ROUGH MULTI- PERIOD NETWORK DATA ENVELOPMENT ANALYSIS FOR EVALUATION OF SUPPLY CHAIN: A CASE STUDY OF SKILL TRAINING IN IRAN

Sepideh Ebadi, Ali Tajdin, Iraj Mahdavi, Hamed Fazlollahtabar

DOI Number
10.22190/FUME231115032E
First page
Last page

Abstract


The existence of a comprehensive and complete model, along with accurate and reliable data, helps to evaluate the performance of the supply chain. Given the different layers and various performances in designing the supply chain, a method that can analyze and evaluate such network structure is required. Moreover, data and conditions’ uncertainty highlight the need for a method that can also include uncertainty in evaluation. In this paper, designing a multi-period network is carried out with rough data to embed in various layers and levels of supply chain. The supply chain performance evaluation is performed using rough network data envelopment analysis. Rough Network Data Envelopment Analysis (RNDEA) is a proper method since it analyzes all the current factors in evaluation; besides, it provides efficiency scores for inefficient decision-making units and boundary forecasting for these units on an efficient border. The study’s outcomes reveal the efficiency of different factors in the designed network. On the other hand, unlike common data envelopment analysis that indicates the maximum of a factor efficiency, the efficiency priority is calculated in the proposed rough network model, and divisional efficiency also is determined in each step.


Keywords

Network Data Envelopment Analysis, Rough Numbers, Multi-period, Performance Evaluation

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References


lo Storto, C., 2020, Performance evaluation of social service provision in Italian major municipalities using Network Data Envelopment Analysis, Socio-Economic Planning Sciences, 71, 100821.

Alizadeh, R., Beiragh, R.G., Soltanisehat, L. Soltanzadeh. E., D. Lund, P., 2020, Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach, Energy Economics, 91, 104894.

Vaezi, E., Najafi, S. E., Hajimolana, S.M., Hosseinzadeh Lotfi, F., Ahadzadeh Namin, M., 2019, Measuring performance of a three-stage structure using data envelopment analysis and Stackelberg game, Journal of Industrial and Systems Engineering, 12(2), pp. 151-173.

Gunasekaran, A., Patel, C., McGaughey, R.E., 2004, A framework for supply chain performance measurement, International Journal of Production Economics, 87(3), pp. 333-347.

Cheng, J., Yang, Q., Lu, L., 2021, Study on Performance Evaluation of Service Supply Chain by Extension Method, Discrete Dynamics in Nature and Society, 1223577.

Amirkhan, M., Didehkhani, D., Khalili-Damghani, K. Hafezalkotob, A., 2018, Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application, International Journal of Information Technology & Decision Making, 17(05), pp. 1429-1467.

Li, Y., Abtahi, A.R., Seyedan, M., 2018, Supply chain performance evaluation using fuzzy network data envelopment analysis: a case study in automotive industry, Annals of Operations Research, 275(2), pp. 461-484.

Rostamy-Malkhalifeh, M., Mollaeian, E., 2012, Evaluating performance supply chain by a new non-radial network DEA model with fuzzy data, Journal of Data Envelopment Analysis and Decision, pp. 1-9.

Mirhedayatian, S.M., Azadi, M., Farzipoor Saen, R., 2013, A novel network data envelopment analysis model for evaluating green supply chain management, International Journal of Production Economics, 147(B), pp. 544-554.

Ebrahimpour Azbari, M., Olfat, L., Amiri, M., Bamdad Soofi, J., 2014, A Network Data Envelopment Analysis Model for Supply Chain Performance Evaluation: Real Case of Iranian Pharmaceutical Industry, International Journal of Industrial Engineering & Production Research, 25(2), pp. 125-137.

Izadikhah, M., Azadi, M., Shokri Kahi, V., Farzipoor Saen, R., 2018, Developing a new chance constrained NDEA model to measure the performance of humanitarian supply chains, International Journal of Production Research, 57(3), pp. 662-682.

Izadikhah, M., Azadi, E., Azadi, M., Farzipoor Saen, R., Toloo, M., 2018, Developing a new chance constrained NDEA model to measure performance of sustainable supply chains, Annals of Operations Research, 316(2), pp. 1319-1347.

Gazori-Nishabori, A., Khalili-Damghani, K., Hafezalkotob, A., 2019, Multi-period network data envelopment analysis to measure efficiency of a real business, Journal of Industrial and Systems Engineering, 12(3), pp. 55-77.

Shariatmadari Serkani, E., Hosseinzadeh Lotfi, F., Najafi, E., Ahadzadeh Namin, M., 2020, Efficiency measurement for hierarchical network systems using network DEA and intuitionistic fuzzy ANP, Sharif University of Technology, 29(4), pp. 2252-2269.

Nojavan M, Heidary A, Mohammaditabar D., 2021, A fuzzy service quality-based approach for performance evaluation of educational units, Socio-Economic Planning Sciences, 73, 100816.

Afsharian, M., Podinovski, V.V., 2018. A linear programming approach to efficiency evaluation in nonconvex meta technologies, European Journal of Operational Research, 268(1), pp. 268-280.

Simar, L., Zelenyuk, V., 2020, Improving Finite Sample Approximation by Central Limit Theorems for Estimates from Data Envelopment Analysis, European Journal of Operational Research, 284(3), pp. 1002-1015.

Beynaghi, A., Moztarzadeh, F., Shahmardan, A., Alizadeh, R., Salimi, J., Mozafari, M., 2016, Makespan minimization for batching work and rework process on a single facility with an aging effect: a hybrid meta-heuristic algorithm for sustainable production management, Journal of Intelligent Manufacturing, 30, pp. 33-45.

Gharizadeh Beiragh, R., Alizadeh, R., Shafiei Kaleibari, S., Cavallaro, F., Hashemkhani Zolfani, S., Bausys, R., Mardani, A., 2020, An integrated multi-criteria decision-making model for sustainability performance assessment for insurance companies, Sustainability, 12(3), 789.

Soltanisehat, L., Alizadeh, R., Nader, M., 2018, Research and Development Investment and Productivity Growth in Firms with Different Levels of Technology, Iranian Economic Review, 23(4), pp. 795-818.

Alizadeh, R., Soltanisehat, L., Lund, P.D., Zamanisabzi, H., 2020, Improving renewable energy policy planning and decision-making through a hybrid MCDM method, Energy Policy, 137, 111174.

Zamani Sabzi, H., Abudu, S., Alizadeh, R., Soltanisehat, L., Dilekli, N., King, J. P., 2018, Integration of time series forecasting in a dynamic decision support system for multiple reservoir management to conserve water sources, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 40(11), pp.1398-1416.

Dar, Q.F., Ahn, Y.H., Dar, G.F., Hee Ma, J., 2022, Data Envelopment Analysis in Three-Stage Network Structure with Slack Based Measure (SBM), Statistics, Optimization and Information Computing, 10, pp. 643–657.

Chen, K., Cook, W.D., Zhu, J., 2020, A conic relaxation model for searching for the global optimum of network data envelopment analysis, European Journal of Operational Research, 280(1), pp. 242-253.

Shafiee, M., 2017, Supply Chain Performance Evaluation with Rough Two-stage Data Envelopment Analysis Model: Non-Cooperative Stackelberg Game Approach, Journal of Computing and Information Science in Engineering, 17(4), 041002.

Bronner, M., Fong See, K., Yu, M.M., 2022, Circular water economy performance evaluation based on dynamic network data envelopment analysis, Journal of Cleaner Production, 367(20), 132474.

Kraude, R., Narayanan, S., Talluri, S., 2022, Evaluating the performance of supply chain risk mitigation strategies using network data envelopment analysis, European Journal of Operational Research, 303(3), pp. 1168-1182.

Emrouznejad, A., Tavana, M., Lotfi, F.H., Shahverdi, R., Yousefpour, M., 2014, A three-stage data envelopment analysis model with application to banking industry, Measurement, 49, pp. 308–1319.

Kao, C., 2014, Efficiency decomposition for general multi-stage systems in data envelopment analysis, European Journal of Operational Research, 232(1), pp. 117–124.

Božanić, D., Epler, I., Puška, A., Biswas, S., Marinković, D., Koprivica, S., 2024, Application of the DIBR II – Rough MABAC Decision-Making Model for Ranking Methods and Techniques of Lean Organization Ssystems Management in the Process of Technical Maintenance, Facta Universitatis-Series Mechanical Engineering, 22(1), pp. 101-123.

Marković, D., Stanković, A., Marinković, D., Pamučar, D., 2024, Metaheuristic Algorithms for the Optimization of Integrated Production Scheduling and Vehicle Routing Problems in Supply Chains, Tehnički Vjesnik, 31(3), pp. 800-807.

Ézsiás, L., Tompa, R., Fischer, S., 2024, Investigation of the Possible Correlations between Specific Characteristics of Crushed Stone Aggregates, Spectrum of Mechanical Engineering and Operational Research, 1(1), pp. 10-26.


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ISSN: 0354-2025 (Print)

ISSN: 2335-0164 (Online)

COBISS.SR-ID 98732551

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