Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - The Impact of Big Data Analytics on Firm’s Operational Performance
T2 - Second Asia Pacific International Conference on Industrial Engineering and Operations Management
AU - Iftikhar, Anas
AU - Ali, Imran
AU - Shah, Adeel
N1 - Conference code: Second
PY - 2021/9/16
Y1 - 2021/9/16
N2 - Big data analytics is the use of advanced analytical techniques on a large dataset to extract meaningful information and knowledge for rational decision making on complex operational problems. Despite the conceptualized nexus between big data analytics and knowledge management, there is a lack of empirical evidence at the nexus of these two important concepts. This research aims to bridge the current gap by devising a model that delves into the direct influence of big data analytics on a firm's operational performance and mediating effect of the knowledge management process (knowledge acquisition, knowledge dissemination, and knowledge application). The model is tested with data based on a sample of 84 manufacturing companies from Pakistan. The results reveal that the knowledge management process has a full mediating effect between big data analytics and operational performance. We contribute to the extant literature of big data analytics and operational performance by offering a more nuanced understanding of the different components of the knowledge management process. These findings provide strategic insights for the senior management on how to best capitalize on the benefits of big data analytics.
AB - Big data analytics is the use of advanced analytical techniques on a large dataset to extract meaningful information and knowledge for rational decision making on complex operational problems. Despite the conceptualized nexus between big data analytics and knowledge management, there is a lack of empirical evidence at the nexus of these two important concepts. This research aims to bridge the current gap by devising a model that delves into the direct influence of big data analytics on a firm's operational performance and mediating effect of the knowledge management process (knowledge acquisition, knowledge dissemination, and knowledge application). The model is tested with data based on a sample of 84 manufacturing companies from Pakistan. The results reveal that the knowledge management process has a full mediating effect between big data analytics and operational performance. We contribute to the extant literature of big data analytics and operational performance by offering a more nuanced understanding of the different components of the knowledge management process. These findings provide strategic insights for the senior management on how to best capitalize on the benefits of big data analytics.
KW - Big data analytics
KW - Knowledge Management
KW - Performance
KW - Structural Equation Model
KW - Empirical study
M3 - Conference contribution/Paper
T3 - Asia Pacific Conference on Industrial Engineering and Operations Management
SP - 122
EP - 132
BT - 2nd Asia Pacific Conference on Industrial Engineering and Operations Management - Proceedings
PB - IEOM
Y2 - 14 September 2021 through 16 September 2021
ER -