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同侪影响对用户贡献行为的作用研究———基于网络客观大数据的分析 《科学学研究》2021,39(12):2294-2304
本文将同侪影响引入在线创新社区的用户行为研究中,从广度和深度两方面考察同侪影响对用户贡献行为的影响,并分析感知收益的中介作用。研究以小米社区MIUI功能与讨论区的创意集市板块为对象构建S-O-R模型,采用6567名用户发布的8830条创意、5.26万条评论和收到的103.36万条评论数据,利用Mplus8.1分析检验,结果发现：同侪影响广度与深度均有利于促进用户贡献行为,综合收益在同侪影响广度、深度与用户贡献行为间起正向中介效应,情感收益仅在同侪影响广度、深度与主动贡献行为间起正向中介效应,而认知收益则在同侪影响深度与反应贡献行为间起负向中介效应。研究拓展了在线网络情境下知识管理与社会学领域的交叉研究,并为在线创新社区社交网络和知识管理提供重要启示。 相似文献
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Fattane Zarrinkalam Mohsen Kahani Ebrahim Bagheri 《Information processing & management》2018,54(2):339-357
Inferring users’ interests from their activities on social networks has been an emerging research topic in the recent years. Most existing approaches heavily rely on the explicit contributions (posts) of a user and overlook users’ implicit interests, i.e., those potential user interests that the user did not explicitly mention but might have interest in. Given a set of active topics present in a social network in a specified time interval, our goal is to build an interest profile for a user over these topics by considering both explicit and implicit interests of the user. The reason for this is that the interests of free-riders and cold start users who constitute a large majority of social network users, cannot be directly identified from their explicit contributions to the social network. Specifically, to infer users’ implicit interests, we propose a graph-based link prediction schema that operates over a representation model consisting of three types of information: user explicit contributions to topics, relationships between users, and the relatedness between topics. Through extensive experiments on different variants of our representation model and considering both homogeneous and heterogeneous link prediction, we investigate how topic relatedness and users’ homophily relation impact the quality of inferring users’ implicit interests. Comparison with state-of-the-art baselines on a real-world Twitter dataset demonstrates the effectiveness of our model in inferring users’ interests in terms of perplexity and in the context of retweet prediction application. Moreover, we further show that the impact of our work is especially meaningful when considered in case of free-riders and cold start users. 相似文献
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本文从开放广度和深度2个维度系统探索软件平台开放对创新绩效的影响以及平台吸引力对上述过程的调节作用。结合文献研究和专家访谈法，确定平台创新绩效的测度指标体系；选取2008-2015年间中国上线并上市的30家软件平台有效样本及其主导企业相关数据，采用层次回归分析方法进行实证检验。结果表明，平台开放广度对平台创新绩效所有指标具有正向影响；开放深度呈倒U型影响平台创新绩效；不同维度平台吸引力对开放度影响创新绩效过程的调节作用存在差异，其中，正向调节开放广度的影响成立，但对开放深度影响的调节作用不尽一致。研究结论对于系统认识软件平台开放性与平台整体创新绩效的关系，促进平台产业转型升级，尤其是指导主导企业的平台开放决策，提升开放创新效率具有重要启示。 相似文献
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[目的/意义]探寻深度契合用户需求的有效学科服务模式,指导高校图书馆学科服务工作。[方法/过程]基于文献调研的方法,对传统学科服务模式进行了归纳和总结。针对传统学科服务模式普遍存在的不足,引入服务经济学领域的价值共创理论,论证该理论对学科服务工作的理论指导适用性。[结果/结论]基于价值共创理论的高校图书馆学科服务模式包含用户需求分析、设计和制定解决方案、整合资源及实施解决方案、管理价值冲突、目标达成五个环节。该模式下,图书馆与用户在特定学科服务活动中发挥着同等重要的作用。 相似文献
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【目的/意义】虚拟品牌社区日渐成为企业和用户之间的重要沟通渠道,对于企业而言,如何引导用户助力
社区发展至关重要。基于自我决定理论探寻用户参与行为的影响因素及形成机制。【方法/过程】运用自我决定理
论,构建信息交互对用户参与行为（奉献行为、浏览行为）的影响机制模型,并探寻用户承诺（情感承诺、算计承诺）
在其中的中介作用。利用结构方程模型对收集的386份有效问卷进行分析。【结果/结论】研究结果表明,信息交互
能够有效促进用户参与行为,如奉献行为及浏览行为;情感承诺在信息交互与用户奉献行为间具有中介效应,算计
承诺在信息交互与用户浏览行为间具有中介效应;与算计承诺相比,情感承诺对奉献行为具有较强影响;与情感承
诺相比,算计承诺对浏览行为具有较强影响。【创新/局限】本文基于动机视角探寻信息交互对用户不同参与行为的
影响及作用机制,但尚未对其它影响因素如社会影响及社区类型等开展研究。 相似文献
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伴随着社会化媒体的普及,企业日益注重虚拟品牌社区的建设,借此向顾客展示产品独特价值,以期形成良好的口碑传播效应。通过采用扎根理论研究方法,搜集社区评论信息作为经验资料,并进行编码分析,提炼出互动体验、社区归属感以及品牌定位等范畴,阐释了顾客参与价值共创与品牌形象塑造的关系。研究表明,产品价值共创包括价值认知以及用户需求等核心要素,且有利于形成良好的品牌文化,而品牌形象的塑造则依赖于创新产品及建构以用户价值交互为基础的生态圈,顾客参与价值共创有助于品牌形象的塑造,企业应围绕产品创新打造虚拟品牌社区,强化顾客互动体验,并建立完善的信息沟通机制,引导顾客积极参与价值共创。 相似文献
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领先用户在开放式创新社区中发挥着重要作用,成为产品创新的有力推动者。但网络环境下领先用户识别的研究刚刚兴起,相关研究非常缺乏。本文首先对开放式创新社区中领先用户特征进行理论研究,提出需求领先力、活跃表现力、社区影响力三大特征。然后基于改进的网络志方法,将定性的网络志和定量的数据分析结合,构建了识别领先用户的理论步骤。遵循社区选择原则,以知乎社区扫地机器人版块103位用户为研究对象,对用户的提问数、回答数等7个指标进行因子分析和聚类分析,识别出2位领先用户;并采用扎根理论,比较发帖内容和未来市场上扫地机器人新产品功能,发现领先用户提出的大部分建议会体现于未来新产品功能上,证明了领先用户识别方法的有效性。研究有助于完善领先用户识别方法,并为后续领先用户行为研究奠定坚实基础。 相似文献
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随着数字经济的兴起与发展,企业能够通过跨界创新实现与用户的价值共创,然而目前尚未有关于企业跨界创新和用户价值共创关系的研究。本文基于价值共创理论与社会交换理论,引入用户驱动创新作为中介变量,冗余资源作为调节变量,构建了一个有调节的中介模型。基于352份调查数据,运用层级回归、Bootstrap和结构方程模型等方法,本文实证检验了企业跨界创新对价值共创的影响,以及用户驱动创新的中介效应和冗余资源的调节效应。结果表明企业跨界创新能够显著正向影响用户价值共创,用户驱动创新在企业跨界创新和用户价值共创中起部分中介作用,冗余资源正向调节企业跨界创新对用户驱动创新的影响。本研究不仅从理论上证实了企业跨界创新对用户价值共创的作用机制和边界条件,而且对现实中企业管理也具有一定启示。 相似文献
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【目的/意义】基于网络视频的用户交互式持续学习行为对于推动网络视频学习资源价值最大化以及教育
信息化发展具有重要意义,对其影响因素及作用机理的探究有助于增加用户粘性并推动在线学习良好生态的构
建。【方法/过程】通过采集交互式学习视频的186038条弹幕数据,并以此为原始资料采用扎根理论的质性研究方法
对弹幕数据进行三级编码提取出概念和范畴,进而构建影响因素理论模型。【结果/结论】研究发现,个体因素、课程
因素和教师因素通过影响用户交互行为因素达到影响用户满足感,并进一步影响用户交互式持续学习行为;此外,
用户的个体特征会调节用户交互行为因素对用户满足感的影响,且教师的授课风格会直接影响用户交互式持续学
习行为。【创新/局限】本文采用扎根理论并以弹幕数据为原始资料构建了交互式持续学习行为影响因素模型,各影
响因素的定量分析有待后续验证,亦可通过对比分析其他类型网络视频学习资源拓展本文研究结论。 相似文献
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《Information processing & management》2022,59(2):102861
Integrating useful input information is essential to provide efficient recommendations to users. In this work, we focus on improving items ratings prediction by merging both multiple contexts and multiple criteria based research directions which were addressed separately in most existent literature. Throughout this article, Criteria refer to the items attributes, while Context denotes the circumstances in which the user uses an item. Our goal is to capture more fine grained preferences to improve items recommendation quality using users’ multiple criteria ratings under specific contextual situations. Therefore, we examine the recommenders’ data from the graph theory based perspective by representing three types of entities (users, contextual situations and criteria) as well as their relationships as a tripartite graph. Upon the assumption that contextually similar users tend to have similar interests for similar item criteria, we perform a high-order co-clustering on the tripartite graph for simultaneously partitioning the graph entities representing users in similar contextual situations and their evaluated item criteria. To predict cluster-based multi-criteria ratings, we introduce an improved rating prediction method that considers the dependency between users and their contextual situations, and also takes into account the correlation between criteria in the prediction process. The predicted multi-criteria ratings are finally aggregated into a single representative output corresponding to an overall item rating. To guide our investigation, we create a research hypothesis to provide insights about the tripartite graph partitioning and design clear and justified preliminary experiments including quantitative and qualitative analyzes to validate it. Further thorough experiments on the two available context-aware multi-criteria datasets, TripAdvisor and Educational, demonstrate that our proposal exhibits substantial improvements over alternative recommendations approaches. 相似文献
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[目的/意义] 对于一个创新平台的繁荣与发展来说,用户间进行社交互动并为平台做出贡献是至关重要的。因此,本文研究用户交互中的内容特征（信息冗余）对用户知识贡献的影响。[方法/过程] 爬取典型开放式创新平台（LEGO IDEAS）的数据,使用Python NLTK包挖掘创意文本内容,并结合信息论中的冗余度计算方法和零膨胀负二项回归模型进行实证分析。[结果/结论] 结果表明,用户交互过程中获取的信息量正向影响用户知识贡献,促进用户发布更多创意,但当获取的创意之间存在冗余信息时,信息冗余会调节获取信息量对用户知识贡献的影响。 相似文献
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用户因当前产品或服务无法满足自身需求,而主动进行创新并将其商业化的过程称为“用户创业”。用户创业主体及其创业活动均呈现独特性,然而现有研究主要从各自研究视角关注用户创业的某方面问题,缺乏对用户创业进行全面揭示。基于此,本研究在系统梳理经典文献基础上首先界定用户创业内涵,随后提炼用户创业动机,梳理用户创业的关键影响因素,进一步从机会开发和资源开发视角解析用户创业活动独特性,最后总结用户创业结果。在此基础上,本研究构建用户创业的综合研究框架,总结当前研究不足并展望未来研究方向,为后续研究奠定基础。 相似文献
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Sven H. Koch Rumyana Proynova Barbara Paech Thomas Wetter 《Ethics and Information Technology》2013,15(1):45-61
Software users have different sets of personal values, such as benevolence, self-direction, and tradition. Among other factors, these personal values influence users’ emotions, preferences, motivations, and ways of performing tasks—and hence, information needs. Studies of user acceptance indicate that personal traits like values and related soft issues are important for the user’s approval of software. If a user’s dominant personal value were known, software could automatically show an interface variant which offers information and functionality that best matches his or her dominant value. A user’s dominant personal value is the one that most strongly influences his or her attitudes and behaviors. However, existing methods for measuring a user’s values are work intensive and/or interfere with the user’s privacy needs. If interface tailoring for very large groups of users is planned, value approximation has to be achieved on a large scale to assign individualized software to all users of the software. Our work focuses on approximating the dominant values of a user with less effort and less impact on privacy. Instead of probing for a user’s values directly, we explore the potential of approximating these values based on the user’s preferences for key tasks. Producing tailored versions of software is a separate topic not in the focus here. In this paper we rather describe a method to identify user values from task preferences and an empirical study of applying parts of this method. We are proposing the method in this paper for the first time except for a preliminary version orally presented at a workshop. The method consists of a research process and an application process. In the research process a researcher has to identify key tasks occurring in a context under investigation which have a relationship to personal values. These key tasks can be used in the application process to approximate the dominant values of new users in a similar context. In this empirical study we show that the research process of our method allows us to determine key tasks which approximate values in the shared context of nursing. The majority of the nurses were found to have one of the three following dominant values: benevolence, self-direction, or hedonism. Data confirmed common expectations: that nurses with the value of benevolence, when compared to all other nurses, had a higher preference for tasks which helped people immediately or improved their circumstances of the treatment. In relation to all other nurses, participants with self-direction disliked tasks which affected their personal freedom, and users with hedonism had a lower preference for tasks which involved physical work and preferred tasks which promised gratification. Our findings advance measurement of personal values in large user groups by asking questions with less privacy concern. However, the method requires substantial efforts during the initial research process to prepare such measurements. Future work includes replicating our method in other contexts and identifying value-dependent tasks for users with other values than the three values our empirical study mainly focused on. 相似文献
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在网络虚拟品牌社区（OUIC）前端创新环节,企业是否参与、何时参与、如何参与知识创造管理不仅会影响到企业的产品创新绩效,甚至会影响企业在市场中的核心竞争力。本研究选择具有一定高新技术信息支撑的家电电器行业OUIC为研究背景,引入创意组合管理（IPM）为研究的核心变量,通过构建不同创意主题发布模式（B端创意主题与C端创意主题）与不同前端创新阶段（创意产生阶段与创意发展阶段）的2×2组间设计来验证相关命题。结果表明,针对不同创意主题社区,企业采取的不同决策行为,对产品创新绩效均存在显著差异。（1）证明了不同创意主题发布模式（B端创意主题或C端创意主题）,会对用户的知识创造力产生差异性影响。B端创意主题（企业主导发布）,企业可以引导社区用户重点进行新产品核心子系统相关创意的开发;C端创意主题（用户主导发布）,企业可以引导社区用户重点进行新产品周边子系统相关创意的开发。（2）验证了在用户参与OUIC 前端创新环节知识创造过程中,企业实施创意组合管理（IPM）对用户知识创造力与产品创新绩效产生的正面显著效果。（3）验证了用户参与OUIC前端创新环节知识创造过程中,企业对用户创新行为的最佳干预时机。在B端创意主题（企业主导发布）下,企业在创意产生阶段（第一阶段）实施创意组合管理（IPM）为最佳导入时机;C端创意主题（用户主导发布）下,企业在创意发展阶段（第二阶段）实施创意组合管理（IPM）为最佳导入时机。研究在理论上不仅丰富和完善了虚拟经济营销管理相关理论,而且在应用上有助于企业利用互联网工具为产品创新发掘新的途径,并培育企业市场核心竞争力。 相似文献
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Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores
《Information processing & management》2020,57(5):102274
Studies of knowledge communities have focused predominantly on contributors who ask questions and/or post replies, while little research has examined the contributions of those who neither pose questions nor suggest answers in knowledge communities. To illuminate member contributions of various sorts, this study evaluated user contribution to knowledge community from three dimensions (influence, content-contribution, and activeness) of immersion. Based on the user activity data of more than 4 million users from Zhihu, the largest online knowledge community in China, we calculated the immersion level for the four user groups (Lurkers, Questioners, Answerers, and Questioner-Answerers) in line with their question-asking and question-answering behaviors in Zhihu. The research findings revealed that Lurkers (members who posted nothing) showed higher community-immersion score than Questioners who asked questions only. The latter, Questioners, had the lowest community-immersion score, while Questioner-Answerers, who posted both questions and answers, exhibited the greatest contribution in the case knowledge community. We further made horizontal comparison of immersion score among the four different user groups, and found that when immersion scores of the four different user groups are above a certain threshold, the immersion scores of the four different user groups display a consistent distinguishing pattern. This result highlights the similarity of tendencies in behavioral orientation among different users in knowledge communities. Theoretical contributions and practical implications to be gleaned from this research are discussed. 相似文献
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利用中国国家知识产权局1999—2015年间ICT产业的联合授权专利数据,构建产学研合作创新网络,并提取14 596家企业的大样本面板数据,使用负二项式回归模型分别从合作广度和合作深度两个维度,考察产学研合作开放度的异质性对企业创新绩效的影响。结果表明：大学、科研机构在我国ICT领域的产学研合作创新中的作用存在异质性。无论从合作广度还是合作深度来看,大学对我国ICT企业创新绩效的提升具有重要作用;科研机构对其创新绩效的促进作用则有待进一步提升。 相似文献
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本文从资源能力视角解释用户驱动制造业企业服务创新的过程逻辑,基于动态资源基础观和价值共创理论分析互动导向、战略柔性对服务创新绩效的影响。使用Amos 240对319家样本企业的调查数据进行实证检验。研究发现：（1）战略柔性在互动响应能力、顾客授权、顾客价值管理与服务创新绩效之间起部分中介作用,在顾客理念与服务创新绩效之间的中介作用不显著。（2）售后服务情景下资源柔性对互动导向与服务创新绩效的中介作用高于协调柔性,相反,增值服务情景下协调柔性的中介作用更显著。研究在还原互动导向多维度构念的基础上,发现制造业企业服务创新需打破组织边界引入用户参与价值共创,依据资源柔性与协调柔性的演化水平为用户提供创新性服务。 相似文献
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研究领先用户,可以了解未来市场发展趋势和捕捉用户需求变化,开发更具市场潜力的新产品或服务等,并增加企业新产品或服务的竞争优势。但相关研究尚未成熟,且国内研究十分缺乏。基于相关外文数据库对领先用户理论研究的重要成果进行了梳理,深入分析了领先用户的概念、量表与测量和影响因素等。研究发现：（1）领先用户是指在特定领域处于重要市场前沿地位（领先市场趋势）,并期望从满足需求的解方案中获得高收益（高期望收益）的用户;（2）量表包括领先市场趋势和高期望收益两个基本维度;（3）影响因素由领域相关变量、领域独立变量和动机构成。最后,对未来研究方向进行了展望,以期为国内学者进一步研究领先用户及企业与领先用户合作进行新产品开发提供参考。 相似文献