Case Study on Data Envelopment Analysis for Product Line Selection

Data Envelopment Analysis for Product Line Selection

Abstract: We define product line selection problem as selecting a subset of potential product variants that can simultaneously minimize product proliferation and maintain market coverage. Selecting the most efficient product mix is a complex problem, which requires analyses of multi-criteria. This paper proposes a method based on Data Envelopment Analysis (DEA) for product line selection. Data Envelopment Analysis (DEA) is a linear programming based technique used for measuring the relative performance of a group of decision making units with multiple inputs and outputs.

Introduction: Designing product families in place of single products is an approach many companies have taken to reduce product development and production costs, and to diversify their product offerings (Simpson et al., 2005). A key strategy in creating product families is to identify products that can be produced effectively from a single platform, while maintaining the competitiveness of the product line. As more manufacturing companies consolidate their product lines, there is an increasing need for more systematic and consistent approaches to help them do so..
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• in what industry has product proliferated

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