Title

Transforming information into supply chain agility: an agility adaptation typology

Document Type

Article

Publication Date

2-12-2019

Abstract

Purpose: The purpose of this paper is to investigate the mediators that occupy the gap between information processing theory and supply chain agility. In today’s Mach speed business environment, managers often install new technology and expect an agile supply chain when they press. This study reveals the naivety of such an approach, which has allowed new technology to be governed by old processes. Design/methodology/approach: This work takes a qualitative approach to the dynamic conditions surrounding information processing and its connection to supply chain agility through the assessment of 60 exemplar cases. The situational conditions that have created the divide between information processing and supply chain agility are studied. Findings: The agility adaptation typology (AAT) defining three types of adaptations and their mediating constructs is presented. Type 1: information processing, is generally an exercise in synchronization that can be used to support assimilation. Type 2: demand sensing, is where companies are able to incorporate real-time data into everyday processes to better understand demand and move toward a real-time environment. Type 3: supply chain agility, requires fundamentally new thinking in the areas of transformation, mindset and culture. Originality/value: This work describes the reality of today’s struggle to achieve supply chain agility, providing guidelines and testable propositions, and at the same time, avoids “ivory tower prescriptions,” which exclude the real world details from the research process (Meredith, 1993). By including the messy real world details, while difficult to understand and explain, the authors are able to make strides in the AAT toward theory that explains and guides the manager’s everyday reality with all of its messy real world details.

Publication Title

International Journal of Logistics Management

Volume

30

Issue

1

First Page

329

Last Page

355

Digital Object Identifier (DOI)

10.1108/IJLM-09-2017-0237

ISSN

09574093

E-ISSN

17586550

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