Hua, Liangliang and Mao, Di and Nicholson, Rekha Rao and Yu, Chia-Hui and Lue, Huimin and Wang, Yichuan (2026) From Aspirational to Transformed: Configurational Recipes for Analytics-Driven Operational Excellence. Enterprise Information Systems, 20 (1). p. 2595700. DOI https://doi.org/10.1080/17517575.2025.2595700
Hua, Liangliang and Mao, Di and Nicholson, Rekha Rao and Yu, Chia-Hui and Lue, Huimin and Wang, Yichuan (2026) From Aspirational to Transformed: Configurational Recipes for Analytics-Driven Operational Excellence. Enterprise Information Systems, 20 (1). p. 2595700. DOI https://doi.org/10.1080/17517575.2025.2595700
Hua, Liangliang and Mao, Di and Nicholson, Rekha Rao and Yu, Chia-Hui and Lue, Huimin and Wang, Yichuan (2026) From Aspirational to Transformed: Configurational Recipes for Analytics-Driven Operational Excellence. Enterprise Information Systems, 20 (1). p. 2595700. DOI https://doi.org/10.1080/17517575.2025.2595700
Abstract
Analytics technologies are vital for improving operational performance, yet the configurations that maximise their value remain unclear. Drawing on complexity theory and contingency theory, this study examines how supply chain governance, organisational capability, and environmental conditions interact with different levels of analytics capability. Using secondary data from 205 Chinese high-tech firms over two years, we combine content analysis with fuzzy-set qualitative comparative analysis to uncover configurations that enhance performance. Results show that firms must align governance, capabilities, and environmental strategies with their analytics maturity, aspirational, experienced, or transformed. The study advances understanding of analytics implementation and offers practical guidance.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | analytic technology; complexity theory; fuzzy-set qualitative comparative analysis (fsQCA); Operational performance; supply chain governance |
| Subjects: | Z Bibliography. Library Science. Information Resources > ZR Rights Retention |
| Divisions: | Faculty of Social Sciences > Essex Business School |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 18 Feb 2026 13:32 |
| Last Modified: | 18 Feb 2026 13:35 |
| URI: | http://repository.essex.ac.uk/id/eprint/42145 |
Available files
Filename: EIS_Main text_Analytics_Final version.pdf
Licence: Creative Commons: Attribution 4.0