Programming and Data Analysis: Impact on the Performance of Business Managers
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https://doi.org/10.5281/zenodo.14580302Keywords:
Programming skills, business management, decision making, digital transformation, performanceAbstract
In the age of digital transformation, business managers need to gain new skills in areas such as data-driven decision-making, process optimization, and developing innovative business models. In this context, computer programming skills offer significant advantages to managers in a wide range from enabling operational processes to supporting strategic goals. This study, which evaluates the contribution of programming skills to the performance of business managers and business processes, was carried out by literature review method. In this study, the place of programming skills and data analysis in managerial roles, their effect on decision-making processes and their importance in innovative applications are discussed through the existing findings in the literature. In addition, the future potential of programming skills in business administration and research gaps in this field are also discussed.
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Aljumah, A. I., Nuseir, M. T., & Alam, M. M. (2021). Organizational performance and capabilities to analyze big data: Do the ambidexterity and business value of big data analytics matter? Business Process Management Journal, 27(4), 1088-1107. https://doi.org/10.1108/BPMJ-07-2020-0335
Akhtar, P., Frynas, J. G., Mellahi, K., & Ullah, S. (2019). Big data‐savvy teams’ skills, big data‐driven actions and business performance. British Journal of Management, 30(2), 252-271.
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment?. International journal of production economics, 182, 113-131.
Benzidia, S., Makaoui, N., & Bentahar, O. (2021). The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance. Technological forecasting and social change, 165, 120557.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & company.
Chatterjee, S., Rana, N. P., & Dwivedi, Y. K. (2024). How does business analytics contribute to organisational performance and business value? Information Technology & People, 37(2), 874-894. https://doi.org/10.1108/ITP-08-2020-0603
Davenport, T. (2014). Big data at work: dispelling the myths, uncovering the opportunities. Harvard Business Review Press.
Diván, M. J. (2017). Data-driven decision making. Proceedings of the International Conference on Theory and Practice of Electronic Governance (ICTUS), 8285973, 1-8. https://doi.org/10.1109/ICTUS. 2017.8285973
Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., ... & Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International Journal of Production Economics, 226, 107599. https://doi.org/10.1016/ j.ijpe.2019.107599
George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of management Journal, 57(2), 321-326.
Ghasemaghaei, M. (2020). Improving Organizational Performance Through the Use of Big Data. Journal of Computer Information Systems. https://doi.org/10.1080/08874417.2018.1496805
Gupta, S., Drave, V. A., Dwivedi, Y. K., Baabdullah, A. M., & Ismagilova, E. (2020). Achieving superior organizational performance via big data predictive analytics: A dynamic capability view. Industrial Marketing Management, 90, 581–592. https://doi.org/10.1016/j.indmarman.2019.11.009
Holsapple, C., Lee-Post, A., & Pakath, R. (2014). A unified foundation for business analytics. Decision support systems, 64, 130-141.
Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design. SAGE Publications.
Lutfi, A., Alsyouf, A., Almaiah, M. A., Alrawad, M., Abdo, A. A. K., Al-Khasawneh, A. L., Ibrahim, N., & Saad, M. (2022). Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs. Sustainability, 14(3), 1802. https://doi.org/ 10.3390/su14031802
Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20, 209-222.
Sebesta, R. W. (2012). Concepts of Programming Languages (10th ed.). Addison-Wesley.
Sestino, A., Prete, M. I., Piper, L., & Guido, G. (2020). Internet of Things and Big Data as enablers for business digitalization strategies. Technovation, 98, 102173. https://doi.org/10.1016/j.technovation. 2020.102173
Stone, B. (2013). The everything store: Jeff Bezos and the age of Amazon. Random House.
Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, xiii-xxiii.
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