Resumo

This research distinguishes Interorganizational Learning (IOL) from Network Learning (NL), a crucial distinction for sustainability. While IOL is an individual organization's learning through interaction, NL is the network's collective learning—a frequently conflated and empirically underexplored concept. Following Watanabe-Wilbert et al. (2022), this study applies a multilevel perspective to recent literature (2022-2025) to analyze their distinct subprocesses and interrelationships, thereby advancing the theoretical framework.

In the face of global sustainability challenges, this research addresses the conceptual confusion between Interorganizational Learning (IOL) and Network Learning (NL), which are crucial mechanisms for educating a system of actors towards more responsible practices. Noting the scarcity of empirical studies on NL, the objective is to advance the theoretical framework that distinguishes the two constructs by analyzing their subprocesses and interrelationships from a multilevel perspective to better understand organizational learning for sustainability.

The theoretical foundation is grounded in disciplines like complexity theory and constructivism, which posit that knowledge is socially constructed—a key principle for sustainability education. It distinguishes Interorganizational Learning (IOL), which focuses on an individual firm's absorptive capacity, from Network Learning (NL), a higher-order phenomenon that transforms the network to build collective competencies for sustainable practices. The 4I framework is used to analyze how learning flows across levels, enabling a system of actors to adopt more responsible behaviors.

To understand learning mechanisms for sustainability and the education of actors towards responsible practices, this research employs an integrative literature review. The study analyzed articles published between 2022 and 2026 from Scopus and Web of Science databases. The selection, guided by the PICOC protocol, resulted in 33 articles on Interorganizational Learning (IOL) and 22 on Network Learning (NL) for analysis. Qualitative content analysis used a seven-code system from multilevel learning theory, focusing on contexts, including education.

The analysis reveals how network learning (NL) functions in the education of a system of actors for sustainability. The process is not a mere accumulation but the synchronization of the learning of individual organizations (IOL). For the network to develop a collective sustainable capability, essential subprocesses include the creation of shared meaning, joint commitment to common goals, and specific methods that standardize responsible practices. Power dynamics can distort these learning outcomes.

The research advances the understanding of how network learning (NL) creates a collective capability for sustainability, distinguishing it from individual learning (IOL). In practice, it offers a guide for managers and policymakers on how to design interventions and governance that effectively educate the network to address complex challenges. As a recommendation, it points to the need for future research to investigate how different learning patterns directly impact the network's sustainability outcomes.

The central references include the works of Knight (2002) and Knight & Pye (2005), which established the distinction between Interorganizational Learning (IOL) and Network Learning (NL). The analysis uses the 4I framework from Crossan, Lane, and White (1999), which was expanded by Jones and Macpherson (2006) for interorganizational dynamics. The concept of absorptive capacity from Cohen and Levinthal (1990) is fundamental to IOL. The research methodology follows the model of Watanabe-Wilbert, Steil, and Dandolini (2022).