The impact of dynamic marketing capabilities on startup performance: A case of business incubators in Jordan

  • Received October 31, 2023;
    Accepted January 22, 2024;
    Published February 8, 2024
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.20(1).2024.12
  • Article Info
    Volume 20 2024, Issue #1, pp. 132-145
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This work is licensed under a Creative Commons Attribution 4.0 International License

Dynamic marketing capabilities provide startups with the platform and market knowledge that entitle them to achieve their goals and survive the competition. The study aims to examine the impact of dynamic marketing capabilities dimensions on startups’ performance in Jordan. This quantitative study employs a questionnaire to solicit answers from respondents who are the incubates that use business incubator services. A total of 302 entrepreneurs from different incubator centers in Jordan participated in the online survey. Using the SmartPLS program version 4, structural equation modeling (PLS-SEM) was used to examine the study model. The findings indicate that startup performance is significantly impacted by dynamic marketing capabilities (β = 0.937, t = 127.2, p = >0.00). Concerning absorptive capacity, both dimensions revealed a significant impact on startup performance: potential absorptive capacity (β = 0.251, t = 7.932, p > 0.000) and realized absorptive capacity (β = 0.177, t = 5.409, p > 0.000). For knowledge management, the results for knowledge acquisition were β = 0.360, t = 11.089, p = >0.000, for knowledge dissemination, β = 0.102, t = 2.367, p = >0.018, and for responsiveness to knowledge β = 0.318, t = 6.852, p = >0.000.

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    • Figure 1. Research model
    • Figure 2. Main hypothesis testing
    • Figure 3. The impact of absorptive capacity on startup performance
    • Figure 4. The impact of knowledge management on startup performance
    • Table 1. Variance inflation factor (VIF) and tolerance values for variable dimensions
    • Table 2. Demographic profile
    • Table 3. Factor loadings, Cronbach’s alpha, average variance extracted (AVE), and weight of item loading
    • Table 4. Discriminant validity: Fornell-Larcker criterion
    • Table 5. Results of hypotheses testing
    • Conceptualization
      Hamza Salim Khraim
    • Data curation
      Hamza Salim Khraim
    • Formal Analysis
      Hamza Salim Khraim
    • Investigation
      Hamza Salim Khraim
    • Methodology
      Hamza Salim Khraim
    • Project administration
      Hamza Salim Khraim
    • Resources
      Hamza Salim Khraim
    • Software
      Hamza Salim Khraim
    • Validation
      Hamza Salim Khraim
    • Visualization
      Hamza Salim Khraim
    • Writing – original draft
      Hamza Salim Khraim
    • Writing – review & editing
      Hamza Salim Khraim