A conceptual model for the adoption of autonomous robots in supply chain and logistics industry
Mohamed Dawood Shamout; Rabeb Ben-Abdallah; Muhammad Turki Alshurideh; Haitham M. Alzoubi; Barween Al Kurdi; Samer Hamadneh · 2022 · Uncertain Supply Chain Management
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
The arrival of the era of robots and autonomous machines is undisputable. It is anticipated that the future business environment will be characterized by a variety of intelligent systems and autonomous robots. In 2017, the International Federation of Robotics reported that momentum gained by robotic technologies is strong and that the sales volumes of both service and industrial robots is expected to grow. Building on this projection, the present study proposes a set of prerequisites or key determinants for the adoption of autonomous robots in the supply chain and logistics industry: technolog
Abstract by Mohamed Dawood Shamout; Rabeb Ben-Abdallah; Muhammad Turki Alshurideh; Haitham M. Alzoubi; Barween Al Kurdi; Samer Hamadneh, Uncertain Supply Chain Management (2022) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Aggregation Kinetics of Graphene Oxides in Aqueous Solutions: Experiments, Mechanisms, and Modeling
Negative / Null Result ReportThe reaction between metakaolin and limestone and its effect in porosity refinement and mechanical properties
Negative / Null Result ReportTuning Alginate Bioink Stiffness and Composition for Controlled Growth Factor Delivery and to Spatially Direct MSC Fate within Bioprinted Tissues
Negative / Null Result ReportEx-situ characterisation of gas diffusion layers for proton exchange membrane fuel cells
Negative / Null Result ReportCobb Angle Measurement of Spine from X-Ray Images Using Convolutional Neural Network
Negative / Null Result ReportDeterminants of residential water consumption: Evidence and analysis from a 10‐country household survey
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.5267/j.uscm.2021.11.006
