Adoption of business intelligence in Jordanian hospitals: Examining moderating effects of support, readiness, compatibility, and user satisfaction
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DOIhttp://dx.doi.org/10.21511/ppm.23(2).2025.61
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Article InfoVolume 23 2025, Issue #2, pp. 838-847
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Business intelligence (BI) systems are crucial to hospitals, as they enable organizations to make informed decisions through data analysis and enhance operational efficiency. BI adoption experiences barriers in Jordanian hospitals as a result of both organization-specific needs and technological limitations of their environments. This study assessed BI adoption by surveying employees at different departments in Jordanian hospitals. From January to May 2024, a total of 350 surveys were distributed, resulting in 312 valid responses collected through online and paper-based methods. The analysis involved participants from various departments, including administrative staff, clinical personnel, and IT department professionals, to gain a comprehensive understanding of BI readiness throughout the organization. The results demonstrate that technological compatibility and environmental factors are critical for successful BI adoption (p < 0.05), yet findings show organizational readiness has no direct effect (p > 0.05). Top management support has a positive effect on BI adoption, and user satisfaction serves as a critical moderating variable, positively influencing the relationship between these elements (p < 0.05). Business intelligence systems require dedicated leadership focus, along with proper technological infrastructure and active user engagement, for successful deployment. The study offers practical recommendations for hospital executives and policymakers with strategies to deploy BI using leadership initiatives plus technological integration and worker development. The establishment of digital healthcare advancement programs stands as a goal that government authorities must achieve. Furthermore, the establishment of national digital healthcare advancement programs and the expansion of cross-institutional data collection are essential in different settings.
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JEL Classification (Paper profile tab)M15, I11, O33
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References45
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Tables4
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Figures2
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- Figure 1. Conceptual model of the study
- Figure 2. Conceptual framework
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- Table 1. Demographic profile of respondents
- Table 2. Construct reliability and validity assessment
- Table 3. Model fit indices
- Table 4. Hypotheses testing results
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- Ahmad, S., Miskon, S., Alkanhal, T. A., & Tlili, I. (2020). Modeling of business intelligence systems using the potential determinants and theories with the lens of individual, technological, organizational, and environmental contexts – A systematic literature review. Applied Sciences, 10(9).
- Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y. K., D’Ambra, J., & Shen, K. N. (2021). Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management, 60, Article 102387.
- Ali, A. A., Sharabati, A. A., Alqurashi, D. R., Shkeer, A. S., & Allahham, M. (2024). The impact of artificial intelligence and supply chain collaboration on supply chain resilience: Mediating the effects of information sharing. Uncertain Supply Chain Management, 12, 1801-1812.
- 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.
- Al-Muhrami, M. A. S., Alawi, N. A., Alzubi, M., & Al-Refaei, A. A. A. (2021, June). Affecting the behavioural intention to use electronic banking services among users in Yemen: Using an Extension of the unified theory of acceptance and use of technology. In 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE) (pp. 257-264). IEEE.
- Al-Sharafi, M. A., Al-Qaysi, N., Iahad, N. A., & Al-Emran, M. (2022). Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach. International Journal of Bank Marketing, 40(5), 1071-1095.
- Alzubi, M. M., Ismaeel, B., & Ateik, A. H. (2021). The Moderating Effect of Compatibility Factor in The Usage of E-Government Services Among Malaysian Citizens. In 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE) (pp. 224-232). IEEE.
- Arefin, M. S., Hoque, M. R., & Rasul, T. (2021). Organizational learning culture and business intelligence systems of healthcare organizations in an emerging economy. Journal of Knowledge Management, 25(3), 573-594.
- Awais, S., Yasin, Z., & Raza, F. (2022). Impact of mobile application compatibility, online shopping and payment on the user satisfaction in Pakistan context: Mediating role of social networking site adoption. Journal of Management Practices, Humanities and Social Sciences, 6(1), 28-39.
- Bany 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, 8(4).
- Bartlett, L., Kabir, M. A., & Han, J. (2023). A review on business process management system design: The role of virtualization and work design. IEEE Access, 11, 116786-116819.
- Begum, F., Khan, R., Mandal, J., Kaium, M. A., Rahman, M. S., & Zahan, I. (2024). Unveiling end-users’ satisfaction and actual use of blockchain in e-health: Empirical evidence from Bangladesh. Journal of Consumer Sciences, 9(2), 163-184.
- Bhatiasevi, V., & Naglis, M. (2020). Elucidating the determinants of business intelligence adoption and organizational performance. Information Development, 36(1), 78-96.
- De Luna, I. R., Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2019). Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied. Technological Forecasting and Social Change, 146, 931-944.
- DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
- Elbashir, M. Z., Sutton, S. G., Arnold, V., & Collier, P. A. (2022). Leveraging business intelligence systems to enhance management control and business process performance in the public sector. Meditari Accountancy Research, 30(4), 914-940.
- Gangwar, H. (2020). Big data analytics usage and business performance: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Electronic Journal of Information Systems Evaluation, 23(1), 45-64.
- Gautam, R., & Sharma, M. (2020). 2019-nCoV pandemic: A disruptive and stressful atmosphere for Indian academic fraternity. Brain, Behavior, and Immunity, 88, 948-949.
- Gkrimpizi, T., Peristeras, V., & Magnisalis, I. (2023). Classification of barriers to digital transformation in higher education institutions: Systematic literature review. Education Sciences, 13(7).
- Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
- 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.
- 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), Article 100111.
- Indrasari, A., Nugraheni, P., Hamzah, N., & Maelah, R. (2021). Motivational factors of implementing corporate social and environmental reporting and its impact on performance. Journal of Asian Finance, Economics and Business, 8(2), 883-892.
- Isiaku, L., & Adalier, A. (2024). Determinants of business intelligence systems adoption in Nigerian banks: The role of perceived usefulness and ease of use. Information Development.
- Jaklič, J., Grublješič, T., & Popovič, A. (2018). The role of compatibility in predicting business intelligence and analytics use intentions. International Journal of Information Management, 43, 305-318.
- 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.
- Kaur, B., Kiran, S., Grima, S., & Rupeika-Apoga, R. (2021). Digital banking in Northern India: The risks on customer satisfaction. Risks, 9(11).
- Kitsios, F., & Kapetaneas, N. (2022). Digital transformation in healthcare 4.0: Critical factors for business intelligence systems. Information, 13(5).
- Kowalski, C. M., Rogoza, R., Saklofske, D. H., & Schermer, J. A. (2021). Dark triads, tetrads, tents, and cores: Why navigate (research) the jungle of dark personality models without a compass (criterion)? Acta Psychologica, 221, 10345.
- Krejcie, R., & Morgan, S. (1970). Sample size determination. Business Research Methods, 4(5), 34-36.
- Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272-298.
- Nirwanto, N., & Andarwati, M. (2019). End-user satisfaction as an impact of the system quality, information quality, and top management support, upon the perceived usefulness of technology utilization. Journal of Marketing Development and Competitiveness, 13(1).
- Nwosu, N. T. (2024). Reducing operational costs in healthcare through advanced BI tools and data integration. World Journal of Advanced Research and Reviews, 22(3), 1144-1156.
- Prasetio, A. B., Aboobaider, B. bin M., & Ahmad, A. bin. (2022). Organizational ambidexterity as an outcome of quality dimensions and triple helix: The role of technology readiness and user satisfaction. Sustainability, 14(21).
- Puklavec, B., Oliveira, T., & Popovič, A. (2018). Understanding the determinants of business intelligence system adoption stages: An empirical study of SMEs. Industrial Management & Data Systems, 118(1), 236-261.
- Rouhani, S., Ashrafi, A., Zare Ravasan, A., & Afshari, S. (2016). The impact model of business intelligence on decision support and organizational benefits. Journal of Enterprise Information Management, 29(1), 19-50.
- Shittu, R. A., Ehidiamen, A. J., Ojo, O. O., Zouo, S. J. C., Olamijuwon, J., Omowole, B. M., & Olufemi-Phillips, A. Q. (2024). The role of business intelligence tools in improving healthcare patient outcomes and operations. World Journal of Advanced Research and Reviews, 24(2), 1039-1060.
- Sidharta, I., & Rahmahwati, R. (2023). Cross sectional study on information system facilities on end-user satisfaction: Study at retail in Bandung. Electronic, Business, Management and Technology Journal, 1(1), 1-11.
- Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
- Trincanato, E., & Vagnoni, E. (2024). Business intelligence and the leverage of information in healthcare organizations from a managerial perspective: A systematic literature review and research agenda. Journal of Health Organization and Management, 38(3), 305-330.
- Uzir, M. U. H., Al Halbusi, H., Lim, R., Jerin, I., Hamid, A. B. A., Ramayah, T., & Haque, A. (2021). Applied artificial intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19. Technology in Society, 67, Article 101780.
- Wamba, S. F., Queiroz, M. M., & Trinchera, L. (2020). Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation. International Journal of Production Economics, 229, Article 107791.
- Wong, L.-W., Leong, L.-Y., Hew, J.-J., Tan, G. W.-H., & Ooi, K.-B. (2020). Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs. International Journal of Information Management, 52, Article 101997.
- Zhao, J., Feng, H., Chen, Q., & de Soto, B. G. (2022). Developing a conceptual framework for the application of digital twin technologies to revamp building operation and maintenance processes. Journal of Building Engineering, 49, Article 104028.
- Zheng, J., & Khalid, H. (2022). The adoption of enterprise resource planning and business intelligence systems in small and medium enterprises: A conceptual framework. Mathematical Problems in Engineering.
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The influence of digital transformation on the growth of small and medium enterprises in South Africa
Sanele Jeza
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Lawrence Mpele Lekhanya
doi: http://dx.doi.org/10.21511/ppm.20(3).2022.24
Problems and Perspectives in Management Volume 20, 2022 Issue #3 pp. 297-309 Views: 2534 Downloads: 1273 TO CITE АНОТАЦІЯFrom a global perspective, the business environment has become highly dynamic, unpredictable, and competitive due to external forces – mostly technology – that generate change. The aim of this study is to investigate the influence of digital technologies on South African business sectors. The sample includes small and medium enterprises (SMEs) in the KwaZulu-Natal province. Being qualitative by design, the study used semi-structured interviews for data collection, with eight interviews in the Durban area. SME managers were purposefully selected as participants based on their management positions in the business/company and that they oversee the business operation and understand the influence of digital transformation in the business. The interviews were then transcribed after data collection to determine any recurring themes. In the effectiveness of digital transformation, the study identified themes such as “gaining exposure” and “gaining effective sales figures” as a result of implementing digital transformation, which was indicated by six of eight participants. The findings showed that digital transformation significantly affects building customer relationships and ensuring easy accessibility of the business. The results further indicate online selling and digital marketing as the leading digital platforms successfully implemented by most South African SMEs. Lastly, the study revealed digital maintenance and rapid changes in technology as challenging factors. Moreover, the study recommends that South African SMEs implement more available digital technologies to gain additional exposure.
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Digital transformation to enhance Indonesian SME performance: Exploring the impact of market competition and digital strategy
Dorojatun Prihandono 
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Angga Pandu Wijaya ,
Bayu Wiratama ,
Widya Prananta ,
Syam Widia
doi: http://dx.doi.org/10.21511/ppm.22(2).2024.09
Problems and Perspectives in Management Volume 22, 2024 Issue #2 pp. 103-113 Views: 2171 Downloads: 393 TO CITE АНОТАЦІЯIn the current era, the challenges faced by SMEs in Indonesia are becoming increasingly complex. Previously, the primary challenge for SMEs has been to enhance performance. However, with the emergence of information technology, SMEs are now required to compete fiercely. SMEs in Indonesia are still in the process of digital transformation to improve their business strategies, thus limiting research focused on digital transformation in SMEs. Research also considers market complexity and digital strategy as crucial factors for SMEs. The aim of this study is to analyze the role of digital transformation in influencing SME performance. The research approach is quantitative, involving 171 SMEs owners as respondents. The instrument utilized is a Likert scale questionnaire, focusing on the majority of SMEs in Indonesia, particularly those in Java, the most populous island and business center of the country. This includes SMEs operating within various sectors, such as culinary, fashion, retail, and creative industries. The results indicate that digital strategy and market complexity influence digital transformation and SMEs performance. The research findings suggest that digital transformation mediates the influence of digital strategy and market complexity on SME performance. The novelty of this study lies in its focus on the current SMEs digitalization strategy area. This study indicates that digital transformation is an essential aspect affecting current SME performance. The results suggest that SMEs require focused strategies to strengthen resources and gain competitive advantage in complex markets.
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Impact of digital transformation on the organization’s financial performance: A case of Jordanian commercial banks listed on the Amman Stock Exchange
Nahed Habis Alrawashedh ,
Mohammad Fawzi Shubita
doi: http://dx.doi.org/10.21511/bbs.19(1).2024.11
Banks and Bank Systems Volume 19, 2024 Issue #1 pp. 126-134 Views: 1537 Downloads: 469 TO CITE АНОТАЦІЯDigital transformation refers to strategic activities undertaken by organizations to improve and simplify their process and even alter their business models with abreast to enhance firm performance. Thus, the aim of this study was to analyze the impact of digital transformation on organizational performance among the Jordanian commercial banks listed on the Amman Stock Exchange. The descriptive research design was used in this quantitative study. Primary data were collected to achieve the objectives of the study. The target population was employees (managers and non-managers) of Jordanian commercial banks listed on the Amman Stock Exchange. The sample size was selected using Krejcie and Morgan rule; after data cleaning procedures, the final sample of 282 respondents was used for final analysis. The study employed regression analysis to arrive at the results. The results confirm that digital transformation has a significant positive effect on customer experience and IT innovation. These results were significant at a 1% level. The results also confirm that digital transformation has a significant positive effect on firm performance, with a significance level of 1%. Moreover, the significant positive impact of customer experience and IT innovation was confirmed. Therefore, the significant positive impact of digital transformation on firm performance was found viz-a-viz direct as well as indirect route.
