Development of a Comprehensive Agent-Based Simulation Model for Smart Transformation of Iran’s Hotel Industry within the Tourism 4.0 Framework

Document Type : Original Article

Authors

1 Associate Professor, Faculty of Technology and Industrial Management, School of Management, University of Tehran, Tehran, Iran.

2 Assistant Professor, Faculty of Technology and Industrial Management, School of Management, University of Tehran, Tehran, Iran.

3 Ph.D. student, Kish Campus, University of Tehran, Kish, Iran.

10.48308/jimp.16.1.9

Abstract

Introduction and Purpose: Luxury hotels, which rely on precise interaction between staff and guests, have actively introduced technologies to enhance guest experience and satisfaction. The upgrading of smart hotels has brought about significant changes in the development environment of the hotel industry, which has led to the emergence of smart hotels. In the modern era, it is very important to make full use of the functions of smart hotels and strive to develop them. Smart hotels allow guests to register their identities, process orders, and receive room cards online. In addition, guests can personalize the services they receive, making the reception and service process simpler and more satisfying. To build a smart tourism hotel, it is necessary to optimize and innovate the core business content of the hotel to enhance the customer experience. This research aimed to develop a comprehensive model for smartening Iran's hotel industry within the Tourism 4 framework and using agent-based simulation.
Methodology: The research approach was hybrid and included library and field stages. First, using the systematic litrature review method, the findings of recent quantitative and qualitative research (2020 onwards) were reviewed and initial codes were extracted. Then, to identify neglected factors and localize the model, thematic analysis was performed on data from 13 semi-structured interviews with hotel industry experts. Combining the results of these two stages led to the identification of 5 main factors (customer, hotel, human resources, government, housekeeping) and 19 key variables. Using interpretive structural modeling, causal and hierarchical relationships of the determinants were determined and the final conceptual model was drawn. The model was implemented in a factor-based simulation environment and evaluated with internal (expert confirmation) and external (comparison with real data) validation, which showed a deviation of less than 0.2 percent.
Findings: The results of this study have increased the awareness of managers and those interested in the field of hotel management and management in the field of smart hotel industry and factor-based models. Also, based on the results of the simultaneous interpretation structural modeling and weighting method, it is concluded that the factors "Customer" and "Hotel (Acceptance / Booking / Reservation)" which are located in the link area have high influence and dependence. In fact, any action on these variables causes changes in other variables. The variable "Government" is located between the autonomous and dependent area, has low influence and medium dependence. Also, the variables "Room and Reception Services (Housekeeping)" and "Human Resources" are located in the neutral area. It was also found that "Room and Reception Services (Housekeeping)", "Human Resources" and "Government" are at the highest level and are most influenced by the "Customer" and "Hotel (Reception/Booking/Reservation)" factors.
Conclusions: Scenario analysis based on two key variables, "technological infrastructure" and "expert human resources," indicated that the simultaneous improvement of these two has the greatest impact on achieving the goal of providing 65 million person-nights of accommodation by 2025. The main innovation of the research is the integration of the three flows of materials, information, and finance in the Tourism 4 framework and the provision of a native and comprehensive model for strategic decision-making in the hotel industry that can help improve service quality, operational efficiency, and competitiveness in the smart tourism market.

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References

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