Orchestrating resources for Big data analytics implementation in manufacturing SMEs: insights into managerial role and engagement
通过对17位中小企业管理者的访谈，研究管理者如何编排资源以克服约束、有效部署大数据分析，为资源受限的制造企业提供实践路线图。
Big Data Analytics (BDA) offers transformative potential for Small and Medium Enterprises (SMEs), enabling enhanced performance, improved decision-making, innovation and business growth. Yet, manufacturing SMEs often face considerable constraints that hinder effective BDA implementation. This study adopts Resource Orchestration Theory (ROT) to explore how managers in manufacturing SMEs structure, bundle, and leverage resources to overcome these challenges and deploy BDA effectively. Using semi-structured interviews with 17 SMEs managers, we examine BDA deployment across supply chain operations guided by the SCOR model. The findings reveal key managerial roles and strategies, including approaches to selecting, configuring, and operationalising BDA solutions. This study contributes to theory by applying ROT to the underexplored context of BDA implementation in SMEs, highlighting the dynamic capabilities managers must develop to succeed. Practically, it provides actionable insights for SMEs managers navigating digital transformation in resource-constrained settings. The study proposes a roadmap to guide BDA adoption in manufacturing SMEs.