Orchestration in Marketing Ecosystems: Actors, Mechanisms, and Outcomes

Document Type : Original Article

Authors

Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.

Abstract


Objectives: In the digital and interconnected economy, marketing has evolved beyond dyadic firm-customer relationships into a dynamic multi-actor system in which companies, platforms, and customers jointly create and exchange value. Despite growing research on marketing ecosystems, there remains a lack of theoretical framework explaining how orchestration mechanisms align diverse actors and resources. This fragmentation limits a comprehensive understanding of how value co-creation occurs in complex, data-driven contexts. This study aims to develop a conceptual and integrative framework that explains the dimensions, mechanisms, and outcomes of orchestration within marketing ecosystems. This study seeks to develop a conceptual and integrative framework for understanding orchestration in marketing ecosystems by examining its core dimensions, underlying mechanisms, and resulting outcomes. Specifically, the research investigates how orchestration is constituted through different actors and components, and how these elements interact within digitally enabled ecosystems. It further explores the ways in which orchestration mechanisms evolve and coexist across diverse technological and market contexts, reflecting the dynamic nature of contemporary marketing environments. Finally, the study examines the outcomes of orchestration at multiple levels, including market dynamics, organizational performance, brand-related outcomes, and broader societal implications, thereby providing a comprehensive and multi-level understanding of value co-creation in marketing ecosystems.

Methods: This study adopts a mixed-method approach. In the first phase, a systematic literature review was conducted across major databases including Web of Science, ScienceDirect, and reputable Persian sources, covering the period 2005–2025. From an initial 147 records, after screening and eligibility assessment, 21 studies were selected following PRISMA guidelines. 
Qualitative data were analyzed through thematic analysis using MAXQDA 2024 software to extract codes, sub-themes, and overarching dimensions. Inter-coder reliability was verified using the Cohen’s Kappa coefficient (0.71), indicating substantial agreement. In the second phase, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was employed to identify causal relationships among the key factors. Seven criteria derived from the synthesis (C1-C7) were rated by 12 experts (six academics and six specialists in digital marketing and ecosystem design) using a five-point scale (0 = no influence to 4 = very high influence). Direct-relation and total-relation matrices were computed, and key indices impact (R), dependence (C), prominence (R+C), and causal role (R–C) were analyzed in Excel 2021.

Findings: The meta-synthesis revealed three main dimensions of orchestration. Actors, comprising macro-level organizations, regulatory institutions, technology/data providers, internal teams, and end users. Mechanisms, consisting of six integrated categories: digital integration, co-creation platforms, market agility, predictive/personalized marketing, organizational transformation, and human-capital development. Outcomes, including market expansion and competitiveness, enhanced performance and agility, stronger brand engagement and loyalty, and social/environmental sustainability.The word-cloud analysis indicated that marketing, customer, ecosystem, and data were the most frequent terms. The conceptual framework integrates these findings, positioning orchestration as a multi-level strategic capability linking technological enablers, organizational structures, and collaborative processes.The DEMATEL analysis confirmed causal relationships among the seven core factors. Technology and data suppliers (C2) and digital integration (C3) emerged as major causal drivers, while personalized/predictive marketing (C5) and customer value (C6) acted as dependent outcomes. Organizational agility (C7) played a balancing and feedback role, mediating between technological enablers and customer-centered results. The overall causal network showed that strengthening technological foundations and data infrastructure is essential for realizing customer-centric value and maintaining ecosystem sustainability.

Conclusion: The study introduces an integrative and multi-level framework for understanding orchestration in marketing ecosystems. It highlights that orchestration is not a linear or control-based process but a distributed coordination mechanism that aligns diverse actors toward shared value creation. Technological and digital integration are primary enablers, while agility, personalization, and value co-creation represent strategic outcomes. Theoretically, the study contributes by unifying fragmented literature and emphasizing the interplay between technological, human, and structural orchestration mechanisms. Managerially, it suggests that marketing leaders should move from control to facilitation
 by developing capabilities in predictive analytics, platform management, and cross-organizational learning. Limitations include reliance on secondary qualitative data, limited generalizability across industries, and a small expert sample. Future research should empirically validate the framework in emerging markets and explore the roles of AI, machine learning, and blockchain in developing self-orchestrated ecosystems.
 

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