How to cite this paper
ALzoubi, K., Bataineh, K., Matalka, M., Al-Rawashdeh, O., Malkawi, A., AlGhasawneh, Y., Alghadi, M., Alibraheem, M & ALzoubi, M. (2023). Critical success factors for business intelligence and bank performance.Uncertain Supply Chain Management, 11(3), 1257-1264.
Refrences
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Aghion, P., Jones, B. F., & Jones, C. I. (2018). Artificial intelligence and economic growth. In The economics of artificial intelligence: An agenda (pp. 237-282). University of Chicago Press.
Ahani, A., Rahim, N. Z. A., & Nilashi, M. (2017). Forecasting social CRM adoption in SMEs: A combined SEM-neural network method. Computers in Human Behavior, 75, 560-578.
Airinei, D., & Berta, D. (2012). Semantic business intelligence – a new generation of business intelligence. Informatica Economica [Online]. 16(2/2012).
Al-Okaily, A., Al-Okaily, M., & Teoh, A. P. (2021). Evaluating ERP systems success: Evidence from Jordanian firms in the age of the digital business. VINE Journal of Information and Knowledge Management Systems, (ahead-of-print).
Al-Okaily, M., & Al-Okaily, A. (2022). An empirical assessment of enterprise information systems success in a developing country: the Jordanian experience. The TQM Journal, 34(6), 1958-1975.
AlSheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. Conference on Information Systems, 15, pp. 25-36. Twenty-Second Pacific Asia Japan.
Aruldoss, M., Lakshmi Travis, M., & Prasanna Venkatesan, V. (2014). A survey on recent research in business intelligence. Journal of Enterprise Information Management, 27(6), 831-866.
Aws, A. L., Ping, T. A., & Al-Okaily, M. (2021). Towards business intelligence success measurement in an organization: A conceptual study. Journal of Systems Management Science, 11, 155-170.
Bollier, T. (2020). Artificial Intelligence Comes of Age. The Promise and Challenge of Integrating AI into Cars, Healthcare and Journalism. Washington, DC: The Aspen Institute.
Cartwright, M. (1997). Applications of Artificial Intelligence Chem Oxcp 11. Oxford University Press,Inn.
Chiang, Y. H., & Hung, K. P. (2014). Team control mode, workers' creativity, and new product innovativeness. R&D Management, 44(2), 124-136.
Cruz-Jesus, F., Pinheiro, A., & Oliveira, T. (2019). Understanding CRM Adoption Stages: Empirical Analysis Building on the TOE Framework. Computers in Industry, 25(10), 1-13. doi:https://doi.org/10.1016/j.compind.2019.03.007
Dobbs, M., & Hamilton, R. T. (2007). Small business growth: recent evidence and new directions. International journal of entrepreneurial behavior & research, 13(5), 296-322.
Fast, E., & Horvitz, E. (2017, February). Long-term trends in the public perception of artificial intelligence. In Proceedings of the AAAI conference on artificial intelligence (Vol. 31, No. 1).
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate data analysis. Englewood Cliffs, New Jersey: Prentice Hall.
Hair. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage. https://doi.org/10.1016/j.lrp.2013.01.002.
http://dx.doi.org/10.1016/j.chb.2017.05.032.
Iacovou, C. L., Benbasat, I., & Dexter, A. S. (1995). Electronic data interchange and small organizations: Adoption and impact of technology. MIS quarterly, 19(4), 465-485.
Idris, A. O. (2015). Assessing a Theoretically-Derived E-Readiness Framework for E-Commerce in a Nigerian SME. Evidence Based Information Systems Journal, 1(1), 1-20.
Infosys, S. (2016). Towards Purposeful Artificial Intelligence, pp. 4-8.
Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60.
Martins, R., Oliveira, T., & Thomas, M. A. (2016). An empirical analysis to assess the determinants of SaaS diffusion in firms. Computers in Human Behavior, 62, 19-33.
Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: A resource-based analysis. MIS quarterly, 19(4), 487-505.
Mohammad, A., Al-Okaily, M., Al-Majali, M., & Masa’deh, R. (2022). Business Intelligence and Analytics (BIA) Usage in the Banking Industry Sector: An Application of the TOE Framework. Journal of Open Innovation: Technology, Market, and Complexity, 24(2), 1-17. doi:https://doi.org/10.3390/joitmc8040189
Nithya, N., & Kiruthika, R. (2021). Impact of Business Intelligence Adoption on performance of banks:a conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 24(2), 1-12.
Owusu, A. (2017). Business intelligence systems and bank performance in Ghana: The balanced scorecard approach. Cogent Business & Management, 4(1), 1364056.
Purdy, M., & Daugherty, P. (2016). Why artificial intelligence is the future of growth. Remarks at AI now: the social and economic implications of artificial intelligence technologies in the near term, 1-72.
Ramesh, A. N., Kambhampati, C., Monson, J. R., & Drew, P. J. (2004). Artificial intelligence in medicine. Annals of the Royal College of Surgeons of England, 86(5), 334.
Ramirez, E., David, M. E., & Brusco, M. J. (2013). Marketing's SEM based nomological network: Constructs and research streams in 1987–1997 and in 1998–2008. Journal of Business Research, 66(9), 1255-1260.
Ritter, T., & Gemünden, H. G. (2004). The impact of a company's business strategy on its technological competence, network competence and innovation success. Journal of business research, 57(5), 548-556.
Rogers, M. E. (2003). Attributes of Innovations and Their Rate of Adoption. Library of Congress Cataloging-in-Publication Dat.
Rumler, F., & Waschiczek, W. (2010). The impact of economic factors on bank profits. Monetary Policy & the Economy, 4(10), 49-67.
San-Martín, S., Jiménez, N. H., & López-Catalán, B. (2016). The firms benefits of mobile CRM from the relationship marketing approach and the TOE model. Spanish journal of marketing-ESIC, 20(1), 18-29.
Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, 29(1), 28-45.
Vempati, S. (2016). The Artificial Intelligence Revolution. Carnegie Endowment for International Peace.
Wade, M., & Hulland, J. (2004). The Resource-Based View and Information Systems Research: Review, Extension, and Suggestions for Future Research. MIS quarterly, 28(1), 107-142.
Wells, D. (2022). Business Analytics—Getting the Point. BeyeNetwork. 2008. Available online: http://www.b-eyenetwork.com/view/7133 (accessed on 5 January 2022).
Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS Adoption from the Perspective of Organizational Users: A Tripod Readiness Model, Computers in Human Behavior (45), pp.
Zhai, I. (2010). Research on Post-Adoption Behavior of B2B E-Marketplace in China, Management and Service Science (MASS), 2010 International Conference on: IEEE, pp. 1-5.
Aghion, P., Jones, B. F., & Jones, C. I. (2018). Artificial intelligence and economic growth. In The economics of artificial intelligence: An agenda (pp. 237-282). University of Chicago Press.
Ahani, A., Rahim, N. Z. A., & Nilashi, M. (2017). Forecasting social CRM adoption in SMEs: A combined SEM-neural network method. Computers in Human Behavior, 75, 560-578.
Airinei, D., & Berta, D. (2012). Semantic business intelligence – a new generation of business intelligence. Informatica Economica [Online]. 16(2/2012).
Al-Okaily, A., Al-Okaily, M., & Teoh, A. P. (2021). Evaluating ERP systems success: Evidence from Jordanian firms in the age of the digital business. VINE Journal of Information and Knowledge Management Systems, (ahead-of-print).
Al-Okaily, M., & Al-Okaily, A. (2022). An empirical assessment of enterprise information systems success in a developing country: the Jordanian experience. The TQM Journal, 34(6), 1958-1975.
AlSheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. Conference on Information Systems, 15, pp. 25-36. Twenty-Second Pacific Asia Japan.
Aruldoss, M., Lakshmi Travis, M., & Prasanna Venkatesan, V. (2014). A survey on recent research in business intelligence. Journal of Enterprise Information Management, 27(6), 831-866.
Aws, A. L., Ping, T. A., & Al-Okaily, M. (2021). Towards business intelligence success measurement in an organization: A conceptual study. Journal of Systems Management Science, 11, 155-170.
Bollier, T. (2020). Artificial Intelligence Comes of Age. The Promise and Challenge of Integrating AI into Cars, Healthcare and Journalism. Washington, DC: The Aspen Institute.
Cartwright, M. (1997). Applications of Artificial Intelligence Chem Oxcp 11. Oxford University Press,Inn.
Chiang, Y. H., & Hung, K. P. (2014). Team control mode, workers' creativity, and new product innovativeness. R&D Management, 44(2), 124-136.
Cruz-Jesus, F., Pinheiro, A., & Oliveira, T. (2019). Understanding CRM Adoption Stages: Empirical Analysis Building on the TOE Framework. Computers in Industry, 25(10), 1-13. doi:https://doi.org/10.1016/j.compind.2019.03.007
Dobbs, M., & Hamilton, R. T. (2007). Small business growth: recent evidence and new directions. International journal of entrepreneurial behavior & research, 13(5), 296-322.
Fast, E., & Horvitz, E. (2017, February). Long-term trends in the public perception of artificial intelligence. In Proceedings of the AAAI conference on artificial intelligence (Vol. 31, No. 1).
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate data analysis. Englewood Cliffs, New Jersey: Prentice Hall.
Hair. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage. https://doi.org/10.1016/j.lrp.2013.01.002.
http://dx.doi.org/10.1016/j.chb.2017.05.032.
Iacovou, C. L., Benbasat, I., & Dexter, A. S. (1995). Electronic data interchange and small organizations: Adoption and impact of technology. MIS quarterly, 19(4), 465-485.
Idris, A. O. (2015). Assessing a Theoretically-Derived E-Readiness Framework for E-Commerce in a Nigerian SME. Evidence Based Information Systems Journal, 1(1), 1-20.
Infosys, S. (2016). Towards Purposeful Artificial Intelligence, pp. 4-8.
Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60.
Martins, R., Oliveira, T., & Thomas, M. A. (2016). An empirical analysis to assess the determinants of SaaS diffusion in firms. Computers in Human Behavior, 62, 19-33.
Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: A resource-based analysis. MIS quarterly, 19(4), 487-505.
Mohammad, A., Al-Okaily, M., Al-Majali, M., & Masa’deh, R. (2022). Business Intelligence and Analytics (BIA) Usage in the Banking Industry Sector: An Application of the TOE Framework. Journal of Open Innovation: Technology, Market, and Complexity, 24(2), 1-17. doi:https://doi.org/10.3390/joitmc8040189
Nithya, N., & Kiruthika, R. (2021). Impact of Business Intelligence Adoption on performance of banks:a conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 24(2), 1-12.
Owusu, A. (2017). Business intelligence systems and bank performance in Ghana: The balanced scorecard approach. Cogent Business & Management, 4(1), 1364056.
Purdy, M., & Daugherty, P. (2016). Why artificial intelligence is the future of growth. Remarks at AI now: the social and economic implications of artificial intelligence technologies in the near term, 1-72.
Ramesh, A. N., Kambhampati, C., Monson, J. R., & Drew, P. J. (2004). Artificial intelligence in medicine. Annals of the Royal College of Surgeons of England, 86(5), 334.
Ramirez, E., David, M. E., & Brusco, M. J. (2013). Marketing's SEM based nomological network: Constructs and research streams in 1987–1997 and in 1998–2008. Journal of Business Research, 66(9), 1255-1260.
Ritter, T., & Gemünden, H. G. (2004). The impact of a company's business strategy on its technological competence, network competence and innovation success. Journal of business research, 57(5), 548-556.
Rogers, M. E. (2003). Attributes of Innovations and Their Rate of Adoption. Library of Congress Cataloging-in-Publication Dat.
Rumler, F., & Waschiczek, W. (2010). The impact of economic factors on bank profits. Monetary Policy & the Economy, 4(10), 49-67.
San-Martín, S., Jiménez, N. H., & López-Catalán, B. (2016). The firms benefits of mobile CRM from the relationship marketing approach and the TOE model. Spanish journal of marketing-ESIC, 20(1), 18-29.
Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, 29(1), 28-45.
Vempati, S. (2016). The Artificial Intelligence Revolution. Carnegie Endowment for International Peace.
Wade, M., & Hulland, J. (2004). The Resource-Based View and Information Systems Research: Review, Extension, and Suggestions for Future Research. MIS quarterly, 28(1), 107-142.
Wells, D. (2022). Business Analytics—Getting the Point. BeyeNetwork. 2008. Available online: http://www.b-eyenetwork.com/view/7133 (accessed on 5 January 2022).
Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS Adoption from the Perspective of Organizational Users: A Tripod Readiness Model, Computers in Human Behavior (45), pp.
Zhai, I. (2010). Research on Post-Adoption Behavior of B2B E-Marketplace in China, Management and Service Science (MASS), 2010 International Conference on: IEEE, pp. 1-5.