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机构地区:[1]山东财经大学管理科学与工程学院信息管理与信息系统系 [2]山东财经大学管理科学与工程学院
出 处:《中国图书馆学报》2015年第1期76-91,共16页Journal of Library Science in China
基 金:国家自然科学基金"社会化阅读服务用户持续使用的行为机理研究"(编号:71373144);教育部人文社会科学研究规划基金"移动阅读系统用户持续使用的理论模型:基于情感视角的实证研究"(编号:12YJA860010)的研究成果之一
摘 要:微博等社会媒体正面临用户活跃程度下降,老用户停止使用的困境。以往的信息系统持续使用理论忽略了用户情感的重要作用,因而对微博等信息系统用户持续使用行为的解释力不足。基于此,本文旨在探究微博用户情感体验与用户满意度之间的关系。研究分两个阶段进行:第一阶段采用心理学中的情感测量方法,分析微博用户在使用过程中的情感体验;第二阶段测量在前一阶段中得到的各种情感的强度,通过回归分析验证用户情感与用户满意度之间的关系。研究发现了用户使用微博中体验到的、出现频率最高的16种情感,其中9种正向情感和7种负向情感,正向情感与用户满意度之间存在显著的正向影响关系,微博用户使用经验对正向情感与用户满意度之间的关系有正向调节作用。这对全面理解微博用户的行为规律具有理论意义,对微博平台运营以及微博营销等应用有实际的指导意义。Micro-blogging companies are facing troubles that user activity is decreasing and older users stop using it. Expectation-Con- firmation Model of IS Continuance (ECM-ISC) neglects the important influence of users' affections and does not have e- nough capacity to explain Miem-blogging users' continuance usage behavior. Currently, there are two deficiencies in resear- ches of users' affections in the IS field. Firstly, limited affections are studied. Secondly, there is no researcher who explores micro-blogging users' emotional experience and the relationship between affection and satisfaction. This paper tries to answer the following questions: what affection do users experience while they are using miero-blog- ging? Do these affections have effect on satisfaction? What is the effect? Two steps of research are adopted: in the first step, we use serf-reported affection inventory to measure people's affections. We ask participants to recall and write down their most frequently experienced affections in the last month while they were using micro-blogging. All questionnaires axe sent through Intemet and 350 validated ones are finally collected. Through synonym analysis, we ultimately get 25 different affection words. In the second step, we use Westbreok's method to measure frequency of the 16 affections that are reported by more than 1% subjects in step one. 7 level Liker scale is used to measure the frequency of affections that are experienced by every subject in the last week. Meanwhile, satisfaction questionnaire is used to measure users' satisfaction. All questionnaires are sent through Internet and finally 155 validated ones are collected. We use satisfaction as dependent vari- able, affections as independent variables to build regression model and gender, age and experience of usage as moderator between affections and satisfaction. Results of step one reveal that: 1) happiness, interest are the most experienced affections, separately 41.7% and 11.1% users experience these affecti
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