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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Manexia
Ahmad Mundzir
VISTA Research Center
Economics, Econometrics & Finance

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Dominance, Interruption, and Corrective Strategic Rebalancing Under Market Volatility Ahmad Mundzir
Manexia: Journal of Business, Management, and Creative Economy Vol. 1 No. 1 (2025): Strategic Architecture Under Persistent Market Volatility
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.01103

Abstract

Market volatility frequently exposes structural imbalances that accumulate during periods of sectoral or strategic dominance. While prior research has examined diversification and strategic scope largely through structural or performance lenses, limited attention has been given to the endogenous processes through which dominance emerges, stabilizes, and is subsequently disrupted. This conceptual paper develops a process theory explaining how strategic dominance forms through recursive reinforcement, how volatility acts as an interruption mechanism that reveals latent imbalance, and how organizations engage in corrective strategic rebalancing. The framework conceptualizes dominance as an internally reinforced concentration of strategic attention and resource allocation, rather than merely an external market outcome. Volatility functions not simply as exogenous shock but as a revelatory condition that activates managerial interpretation and strategic recalibration. Corrective rebalancing is theorized as a disciplined, governance-mediated response aimed at restoring coherence and long-term viability. By integrating strategic management, managerial cognition, and governance perspectives, the paper advances a dynamic account of how organizations oscillate between dominance and balance. The study contributes to strategy theory by reframing imbalance as an endogenous process and positioning corrective rebalancing as a core mechanism of strategic resilience under persistent uncertainty.
Digital Authenticity under Generative AI: Mechanisms of Synthetic Signal Construction and Strategic Legitimacy in Branding Nuk Ghurroh Setyoningrum; Ahmad Mundzir
Manexia: Journal of Business, Management, and Creative Economy Vol. 1 No. 2 (2025): Strategic Reconfiguration and Generative AI in Marketing and Creative Economy
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.01205

Abstract

The diffusion of generative artificial intelligence (GenAI) in branding practices challenges a central assumption in authenticity research: that legitimacy derives primarily from indexical continuity between expressive artifacts and experiential origin. As firms increasingly rely on synthetic systems to produce scalable, adaptive, and stylistically coherent brand communications, the structural linkage between expression and embodied authorship becomes attenuated. This article develops a mechanism-based framework to explain how authenticity and strategic legitimacy are reconstructed under conditions of generative intensification. Integrating signaling theory, legitimacy theory, and dynamic capabilities, the analysis conceptualizes authenticity as an emergent property of orchestrated synthetic signal regimes rather than as an intrinsic attribute of origin. The framework specifies a curvilinear relationship between generative AI intensity and perceived authenticity: moderate integration enhances coherence and responsiveness, while uncalibrated intensification risks signal dilution and perceived artificiality. Perceived authenticity mediates the effect of generative intensity on strategic legitimacy, and synthetic signal orchestration capability conditions the threshold at which legitimacy erosion occurs. Contextual salience, including heritage intensity and customer epistemic sensitivity, further shapes these dynamics. By reframing authenticity as governance-dependent under digital abundance, the article extends branding theory and dynamic capabilities scholarship while providing a structured agenda for empirical examination of AI-enabled marketing transformation.
The AI Productivity Paradox Revisited: A Multi-Level Theory of Performance Divergence in SME-Dominated Digital Ecosystems Ahmad Mundzir
Manexia: Journal of Business, Management, and Creative Economy Vol. 2 No. 1 (2026): Algorithmic Restructuring of Digital Markets
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.02107

Abstract

Artificial intelligence (AI) has intensified debates surrounding the contemporary productivity paradox, where rapid technological progress coexists with uneven improvements in measured productivity. Although growing evidence shows that AI can significantly enhance task-level performance—reducing completion time, improving output quality, and standardizing decision processes—these gains do not always translate into consistent firm-level productivity outcomes, particularly among small and medium-sized enterprises (SMEs) operating in platform-mediated digital markets. This article develops a conceptual framework that revisits the AI productivity paradox through a multi-level theoretical perspective. Integrating insights from productivity paradox research, general-purpose technology theory, task-based technological change, and platform ecosystem scholarship, the study proposes that AI-induced productivity gains propagate unevenly across four analytical layers: tasks, SMEs, platforms, and digital ecosystems. Three generative mechanisms—complement lag, measurement wedge, and compounding learning effects—explain how productivity gains are translated, partially observed, or redistributed across these levels. While SMEs may experience delayed or weakly measured productivity improvements due to complement constraints and measurement limitations, platform infrastructures can accumulate accelerated gains through data-enabled learning and cross-merchant aggregation. The framework introduces productivity divergence as a concept explaining how ecosystem-level efficiency can increase even when individual firms experience uneven productivity outcomes.
Co-Authors Nuk Ghurroh Setyoningrum