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Manexia
Published by UDEX Institute
ISSN : -     EISSN : 31246532     DOI : https://doi.org/10.66203
Core Subject : Economy,
Economics, Econometrics & Finance
Manexia: Journal of Business, Management, and Creative Economy is a peer-reviewed academic journal that publishes original research articles, conceptual papers, and case studies in the fields of business, management, and creative economy. The journal aims to advance scholarly discussion and practical insights in areas including strategic management, human resource management, marketing, entrepreneurship, digital business, innovation, and creative industry development. The journal particularly emphasizes interdisciplinary approaches and contemporary issues such as digital transformation, sustainable business practices, and the development of human capital in the creative economy. Manexia welcomes contributions from academics, researchers, practitioners, and policymakers that provide theoretical contributions as well as practical implications for business and organizational development in both local and global contexts.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis dan Menejemen Intetrnasional
Articles 35 Documents
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Creativity in the Age of Artificial Intelligence: A Hybrid Human–AI Co-Creation Framework Maman Sulaeman
Manexia: Journal of Business, Management, and Creative Economy Vol. 2 No. 2 (2026): Human–AI Value Systems
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.02202

Abstract

The rapid advancement of generative artificial intelligence (AI) has transformed creative work by shifting creativity from an individual cognitive activity to a hybrid, interactional process involving both human and algorithmic agents. Despite extensive research on creativity and computational systems, existing theories remain fragmented, largely treating human and machine creativity as separate domains and failing to capture their dynamic integration. This study addresses this theoretical gap by reconceptualizing creativity as a distributed, iterative, and hybrid process emerging from human–AI co-creation. Adopting a conceptual and integrative analytical approach, the study synthesizes insights from creativity theory, computational creativity, human–AI interaction, and digital innovation literature to develop a unified theoretical framework. It further introduces a process-oriented Human–AI Creative Co-Creation Model that explains how creative outcomes emerge through stages of intent formation, generative expansion, evaluation, and iterative refinement. The study contributes to theory by redefining creativity as a system-level phenomenon characterized by hybrid agency and co-evolutionary interaction, while offering implications for future empirical research on measuring and managing creativity in AI-mediated environments.
Reframing Innovation in the Age of Artificial Intelligence: A Human–AI Innovation Dynamics Model Wilman San Marino
Manexia: Journal of Business, Management, and Creative Economy Vol. 2 No. 2 (2026): Human–AI Value Systems
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.02203

Abstract

The rapid advancement of artificial intelligence, particularly generative AI, is fundamentally transforming how innovation is conceived and executed within organizations, yet existing research remains limited by human-centric, linear, and static conceptualizations of innovation processes. This study addresses this gap by developing a conceptual framework that explains how human–AI collaboration reshapes the dynamics of innovation. Adopting a theory synthesis approach, the study integrates insights from innovation theory, knowledge-based perspectives, hybrid intelligence, and co-creation literature to construct the Human–AI Innovation Dynamics Model. The model conceptualizes innovation as an interaction-based, iterative, and co-adaptive process driven by continuous exchanges between human cognition and AI-generated outputs. It further identifies key mechanisms, including iterative co-creation and iteration depth, as well as moderating and boundary conditions that influence innovation outcomes. The study contributes to the literature by reconceptualizing AI as a co-creative agent, extending dynamic capability theory toward interaction-based systems, and advancing the notion of distributed creativity. The framework provides a foundation for future empirical research and offers strategic implications for organizations navigating AI-enabled innovation environments.
Human–AI Collaboration Reshaping Creative Labor and Professional Identity Dynamics Galih
Manexia: Journal of Business, Management, and Creative Economy Vol. 2 No. 2 (2026): Human–AI Value Systems
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.02204

Abstract

Creativity is increasingly no longer an exclusively human endeavor, as artificial intelligence becomes deeply embedded in processes of ideation, production, and evaluation. This shift challenges established assumptions about authorship, originality, and professional identity within the creative economy. Despite growing research on digital labor, artificial intelligence, and identity work, these domains remain theoretically fragmented, limiting understanding of how human–AI collaboration reshapes both creative processes and identity construction. This study addresses this gap by developing an integrative conceptual framework that bridges creative labor theory, identity work, and socio-technical perspectives. Using a mechanism-based analytical approach, the study conceptualizes creative labor as a hybrid co-creative system characterized by generative expansion, iterative co-creation, algorithmic mediation, and human curation. It further explains how these processes trigger identity transformation through recursive stages of destabilization, experimentation, negotiation, and reconstruction. The study contributes by reframing creativity as a distributed process, extending identity theory to incorporate AI as an active participant, and introducing the concept of hybrid intelligent labor, offering a foundation for future empirical inquiry.
Perceived Authenticity and Consumer Response to AI-Generated Content: A Human–AI Co-Creation Perspective Euis Bandawaty
Manexia: Journal of Business, Management, and Creative Economy Vol. 2 No. 2 (2026): Human–AI Value Systems
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.02205

Abstract

The growing use of generative artificial intelligence in marketing has transformed how content is produced and evaluated, raising critical concerns regarding how consumers perceive authenticity when authorship extends beyond human creators. While prior research has largely focused on technological adoption and trust, limited attention has been given to how consumers construct meaning and evaluate authenticity in AI-mediated environments. This study addresses this gap by developing a conceptual framework that positions perceived authenticity as a central mechanism linking AI involvement in content creation to consumer psychological and behavioral responses. Drawing on authenticity theory, consumer behavior, and artificial intelligence literature, the study adopts a theory integration approach to synthesize fragmented insights into a unified model. The proposed framework reconceptualizes authenticity as a hybrid construct emerging from the perceived interaction between human intention and algorithmic generation, and explains how this perception shapes trust, emotional engagement, and behavioral outcomes. By offering a multi-level and process-oriented perspective, the study contributes to extending authenticity theory and advancing AI marketing research toward meaning-based evaluation, while providing a foundation for future empirical investigation in human–AI collaborative contexts.
Value Ownership in Human–AI Co-Creation: A Multi-Level Framework of Distributed Agency and Ethical Tensions Richard Abdulloh Mundzir; Rohimat Nurhasan
Manexia: Journal of Business, Management, and Creative Economy Vol. 2 No. 2 (2026): Human–AI Value Systems
Publisher : UDEX Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66203/manexia.02206

Abstract

The increasing integration of generative artificial intelligence into creative and organizational processes challenges traditional assumptions about value creation, authorship, and ownership. In human–AI co-creation contexts, value emerges through iterative interactions between human cognition and algorithmic generation, leading to ambiguity in contribution, attribution, and ownership. Despite growing research on artificial intelligence and digital transformation, existing literature remains fragmented, lacking an integrative framework that explains how value ownership is constructed across multiple levels. This study aims to address this theoretical gap by developing a process-oriented conceptual framework that integrates perspectives from ethics, ownership theory, and co-creation. Using an integrative analytical approach, the study conceptualizes human–AI collaboration as a dynamic system characterized by distributed agency, iterative interaction loops, and multi-level value attribution mechanisms. The proposed model identifies key ethical tensions—authorship ambiguity, value attribution uncertainty, responsibility diffusion, and authenticity erosion—and positions them within an ethical paradox system. The study contributes by reconceptualizing ownership as a multi-dimensional and relational construct while providing a structured framework for analyzing how value is generated, interpreted, and allocated in human–AI systems, offering directions for future empirical research.

Page 4 of 4 | Total Record : 35

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