  The importance of supply chain management in analyzing and later catalyzing
economic expectations while simultaneously prioritizing cleaner production
aspects is a vital component of modern finance. Such predictions, though, are
often known to be less than accurate due to the ubiquitous uncertainty plaguing
most business decisions. Starting from a multi-dimensional cost function
defining the sustainability of the supply chain (SC) kernel, this article
outlines a 4-component SC module - environmental, demand, economic, and social
uncertainties - each ranked according to its individual weight. Our
mathematical model then assesses the viability of a sustainable business by
first ranking the potentially stochastic variables in order of their subjective
importance, and then optimizing the cost kernel, defined from a utility
function. The model will then identify conditions (as equations) validating the
sustainability of a business venture. The ranking is initially obtained from an
Analytical Hierarchical Process; the resultant weighted cost function is then
optimized to analyze the impact of market uncertainty based on our supply chain
model. Model predictions are then ratified against SME data to emphasize the
importance of cleaner production in business strategies.
