【作者】 王亚明；

【导师】 邵真；

【作者基本信息】 哈尔滨工业大学 ， 管理科学与工程， 2016， 硕士

【摘要】 大数据环境下,各个企业都意识到了数据的价值,纷纷引进技术和人才,建立企业自己的数据分析能力。企业数据分析能力的高低取决于企业员工个体的数据分析能力,因此,企业的大数据分析人才成为企业一个重要的竞争资源。本文基于数据分析能力相关理论,通过案例分析和问卷调研的实证研究方法,探索企业员工个体层次数据分析能力的度量维度并设计相应的度量指标,在此基础上从组织和个体两个层面分析企业员工个体层次的数据分析能力的关键影响因素。基于以往的研究文献,对个体层次的数据分析能力进行了界定,通过对企业员工进行访谈,确定了个体层次的数据分析能力的五个维度:技术知识、业务知识、沟通协调能力、个体的创新性和个体的吸收能力。参考各个维度度量指标的相关文献,设计了个体层次数据分析能力五个维度的度量指标,并通过验证性因子分析,检验了五个维度度量指标的有效性和可靠性。基于组织文化、知识共享和个体动机的相关理论,构建了个体层次数据分析能力影响因素的结构方程模型,通过对企业员工的问卷调研,收集了152份问卷,利用Smart PLS对结构方程模型进行了分析。研究结果表明,组织内部创新发展的文化、合作交流的文化、目标导向的文化、组织培训和IT支持对个体的数据分析能力有显著的正向影响;个体心理动机因素如个人兴趣和个体的自我效能,对个体的数据分析能力也有显著的正向影响。实证研究表明,知识共享在创新发展的文化、合作交流的文化、目标导向的文化、组织培训、IT支持和个体的数据分析能力影响关系中起到了部分的中介作用。本研究进一步丰富了个体层次数据分析能力的理论文献,能够为企业选拔和培训数据分析人才提供理论参考。更多还原

【Abstract】 In the environment of big data, organizations have recognized the significant value of big data and introduced technology and talents to establish data analysis ability. Since organization level data analysis ability depends on individuals’ ability,big data talents have become an important competitive resource for organizations.Based on the related theory of data analysis ability, this study explores five dimensions of individual level data analysis ability and design the corresponding measurement through case study and empirical survey. On the basis of the measurement design, this study examines the critical influencing factors of individual level data analysis ability from organization and individual aspects.Drawing upon theoretical literatures and case interviews, this study first defines individual level data analysis ability and divides it into five dimensions:technical knowledge, business knowledge, communication and coordination ability,innovativeness and absorptive capacity; then design the measurement metrics of the five dimensions of individuals’ data analysis ability and examines its validity and reliability through confirmatory factor analysis. Based on organizational culture,knowledge sharing and psychological motivation theory, this study further establishes a structural equation model to examine the influencing factors of individuals’ data analysis capability. 152 questionnaires are collected through an investigation of enterprise data analysts, Smart PLS is used to analyze the structural equation model. Research results show that organizational level factors such as innovation and development culture, cooperation and communication culture, goal oriented culture, organizational training and IT support have significant positive impact on individuals’ data analysis ability; while individual psychological motivational factors such as personal interest and self-efficacy also have significant positive impact on individuals’ data analysis ability. The empirical results also show that knowledge sharing partially mediates the relationship between organizational culture, organization training, IT support and individuals’ data analysis ability. The study can contributes to the extant literatures in data analysis ability and provides a theoretical reference for the enterprises to select and train data analysis talents.更多还原