Assessing how supply chains strategy contributes to business success and varies by firm size and industry

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In today’s volatile global market, supply chain performance is vital for maintaining business success, especially in Jordan, where companies face regulatory limitations, import dependence, and political uncertainty. The purpose of this study is to assess how strategic elements within supply chains contribute to business outcomes and whether their impact varies by firm size and industry. A cross-sectional survey was conducted between September and December 2024 in Jordan, targeting firms across key economic sectors. Using a stratified sampling method, 366 firms (152 small, 114 medium, and 100 large enterprises) across manufacturing, retail, pharmaceuticals, and other industries were selected. This sample was chosen to ensure diversity in supply chain structure and resource capacity, making it suitable for examining size- and sector-specific effects. Data were analyzed using partial least squares structural equation modeling and multi-group analysis. Results show that strategic supply chain actions significantly influence performance: internal collaboration enhances external partnerships (β = 0.42, p = 0.002), which increase responsiveness (β = 0.44, p = 0.001) and resilience (β = 0.41, p = 0.002). Larger firms benefit more from structured coordination and diversified sourcing (β = 0.50, p = 0.001), while SMEs face limitations due to resource constraints. Pharmaceutical firms show the strongest sector-based results (β = 0.54, p = 0.002). The findings highlight that universal supply chain strategies are ineffective. Customization by firm size and industry is essential for building agility and long-term success.

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    • Table 1. Sample distribution
    • Table 2. Descriptive statistics of key variables
    • Table 3. Reliability and validity analysis
    • Table 4. Fornell–Larcker criterion
    • Table 5. Heterotrait-monotrait (HTMT) ratio
    • Table 6. Path coefficients and significance tests
    • Table 7. Model fit (SRMR and bootstrapping)
    • Table 8. Partial least squares multi-group analysis (PLS-MGA)
    • Table 9. PLS-MGA by industry sectors
    • Table 10. Mann–Whitney U test (Non-parametric group comparisons)
    • Table 11. Mediation analysis (Bootstrapping and Sobel test)
    • Table 12. Moderation analysis – Business size and industry type as moderators
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Problems and Perspectives in Management
Problems and Perspectives in Management