Work

An interpretive analysis of influential drivers for control tower adoption in supply chains

Year: 2025

Type: article

Abstract: A Supply Chain Control Tower (SCCT) provides real-time information, analytics, and decision support for supply chain management, helping organizations manage disruptions and inefficiencies before they occur. The complexity of contemporary supply chains is characterized by various influential factors that significantly affect the performance of Supply Chain Control Towers (SCCT). Interpreting the interactions among these factors is the key for supply chain managers in their efforts to improve decision quality and performance. Factor analysis is used to identify, prioritize, and rank the influential success factors that help accomplish SCCT effectiveness. This study investigates the influential drivers that shape SCCT adoption by applying Total Interpretive Structural Modeling (TISM) to evaluate how they relate and MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée à un Classement) analysis to determine their relative importance. The results illustrate that SC visibility and transparency are the principal factors, while the sustainable growth strategy is the least important factor influencing SCCT. This study delivers valuable practical understanding to supply chain managers regarding expediting efforts and effectively applying SCCT, ultimately boosting supply chain performance. • Identify key success factors for control tower implementation in supply chains. • Analyze factor relationships using interpretive structural modeling methods. • Highlight visibility and transparency as the most influential control tower driver. • Redevelop a hierarchical model to guide control tower deployment strategies. • Provide practical insights for enhancing decision-making in supply chain operations.

Source: Supply Chain Analytics

DOI: 10.1016/j.sca.2025.100178

Authors: Magesh kumar M. Nadar, Angappa Gunasekaran, Vaibhav S. Narwane

Institutions: Somaiya Vidyavihar University, Pennsylvania State University, Pennsylvania State System of Higher Education

Language: English

Topic: Quality and Supply Management

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,050