@inbook{4065625b1bf6420ca5825cb2eba17c1a,
title = "Exploratory Study in Determining the Importance of Key Criteria in Mobile Supply Chain Management Adoption for Manufacturing Firms: A Multi-criteria Approach",
abstract = "Mobile supply chain management can help manufacturers to reduce cost and improve supply chain performances. However, the decisions to adopt mobile supply chain management are complex as it involved multi-criterion decisions that need to be considered by manufacturing firms. This research aims to predict the factors that can lead to successful mobile supply chain management adoption. Variables from the technology-organization-environment (TOE) model were used as predictors for this research. A non-compensatory adoption decision process is modeled using neural network analysis. Data was collected from 192 manufacturing firms. Our results showed that some of the strongest predictors for mobile supply chain management adoption are senior management support, security perceptions, technology integrations, and financial and technical competence. Firm size and environmental factors on the other hand have less predictive power than technological and organizational factors on mobile supply chain management adoption decisions.",
keywords = "Manufacturing firms, Mobile supply chain management, Neural network, Technology adoption decisions",
author = "Chong, {A. Y.L.} and Chan, {F. T.S.} and Ooi, {K. B.}",
note = "Publisher Copyright: {\textcopyright} 2014, Springer-Verlag London.",
year = "2014",
doi = "10.1007/978-1-4471-5295-8_6",
language = "English",
series = "Springer Series in Advanced Manufacturing",
publisher = "Springer Nature",
pages = "123--135",
booktitle = "Springer Series in Advanced Manufacturing",
address = "United States",
}