Strategic enablers of business intelligence in marketing: Insights from the digital transformation of Jordanian firms
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DOIhttp://dx.doi.org/10.21511/im.22(2).2026.06
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Article InfoVolume 22 2026, Issue #2, pp. 71-82
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Type of the article: Research Article
Abstract
Investments such as technological investments in useful marketing intelligence are an important organizational challenge because companies raise the pace of their digital transformation activities. The research is based on the Resource-Based View and Dynamic Capabilities Theory and aims to investigate how the data on important organizational and technological enablers’ data-driven culture, technological readiness, top management support, and marketing analytics maturity influence Business Intelligence (BI) capability in marketing functions. The primary data were gathered between February and May 2025 with the help of a structured online survey among the marketing managers, BI specialists, analytics professionals, and IT decision-makers, working in Amman, Irbid, Zarqa, and Aqaba, Jordan. Based on a purposive sampling technique, 602 valid responses were interpreted with the help of Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings show that Marketing Analytics Maturity has the most significant impact on BI capability (β = 0.367, p = 0.001), then Data Culture (β = 0.321, p = 0.001) and Technological Readiness (β = 0.287, p = 0.01). The positive, relatively weak effect (β = 0.224, p < 0.05) is demonstrated by Technology Readiness. The structural model shows significant explanatory power and explains 78.1 percent of the variance on BI capability. Such results indicate that building BI capabilities among emerging market companies is not as much about acquiring technology, but rather about integrating managerial support and analytics maturity, which emphasizes the importance of readiness in an organization in changing digital investments into the value of marketing intelligence.
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JEL Classification (Paper profile tab)M31, C38, L86, M15
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References59
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Tables6
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Figures0
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- Table 1. Demographic characteristics
- Table 2. Descriptive statistics and reliability analysis
- Table 3. CFA results and validity metrics
- Table 4. Correlation matrix (Pearson coefficients)
- Table 5. Model fit indices
- Table 6. Structural model and hypothesis testing
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