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All Journal International Journal of Management Science and Application Maroon Journal De Management
Semefa Elikplim Dzreke
Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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The Enterprise Lingua Franca: A Foundational Framework for Semantic Interoperability and Cross-Functional Cognition Simon Suwanzy Dzreke; Semefa Elikplim Dzreke
International Journal of Management Science and Application Vol. 5 No. 1 (2026): IJMSA
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v5i1.467

Abstract

Digital transformation often fails at the conceptual level: Seventy-three percent of cross-functional initiatives fail because the functional mental models don't match up, making it impossible to solve difficult problems like making sustainability profitable. This research identifies a significant deficiency in enterprise interoperability, wherein disparate departmental epistemologies manifested in conflicting interpretations of fundamental constructs such as "customer" or "value" among Marketing, Finance, and Operations—result in strategic incoherence despite technological integration. Technological solutions are inadequate in addressing these profound philosophical gaps. This paper introduces the Enterprise Lingua Franca, a new cognitive framework created through design science research that combines case studies, ontology engineering, and cognitive task analysis to make organizational intelligence more cohesive. It creates the first theory of Cross-Functional Cognition and gives tangible steps for semantic alignment that turn conceptual fragmentation into strategic coherence, which opens up new ways to solve problems.
The Cognitive Chrysalis: Engineering Metamorphic Resilience in Tourism Through Post-Outbreak Intelligence and Adaptive Design Simon Suwanzy Dzreke; Semefa Elikplim Dzreke
International Journal of Management Science and Application Vol. 5 No. 1 (2026): IJMSA
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v5i1.468

Abstract

This work fills a major theoretical gap in tourist resilience: the systemic imbalance between cognitive processes and physical infrastructure, which increases susceptibility during hydrometeorological crises. Existing frameworks fail to explain why locations with similar hazard exposure display substantial outcome disparities, as seen by Venice's lengthy flood disruption against Singapore's predictive mitigation success. The study makes two major theoretical contributions: the Resilience Engineering Framework (REF), which combines cognitive load theory, behavioral intelligence, and AI-mediated feedback loops to model systemic brittleness; and the Adaptive Design Protocol (ADP), which applies REF principles to spatial, governance, and infrastructural interventions. The study takes a sequential mixed-methods approach, with (1) big data analytics across 20 destinations quantifying cognitive stressors (e.g., decision fatigue amplifying evacuation errors by 22%), (2) stakeholder surveys identifying governance misalignments, and (3) agent-based modeling validating REF dynamics. Empirical results show that ADP implementation reduces rebound time by 41% and infrastructure damage costs by 37% through metamorphic adaptation, as demonstrated by Bali's AI-driven crowd-flow systems, which speed up recovery by 58% through cognitive load optimization. The findings demonstrate that shifting fragility into anticipatory capacity necessitates cognitively grounded design, providing a reproducible approach for regenerative tourist ecosystems.
The Relational Algorithm: Axiomatizing the Divergent Social Calculus of Trust in Collectivist and Individualist Market Ontologies Simon Suwanzy Dzreke; Semefa Elikplim Dzreke
International Journal of Management Science and Application Vol. 5 No. 1 (2026): IJMSA
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v5i1.500

Abstract

Global brands incur annual losses of around $23 billion due to culturally incompatible trust practices, as demonstrated by Uber's contractual misalignment in China's guanxi-centric markets. This ongoing insufficiency highlights a significant theoretical void: cross-cultural marketing lacks a foundational framework that elucidates ontological differences in the formation of trust. This study employs ethnographic fieldwork (n = 42 industry experts), agent-based computer modelling, and discrete-choice experiments (DCEs; n = 1,200 participants across 4 markets) to address the issue. Findings indicate that trust functions through incommensurable cultural relational algorithms individualistic contractarian principles vs collectivist contextualist principles. Violating these ontological principles diminishes purchase intent by 38–61% (hierarchical Bayesian estimation, 95% HDI), highlighting the behavioral repercussions of infringing ontological expectations. This paper proposes a new axiomatic framework for market ontology that facilitates the algorithmic adaptation of trust methods across cultural barriers. The framework provides a theoretically informed method for mitigating relational friction in international trade, with clear implications for market entry strategy, partnership formation, and platform management.
The Algorithmic Canvas: On the Autopoietic Redefinition of STP in the Age of Strategic Resilience Simon Suwanzy Dzreke; Semefa Elikplim Dzreke
International Journal of Management Science and Application Vol. 5 No. 1 (2026): IJMSA
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v5i1.501

Abstract

Traditional Segmentation, Targeting, and Positioning (STP) frameworks demonstrate significant deficiencies in unstable markets, with actual data revealing a 67% decline after six months. This research redefines STP not as a structured process but as an autopoietic system—an entity that self-organizes and constantly redefines its limits. It presents the Algorithmic Canvas as the operational medium that facilitates this paradigm, in which segmentation, targeting, and positioning parameters dynamically evolve through human-AI collaboration. Using a sequential mixed-methods design that included a 6-month Fortune 500 lab ethnography (n=23), a computational analysis of 150 million customer interactions, and an empirically based agent-based simulation (ABS), the study shows that autopoietic STP implemented through the Canvas is 44% more resilient (p < 0.01) to market shocks and cuts strategic planning cycles by 90% compared to traditional models. Algorithmic co-creation methods enhanced the identification of substantial market fluctuations by a factor of 5.8. The study enhances the Autopoietic STP Framework and empirically substantiates Canvas Design Principles, effectively addressing algorithmic myopia and offering businesses a framework for improved adaptability and resource efficiency during turbulent conditions.
Synergizing Sustainability: Integrated Demand-Supply Strategies for Resilient Retail, Transport, and Logistics Systems: JEL Classification: L91; Q56; R41; O33; M11 Simon Suwanzy Dzreke; Semefa Elikplim Dzreke
Maroon Journal De Management Vol. 3 No. 1 (2026): Maroon Journal De Management (MJDM)
Publisher : Generasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/mjdm.v3i1.302

Abstract

Global supply chains confront existential threats from climate volatility manifest in port-crippling storms and agricultural collapse and chronic disruptions spanning pandemics to geopolitical fragmentation, exposing the fragility of efficiency-optimized models. This research pioneers integrated computational frameworks that transcend disciplinary silos to synchronize environmental sustainability with operational resilience across retail, transport, and logistics ecosystems. Multi-method analysis combining Life Cycle Assessment, Agent-Based Modelling, and policy scenario testing demonstrates that harmonized demand-supply coordination consistently outperforms isolated interventions. Synchronized demand shaping (AI-facilitated circular consumption) and regionalized supply redesign (micro-factories) reduce end-to-end emissions by 30–40%, while dynamic AI routing cuts logistics costs by 22% during severe disruptions. Integrating policy instruments like harmonized carbon accounting amplifies stakeholder ROI by 2.8× versus fragmented approaches. The framework empowers industry and policymakers to co-optimize decarbonization and disruption preparedness, transforming brittle networks into adaptive, low-carbon value chains resilient to systemic shocks a strategic imperative beyond incremental adjustment.
Alexa, Reshape My Supply Chain: How Voice Commerce Alters Demand Forecasting, Fulfillment Speed, and Marketing Messaging: JEL Classification: D91; L81; M15; M31; O33 Simon Dzreke; Semefa Elikplim Dzreke
Maroon Journal De Management Vol. 3 No. 2 (2026): Maroon Journal De Management:
Publisher : Generasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/mjdm.v3i2.303

Abstract

The simple utterance "Alexa, order more batteries!" triggers significant operational discontinuities across global supply chains. Voice commerce, now constituting 35% of smart speaker interactions, fundamentally restructures retail logistics, consumer expectations, and marketing psychology. With 47% of voice orders demanding last-minute, low-margin essentials like toilet paper or allergy medicine, traditional demand forecasting succumbs to pronounced "voice shock," characterized by 27% higher volatility spikes concentrated within narrow 15-minute windows. Analysis of 2.3 million anonymized voice transactions, combined with eye-tracking studies of 450 participants and logistics simulations, reveals a critical shift: consumers now expect 2-hour delivery for voice-activated purchases, representing a 96% compression from the established 2-day standard for mobile or web orders. This heightened urgency necessitates hyperlocal fulfillment pods within five miles of users, demonstrably outperforming regional warehouses by reducing delivery failures by 44%. Critically, sonic marketing adheres to a strict "3-second rule," where audio advertisements exceeding this duration experience 62% abandonment. This research introduces a voice-optimized framework demonstrating how enterprises can leverage micro-fulfillment algorithms, ethical conversational design, and predictive audio mnemonics to convert voice-induced operational chaos into sustainable competitive advantage. The era of voice-driven supply chains represents a contemporary imperative.
Co-Authors Simon Dzreke Simon Suwanzy Dzreke Simon Suwanzy Dzreke