The relationship between social entrepreneurship orientation, business planning, and competitive advantage on cooperative performance: Moderation of the socio-economic context

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This study delves into the determinants influencing the efficacy of social enterprises, specifically cooperatives. This study aims to examine the interaction between social entrepreneurial orientation (SEO), strategic planning, and competitive advantage in shaping cooperative performance, accounting for the moderating influence of the socio-economic context. A population of cooperatives in Indargiri Hilir and Bengkalis regencies, Riau Province, Indonesia, served as the study’s focus. A sampling strategy was employed to distribute 500 questionnaires to cooperative managers. Of these, 298 were returned and analyzed using partial least squares (PLS). The findings corroborate a positive association between SEO and financial performance with a p-value of 0.000. Likewise, SEO affects competitive advantage and company planning (p-value 0.000). The exploration indicates no mediating role for business strategy in the relationship between financial performance and SEO, with a p-value of 0.136. However, strategic planning acted as a mediator in the relationship between SEO and social performance (p-value 0.011). Moreover, the findings show that SEO has a favorable influence on social performance through competitive advantage with a p-value of 0.000. Thus, the moderating role of socio-economic context on the relationship between SEO and financial performance can be proven with a p-value of 0.000, as well as on the relationship between business planning and financial performance with a p-value of 0.016. These empirical findings can inform policymakers’ strategic development of inclusive and sustainable policies that foster growth and resilience of cooperatives.

Acknowledgment
Authors are grateful to LPPM Riau University for providing research grants with contract number 993/UN19.5.1.3/AL.04/2024.

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    • Figure 1. SEM equation model
    • Table 1. Characteristics of respondents
    • Table 2. Operational definition of research variables
    • Table 3. Descriptive statistics
    • Table 4. Cross loading
    • Table 5. Discriminant validity testing with Fornel and Larcker criteria
    • Table 6. Reliability with Cronbach’s alpha
    • Table 7. Hypotheses testing results – Direct and indirect effects
    • Conceptualization
      Poppy Nurmayanti, Yesi Mutia Basri, Novita Indrawati
    • Data curation
      Poppy Nurmayanti, Yesi Mutia Basri, Novita Indrawati
    • Formal Analysis
      Poppy Nurmayanti, Yesi Mutia Basri, Novita Indrawati
    • Funding acquisition
      Poppy Nurmayanti, Yesi Mutia Basri, Emrinaldi Nur DP
    • Investigation
      Poppy Nurmayanti, Yesi Mutia Basri, Emrinaldi Nur DP
    • Methodology
      Poppy Nurmayanti, Yesi Mutia Basri, Emrinaldi Nur DP, Novita Indrawati
    • Writing – original draft
      Poppy Nurmayanti
    • Writing – review & editing
      Poppy Nurmayanti, Yesi Mutia Basri, Emrinaldi Nur DP, Novita Indrawati
    • Project administration
      Emrinaldi Nur DP, Novita Indrawati
    • Resources
      Emrinaldi Nur DP, Novita Indrawati
    • Software
      Emrinaldi Nur DP
    • Supervision
      Emrinaldi Nur DP