Ready or Not: Exploring Machine Learning Readiness in the Supplier Selection Process

Sammanfattning: Title: Ready or Not: Exploring Machine Learning Readiness in the Supplier Selection Process Authors: Nazish Rashid and Afra Mukhtar Supervisor Yulia Vakulenko Purpose: The aim of this research paper is to gain a better understanding of machine learning readiness in the supplier selection process. The study aims to analyse the readiness factors that constitute this and barriers that may hinder this process for companies. Methodology: This study made use of a qualitative research approach, which includes a single case study. The case study covers a company interview and a content analysis of company documents. Findings: The findings reveal that academia relates readiness factors to measure readiness in terms of adopting machine learning in the supplier selection process to the industry. However, this study is able to identify several other factors related to three contexts at an organisational level. Furthermore, the findings also validate the barriers found in academia, as well as recognise that additional barriers might hinder machine learning readiness in the supplier selection process. Value: The purpose of this research paper was to connect academia with industry practises, as well as to identify the perception of readiness regarding machine learning technology in the supplier selection process to highlight the gaps within this field of study. Research Implications: This study attempts to enhance insights on the current literature regarding readiness factors and potential barriers for machine learning in the supplier selection process by adding new readiness factors in the existing TOE framework. In addition to that, the authors introduced a new aspect to the framework in the form of barriers that should be taken into account. Practical Implications: The research paper aims to provide valuable insights for procurement professionals in the retail industry to improve their understanding of how a company is able to facilitate machine learning readiness in the supplier selection process.