Title: Effects of big data analytics capability on performance of internet enterprises: chain mediating effects of strategic flexibility and strategic innovation

Authors: Hua Zhang; Lifang Wang; Hongji Yang; Chunyuan Yu; Fubin Xia; Xinzhe Xue

Addresses: Sunwah International Business School, Liaoning University, Shenyang, Liaoning Province, China ' School of Economy and Business, Heilongjiang University, Nangang District, Harbin, Heilongjiang Province, China ' School of Computing and Mathematical Sciences, Leicester University, Leicester, England, UK ' Fundamental Education Department, Liaoning Mechatronics College, Dandong, Liaoning, China ' School of Economy and Business, Heilongjiang University, Nangang District, Harbin, Heilongjiang Province, China ' Huainan Vocational and Technical College, Tianjiaan District, Huainan, Anhui Province, China

Abstract: The recent interest in big data has led many companies to develop big data analytics capability (BDAC) in order to enhance Firm Performance (FP). However, BDAC pays off for some companies but not for others. It appears that very few have achieved a big impact through big data. To address this challenge, this study proposes a BDAC model drawing on the resource-based theory and the dynamic capability theory. In order to carry out the research, this paper takes Chinese internet enterprises as the research object and obtains survey data from 629 employees through questionnaires. Through the test of the proposed chain mediation model using the bootstrap method, it is found that: (1) big data analytics capability has significant positive influences on firm performance of internet enterprises; (2) strategic flexibility and strategic innovation play chain mediating roles on the path joining big data analytics capability and firm performance.

Keywords: big data analytics capability; firm performance; internet enterprises; strategic flexibility; strategic innovation; chain mediating effects.

DOI: 10.1504/IJCAT.2023.131062

International Journal of Computer Applications in Technology, 2023 Vol.71 No.1, pp.52 - 63

Received: 17 Dec 2021
Accepted: 01 Mar 2022
Published online: 23 May 2023 *

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