AI Analytics as Intelligent Management Technology: The Mediating Role of Organizational Agility in Digital Business Performance
Abstract
Keywords
Full Text:
PDFReferences
S. Fosso Wamba, M. Queiroz, I. Pappas, and Y. Sullivan, “Artificial Intelligence Capability and Firm Performance: A Sustainable Development Perspective by the Mediating Role of Data-Driven Culture,” Information Systems Frontiers, vol. 26, pp. 2189–2203, Jan. 2024, doi: 10.1007/s10796-023-10460-z.
A. D. F. S. Borges, F. Laurindo, M. Spinola, R. Gonçalves, and C. Mattos, “The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions,” Int. J. Inf. Manage., vol. 57, p. 102225, Sep. 2020, doi: 10.1016/j.ijinfomgt.2020.102225.
K. Ansari and M. Ghasemaghaei, “Big Data Analytics Capability and Firm Performance: Meta-Analysis,” Journal of Computer Information Systems, vol. 63, pp. 1477–1494, Feb. 2023, doi: 10.1080/08874417.2023.2170300.
A.-T. Walter, “Organizational agility: ill-defined and somewhat confusing? A systematic literature review and conceptualization,” Management Review Quarterly, vol. 71, pp. 343–391, Apr. 2020, doi: 10.1007/s11301-020-00186-6.
C. Xie, X. Xu, Y. Gong, and J. Xiong, “Big Data Analytics Capability and Business Alignment for Organizational Agility: A Fit Perspective,” Journal of Global Information Management, vol. 30, pp. 1–27, Jan. 2022, doi: 10.4018/JGIM.302915.
M. L. Khalil, N. A. Aziz, F. Long, and H. Zhang, “What factors affect firm performance in the hotel industry post-Covid-19 pandemic? Examining the impacts of big data analytics capability, organizational agility and innovation,” Journal of Open Innovation: Technology, Market, and Complexity, vol. 9, no. 2, Jun. 2023, doi:
1016/j.joitmc.2023.100081.
S. Fosso Wamba, “Impact of artificial intelligence assimilation on firm performance: The mediating effects of organizational agility and customer agility,” Int. J. Inf. Manage., vol. 67, p. 102544, Dec. 2022, doi: 10.1016/j.ijinfomgt.2022.102544.
S. Adipat, “An Artificial Intelligence-Enhanced Phenomenon-Based Learning Approach for Interdisciplinary Understanding and Speaking Skills,” International Journal of Instruction, vol. 16, no. 3, pp. 531–550, Jul. 2023, doi: 10.29333/iji.2023.16329a.
S. Ghosh, M. Hughes, I. R. Hodgkinson, and P. Hughes, “Digital Transformation of Industrial Businesses: A Dynamic Capability Approach,” Technovation, vol. 113, p. 102414, 2022, doi: 10.1016/j.technovation.2021.102414.
F. Kitsios and M. Kamariotou, “Artificial intelligence and business strategy towards digital transformation: A research agenda,” Sustainability (Switzerland), vol. 13, no. 4, pp. 1–16, 2021, doi: 10.3390/su13042025.
M. S. S. E. Namaki, Neo Strategic Management: Conceptual and Operational Foundations of Tomorrow’s Strategic Thinking. Springer Nature, 2023. doi: 10.1007/978-3-031-37208-7.
Z. Wang and J. Jia, “Digital transformation and organizational resilience,” Financ. Res. Lett., vol. 78, p. 107165, Mar. 2025, doi: 10.1016/j.frl.2025.107165.
A. Sindarov, A. Vafaei-Zadeh, S. Syafrizal, and R. C. Chanda, “Big data analytical capability and firm performance: moderating effect of analytics capability business strategy alignment,” International Journal of Applied Decision Sciences, vol. 16, no. 6, pp. 663–685, 2023, doi: 10.1504/IJADS.2023.134188.
J. Hair and A. Alamer, “Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example,” Research Methods in Applied Linguistics, p. 100027, Aug. 2022, doi: 10.1016/j.rmal.2022.100027.
H. Ames, C. Glenton, and S. Lewin, “Purposive sampling in a qualitative evidence synthesis: A worked example from a synthesis on parental perceptions of vaccination communication,” BMC Med. Res. Methodol., vol. 19, no. 1, Jan. 2019, doi: 10.1186/s12874-019-0665-4.
L. Johnson and R. Eccleston, “Interrogating inclusive growth: Implications for conceptualisation, measurement and policy practice,” Aust. Econ. Pap., vol. 62, no. 2, pp. 362–376, 2023, doi: 10.1111/1467-8454.12294.
D. Ifenthaler, D. Gibson, and E. Dobozy, “Informing learning design through analytics: Applying network graph analysis,” Australasian Journal of Educational Technology, vol. 34, no. 2, pp. 117–132, 2018, doi: 10.14742/ajet.3767.
G. Boateng, T. Neilands, E. Frongillo, H. Melgar-Quiñonez, and S. Young, “Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer,” Front. Public Health, vol. 6, Jun. 2018, doi: 10.3389/fpubh.2018.00149.
D. Muneeb, A. Khattak, K. Wahba, S. Abdalla, and S. Z. Ahmad, “Dynamic capabilities as a strategic flexibility enabler: organizational responsiveness to COVID-19,” Journal of Asia Business Studies, vol. 17, no. 4, pp. 824–849, 2023, doi: 10.1108/JABS-01-2022-0023.
Z. Arifin and Frmanzah, “The Effect of Dynamic Capability to Technology Adoption and its Determinant Factors for Improving Firm’s Performance; Toward a Conceptual Model,” Procedia Soc. Behav. Sci., vol. 207, pp. 786–796, 2015, doi: 10.1016/j.sbspro.2015.10.168.
M. A. Ghonim, A. E.-M. A. Goda, N. M. Khashaba, M. M. Elsotouhy, and M. A. Khashan, “Impact of organizational energy on digital transformation in healthcare services: the movement of human resources from inertia to flexibility,” EuroMed Journal of Business, 2024, doi: 10.1108/EMJB-10-2023-0272.
E. F. Stone-Romero and D. L. Stone, Cross-cultural differences in responses to feedback: Implications for individual, group, and organizational effectiveness, vol. 21, no. March. 2002. doi: 10.1016/S0742-7301(02)21007-5.
M. L. Sheng, “A dynamic capabilities-based framework of organizational sensemaking through combinative capabilities towards exploratory and exploitative product innovation in turbulent environments,” Industrial Marketing Management, vol. 65, no. June, pp. 28–38, 2017, doi: 10.1016/j.indmarman.2017.06.001.
V. O. Akpa, O. U. Asikhia, and N. E. Nneji, “Organizational Culture and Organizational Performance: A Review of Literature,” International Journal of Advances in Engineering and Management, vol. 3, no. 1, pp. 361–372, 2021, doi: 10.35629/5252-0301361372.
P. Mikalef and M. Gupta, “Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance,” Information and Management, vol. 58, no. 3, p. 103434, 2021, doi: 10.1016/j.im.2021.103434.
P. Podsakoff, S. MacKenzie, J.-Y. Lee, and N. Podsakoff, “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies,” Journal of Applied Psychology, vol. 88, pp. 879–903, Oct. 2003, doi: 10.1037/0021-9010.88.5.879.
N. Kock, “Harman’s single factor test in PLS-SEM: Checking for common method bias,” Data Analysis Perspectives Journal, vol. 2, no. 2, pp. 1–6, 2021.
J. Hair, G. T. M. Hult, C. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2022.
J. Henseler, C. Ringle, and M. Sarstedt, “A new criterion for assessing discriminant validity in variance-based structural equation modeling,” J. Acad. Mark. Sci., vol. 43, pp. 115–135, Aug. 2014, doi: 10.1007/s11747-014-0403-8.
C. Nitzl, J. Roldán, and G. Cepeda-Carrion, “Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models,” Industrial Management & Data Systems, vol. 116, pp. 1849–1864, Oct. 2016, doi: 10.1108/IMDS-07-2015-0302.
DOI: http://dx.doi.org/10.38101/sisfotek.v16i2.17324
Refbacks
- There are currently no refbacks.
JURNAL SISFOTEK GLOBAL
Organized by: Research Center and Community Development
Published by: Institut Teknologi dan Bisnis Bina Sarana Global
Jl. Aria Santika No.43A, Margasari, Kec. Karawaci, Kota Tangerang, Banten 15114
Phone. +62 552 2727
Email: lppm@global.ac.id
INDEXED BY:

This work is licensed under a Creative Commons Attribution 4.0 International License..
Based on a work at https://journal.global.ac.id/index.php/sisfotek/index.











