The Impact of Artificial Intelligence on Innovation Products in Food Manufacturing in Jordan, Mediated by Supply Chain Resilience and Supply Chain Agility

Sami Mohammad; Ayşem  Çelebi; Abdulmula Mohamed Almahdi Arab

doi:10.32479/irmm.23709

Authors

Sami Mohammad Department of Business Administration, Cyprus Health and Social Sciences University, Güzelyurt 99700, Turkiye.
Ayşem Çelebi Department of Business Administration, Cyprus Health and Social Sciences University, Güzelyurt 99700, Turkiye.
Abdulmula Mohamed Almahdi Arab Department of Business Administration, Cyprus Health and Social Sciences University, Güzelyurt 99700, Turkiye.

DOI:

https://doi.org/10.32479/irmm.23709

Keywords:

Artificial intelligence adoption; Product innovation; Supply chain resilience; Supply chain agility; Food manufacturing industry

Abstract

Artificial Intelligence (AI) is more and more perceived as a vital enabler of innovation in manufacturing supply chains, particularly for manufacturers working under high uncertainty conditions. Additionally, this study evaluates how the adoption of AI affects product innovation in Jordanian food manufacturing firms and how supply chain resilience and supply chain agility act as mediators in this relationship. Data from 490 middle- and senior-level managers working in food manufacturing firms across 11 different food manufacturing subsectors in Jordan were collected and analysed using Structural Equation Modelling (SEM). The model developed for this study considers two types of product innovation (radical and incremental), which were both validated as latent constructs. The results of the analysis showed that AI adoption has a direct and positive impact on product innovation. In addition, the results also indicate that AI adoption improves supply chain agility and supply chain resilience, both of which positively influence product innovation outcomes. The mediation analysis also indicates partial mediation for both constructs (i.e., that both exert a mediating effect on the influence of AI adoption on product innovation), and, most importantly, a tangible and consequential continuum tying together AI R&D, supply chain elasticity, supply chain resilience, and product innovation. The model explains a focused share of the performance variation related to product innovation, while delivering an excellent fit for firms of various sizes and operational scales. This holistic research provides hugely beneficial empirical testimony based on an emerging economy, yet highlights the indispensable role of AI-driven supply chain capabilities in replicating and nurturing product innovation in a competitive and dynamic ecosystem, with the context of the food manufacturing industry.