The impact of strategic agility on sustainable competitive advantage: The mediating role of strategic renewal at Jordanian telecommunication companies

  • 246 Views
  • 84 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Developing a sustainable competitive advantage has emerged as a pivotal objective for organizations due to the dynamic and constantly evolving business environment, challenges modern organizations encounter, rapid market fluctuations, and intense competition. This study aims to examine the impact of strategic agility on sustainable competitive advantage and the mediating role of strategic renewal within an emerging economy such as Jordan. The study collected data from 217 executives holding senior and intermediate positions in telecommunications companies in Jordan. This paper utilized partial least squares structural equation modeling (PLS-SEM) with SmartPLS4 software to test hypotheses and assess the measurement and structural models. According to the findings, strategic agility has a significant positive impact on sustainable competitive advantage (β = 0.590, t = 8.042, p ≤ 0.000) and high explanation power (R2 = 0.828), which means that 82.8% of the variance in sustainable competitive advantage has been explained by strategic agility and strategic renewal. Moreover, strategic renewal partially mediates the relationship between strategic agility and sustainable competitive advantage. In addition, the study revealed that the model’s predictive power was medium. This paper contributes to the body of knowledge and existing literature about the impact of strategy renewal and agility on sustainable competitive advantage in Jordanian telecommunications companies. Organizations incorporating strategic agility and renewal into their strategy can manage uncertainties, swiftly adjust to changes, and attain sustainable competitive advantage.

view full abstract hide full abstract
    • Figure 1. Research model
    • Figure 2. Structural model
    • Table 1. Descriptive statistics
    • Table 2. Reliability and validity
    • Table 3. Discriminant validity: Fornell-Larcker criterion
    • Table 4. Heterotrait-monotrait ratio (HTMT) – Matrix
    • Table 5. Collinearity statistics (VIF)
    • Table 6. Coefficient of determination (R2)
    • Table 7. f² effect size
    • Table 8. Values of the predictive relevance Q2 predict
    • Table 9. Q2 predict values
    • Table 10. Significance test for the path coefficients (direct effects)
    • Table 11. Significance test for the path coefficients (specific indirect effects)
    • Table 12. Significance test for the total effects
    • Conceptualization
      Khaled Al Shawabkeh
    • Data curation
      Khaled Al Shawabkeh
    • Formal Analysis
      Khaled Al Shawabkeh
    • Funding acquisition
      Khaled Al Shawabkeh
    • Investigation
      Khaled Al Shawabkeh
    • Methodology
      Khaled Al Shawabkeh
    • Project administration
      Khaled Al Shawabkeh
    • Resources
      Khaled Al Shawabkeh
    • Software
      Khaled Al Shawabkeh
    • Supervision
      Khaled Al Shawabkeh
    • Validation
      Khaled Al Shawabkeh
    • Visualization
      Khaled Al Shawabkeh
    • Writing – original draft
      Khaled Al Shawabkeh
    • Writing – review & editing
      Khaled Al Shawabkeh