The ultimate goal of supply chains is to satisfy their end customers. To do so, they implement a set of practices along their chain in order to generate value for customers. Therefore, aligning supply chain practices with customer values is a core objective of supply chains. The current research employs Bayesian Networks (BNs) and Analytic Network Processes (ANPs) to integrate practices and customer values in a supply chain as well as quantifying their mutual correlations. In the first phase, it collects and analyzes data about six specific customer values; in the second phase, the importance of practices is evaluated by experts in the respective industry using ANPs; and in the final phase, the output of the two analyses meet in a BN to generate a model which is capable of quantifying their mutual correlations given the input data. In addition, the proposed approach can handle scenarios for identifying whether a specific customer value is preferred by the end customer and what practices should be implemented; or vice versa, in cases where a specific practice is implemented, identifying how it contributes to customer values. This approach is applied to a case study in the food industry in order to present its application empirically.
|Number of pages||11|
|Journal||International Journal of Management Science and Engineering Management|
|Publication status||Published - 2 Jan 2015|
- customer value
- food industry
- supply chain management