intensive ways to investigate and model social phenomena. Exploitation on mathematics, physics, and computer sciences, and analytic approaches like Social Network Analysis (SNA), Machine Learning (ML), etc, develops and tests the theories of complex social phenomena. In the emerging environment of social media, the new characteristics of social collective behavior and its extensive phenomena have become the hot spot of common concern across many disciplines. In this paper, we propose a general quantitative framework to discover the social collective behavior in temporal social networks. The general framework incorporates the Time-Correlation Function (T.C.F.) in statistical physics and evolutionary approach in Machine Learning, and provides the quantitative evidence of the existence of social collective behavior. Results show collective behaviors are observed and there exists a tiny fraction of users whose behavior are constantly replicated by public, disregard of the behavior itself. Our method is assumption-independent and has the potential to be applied to various temporal systems. 相似文献
12.
Social network sites (SNS) and micro-blogging sites are popular yet distinctive social media. Previous studies have focused on one type of social media and thus overlook how the distinctive features of SNS and micro-blogging sites may affect underlying motivational mechanisms. To address this research gap, we draw from the self-regulation framework and propose a research model to explain how different appraisal factors (i.e., self-image and peer influence) affect continuance use through emotional responses (i.e., a sense of belonging and satisfaction). Furthermore, we argue that the effects of these appraisal and emotional factors are different across types of social media. We tested our research model by survey data collected from SNS and micro-blogging sites. The results confirm our hypotheses: First, self-image is a more significant factor in increasing SNS users’ sense of belonging and satisfaction, while peer influence has a greater effect on micro-blogging sites users’ sense of belonging and satisfaction. Second, the sense of belonging explains the greater variance of continuance intention in SNS as compared with satisfaction. A few theoretical and practical implications are discussed related to our findings on different motivational mechanisms. 相似文献
13.
为确定在使用信息系统进行操作决策的过程中,用户对何种目标框架的安全提示更为遵从,在对安全提示情境进行界定和分类的基础上,以系统用户为对象,设计E-prime情境实验并运用后测问卷分析方法,采用“接收刺激—大脑反应—动作响应”（S—O—R）模式分析用户从接受刺激到作出反应的全过程,研究不同目标框架下用户遵从意愿的差异性。研究发现：较之于负性目标框架,正性目标框架的安全提示更能增强用户的遵从意愿,且不同性别用户在正性目标框架下的遵从意愿程度不同;而在不同学历水平的个体差异下,框架效应的作用无差异。基于此,提出根据用户的性别差异设计不同信息描述的安全提示,同时保证内容表述的可理解性和可遵从性等对策建议,以促进信息系统安全提示完善、增强用户的遵从意愿。 相似文献
14.
【目的/意义】社会化媒体已经成为企业和组织工作中的一种新兴趋势,但少有研究在工作情境下探讨社会化媒体采纳的具体行为和其影响机制。【方法/过程】将工作情境下的社会化媒体使用行为分为强化使用和多样使用两类,以S-O-R理论为基础框架,结合技术接受模型和动机理论,构建工作中使用社会化媒体的两类动机及其对使用行为影响的研究模型,同时还讨论了惯性对意图与两类使用行为影响的调节作用。【结果/结论】通过实际工作中的问卷数据进行实证分析,研究结果表明:个人层面和任务层面的动机在使用者采纳社会化媒体中扮演着积极的角色;使用者的惯性确实能够调节意图与行为之间的关系。 相似文献
15.
Sampsa Hyysalo 《Research Policy》2009,38(5):726-735
Failure to meet the preferences and needs of users has been consistently stressed as a major cause of unsuccessful R&D for over 30 years. Yet little seems to change. An important element in this “producer-user paradox” is a lack of frameworks able to inform empirical research and the work that people do when they bridge designing, implementing, using and managing new technology. “Learning economy” and “social learning in technological innovation” appear promising as such integrative frameworks not least due to their emphasis on learning between producers and users. The present paper examines the value in the way learning is treated in these frameworks for empirical research and for the practitioners, and to this aim contrasts these frameworks to findings from a line of studies on learning between producers and users of new health technologies. 相似文献
16.
Information systems research provides increasing evidence that women and men differ in their use of information technology. However, research has not sufficiently explained why these differences exist. Using the theory of reasoned action and social role theory, this paper investigates gender differences in people’s decisions about information sharing in the context of social networking sites (SNSs). We developed a comparative model of the information-sharing decision process across genders and theoretically explained why these differences exist. Data was collected from an online survey taken by American SNS users. We found that privacy risks, social ties, and commitment were more important in the formation of attitudes toward information sharing for women than men. Gender significantly moderates the relationship between people’s perceptions of information sharing and their intention to share information. This paper provides an enhanced understanding of gender differences in people’s decisions about sharing information on SNSs. It advances gender differences research into the use of newly emerged information technology and provides researchers insightful views of the role that gender plays in the social media era. Being aware of the research findings, practitioners may better engage their targeted stakeholders on SNSs and collect more useful information for business purposes. 相似文献
17.
《Information processing & management》2020,57(6):102321
Influence diffusion is extensively studied in social networks for product or service promotion and viral-marketing applications. This paper proposes two models for social influence estimation, namely Time Decay Features Cascade Model (TDF-C) and Time Decay Features Cascade Threshold Model (TDF-CT). These models overcome three main existing challenges - first, measure the strength of user's influence as an influencer; second, identify the set of users influenced by an influencer; third, estimate the time frame of the influence. TDF-C is an M-TAP based diffusion model, which learns influence probabilities between users using four types of features, namely temporal, interaction, structural, and profile features, and uses Independent Cascade (IC) model for influence estimation. TDF-CT is an extension of the TDF-C model, which uses temporal and interaction features to calculate the diffusion through the Progressive Feedback Estimation (PFE) model in place of IC model. PFE model is a fusion of two diffusion models, i.e., Linear Threshold (LT) and Independent Cascade. TDF-CT handles the limitations of the contemporary diffusion models, i.e., IC and LT. The efficacy of proposed models is evaluated with respect to existing models Independent Cascade (IC), Time Constant Cascade (TC-C), Time Decay Cascade (TD-C), and Time-Depth Decay Cascade (TDD-C). Experimental evaluation over two benchmark datasets namely Darwin and MelCup17 reveal that proposed models are able to make the predictions very close to the real-time in a given time frame. TDF-CT and TDF-C are most suitable for applications requiring high precision and high recall, respectively. Results of spread shape establish the efficacy of models to spread the influence with good coverage of the social network. Results are obtained with improved accuracy by up to 39%. 相似文献
18.
[目的/意义] 从动机、机会、能力3个维度揭示学术社交网络用户知识共享意愿的影响因素。[方法/过程] 基于MOA理论,构建学术社交网络用户知识共享意愿影响因素模型,搜集数据并采用结构方程模型方法对模型研究假设进行验证。[结果/结论] 利他动机、声誉动机、社区认同动机、知识获取动机、信息质量、系统质量、自我效能对学术社交网络用户的知识共享意愿影响显著,社交关系动机、服务质量对学术社交网络用户的知识共享意愿影响并不显著。该模型对解释我国学术社交网络用户的知识共享意愿和指导学术社交平台建设具有指导意义。 相似文献
19.
Voluntary sharing and mandatory provision: Private information disclosure on social networking sites
《Information processing & management》2020,57(1):102128
Private information disclosure on social networking sites (SNS) is one of the most important and active issues in the information management arena. The growing phenomenon of platforms requiring users to disclose personal information exposes the limitations of previous studies that only focus on users’ voluntary disclosure. In this study, we define two modes of users’ private information disclosure behavior: voluntary sharing and mandatory provision. Using the Communication Privacy Management theory, we built a framework to explain the impact of individual characteristics, context, motivation, and benefit–risk ratio on the user's willingness to disclose voluntarily or mandatorily. Our research shows that voluntary sharing is more likely to be driven by positive factors, such as perceived benefits, social network size, and personalization, while mandatory provision is affected by individual characteristics such as age, privacy policy, and perceived risks. One of our interesting findings is that perceived risk has less impact on voluntary sharing than previous studies suggested. When encouraging users to share information voluntarily, platforms do not need to pay as much attention to reducing perceived risk as in the mandatory providing mode, but should focus on improving perceived benefits. Being the first to classify and compare the private information disclosure modes of SNS users, our research enriches the existing literature and opens up new avenues for researchers and social networking platforms. 相似文献
20.
Seyed Amin Mirlohi Falavarjani Fattane Zarrinkalam Jelena Jovanovic Ebrahim Bagheri Ali A. Ghorbani 《Information processing & management》2019,56(6):102070
The ever increasing presence of online social networks in users’ daily lives has led to the interplay between users’ online and offline activities. There have already been several works that have studied the impact of users’ online activities on their offline behavior, e.g., the impact of interaction with friends on an exercise social network on the number of daily steps. In this paper, we consider the inverse to what has already been studied and report on our extensive study that explores the potential causal effects of users’ offline activities on their online social behavior. The objective of our work is to understand whether the activities that users are involved with in their real daily life, which place them within or away from social situations, have any direct causal impact on their behavior in online social networks. Our work is motivated by the theory of normative social influence, which argues that individuals may show behaviors or express opinions that conform to those of the community for the sake of being accepted or from fear of rejection or isolation. We have collected data from two online social networks, namely Twitter and Foursquare, and systematically aligned user content on both social networks. On this basis, we have performed a natural experiment that took the form of an interrupted time series with a comparison group design to study whether users’ socially situated offline activities exhibited through their Foursquare check-ins impact their online behavior captured through the content they share on Twitter. Our main findings can be summarised as follows (1) a change in users’ offline behavior that affects the level of users’ exposure to social situations, e.g., starting to go to the gym or discontinuing frequenting bars, can have a causal impact on users’ online topical interests and sentiment; and (2) the causal relations between users’ socially situated offline activities and their online social behavior can be used to build effective predictive models of users’ online topical interests and sentiments. 相似文献