Huang Xiangmeng, Yang Shuai, Wang Junbin, Lin Fengli, Jiang Yunfei
Department of Logistic Management, Business School, Changshu Institute of Technology, Changshu, China.
Department of Management Science, School of Management, Fudan University, Shanghai, China.
Front Psychol. 2022 Sep 23;13:948764. doi: 10.3389/fpsyg.2022.948764. eCollection 2022.
With the development of network technology, enterprises face the explosive growth of data every day. Therefore, to fully mine the value of massive data, big data analysis (BDA) technology has become the key to developing the core competitiveness of enterprises. However, few empirical studies have investigated the influencing mechanism of the BDA capability of an enterprise on its operational performance. To fill this gap, this study explores how BDA technology capability influences enterprise operation performance, based on dynamic capabilities theory and resource-based theory. It proposes the key variables, including the connectivity, compatibility, and modularization of big data analysis technical capability, enterprise's operational performance, and the fit between data and tools, to establish a model and study the correlation between the variables. The results highlight the mediating role of data-tool fit in the relationships between BDA capability and the enterprise's operational performance, which is a major finding that has not been underlined in the extant literature. This study provides valuable insight for operational managers to help them in mobilizing BDA capability for enterprises' operational management and improving operational performance.
随着网络技术的发展，企业每天都面临着数据的爆炸式增长。因此，为了充分挖掘海量数据的价值，大数据分析（BDA）技术已成为企业发展核心竞争力的关键。然而，很少有实证研究探讨企业的BDA能力对其运营绩效的影响机制。为了填补这一空白，本研究基于动态能力理论和资源基础理论，探讨BDA技术能力如何影响企业运营绩效。它提出了关键变量，包括大数据分析技术能力的连通性、兼容性和模块化、企业的运营绩效以及数据与工具的匹配度，以建立一个模型并研究变量之间的相关性。结果突出了数据-工具匹配在BDA能力与企业运营绩效关系中的中介作用，这是现有文献中尚未强调的一项主要发现。本研究为运营经理提供了有价值的见解，帮助他们调动企业的BDA能力进行运营管理并提高运营绩效。
