Navigating the Complex Cloud Manufacturing Landscape: A Multi-Context Framework for Informed Adoption Decision-Making

Abstract

Cloud Manufacturing offers a transformative approach to manufacturing by integrating cloud-based technologies and the sharing economy to enable on-demand access to distributed manufacturing resources and services. Its scalability, flexibility, and cost-efficiency have attracted growing interest from researchers and organizations. However, adopting such innovation is complex and requires a comprehensive understanding of the decision-making considerations. This study aims to develop a multi-context framework that supports informed adoption decisions by identifying the key enablers and inhibitors across various organizational roles. The research was conducted in three phases: framework development, validation, and field testing. In the first phase, an extensive literature review was conducted to extract relevant considerations from Cloud Manufacturing, Cloud Computing, innovation adoption theories, service-oriented manufacturing, and sharing economy. These considerations were filtered and structured into a five-context framework covering technology, organization, environment, human, and business aspects. The second phase involved validating the framework through a qualitative survey with leading researchers in related fields. Their feedback refined the framework, resulting in 28 adoption considerations. The final phase tested the framework through a multi-case study involving interviews with decision-makers from organizations representing the main Cloud Manufacturing actors: platform providers, resource providers, and users. These interviews explored how adoption decisions are made in practice and revealed distinct patterns, motivators, and concerns. To operationalize the framework, an AHP-based interactive tool was developed to help leaders evaluate adoption suitability based on weighted contextual priorities. This tool translates theoretical insights into practical guidance. The thesis outcomes include a validated multi-context framework, an empirically grounded understanding of adoption practices, and a practical decision-support tool.