1. Matović, V. and Dobrodolac, M., “Forecasting the number of postal services in the region of south east Europe”, 1st Int. Conf. Transp. Today’s Soc., pp. 571–579 (2016).
2. Qin, M., Li, Z., and Du, Z., “Red tide time series forecasting by combining ARIMA and deep belief network”, Knowledge-Based Syst., 125, pp. 39–52 (2017).
3. Meade, N. and Islam, T., “Forecasting in telecommunications and ICT- A review”, Int. J. Forecast., 31(4), pp. 1105–1126 (2015).
4. Cazals, C., Florens, J.-P., Veruete-McKay, L., Rodriguez, F., and Soteri, S., “UK letter mail demand: A content based time series analysis using overlapping market survey statistical techniques”, Reinventing Post. Sect. an Electron. Age, pp. 91–108 (2011).
5. Odeck, J. and Welde, M., “The accuracy of toll road traffic forecasts: An econometric evaluation”, Transp. Res. Part A Policy Pract., 101, pp. 73–85 (2017).
6. Cabral, J. de A., Legey, L. F. L., and Freitas Cabral, M. V. de, “Electricity consumption forecasting in Brazil: A spatial econometrics approach”, Energy, 126, pp. 124–131 (2017).
7. Trinkner, U. and Grossmann, M., Forecasting E‐Substitution and Mail Demand (2006).
8. Voyant, C., Notton, G., Darras, C., Fouilloy, A., and Motte, F., “Uncertainties in global radiation time series forecasting using machine learning: The multilayer perceptron case”, Energy, 125, pp. 248–257 (2017).
9. Farajpour, G., “Forecasting postage traffic using principal component analysis and artificial neural network”, African J. Bus. Manag., 6(33), p. 9496 (2012).
10. Ostadi, B., Motamedi Sedeh, O., Husseinzadeh Kashan, A., and Amin-Naseri, M. R., “An intelligent model to predict the day-ahead deregulated market clearing price: a hybrid NN, PSO and GA approach”, Sci. Iran. (2018).
11. Wu, L., “Forecasting natural gas production and consumption using grey model with latent information function: The cases of China and USA”, Sci. Iran. (2019).
12. Xie, M., Wu, L., Li, B., and Li, Z., “A novel hybrid multivariate nonlinear grey model for forecasting the traffic-related emissions”, Appl. Math. Model. (2019).
13. Şahin, U., “Forecasting of Turkey’s greenhouse gas emissions using linear and nonlinear rolling metabolic grey model based on optimization”, J. Clean. Prod., 239, p. 118079 (2019).
14. Leitner, S., Rausch, A., and Behrens, D. A., “Distributed investment decisions and forecasting errors: An analysis based on a multi-agent simulation model”, Eur. J. Oper. Res., 258(1), pp. 279–294 (2017).
15. Sharma, P., Kulkarni, M. S., and Yadav, V., “A simulation based optimization approach for spare parts forecasting and selective maintenance”, Reliab. Eng. Syst. Saf. (2017).
16. Cazals, C., Florens, J. P., Rodriguez, F., and Soteri, S., “Forecast uncertainty in dynamic models: an application to the demand for mail”, Compet. Regul. Post. Deliv. Sect., Edward Elgar publishers, pp. 63–73 (2008).
17. Phillips, P. C. B., “Laws and limits of econometrics”, Econ. J., 113, p. 486 (2003).
18. Elsawah, S., Pierce, S. A., Hamilton, S. H., van Delden, H., Haase, D., Elmahdi, A., and Jakeman, A. J., “An overview of the system dynamics process for integrated modelling of socio-ecological systems: Lessons on good modelling practice from five case studies”, Environ. Model. Softw., 93, pp. 127–145 (2017).
19. Suryani, E., Chou, S.-Y., Hartono, R., and Chen, C.-H., “Demand scenario analysis and planned capacity expansion: A system dynamics framework”, Simul. Model. Pract. Theory, 18(6), pp. 732–751 (2010).
20. Hu, B., Zhang, D., Ma, C., Jiang, Y., Hu, X., and Zhang, J., “Modeling and simulation of corporate lifecycle using system dynamics”, Simul. Model. Pract. Theory, 15(10), pp. 1259–1267 (2007).
21. Georgiadis, P., “An integrated System Dynamics model for strategic capacity planning in closed-loop recycling networks: A dynamic analysis for the paper industry”, Simul. Model. Pract. Theory, 32(Supplement C), pp. 116–137 (2013).
22. Rafiei, H., Rabbani, M., and Hosseini, S. H., “Capacity Coordination under Demand Uncertainty in a Hybrid Make-To-Stock/Make-To-Order Environment: A System Dynamics Approach”, Sci. Iran., 21(6), pp. 2315–2325 (2014).
23. Heidarzadeh, S., Doniavi, A., and Solimanpur, M., “Development of Supply Chain Strategy in Iranian Automotive Industry Based on System Dynamics and Game Theory”, Sci. Iran., 24(6), pp. 3345–3354 (2017).
24. Langellier, B. A., Kuhlberg, J. A., Ballard, E. A., Slesinski, S. C., Stankov, I., Gouveia, N., Meisel, J. D., Kroker-Lobos, M. F., Sarmiento, O. L., Caiaffa, W. T., and Diez Roux, A. V, “Using community-based system dynamics modeling to understand the complex systems that influence health in cities: The SALURBAL study”, Health Place, 60, p. 102215 (2019).
25. Gary, M. S., Kunc, M., Morecroft, J. D. W., and Rockart, S. F., “System dynamics and strategy”, Syst. Dyn. Rev., 24(4), pp. 407–429 (2008).
26. “Iran Post Company”, www.post.ir.
27. Sterman, J., Business Dynamics: Systems Thinking and Modeling for a Complex World, McGraw-Hill/Irwin (2000).
28. Makridakis, S. G., Wheelwright, S. C., and Hyndman, R. J., Forecasting: Methods and Applications, 3rd Edn., John Wiley & Sons Ltd (1998).
29. Crew, M. A., Kleindorfer, P. R., and Campbell, J. I., Handbook of Worldwide Postal Reform, Edward Elgar Publishing (2009).
30. Crew, M. A. and Kleindorfer, P. R., Eds., Heightening Competition in the Postal and Delivery Sector, Edward Elgar Publishing Limited (2008).
31. Burt, G., Wright, G., Bradfield, R., Cairns, G., and Van Der Heijden, K., “The role of scenario planning in exploring the environment in view of the limitations of PEST and its derivatives”, Int. Stud. Manag. Organ., 36(3), pp. 50–76 (2006).
32. Fildes, R. and Kumar, V., “Telecommunications demand forecasting—a review”, Int. J. Forecast., 18(4), pp. 489–522 (2002).
33. Veruete-McKay, L., Soteri, S., Nankervis, J., and Rodriguez, F., “Letter Traffic Demand in the UK: An Analysis by Product and Envelope Content Type”, Rev. Netw. Econ., 10 (2011).
34. Anson, J. and Helble, M., “Postal economics and statistics for strategy analysis – the long view”, In Development Strategies for the Postal Sector: An Economic Perspective, Universal Postal Union, Berne, Switzerland (2014).
35. Plum, M., “The challenge of electronic competition: empirical analysis of substitution effects on the demand for letter services”, In Managing Change in the Postal and Delivery Industries, Springer, pp. 270–287 (1997).
36. Hyndman, R. J. and Koehler, A. B., “Another Look at Measures of Forecast Accuracy”, Int. J. Forecast., 22(4), pp. 679–688 (2006).