Exploring the factors influencing the adoption of business intelligence in Malaysia’s service sector

Baboo Daniel James Sivanathan ,Ainin Sulaiman ,Nadisah Zakaria ,Siong Min Foo

doi:10.24294/jipd4971

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Exploring the factors influencing the adoption of business intelligence in Malaysia’s service sector

Baboo Daniel James Sivanathan

Ainin Sulaiman

Nadisah Zakaria

Siong Min Foo

Journal of Infrastructure Policy and Development 2024, 8(16), 4971; https://doi.org/10.24294/jipd4971

Submitted：04 Mar 2024

Accepted：29 Nov 2024

Published：25 Dec 2024

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Abstract

In the realm of contemporary business, Business Intelligence (BI) offers significant potential for informed decision-making, particularly among executives. However, despite its global popularity, BI adoption in Malaysia’s service sector remains relatively low, even in the face of extensive data generation. This study explores the factors influencing BI adoption in this sector, employing the Technology Acceptance Model (TAM) as its conceptual framework. Drawing on relevant BI literature, the study identifies key TAM factors that impact BI adoption. Using SEM modelling, it analyses quantitative data collected from 45 individuals in managerial roles within Malaysia’s service sector, particularly in the Klang Valley. The findings highlight the crucial role of Perceived Usefulness in influencing the Behavioral Intention to adopt BI, serving as a mediating factor between Computer Self-efficacy and BI adoption. In contrast, Perceived Ease of Use does not have a direct impact on BI adoption and does not mediate the relationship between Computer Self-efficacy and Behavioral Intention. These insights demonstrate the complex nature of BI adoption, emphasizing the importance of Perceived Usefulness in shaping Behavioral Intentions. The outcomes of the study aim to guide executives in Malaysia’s service sector, outlining key considerations for successful BI adoption.

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References

Abdulnabi, S. M. (2024). Adoption of Business Intelligence Among Iraqi SMEs Culture: Impact of Technology Acceptance Model, Information Quality, And Organizational Readiness. Journal of Intercultural Communication, 24(3), 32-43. https://doi.org/10.36923/jicc.v24i3.833

Ahmad, A., Hossain, M.A. (2018). Assimilation of Business Intelligence Systems: The Mediating Role of Organizational Knowledge Culture. In: et al. Challenges and Opportunities in the Digital Era. I3E 2018. Lecture Notes in Computer Science, vol 11195. Springer, Cham.

Ahmad, S., Miskon, S., Alabdan, R., & Tlili, I. (2020). Exploration of influential determinants for the adoption of business intelligence systems in the textile and apparel industry. Sustainability, 12(18), 7674. https://doi.org/10.3390/su12187674

Ain, N., Vaia, G., DeLone, W. H., & Waheed, M. (2019). Two decades of research on business intelligence system adoption, utilization and success–A systematic literature review. Decision Support Systems, 125, 113113. https://doi.org/10.1016/j.dss.2019.113113

Albelbisi, N.A., Al-Adwan, A.S., Habibi, A., (2021). Impact of quality antecedents on satisfaction toward MOOC. Turk. Online J. Distance Educ. 22 (2), 164–175. https://doi.org/10.17718/tojde.906843.

Alkhwaldi, A. F. (2024). Understanding the acceptance of business intelligence from healthcare professionals’ perspective: An empirical study of healthcare organizations. International Journal of Organizational Analysis, 32(9), 2135-2163. https://doi.org/10.1108/IJOA-10-2023-4063

Almulla, M. (2021). Technology Acceptance Model (TAM) and e-learning system used for education sustainability. Academy of Strategic Management Journal, 20(4), 1-13.

Andar, J., & Kasparova, P. (2024). Impact of Management Support on Business Intelligence Adoption: Illustrative Case Study Testing Different Managerial Strategies. Acta Informatica Pragensia, 13(1), 85-99. https://doi.org/10.18267/j.aip.230

Basuki, R., Tarigan, Z., Siagian, H., Limanta, L., Setiawan, D., & Mochtar, J. (2022). The effects of perceived ease of use, usefulness, enjoyment and intention to use online platforms on behavioural intention in online movie watching during the pandemic era. International Journal of Data and Network Science, 6(1), 253-262. http://doi.org: 10.5267/j.ijdns.2021.9.003

Bernama. (2020, February 9). - Malaysia still lagging. BERNAMA. Retrieved May 4, 2023, from https://www.bernama.com/en/thoughts/news.php?id=1875164

Bhatiasevi, V., & Naglis, M. (2020). Elucidating the determinants of business intelligence adoption and organizational performance. Information development, 36(1), 78-96. https://doi.org/10.1177/026666691881139

Bhattarai, S., & Maharjan, S. (2020). Determining the factors affecting digital learning adoption among the students in Kathmandu Valley: An application of technology acceptance model (TAM). International Journal of Engineering and Management Research, 10(3).

Buhasho, E., Wausi, A., & Njihia, J. (2021). Moderating Effect of Organizational Capability on the Relationship Between Business Intelligence Capability and Performance Among Public Listed Firms in Kenya. European Scientific Journal, 17(1), 335-352. https://doi.org/10.19044/esj.2021.v17n1p335

Chaveesuk, S., & Chaiyasoonthorn, W. (2022). COVID-19 in emerging countries and students’ intention to use cloud classroom: evidence from Thailand. Education Research International. https://doi.org/10.1155/2022/6909120

Chi, T. W., Tan, C.L & Mahmud, I. (2020). Business intelligence system adoption: A systematic literature review of two decades. International Journal of Industrial Management, 6(1), 1-8. https://doi.org/10.15282/ijim.6.0.2020.5624

CPA Australia. (2021). Business Technology Report 2021. Retrieved from: https://www.cpaaustralia.com.au/-/media/project/cpa/corporate/documents/tools andresources/financial-reporting/business-technology-report-2021.pdf?rev=b99ab28c4c9b4e299402b9fd010a8d8f

Department of Statistics Malaysia (DOSM). (2021). Gross Domestic Product (GDP) by Economic Activity. Retrieved from: https://www.dosm.gov.my/v1/index.php?r=column/ctheme&menu_id=U3VPMldoYUxzVzFaYmNkTjVabVl4UT09&bul_id=MDY4MzI=

Dewanti, R., & Sabri, R. (2022). An Acceptance Models of Behavioural Intention On E-Learning. In:ICCD, 4(1), 507-513. https://doi.org/10.33068/iccd.v4i1.513

Economic Planning Unit (EPU). (2021). Twelfth Malaysia Plan 2021-2025. Retrieved from https://rmke12.epu.gov.my/en.

El Malki, A., & touate, S. (2024). An overview of human and organizational determinants in business intelligence adoption. Multidisciplinary Reviews, 7(11), 2024253. https://doi.org/10.31893/multirev.2024253

Ernst & Young (EY). (2020). EY Growth Barometer Malaysia 2020. Retrieved from https://www.ey.com/en_my/growth-barometer-malaysia-2020.

Feyen, E., Frost, J., Gambacorta, L., Natarajan, H., & Saal, M. (2021). Fintech and the digital transformation of financial services: implications for market structure and public policy. Www.bis.org. https://www.bis.org/publ/bppdf/bispap117.htm

Gaol, F. L., Abdillah, L., & Matsuo, T. (2020). Adoption of business intelligence to support cost accounting based financial systems—case study of XYZ company. Open Engineering, 11(1), 14-28. https://doi.org/10.1515/eng-2021-0002

Gottfried, A., Hartmann, C., Yates, D., 2021. Mining open government data for business intelligence using data visualization: a two-industry case study. J. Theor. Appl. Electron. Commer. Res. 16 (4), 1042–1065. https://doi.org/10.3390/jtaer16040059.

Hasa. (2021). What is the Difference Between Explanatory and Exploratory Research? Pedia. Retrieved from https://pediaa.com/what-is-the-difference-between-explanatory-andexploratory-research/

Hatamlah, H., Allahham, M., Abu-AlSondos, I., Al-Junaidi, A., Al-Anati, G., & Al-Shaikh, M. (2023). The role of business intelligence adoption as a mediator of big data analytics in the management of outsourced reverse supply chain operations. Applied Mathematics & Information Sciences, 17(5), 897-903. https://dx.doi.org/10.18576/amis/170516

Hmoud, H., Al-Adwan, A. S., Horani, O., Yaseen, H., & Al Zoubi, J. Z. (2023). Factors influencing business intelligence adoption by higher education institutions. Journal of Open Innovation: Technology, Market, and Complexity, 9(3), 100111. https://doi.org/10.1016/j.joitmc.2023.100111

Jaradat, Z., Al-Dmour, A., Alshurafat, H., Al-Hazaima, H., & Al Shbail, M. O. (2024). Factors influencing business intelligence adoption: evidence from Jordan. Journal of Decision Systems, 33(2), 242-262. http://doi.org: 10.1080/12460125.2022.2094531

Jaradat, Z., AL-Hawamleh, A., Altarawneh, M., Hikal, H., & Elfedawy, A. (2024). The interplay between intellectual capital, business intelligence adoption, and the decision to innovate: evidence from Jordan. International Journal of Computing and Digital Systems, 15(1), 1375-1389. http://dx.doi.org/10.12785/ijcds/150197

Jiménez-Partearroyo, M., Medina-López, A., & Rana, S. (2024). Business intelligence and business analytics in tourism: insights through Gioia methodology. International Entrepreneurship and Management Journal, 20, 2287-2321.https://doi.org/10.1007/s11365-024-00973-7

Jourdan, Z., & Massey, A. P. (2016). Business intelligence: An overview. Journal of Intelligence Studies in Business, 6(1), 7-20.

Kamal, M., Andriadi, R., Herwanto, H., & Wijaya, L. (2022). Factors Determining the Behavioural Intention to Use ConSite Application for Heavy Machine Management System: Using TAM 2 Model. https://doi.org/10.46254/EU05.20220081

Kesmodel, U. S. (2018). Cross-sectional studies – what are they good for? Acta Obstetricia et Gynecologica Scandinavica. https://doi.org/10.1111/aogs.13331

Kikawa, C. R., Kalema, B. M., & Carol, M. N. (2019). A statistical analysis of business intelligence acceptance by SMEs in the city of Tshwane, Republic of South Africa. Academy of Entrepreneurship Journal, 25(2), 1-19.

Kronz, A., Schlegel, K., Sun, J., Pidsley, D., & Ganeshan, A. (2022). Magic Quadrant for Analytics and Business Intelligence Platforms. Gartner.

Kumar, V., Sen, C., Jain, A., Jain, A., & Sharma, A. (2024). Analysis of Business Intelligence in Healthcare Using Machine Learning. Optimized Predictive Models in Healthcare Using Machine Learning, 329-339. https://doi.org/10.1002/9781394175376.ch19

L. Chen and A. K. Aklikokou, “Determinants of e-government adoption: testing the mediating effects of perceived usefulness and perceived ease of use,” International Journal of Public Administration, 43 (10), 850–865. https://doi.org/10.1080/01900692.2019.1660989

Lavidas, K., Papadakis, S., Filippidi, A., Karachristos, C., Misirli, A., Tzavara, A. & Karacapilidis, N. (2023). Predicting the Behavioural Intention of Greek University Faculty Members to Use Moodle. Sustainability, 15(7), 6290. https://doi.org/10.3390/su15076290

Malaysia Digital Economy Corporation (MDEC). (2020). Malaysia e-commerce & Digital Economy Report 2020. Retrieved from https://mdec.my/wp-content/uploads/2021/01/Malaysia-E-commerce-Digital-Economy-Report-2020.pdf

Malaysian Investment Development Authority (MIDA). (2019). Malaysian SMEs Performance Report 2019. Retrieved from https://www.mida.gov.my/home/malaysian-sme-performance-report-2019-2020/posts

Malaysian Investment Development Authority (MIDA). (2021). The Time to Transform Is Now: Adoption of Technology Across Operations. Retrieved from https://www.mida.gov.my/the-time-to-transform-is-now-adoption-of-technologyacross-operations

Marikyan, D.& Papagiannidis, S. (2023) Technology Acceptance Model: A review. In S. Papagiannidis (Ed), TheoryHub Book. Available at https://open.ncl.ac.uk / ISBN: 9781739604400

Martins, A., Bianchi de Aguiar, M. T., Sambento, M., & Branco, M. C. (2024). Business intelligence system adoption and the leveraging of reporting process capabilities. Journal of Accounting & Organizational Change. https://doi.org/10.1108/JAOC-11-2023-0204

Mohammad, A.B., 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. J. Open Innov. 8 (4), 189 https://doi.org/10.3390/joitmc8040189.

Mohd Shukri, N., & Harun, M. (2021). Malaysia’s Foreign Direct Investment Relations Within the Organisation Developing Eight Economic Cooperation (D8) Within Counterparts. Universiti Malaysia Terengganu Journal of Undergraduate Research, 3(2). https://doi.org/10.46754/umtjur.v3i2.209

Mohsin, M. I. A., Ahmad, R., & Chan, W. M. (2022). Exploring Digitalization of Malaysian Banking and Fintech Companies’ Services from the Customer’s Perspective. International Journal of Management and Applied Research, 9(2),140-160. https://doi.org/10.18646/2056.92.22-007

Morris, A. (16 April 2021). 23 Case Studies and Real-World Examples of How Business Intelligence Keeps Top Companies Competitive. Retrieved from Oracle NetSuite: https://www.netsuite.com/portal/resource/articles/business-strategy/businessintelligence-examples.shtml.

Nazri, S., & Iskandar, Y. H. (2021). How Has the Adoption of Business Intelligence Impacted Performance of Higher Education Institutions: Empirical Evidence from Malaysia. International Journal of Academic Research in Business and Social Sciences, 11(1), 723–740. http://dx.doi.org/10.6007/IJARBSS/v11-i1/8449

Ni, T. W. (2020). Factors influencing behavioural intention towards adoption of digital banking services in Malaysia. International Journal of Asian Social Science, 10(8), 450-457. https://doi.org/10.18488/journal.1.2020.108.450.457

Nithya, N., & Kiruthika, R. (2021). Impact of Business Intelligence Adoption on performance of banks: a conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 12(2), 3139-3150. https://doi.org/10.1007/s12652-020-02473-2

Pan, X. (2020). Technology acceptance, technological self-efficacy, and attitude toward technology-based self-directed learning: learning motivation as a mediator. Frontiers in Psychology, 11, 564294. https://doi.org/10.3389/fpsyg.2020.564294

Phan, K. Y., & Teoh, A. P. (2024). Systematic literature review on the influence of business intelligence capabilities on BI systems success and firm performance: an Asian perspective. International Journal of Business Information Systems, 47(2), 227-254. https://doi.org:10.1504/IJBIS.2021.10040823

Qatawneh, N. (2024). Empirical insights into business intelligence adoption and decision-making performance during the digital transformation era: Extending the TOE model in the Jordanian banking sector. Journal of Open Innovation: Technology, Market, and Complexity, 10(4), 100401. https://doi.org/10.1016/j.joitmc.2024.100401

Ranjan, J., & Foropon, C. (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, 56, 102231. https://doi.org/10.1016/j.ijinfomgt.2020.102231

Salaki, R. J., & Mogea, T. (2020). Agile analytics: Adoption framework for business intelligence in higher education. 98(7).

Salisu, I., Bin Mohd Sappri, M., Bin Omar, M.F., (2021). The adoption of business intelligence systems in small and medium enterprises in the healthcare sector: a systematic literature review. Cogent Bus. Manag. 8 (1), 1935663. https://doi.org/10.1080/23311975.2021.1935663.

Subramaniam, R., Palakeel, P., Arunmozhi, M., Sridharan, M., & Marimuthu, U. (2024). Factors driving business intelligence adoption: an extended technology-organization-environment framework. Indonesian Journal of Electrical Engineering and Computer Science, 34(3), 1893-1903. http://doi.org/10.11591/ijeecs.v34.i3.pp1893-1903

Tavera Romero, C. A., Ortiz, J. H., Khalaf, O. I., & Ríos Prado, A. (2021). Business Intelligence: Business Evolution after Industry 4.0. Sustainability, 13(18), 10026. https://doi.org/10.3390/su131810026

Wee, M., Scheepers, H., & Tian, X. (2022). The role of leadership skills in the adoption of business intelligence and analytics by SMEs. Information Technology & People, 36(4), 1439-1458. https://doi.org/10.1108/ITP-09-2021-0669

Ya’akub, M. (2020), Malaysian Digital Economy Newsletter. Department of Statistics Malaysia (DOSM). Retrieved from https://www.dosm.gov.my/v1/uploads/files/6_Newsletter/Newsletter%202020/DOSM_BPP_4-2020_Series-26.pdf

Yu, S. (2022). A Research on University Students’ Behavioural Intention to Use New Generation Information Technology in Intelligent Foreign Language Learning, 23(5), 1-15. https://doi.org/10.1145/3563774

Zoubi, M., ALfaris, Y., Fraihat, B., Otoum, A., Nawasreh, M., & ALfandi, A. (2023). An extension of the diffusion of innovation theory for business intelligence adoption: A maturity perspective on project management. Uncertain Supply Chain Management, 11(2), 465-472. https://doi.org: 10.5267/j.uscm.2023.3.003

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