A comprehensive 3-phase framework for determining the customer’s product usage in a food supply chain

A fundamental issue in manufacturing systems is moving a local manufacturer into a supply chain network including wholesalers and retailers. In this research, a 3-phase framework is proposed to determine the food consumption pattern in food supply chains. In the first stage of this research, the consumer, availability and society factors for product classification according to the features of populations in Malaysia are identified (phase 1). Then, using statistical analysis, the effective factors are recognised (phase 2). In the third phase, the product clusters are recognised using a hybrid PCA and agglomerative clustering method. For this purpose, different clusters for the training step are used. The outcomes indicated that Age (0.94), City (0.79), Health Benefit Awareness (0.76) and Education (0.75) are the most effective factors in product consumption patterns, respectively. Moreover, the efficiency of the outcomes is evaluated using the Silhouette Coefficient, indicating that the proposed algorithm could provide solutions with a 68% score. Moreover, using Calinski-Harabasz Index, it was found that the algorithm provided more logic scores while the number of product patterns was 3 for the studied region (707.54).

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