Examining The Influence of Various Big Data Capabilities on Tourism Firms in Saudi Arabia
-
https://doi.org/10.14419/v071je64
Received date: May 19, 2025
Accepted date: June 29, 2025
Published date: July 17, 2025
-
Data-Driven, Technology capabilities, Technical Skills, Managerial Skills, and Data-Driven Culture, firm performance, Saudi Arabia, Tourism -
Abstract
The Saudi Vision 2030 promotes digital transformation initiatives, which in turn drive the Big Data Analytics market. Tourism companies with their extensive digital presence, especially on social media, create and capture massive amounts of data. Big Data Analytics (BDA) is are methods that enable large-scale data sets, supporting people management decisions, and cost-effectiveness evaluation. The ability to leverage data effectively has become a key differentiator for firms seeking to enhance their decision-making processes, optimize operations, and drive innovation. To effectively leverage data, companies need a set of related capabilities such as Data-Driven (DD), Technology capability (TECH), Technical Skills (TKSL), Managerial Skills (MSKL), and Data-Driven Culture (DDC). However, the body of knowledge scares studies that assess the impact of these capabilities on firm performance, especially in the Saudi Tourism context. In response, redrawing on the RBT and social materialism theories, the current paper examines the impact of key big data capabilities—Data-Driven (DD), Technology (TECH), Technical Skills (TKSL), Managerial Skills (MSKL), and Data-Driven Culture (DDC)—on firm performance (FP) within Saudi Arabia's tourism sector. By analyzing how these factors influence the effectiveness and success of tourism organizations, the study aims to provide insights into the strategic role of possessing big data analytics capabilities in enhancing competitiveness and driving growth in this rapidly evolving industry. The current study employed a self-administered questionnaire. The variable measurements were derived from previously published studies. The researcher collected 695 responses: 220 were incomplete, and four responses were outliers. The valid responses are 471. The direct impact of DD and TECH on FP shows that DD and TECH capabilities do not directly enhance firm performance. The insignificant roles of DD and TECH may be attributed to the maturity level or implementation quality issues. The direct impact of TSKL, MSKL, and DDC on FP is statistically significant, suggesting that TSKL, MSKL, and DDC capabilities can directly enhance firm performance. Therefore, the corresponding hypotheses H3, H4, and H5 are accepted. While the hypotheses H1 and H2 related to DD and TECH are rejected. Therefore, organizations need to adopt a maturity model of various capabilities to guide the gradual development and integration of analytics capabilities. For future work, it is recommended to investigate contextual factors under which DD and TECH capabilities significantly impact FP, such as complementary capabilities, organizational culture, and analytics maturity.
-
References
- Aburub, F. A. F., Hamzeh, R. F., Alzyoud, M., Alajarmeh, N. S., Al-shanableh, N., Al-Majali, R. T., Al-Hawary, S. I. S., Alshurideh, M. T., & Al-daihani, F. M. F. (2024). The Impact of Big Data Analytics Capabilities on Decision Making at the Telecommunications Sector in Jordan. In A. M. A. Musleh Al-Sartawi, A. S. Aydiner, & M. Kanan (Eds.), Business Analytical Capabilities and Artificial Intelligence-Enabled Analytics: Applica-tions and Challenges in the Digital Era, Volume 1 (pp. 339–354). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56015-6_27
- Ajao, M. G., & Ejokehuma, J. O. (2021). Ownership Structure and Financial Performance of Manufacturing Firms In Sub-Saharan Africa. Facta Universitatis, Series: Economics and Organization, 187. https://doi.org/10.22190/FUEO210319013A
- 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. https://doi.org/10.1016/j.ijpe.2016.08.018
- AlNuaimi, B. K., Khan, M., & Ajmal, M. M. (2021). The role of big data analytics capabilities in greening e-procurement: A higher order PLS-SEM analysis. Technological Forecasting and Social Change, 169, 120808. https://doi.org/10.1016/j.techfore.2021.120808
- Arshad, M., Brohi, M. N., Soomro, T. R., Ghazal, T. M., Alzoubi, H. M., & Alshurideh, M. (2023). NoSQL: Future of BigData Analytics Charac-teristics and Comparison with RDBMS. In M. Alshurideh, B. H. Al Kurdi, R. Masa’deh, H. M. Alzoubi, & S. Salloum (Eds.), The Effect of Infor-mation Technology on Business and Marketing Intelligence Systems (pp. 1927–1951). Springer International Publishing. https://doi.org/10.1007/978-3-031-12382-5_106
- Bag, S., Luthra, S., Mangla, S. K., & Kazancoglu, Y. (2021). Leveraging big data analytics capabilities in making reverse logistics decisions and improving remanufacturing performance. The International Journal of Logistics Management, 32(3), 742–765. https://doi.org/10.1108/IJLM-06-2020-0237
- Bahrawi, S., Abulkhair, M., & Mensi, S. (2021). The Covid-19 Pandemic Impact on the Saudi Arabia Tourism Sector: An Accountancy Approach. 20.
- Bamidele, R. (2022). Organizational Culture (pp. 284–292).
- Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
- Barsha, S., & Munshi, S. A. (2023). Implementing artificial intelligence in library services: A review of current prospects and challenges of develop-ing countries. Library Hi Tech News, 41(1), 7–10. https://doi.org/10.1108/LHTN-07-2023-0126
- Baviskar, D., Ahirrao, S., & Kotecha, K. (2021). Multi-Layout Unstructured Invoice Documents Dataset: A Dataset for Template-Free Invoice Processing and Its Evaluation Using AI Approaches. IEEE Access, 9, 101494–101512. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3096739
- Bazhair, A. H., & Alshareef, M. N. d. (2022). Dynamic relationship between ownership structure and financial performance: A Saudi experience. Cogent Business & Management, 9(1), 2098636. https://doi.org/10.1080/23311975.2022.2098636
- Behl, A. (2020). Antecedents to firm performance and competitiveness using the lens of big data analytics: A cross-cultural study. Management Decision, 60(2), 368–398. https://doi.org/10.1108/MD-01-2020-0121
- Birkel, H. S., & Hartmann, E. (2020). Internet of Things – the future of managing supply chain risks. Supply Chain Management: An International Journal, 25(5), 535–548. https://doi.org/10.1108/SCM-09-2019-0356
- Buzzell, R. D., Gale, B. T., & Sultan, R. G. M. (1975, January 1). Market Share—A Key to Profitability. Harvard Business Review. https://hbr.org/1975/01/market-share-a-key-to-profitability
- Cenfetelli, R. T., & Bassellier, G. (2009). Interpretation of Formative Measurement in Information Systems Research. MIS Quarterly, 33(4), 689–707. https://doi.org/10.2307/20650323
- Cooren, F. (2020). Beyond entanglement:(Socio-) materiality and organization studies. Organization Theory, 1(3), 2631787720954444.
- Davenport, T. H., & Patil, D. J. (2022, July 15). Is Data Scientist Still the Sexiest Job of the 21st Century? Harvard Business Review. https://hbr.org/2022/07/is-data-scientist-still-the-sexiest-job-of-the-21st-century
- Dubey, R., Gunasekaran, A., & Childe, S. J. (2019). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092–2112. https://doi.org/10.1108/MD-01-2018-0119
- Ford, J. D., & Schellenberg, D. A. (1982). Conceptual Issues of Linkage in the Assessment of Organizational Performance. Academy of Manage-ment Review, 7(1), 49–58. https://doi.org/10.5465/amr.1982.4285450
- George, G., Haas, M. R., & Pentland, A. (2014). Big Data and Management. Academy of Management Journal, 57(2), 321–326. https://doi.org/10.5465/amj.2014.4002
- Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049–1064. https://doi.org/10.1016/j.im.2016.07.004
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation model-ing. Journal of the Academy of Marketing Science, 43(1), 115–135.
- Hirschlein, N., Meckenstock, J.-N., & Dremel, C. (2022). Towards Bridging the Gap Between BDA Challenges and BDA Capability: A Conceptu-al Synthesis Based on a Systematic Literature Review. Hawaii International Conference on System Sciences 2022 (HICSS-55). https://aisel.aisnet.org/hicss-55/os/org_issues_in_bi/9
- Jaouadi, M. H. O. (2022). Investigating the influence of big data analytics capabilities and human resource factors in achieving supply chain innova-tiveness. Computers & Industrial Engineering, 168, 108055. https://doi.org/10.1016/j.cie.2022.108055
- Lee, S.-M. (2020). Impact of Big Data Analytics Capability and Strategic Alliances on Financial Performance. In L. C. Jain, S.-L. Peng, & S.-J. Wang (Eds.), Security with Intelligent Computing and Big-Data Services 2019 (pp. 49–63). Springer International Publishing. https://doi.org/10.1007/978-3-030-46828-6_6
- Lnenicka, M., & Komarkova, J. (2019). Big and open linked data analytics ecosystem: Theoretical background and essential elements. Government Information Quarterly, 36(1), 129–144. https://doi.org/10.1016/j.giq.2018.11.004
- Maurya, C. D., & Sharma, A. K. (2017). The role of managerial skills in success of an organization. CLEAR International Journal of Research in Commerce & Management, 8(6).
- McAfee, A., & Brynjolfsson, E. (2012, October 1). Big Data: The Management Revolution. Harvard Business Review. https://hbr.org/2012/10/big-data-the-management-revolution
- Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: Findings from a mixed-method approach. Journal of Business Research, 98, 261–276. https://doi.org/10.1016/j.jbusres.2019.01.044
- Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive per-formance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.05.004
- Nnwobuike, M. R., & Oghenekaro, A. P. (2021). Conventional database management systems. ACADEMICIA: AN INTERNATIONAL MUL-TIDISCIPLINARY RESEARCH JOURNAL, 11(1), 889–903. https://doi.org/10.5958/2249-7137.2021.00149.X
- Nolin, J. M. (2019). Data as oil, infrastructure or asset? Three metaphors of data as economic value. Journal of Information, Communication and Ethics in Society, 18(1), 28–43. https://doi.org/10.1108/JICES-04-2019-0044
- Orlikowski, W. J. (2007). Sociomaterial Practices: Exploring Technology at Work. Organization Studies, 28(9), 1435–1448. https://doi.org/10.1177/0170840607081138
- Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Infor-mation Systems Frontiers, 20(2), 209–222. https://doi.org/10.1007/s10796-016-9720-4
- Salamcı, M. E., & Artar, O. K. (2021). The Effect of Organizational Commitment on Firm Performance: Intergenerational Differences. Journal of International Trade, Logistics and Law, 7(1), Article 1.
- Saleh, S. (2025). Saudi Arabia: International tourist arrivals. Statista. https://www.statista.com/statistics/674149/saudi-arabia-international-tourist-arrivals/
- SHRM. (2021). Managing for Employee Retention. SHRM. https://www.shrm.org/resourcesandtools/tools-and-samples/toolkits/pages/managingforemployeeretention.aspx
- Sindarov, A., Vafaei-Zadeh, A., Syafrizal, S., & Chanda, R. C. (2023). Big data analytical capability and firm performance: Moderating effect of analytics capability business strategy alignment. International Journal of Applied Decision Sciences, 16(6), 663–685. https://doi.org/10.1504/IJADS.2023.134188
- Sousa, M. J., Pesqueira, A. M., Lemos, C., Sousa, M., & Rocha, Á. (2019). Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations. Journal of Medical Systems, 43(9), 290. https://doi.org/10.1007/s10916-019-1419-x
- Straub, D., & Gefen, D. (2004). Validation Guidelines for IS Positivist Research. Communications of the Association for Information Systems, 13. https://doi.org/10.17705/1CAIS.01324
- Surbakti, F. P. S., Wang, W., Indulska, M., & Sadiq, S. (2020). Factors influencing effective use of big data: A research framework. Information & Management, 57(1), 103146. https://doi.org/10.1016/j.im.2019.02.001
- Teece, D. J. (2014). The Foundations of Enterprise Performance: Dynamic and Ordinary Capabilities in an (Economic) Theory of Firms. Academy of Management Perspectives, 28(4), 328–352. https://doi.org/10.5465/amp.2013.0116
- Venkatraman, N., & Ramanujam, V. (1986). Measurement of Business Performance in Strategy Research: A Comparison of Approaches. The Academy of Management Review, 11(4), 801. https://doi.org/10.2307/258398
- Venkatraman, P., & Levin, M. W. (2021). A congestion-aware Tabu search heuristic to solve the shared autonomous vehicle routing problem. Jour-nal of Intelligent Transportation Systems, 25(4), 343–355. https://doi.org/10.1080/15472450.2019.1665521
- Vision 2030. (2025). 2030: Strategic objectives and vision realization programs.
- Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2), 171–180. https://doi.org/10.1002/smj.4250050207
- Wu, D., & Zhang, Y. (2021). Impact of Big Data Analytic Capability on Firm Performance: The Moderating Effect of IT-Strategic Alignment. 2021 5th Annual International Conference on Data Science and Business Analytics (ICDSBA), 115–119. https://doi.org/10.1109/ICDSBA53075.2021.00033
- Žukauskas, P., Vveinhardt, J., & Andriukaitienė, R. (2018). Management Culture and Corporate Social Responsibility. BoD – Books on Demand.
- Zulganef, Z., Pratminingsih, S. A., & Rianawati, A. (2023). Leveraging strategic intuition to reach firm performance: The role of entrepreneurial agility and environmental dynamism. Jurnal Siasat Bisnis, 49–60. https://doi.org/10.20885/jsb.vol27.iss1.art4
-
Downloads
-
How to Cite
Sultan, W. A. M. ., Alsenosy, A. ., & Jaharadak, A. A. B. . (2025). Examining The Influence of Various Big Data Capabilities on Tourism Firms in Saudi Arabia. International Journal of Accounting and Economics Studies, 12(3), 104-114. https://doi.org/10.14419/v071je64
