Eb Business intelligence technology success factors determine business performance within Libyan commercial businesses
Abstract
The present article has the primary goal is to determine the impact of business intelligence on the performance of commercial societies in Libya. The empirical method of linear regression was applied to the data from primary sources on a sample of 384 commercial companies. To that end, the formulated questions correspond to the questionnaire used by Ahumada and Perusquia (2016), which consists of 37 questions based on the variables established in aim's study to determine the general hypothesis. To obtain more precise deductions, different questions were introduced based on the control variables. The findings revealed that business intelligence interventions are positively associated with business performance. Market Stall's financial indicators showed statistically that there is a high level of significance in relation to the independent variable. On the other hand, age, size, and human capital are other factors that influence the optimum performance of companies.
References
References
Arora, M., & Sharma, R. L. (2022). Artificial intelligence and big data: ontological and communicative perspectives in multi-sectoral scenarios of modern businesses. foresight, ahead-of-print(ahead-of-print). https://doi.org/10.1108/FS-10-2021-0216
Baycur, G., Delen, E., & Kayişkan, D. (2022). Digital Conflicts in Marketing and Sales. In F. Özsungur (Ed.), Conflict Management in Digital Business (pp. 43-61). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80262-773-220221004
Binzafrah, F., & Taleedi, F. (2022). The effect of business intelligence practices on job satisfaction in the Saudi Electricity Company in the Asir Region. Journal of Money and Business, 2(1), 107-131. https://doi.org/10.1108/JMB-03-2022-0011
Carvalho, D., Picoto, W., & Busch, P. (2022). Organizational experience of social media: impacts on competitive intelligence. VINE Journal of Information and Knowledge Management Systems, 52(2), 161-183. https://doi.org/10.1108/VJIKMS-05-2019-0067
Cheng, X., Bao, Y., Zarifis, A., Gong, W., & Mou, J. (2022). Exploring consumers' response to text-based chatbots in e-commerce: the moderating role of task complexity and chatbot disclosure. Internet Research, 32(2), 496-517. https://doi.org/10.1108/INTR-08-2020-0460
Fonseka, K., Jaharadak, A. A., & Raman, M. (2022). Impact of E-commerce adoption on business performance of SMEs in Sri Lanka; moderating role of artificial intelligence. International Journal of Social Economics, 49(10), 1518-1531. https://doi.org/10.1108/IJSE-12-2021-0752
Gigante, G., & Zago, A. (2022). DARQ technologies in the financial sector: artificial intelligence applications in personalized banking. Qualitative Research in Financial Markets, ahead-of-print(ahead-of-print). https://doi.org/10.1108/QRFM-02-2021-0025
Ji, F., & Tia, A. (2022). The effect of blockchain on business intelligence efficiency of banks. Kybernetes, 51(8), 2652-2668. https://doi.org/10.1108/K-10-2020-0668
Kapetaneas, N., & Kitsios, F. (2022, 2022//). Digital Transformation Approach to Public Hospitals Environment: Technology Acceptance Model for Business Intelligence Applications. (Ed.),^(Eds.). Information Systems, Cham.
Lateef, M., & Keikhosrokiani, P. (2022). Predicting Critical Success Factors of Business Intelligence Implementation for Improving SMEs’ Performances: a Case Study of Lagos State, Nigeria. Journal of the Knowledge Economy. https://doi.org/10.1007/s13132-022-00961-8
McBreen, B., Silson, J., & Bedford, D. (2022a). Business Stories of Intelligent Organizations (Organizational Intelligence and Knowledge Analytics (pp. 141-164). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80262-177-820211013
McBreen, B., Silson, J., & Bedford, D. (2022b). Capacity Building for Organizational Intelligence and Analytics (Organizational Intelligence and Knowledge Analytics (pp. 115-123). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80262-177-820211009
Okunlaya, R. O., Syed Abdullah, N., & Alias, R. A. (2022). Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education. Library Hi Tech, ahead-of-print(ahead-of-print). https://doi.org/10.1108/LHT-07-2021-0242
Paesano, A. (2021). Artificial intelligence and creative activities inside organizational behavior. International Journal of Organizational Analysis, ahead-of-print(ahead-of-print). https://doi.org/10.1108/IJOA-09-2020-2421
Qaffas, A. A., Ilmudeen, A., Almazmomi, N. K., & Alharbi, I. M. (2022). The impact of big data analytics talent capability on business intelligence infrastructure to achieve firm performance. foresight, ahead-of-print(ahead-of-print). https://doi.org/10.1108/FS-01-2021-0002
Sanil, H. S., Singh, D., Raj, K. B., Choubey, S., Bhasin, N. K. K., Yadav, R., & Gulati, K. (2022). Role of machine learning in changing social and business eco-system – a qualitative study to explore the factors contributing to competitive advantage during COVID pandemic. World Journal of Engineering, 19(2), 238-243. https://doi.org/10.1108/WJE-06-2021-0357
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John Wiley & Sons.
Shiau, W.-L., Chen, H., Wang, Z., & Dwivedi, Y. K. (2022). Exploring core knowledge in business intelligence research. Internet Research, ahead-of-print(ahead-of-print). https://doi.org/10.1108/INTR-04-2021-0231
Stjepić, A.-M., Pejić Bach, M., & Bosilj Vukšić, V. (2021). Exploring Risks in the Adoption of Business Intelligence in SMEs Using the TOE Framework. Journal of Risk and Financial Management, 14(2). https://doi.org/10.3390/jrfm14020058
Talaoui, Y., & Kohtamäki, M. (2021). 35 years of research on business intelligence process: a synthesis of a fragmented literature. Management Research Review, 44(5), 677-717. https://doi.org/10.1108/MRR-07-2020-0386
Tsuchimoto, I., & Kajikawa, Y. (2022). Competitive intelligence practices in Japanese companies: multicase studies. Aslib Journal of Information Management, 74(4), 631-649. https://doi.org/10.1108/AJIM-05-2021-0133
Tze San, O., Latif, B., & Di Vaio, A. (2022). GEO and sustainable performance: the moderating role of GTD and environmental consciousness. Journal of Intellectual Capital, 23(7), 38-67. https://doi.org/10.1108/JIC-10-2021-0290
Ünal, A., & Kılınç, İ. (2021). The feasibility of artificial intelligence performing as CEO: the vizier-shah theory. foresight, 23(6), 698-723. https://doi.org/10.1108/FS-02-2021-0048
Upadhyay, N., Upadhyay, S., Al-Debei, M. M., Baabdullah, A. M., & Dwivedi, Y. K. (2022). The influence of digital entrepreneurship and entrepreneurial orientation on intention of family businesses to adopt artificial intelligence: examining the mediating role of business innovativeness. International Journal of Entrepreneurial Behavior & Research, ahead-of-print(ahead-of-print). https://doi.org/10.1108/IJEBR-02-2022-0154
Uslu, H. (2022). The role of intellectual capital in financial development: evidence from the banking sector of Turkey. Competitiveness Review: An International Business Journal, 32(2), 230-249. https://doi.org/10.1108/CR-06-2020-0084
Wang, P. (2022). A study on the intellectual capital management over cloud computing using analytic hierarchy process and partial least squares. Kybernetes, 51(6), 2089-2108. https://doi.org/10.1108/K-03-2021-0241
Yang, W., & Lin, Y. (2022). Research on the interactive operations research model of e-commerce tourism resources business based on big data and circular economy concept. Journal of Enterprise Information Management, 35(4/5), 1348-1373. https://doi.org/10.1108/JEIM-12-2020-0520
Downloads
Published
How to Cite
License
Copyright (c) 2022 Journal of Reproducible Research
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright of the article belongs to Journal of Reproducible Research (JRR) once the paper is ACCEPTED for publication. Author(s) agrees to this terms, during submission.