Effect of personal branding stereotypes on user engagement on short-video platforms

The emergence of short-video platforms offers individuals an opportunity to build personal branding. This study selected two personal brandings on Bilibili.com, Li Ziqi and HuaNong Brothers, to explore the differences in the effect of personal branding stereotypes on user engagement on short-video platforms. We first identified the perception of users based on the Stereotype Content Model, then adopted regression models to construct the relationship between personal branding stereotypes and user engagement. The results show that perceived warmth exerts a more significant influence on user emotional engagement, while perceived competence impacts more on user cognitive and behavioral engagement. Moreover, we find the live comments’ sentiment moderates these effects. This research provided references for individuals and managers to benefit from personal brandings.     

考虑整数比特率及公平性的认知无线电OFDMA功率分配算法

在基于正交频分多址(OFDMA)的认知无线电系统中,每个认知用户在实际中都是以整数比特进行传输,而以往的速率取整算法只考虑了单认知用户。针对这种情况,提出了一种新的速率取整算法,该算法在原有算法的基础上进行了改进,让每个子载波最多参与一次速率的调整,从而使其在应用于多认知用户时保证了速率取整时的公平性,同时总的传输比特率比原算法有了一定的提高。仿真结果表明,所提算法有效提高了各认知用户在速率取整时的公平性。     

基于可信度计算的分布式共识合作感知算法

对于分布式的认知无线网络,由于不存在融合中心节点,次级用户节点之间的合作感知往往 采用信息交互的渠道进行,其中一种基于共识合作的感知机制受到广泛的研究,但这种机制 在鲁棒性方面存在一定的缺陷,当恶意节点存在时,其错误信息将影响局部的感知判决结果 ,为此,提出一种基于感知节点可信度的共识合作感知机制。在该机制中,各节点对邻居节 点的可信度进行计算,并把计算出的可信度值发送给其他节点,通过对各节点可信度的累加 计算,最终计算出各节点的可信度,各节点以此决定是否与其邻居节点合作以及如何合作。 仿真结果证明,在恶意节点存在的情况下,该算法在感知性能和收敛速度上都较未改进算法 有不同程度的提升,减轻了不可靠节点对合作感知结果的影响。     

主用户活跃性下的多功率分配策略

考虑到认知用户在信息传输过程中主用户的状态可能随时变化,提出了一种新的功率分配模式——多功率分配策略。在基于频谱感知的系统模型中,以认知系统的吞吐量为目标函数,得出了主用户感知过程的多种状态,并分配三种不同的功率,最大化认知系统的容量。仿真结果表明,随着主用户活跃指数的逐渐提高,所提新模型的功率分配策略要优于传统方法。同时分析了新的功率分配下平均干扰功率与主用户接收端的信噪比对系统吞吐量和最优感知时间的影响,进一步验证了所提出新策略的有效性。 〖HT5H〗关键词：〖HT5K〗认知无线电;主用户活跃;频谱感知分配;多功率分配;吞吐量最大化     

基于统计可信度的压缩感知协作频谱检测算法

压缩感知为认知无线电的宽频谱感知提供了一种新的方法和思路。基于压缩感知的原理,提出了一种多认知用户协作场景下基于用户统计可信度的协作频谱检测算法。该算法使用正交匹配协作追踪算法获得认知区域内的频谱占用情况,根据不同认知用户频谱检测的历史准确度综合判定用户感知结果的统计可信度。仿真结果表明,该算法在不同用户数、不同采样值、不同信噪比变化范围下其检测性能均优于传统算术平均方法,有效改善了检测性能。     

How to inspire users in virtual travel communities: The effect of activity novelty on users’ willingness to co-create

Virtual travel community managers tend to incorporate a degree of novelty within activity design to foster interaction between users. Little is known of how users respond to these novel activities. Based on customer inspiration theory, this research investigated the mechanisms of activity novelty on users' willingness to co-create and the moderating effect of user regulatory focus and activity goal attainability. Results of three scenario-based experiments revealed that activity novelty positively influenced users’ willingness to co-create via user inspiration. Promotion-focused users were more inspired by novel activities and in turn had a higher willingness to co-create than those were prevention-focused. When activity goal attainability was high (vs. low), the positive effect of activity novelty on inspiration was attenuated. We present the theoretical and practical implications of activity design within virtual travel communities.     

Don't call us,we'll call you: Considering cognitive and physical effort in designing effective response systems to manage extended in-process wait

People must often wait for days or weeks to receive test results, price quotes, products, etc. Service providers may manage user experience during such in-process waits using notification systems that inform users when a response is available or inquiry systems that require users to inquire about response availability, thereby imposing prospective memory requirements on users. Based on the prospective memory and wait time literature, we make predictions regarding how response system (notification vs. inquiry) moderates the effects of waits that are shorter or longer than the provider promised on user evaluation of the wait. We find that users of a notification system evaluate a wait more positively and are less sensitive to deviations of actual from promised wait time than are users of an inquiry system. This advantage was more pronounced for a wait that was longer (vs. shorter) than promised. These effects of system and expectation on evaluation were fully mediated by their impact on the cognitive and physical effort of navigating the system. Finally, a week after having experienced a wait, users of an inquiry system who had waited longer (vs. shorter) than promised cooperated less on a follow-up task, highlighting another downside of using an inquiry system.     

协作多组多播认知无线网络的资源优化配置

考虑到无线电频谱资源日益紧缺,提出了一种基于组间组内协作传输的多播组新机制,涉及多个多播组并使用同一频谱资源以协作方式传输信息。基于认知无线网络中该机制,研究了系统的资源优化配置,理论分析得出了功率分配方案,进而讨论了系统加权总传输速率的优化,同时考虑了主用户和认知用户之间信号干扰及功率限制对传输速率的影响,最优化用户性能。仿真结果表明,优化方案下多播组传输速率随用户人数的增加而上升,达到最优化用户服务质量;当功率限制时,通过设置加权因子,能够保证主用户拥有良好的通信性能。     

Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction

Human–computer interaction (HCI) is a cornerstone for the success of technical innovation in the logistics and supply chain sector. As a major part of social sustainability, this interaction is changing as artificial intelligence applications (Internet of Things, autonomous transport, Physical Internet) are implemented, leading to larger machine autonomy, and hence the transition from a primary executive to a supervisory role of human operators. A fundamental question concerns the level of control transferred to machines, such as autonomous vehicles and automatic materials handling devices. Problems include a lack of human trust toward automatic decision making or an inclination to override the system in case automated decisions are misperceived. This paper outlines a theoretical framework, describing different levels of acceptance and trust as a key HCI element of technology innovation, and points to the possible danger of an artificial divide at both the individual and firm level. Based upon the findings of four benchmark cases, a classification of the roles of human employees in adopting innovations is developed. Measures at operational, tactical, and strategic level are discussed to improve HCI, more in particular the capacity of individuals and firms to apply state‐of‐the‐art techniques and to prevent an artificial divide, thereby increasing social sustainability.     

Using structural topic modelling to predict users’ sentiment towards intelligent personal agents. An application for Amazon’s echo and Google Home

Despite growing levels of usage of Intelligent Personal Assistants (hereinafter, IPA), their in-home usage has not been studied in depth by scholars. To increase our understanding of user interactions with IPA, our research created a theoretical framework rooted in technology acceptance models and Uses and Gratification Theory. Our empirical method designs an ambitious analysis of natural and non-structured narratives (user-generated content) on Amazon’s Echo and Google Home. And to identify key aspects that differentially influence the evaluation of IPA our method employs machine-learning algorithms based on text summarisation, structural topic modelling and cluster analysis, sentiment analysis, and XGBoost regression, among other approaches. Our results reveal that (hedonic and utilitarian) benefits gratification, social influence and facilitating conditions have a direct impact on the users’ sentiment for IPA. To sum up, designers and managers should recognise the challenge of increasing the customer satisfaction of current and potential users by adjusting doubtful users’ technical skills and the (hedonic, cognitive, and social) benefits and functionalities of IPA to avoid boredom after a short lapse of time. Finally, the discussion section outlines future lines of research and theoretical and managerial implications.     

A comparison of attitudes towards Internet advertising among lifestyle segments in Taiwan

As the Internet gradually diffuses throughout more sectors in society many advertisers have begun to consider the diversity in various aspects of consumer behaviour among Internet users. As Internet users' attitudes towards Internet advertising are found to influence their brand attitudes and purchase intentions, the study can contribute to the design and assessment of Internet advertising. The study identified potential lifestyle segments among Internet users and examined the relationships between lifestyle segments and their attitudes towards Internet advertising. This study surveyed 700 Internet users and employed a lifestyle segmentation approach for categorizing consumers into three distinct lifestyle groups: ‘experiencers’, ‘traditionalists’ and ‘self‐indulgents’. Statistical analyses pointed out that all three groups differed from one another in several demographic characteristics. Moreover, the lifestyle clusters were found partly to predict Internet users' attitudes towards Internet advertising. The findings of the present study provide justifications for marketers to treat Internet users as a heterogeneous group. Furthermore, advertising researchers should be aware of the diversity of the Internet population in order to assess the effectiveness of Internet advertising better.     

一种基于无线电环境地图的路由优化机制

设计认知无线网络路由算法时,需要兼顾主用户保护与路由性能两个方面。为了提高认知无线网络中次用户之间路由的端到端性能,提出了基于无线电环境地图的路由优化机制,该机制中无线电环境地图能够为次用户提供主用户保护有关的无线电环境数据。首先,无线电环境地图根据次用户的数据请求将各授权频段的可用概率与功率控制相关信息反馈到该次用户;其次,次用户可以计算出与上一跳次用户之间的链路稳定性以及传输时延;最后,目的次用户通过计算每条路由的端到端吞吐量的期望值,然后选取期望值最大的一条路由。仿真结果表明,该路由机制在平均分组投递率、平均端到端吞吐量、平均端到端时延方面均优于对比路由算法。     

认知网中感知时间和功率控制的联合优化机制

针对认知无线网中为了最大化认知用户的吞吐量问题,提出了一种感知时间和功率控制的联合优化机制。该机制保证认知系统在低于一定干扰限制下,将认知用户吞吐量描述成为一个多约束优化问题,从理论上分析了最优功率分配方案与最优感知时间分配方案。根据理论分析结果,设计了联合迭代机制通过确定合适的感知参数从而达到最大化认知用户吞吐量的目的。仿真结果表明：提出的联合优化机制复杂度较低,并且该方案的认知吞吐量性能最接近理论最优方案的性能。     

基于网络编码的用户协作分集系统性能分析

针对非协作通信和传统协作通信系统不能达到高天线分集增益的问题,提出基于网络 编码的用户协作系统模型。研究了基于网络编码不同协作用户的天线分集增益,并分析非协 作机制、传统用户协作机制和基于网络编码用户协作机制的中断概率。理论分析和系统仿真 表明,基于网络编码的用户协作系统能显著降低系统中断概率,获得更大的分集增益,且协 作用户数越多,系统分集度越好。     

A Taxonomy of Social Networking Site Users: Social Surveillance and Self‐surveillance Perspective

Since social networking sites (SNS) are widely used in modern society, users increasingly use SNS to manage or maintain their existing social relationships and form new ones. This research applies social surveillance and self‐surveillance to classify SNS user types and explores each type's effect on SNS’ marketing performances. Three hundred three online questionnaires are collected to test the research questions. The results of cluster analysis and multivariate analysis of variance (MANOVA) reveal the following four user types based on the different degrees of social surveillance and self‐surveillance: versatile users, self‐expression users, pass‐along users, and introvert users. Further, the introvert users have the least impact on product‐related information sharing, perception of social presence, purchase intention toward offers on SNS, and emotional experiences in social shopping among the four SNS user types.     

It's not what you know but who you know that's important: the influence of social networks on communities

Since its conception in 1945, the UK National Health Service (NHS) has been the focus of extensive political rhetoric regarding the involvement of patients and the public in the provision of health‐care services both locally and nationally. However, achieving substantial user involvement within local communities has proven to be a complex task. The exploratory research presented in this paper investigates the influence of social networks within local communities and its relevance for user involvement. Four main findings emerged: interviewees have strong informal social networks; there is a strong sense of generalized reciprocity; diversity is limited within the social groupings; and there exists a lack of trust in governmental institutions. With regards to health issues, there is an overriding feeling that ‘things like that should be left to the people who know’. If user involvement is to be achieved at the level envisioned by the UK government, achieving a greater relevance for users is essential.     

Consumers’ Behavioral Intentions Toward Self-Service Technology in the Emerging Markets

ABSTRACT

Self-service technologies (SSTs) allow customers to offer their own service encounters via the interaction of electronic service interfaces or machines rather than by interacting with a firm's service personnel. This lack of personal interaction generates doubts and queries in the minds of the people, especially those unaware or less aware of these technology-based services. Such a situation is quite prevalent in the developing nations (like India), where still a large number of people are apprehensive about using the latest technologies. In this regard, the present study aims to develop an integrated model designed to predict and explain the various factors that influence customers’ behavioral intentions to use or not to use one particular SST (i.e., ATM services). The study finds that bank customers are less innovative and less optimistic to try out new technologies. Usefulness of the technology helps in developing positive attitude toward the technology, which in turn affects customers' intentions to use that technology.     

基于ATM技术的有线接入网入侵检测系统研究

为了对特定用户实行实时动态数据采集,通过分析UTOPIA接口和信元结构,探讨了基于ATM技术的有线网络系统相关的协议、数据处理程序以及基于FPGA实现数据分装与重组,提出了基于ADSL接入网UTOPIA接口的IP数据包提取方法,实现了基于ATM技术的有线网络实时动态入侵检测的目标.     

认知型飞蜂窝网络中的子信道分配与功率控制

为了解决宏蜂窝与飞蜂窝构成的两层异构网络上行干扰与资源分配问题,提出了一种在认知型飞蜂窝的双层异构网中结合子信道分配和功率控制进行资源分配的框架。通过对异构网中跨层干扰问题进行分析与建模,将求解最优子信道分配矩阵和用户发射功率矩阵作为干扰管理问题的解决方法。模型中认知型飞蜂窝网络子信道和飞蜂窝网络用户构成非合作博弈,双方利用效用函数最优值进行匹配,构成初始信道分配矩阵;再由接入控制器根据接入条件从初始信道分配矩阵中筛选用户,并优化接入用户的发射功率矩阵,得到最优子信道分配矩阵和功率矩阵。仿真结果表明,优化框架提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网中跨层干扰。     

联合循环平稳特征PCA与RVM的频谱感知

针对无线信道环境中低信噪比情况下主用户信号检测率较低的问题,提出了一种基于循环平稳特征主成分分析(PCA)与相关向量机(RVM)的认知网络频谱感知算法。该算法结合了主成分分析算法与相关向量机分类方法,应用于解决认知网络频谱感知问题。首先对信号循环平稳特征参数进行特征提取,通过主成分分析进行降维提取信号主成分,生成训练样本和待测样本,并完成对相关向量机的训练,再采用训练完成的相关向量机算法分别对有无主用户情况下的信号进行分类检测,最后获得主用户信号存在性的感知判断。仿真实验表明,与人工神经网络、支持向量机和最大最小特征值算法相比较,所提算法在低信噪比情况下具有较高的分类检测性能,检测率最大可提高61.6%,有效地实现了对主用户信号的感知。