Article ID: | iaor20052989 |
Country: | United States |
Volume: | 23 |
Issue: | 2 |
Start Page Number: | 163 |
End Page Number: | 178 |
Publication Date: | Feb 2005 |
Journal: | Journal of Operations Management |
Authors: | Narasimhan Ram, Sarkis Joseph, Ross A., Talluri Srinivas |
Keywords: | public service, artificial intelligence: decision support |
This paper presents a decision support system for efficient service location design for an agency in the State of Michigan. We consider a total of 169 branch offices of the agency located in 79 counties that process a variety of transactions and provide services including automobile registrations, issuance of driver licenses, recreational vehicle registration, and personal identification registry. The proposed methodology and decision support system incorporate a number of factors such as branch office efficiencies based on multiple measures, budget restrictions, capacity limitations for processing transactions, and demand requirements in designing an efficient service system. Our approach employs data envelopment analysis (DEA) and mixed-integer programming (MIP) models. A series of experiments are conducted with the proposed model by varying the levels of system-wide efficiency, resource reallocation, and budget in generating a set of decisions that executive management of the agency can implement. In addition, we investigate service channel management issues that the agency is currently facing in providing the services by web, phone, facsimile, and mail in addition to branch offices. We discuss how the branch closures influence channel management decisions.