Forecasting the amount of demand for Arba'in pilgrimage by Iranian pilgrims using discrete gray Markov model

Document Type : Original Article

Authors

1 Imam Hosein (as) University

2 Department of Systems Management, Faculty of Management and Economics, Imam Hossein University, Tehran, Iran.

Abstract

data-based Future studies is one of the guides and pathfinders for managers and decision makers in making decisions. Today, forethought,, prediction and forecasting is one of the key areas of management and is highly necessary and important. In this research, for this purpose, using the discrete Markov gray model, the amount of demand for Arbaeen pilgrimage tourism by Iranian pilgrims in the target area has been predicted. The tourism industry is one of the key industries of today's societies. One of the key branches of this industry on a global scale is a branch called tourism of religious places, which is categorized and researched in religious thought under the specific title of pilgrimage, and in general, it is a form and part of tourism that somehow visits It is related to one of the holy places and usually the shrines and tombs of religious elders. One of the most important places of pilgrimage in the world is the holy city of Karbala, which is the shrine of the third Imam of the Shiites, Imam Hussein (peace be upon him) and his brother, Abbas bin Ali (peace be upon him). Every year, on the 40th day of his martyrdom (Day of Arbaeen), a large number of pilgrims walk the distance from Najaf to Karbala. In recent years and after the fall of the Baath regime dictatorship in Iraq, it has become possible for a large number of people to attend this pilgrimage ceremony. For several years, the Corona epidemic affected the growing trend of Arbaeen pilgrims, but with the resumption of the Arbaeen pilgrimage, it is natural that the governments related to this event should make more detailed plans and designs to hold this ceremony more magnificently.

Keywords

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References

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Futures Studies Of The Islamic Revolution
Volume 3, Issue 3
Autumn Quarterly
January 2023
Pages 143-161

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History

  • Receive Date: 14 August 2022
  • Revise Date: 07 November 2022
  • Accept Date: 16 January 2023
  • Publish Date: 22 November 2022

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