Innovative Work Behavior (IWB) within modern organizations does not emerge by chance; it is shaped by the dynamic interaction between individual, social, organizational, and digital factors. A comprehensive study conducted by Nopi Oktavianti, Muhardi, Eneng Nurlaili Wangi, and Tasya Apiranti from Universitas Pamulang and Universitas Islam Bandung in 2026 examines the evolution and theoretical landscape of IWB to help organizations formulate effective adaptation strategies
Background and Context
In a modern business environment characterized by rapid change and digital transformation, innovation can no longer be confined to formal research and development departments
Research Methodology
This study employed a Systematic Literature Review (SLR) approach based on the PRISMA 2020 guidelines
Key Findings
The synthesis reveals that IWB literature has evolved through six distinct eras, ranging from early discussions of organizational structure to the current digital and multilevel era
- Individual psychological resources (such as self-efficacy and work engagement)
. - Social and relational factors (including transformational leadership and supervisor support)
. - Organizational support systems (human resource management practices and innovation climate)
. - Digital contextual factors (ICT adoption, digital tools, and hybrid work environments)
.
Implications and Organizational Impact
This ecosystem perspective reminds industry leaders and the public sector that building a culture of innovation requires comprehensive integration, rather than isolated interventions
Author Profiles
- Nopi Oktavianti – Universitas Pamulang.
- Muhardi, S.E., M.M. – Lecturer and researcher at Universitas Pamulang, focusing on management and organizational behavior.
- Eneng Nurlaili Wangi – Universitas Pamulang.
- Tasya Apiranti – Universitas Pamulang / Universitas Islam Bandung.
Research Source:
- Article: "Innovative Work Behavior as an Organizational Ecosystem: A Systematic Literature Review from Structural Origins to the Digital Era (1969-2026)"
- Journal: International Journal of Management Analytics (IJMA), Vol. 4, No. 3, July 2026
- DOI:
https://doi.org/10.59890/ijma.v4i3.21
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