Estimation and Validation of the Strategic Business Innovation Model Through the Application of Demand Leverage and Supply Chain in Dynamic Ecosystems
Keywords:
Strategic Business Innovation, Demand Leverage, Supply Chain, Dynamic EcosystemsAbstract
This study was conducted with the aim of estimating and validating a strategic business innovation model with an emphasis on the role of demand leverage and supply chain within dynamic ecosystems. The statistical population consisted of senior experts, business managers, and specialists from startup companies in the city of Tehran. The sample size was determined as 335 participants based on Cochran’s formula. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) as well as Confirmatory Factor Analysis (CFA). The conceptual model of the research was developed based on the study by Masoumi et al. (2025) and subsequently validated through both quantitative and qualitative analyses. In the first stage, the descriptive statistics of the main variables indicated that the mean values of all variables were above the average level, while skewness and kurtosis values fell within the acceptable range. Therefore, the data demonstrated relative symmetry and normal distribution. The Kolmogorov–Smirnov test was also non-significant for all variables, confirming the normality of the data. Examination of multicollinearity using the Variance Inflation Factor (VIF) revealed that all index values were below 3, indicating the absence of multicollinearity within the model. In the measurement model, reliability and validity indicators, including Cronbach’s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE), were found to be acceptable across all constructs. Accordingly, internal reliability and convergent validity were confirmed. In addition, discriminant validity was assessed using the Fornell–Larcker criterion and the Heterotrait–Monotrait Ratio (HTMT), and was confirmed for all constructs. In the structural model section, the coefficients of determination for the endogenous constructs demonstrated the appropriate explanatory power of the dependent variables, such that the model was able to explain approximately 35% of the variance in the dependent variables, which is considered acceptable and desirable according to the criteria proposed by Chin and Hair. The overall goodness-of-fit index (GOF = 0.624) indicated a strong model fit. Furthermore, effect size analysis demonstrated that causal, contextual, and intervening variables exerted a strong influence on the core phenomenon and strategic actions. Moreover, predictive relevance indices indicated the strong predictive capability of the model for the endogenous constructs. The final results revealed that causal, contextual, and intervening factors play a significant and decisive role in shaping strategic business innovation strategies, and the implementation of these strategies leads to improved organizational outcomes within dynamic ecosystems.
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Copyright (c) 2025 Sanaz Masoumi (Author); Ahmad Reza Kasraee; Mahmod Mohammadi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
