Investigating Issues in Managing Sustainability Through Digital Servitization: A Soft Systems Approach

With the advent of advanced digital technologies such as artificial intelligence, cloud computing, and blockchain, there is an urgent need to address prominent environmental issues. These environmental issues, such as abrupt climate change, resource depletion, and unsustainable consumption patterns, are forcing manufacturing firms to shift towards service dominant logic from traditional product logic. This shift towards service dominant logic using advanced digital technologies is referred to as digital servitization (DS) in the past literature. Firms find it difficult to implement the DS strategy in practice due to complex, interdependent systemic issues across organizational departments. While existing literature highlights the sustainability benefits of DS, it inadequately addresses the systemic issues that arise during its implementation, particularly in resource-constrained, multi-actor manufacturing ecosystems. This paper aims to diagnose these implementation issues in the context of the Indian automotive manufacturing industry through a systems thinking perspective. This research adopts a perspective of alignment theory, and a systems-based approach grounded in Soft Systems Methodology (SSM) and the McKinsey 7 S framework to explore and diagnose digital servitization implementation issues. This study reveals that the implementation of digital servitization is hindered not merely by technological limitations but by a deeply embedded misalignment between strategic sustainability intentions and operational execution. The framework developed here is especially valuable for firms in emerging economies, where technological ambitions are often constrained by legacy systems, skills gaps, and fragmented governance. Finally, this study supports a shift from fragmented project execution to systems-informed decision-making, contributing to the broader goal of achieving sustainable, digitally enabled, and human-centered industrial ecosystems.