Emerging technologies and the concept of Industry 4.0 are on the rise. Thus, available solutions for SCM get more complex and dynamic. Technology adoption is crucial for…
Abstract
Purpose
Emerging technologies and the concept of Industry 4.0 are on the rise. Thus, available solutions for SCM get more complex and dynamic. Technology adoption is crucial for organizations competitiveness, but resources are limited. Therefore, this paper aims to gain insights into the successful management of technology pre-adoption in SCM.
Design/methodology/approach
In-depth polar case studies of technology pre-adoption initiatives in various industries were collected using an interview-based approach. Subsequently, the paper deploys transcript coding on the data to analyze information within and across the cases. Lastly, utilizing contingency theory, supply chain-specific influencing factors and corresponding management practices were identified.
Findings
The research reveals eight contingency dimensions and corresponding variables that influence the design of successful technology pre-adoption in SCM (e.g. complexity and criticality). Moreover, ten response variables were identified, referring to the pre-adoption process or organization. They systemize possible options when conducting technology pre-adoption initiatives.
Research limitations/implications
The paper contributes to research by systemizing potential influencing factors and responses of technology pre-adoption through an explorative, empirical study. The paper is limited by its qualitative approach and the number of case studies conducted.
Practical implications
The results provide supply chain managers a guideline for analyzing potential influences on the technology pre-adoption process and propositions how to manage pre-adoption accordingly.
Originality/value
This research is among the first to provide in-depth insights into technology pre-adoption from an organization's perspective considering supply chain-specific contingencies. Also, it introduces a new perspective on technology selection as a management process.