Performance measurement of detection and governmental punitive agency by integrated approach based on DEMATEL, ANP, and DEA

Document Type: Research Paper

Authors

Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

The detection and governmental punitive agency is responsible for supervision on correct implementation of the business laws in Iran. Several criteria are involved in performance assessment of detection and governmental punitive agency. The interaction between criteria and sub-criteria may occur in real situations. Moreover, the performance measurement should be accomplished in a multi-period horizon in order to detect the correct perception of the functionality of the organization. So, in this paper a hybrid approach based on DEMATEL, ANP, and DEA-based Malmquist Productivity Index is proposed measure the performance of detection and governmental punitive agency. First, DEMATEL is used to detect the network of interactive criteria through cause and effect relations. Then, the relative importance of the criteria is calculated using ANP method. Finally, a DEA approach is used to evaluate the productivity of alternatives with multiple inputs and outputs during several planning periods while the relative importance achieved from ANP are also considered as constraints of the system. The proposed approach is used at Detection and Governmental Punitive Agency in all provinces in Iran. The results show that the proposed method is able to assess the performance of a service organization while the assessment is accomplished during multiple periods and the organization is compared with technological progress of the industry as well as its historical technical performance. The proposed method is able to identify the complex relations of criteria, prioritizing the criteria, and assess the performance of service organizations due to technical change and technological change during multiple periods.

Keywords

Main Subjects


Atmaca, E., Basar, H. B. (2012). Evaluation of power plants in Turkey using Analytic Network Process (ANP). Energy, 44, 555-563.

Bottero, M., Comino, E., Riggio, V. (2011).Application of the Analytic Hierarchy Process and the Analytic Network Process for the assessment of different wastewater treatment systems. Environmental Modelling & Software, 26, 1211-1224.

Ergu, D., Kou, G., Shi, Y., Shi, Y. (2014). Analytic  network process in risk assessment and decision analysis. Computers &Operations Research, 42, 58–74.

Chiu, Y. J., Chen, H. C., Tzeng, G. H., & Shyu, J. Z. (2006). Marketing strategy based on customer behavior for the LCD-TV. International Journal of Management and Decision Making. 7(2), 143-165.

Chen, C. H., & Tzeng, G. H. (2009). Combined DEMATEL Technique with a Novel MCDM Method for Creating the Aspired Intelligent Assessment Systems for Mandarin Chinese Teaching Materials.Kitakyushu : s.n., APIEMS, 2050-2061.

Dimić, S., Pamučar, D., Ljubojević, S., Đorović, B. (2016). Strategic Transport Management Models—The Case Study of an Oil Industry, Sustainability, 8(9), 1-27.

Gigović, LJ., Pamučar, D., Božanić, D., Ljubojević, S. (2017). Application of the GIS-DANP-MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable Energy, 103, 501-521.

Gigović, Lj., Pamučar, D., Lukić, D., Marković, S. (2016). Application of the GIS - Fuzzy DEMATEL MCDA model for ecotourism development site evaluation: A case study of „Dunavski ključ“, Serbia, Land use policy, 58, 348–365;

Gigović, Lj., Pamučar, D., Bajić, Z., Milićević, M. (2016). The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depot, Sustainability, 8(4), 1-30.

Gigović, Lj., Pamučar, D., Bajić, Z., Drobnjak, S. (2017). Application of GIS-Interval Rough AHP Methodology for Flood Hazard Mapping in Urban Areas, Water, 6(6), 1-26.

Hori, S. & Shimizu, Y. (1999). Designing methods of human interface for supervisory control systems. Control Engineering Practice, 7, 1413-1419.

Karsak, E. E., & et al. (2003). Product planning in quality function deployment using a combined analytic network process and goal programming approach,Computers & Industrial Engineering, 44 (1),  171–190.

Kirytopoulos,  K., Voulgaridou, D., Platis, A., Leopoulos, V. (2011). An effective Markov based approach for calculating the Limit Matrix in the analytic network process.European Journal of Operational Research, 214, 85–90.

Lee, J.W., & Kim, S. H. (2000). Using Analytic Network Process and Goal Programming for Interdependent Information System Project Selection, Computers and Operations Research, 27(4), 367-382.

Liu, S. T., & Chuang, M. (2009). Fuzzy efficiency measures in fuzzy DEA/AR with application to university libraries. Expert Systems with Applications, 36(2), 1105–1113.

Lin, C.J., & Wu, W.W. (2008). A causal analytical method for group decision-making under fuzzy environment. Expert Systems with Applications, 34(1), 205-213.

Lin, C. L., Hsieh, M. S., & Tzeng, G. H., (2009). A Novel Evaluation Model for the Vehicle Navigation Device Market Using Hybrid MCDM Techniques. Berlin : Springer, 769-779

Liou, J. H., James, & et al. (2009). Developing a hybrid multi-crireria model for selection of outsurcing providers.

Lin, C.J., & Wu, W.W. (2008). A causal analytical method for group decision-making under fuzzy environment. Expert Systems with Applications, 34(1), 205-213.

Meade, L.M., & Sarkis, J. (1998). Strategic analysis of logistics and supplychain management systems using theanalytical network process, TransportationResearch Part E: Logistics andTransportation Review, 34(3), 201-215

Meade, L. M., Presley, A. (2002). R&D Project Selection Using the Analytic Network Process, IEEE Transactions on Engineering Management, 49(1), 59-66.

Mikhailov, L., &  Singh, M. S. (2003). Fuzzy Analytic Network Process and its Application to the Development of Decision Support Systems, IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews. 33, 33-41.

Niemira, M. P., & Saaty, T. L. (2004). An Analytical Network Process Model for Financial-Crisis Forecasting, International Journal of Forecasting, 20(4), 573-587.

Partovi, F. Y. (2006). An analytic model for locating facilities strategically,Omega, 34 (1), 41 – 55.

Pamučar, D., Mihajlović, M., Obradović, R., Atanasković, P. (2017). Novel approach to group multi-criteria decision making based on interval rough numbers: Hybrid DEMATEL-ANP-MAIRCA model, Expert Systems with Applications, 88, 58-80.

Shiue, Y-C., Lin, C-Y. (2012). Applying analytic network process to evaluate the optimal recycling strategy in upstream of solar energy industry. Energy and Buildings, 54, 266–277.

Yurdakul, M. (2003). Measuring Long-Term Performance of a Process (ANP) approach, International Journal of Production Research. 41, 2501-2529.