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Tourism

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Tourism

The future of the tourism industry is expected to be affected by technological changes, among other factors. Some of the essential changes in technology influencing the tourism sector trend include mobile technology, augmented reality, the internet of things, 5G, blockchain, big data, and virtual assistants. Research has revealed that operators have been pursuing effectiveness and efficiency to improve their earnings in the industry. The dwindling human touch sensation is going to be overturned soon. The tourism sector cannot take breaths in the absence of human touch. It is an essential requirement for the sector.

Consequently, the tourism sector is an unstable one, and retaining of persons is a challenge. Disaster tourism, dark tourism, slum tourism, beach tourism, cultural tourism, and adventure tourism are emerging markets in the tourism industry. They provide additional earnings in the sector at the end of the day. Micro-segmentation can be referred to as a technique of coming up with zones in cloud deployments and data centers to allow organizations to segregate assignments from one another and secure them individually.

On the other hand, mass customization refers to the use of flexible computer-aided systems to improve production. Micro-segmentation and mass customization help reduce the cost of production in the tourism sector, thus ultimately increasing profitability. They also help generate the loyalty of tourists in destinations (Nunes et al., 2017). Organizations responding to the converging demands of controlling costs and improving quality are bound to witness period marked by competitive consolidation and cooperation. This notion can be attributed to the fact that many companies, both existing and new entrants, are trying to have an ultimate share of the industry’s market. Thus, they are all trying to come up with strategies to achieve the same.

References

Nunes, S., & Chemli, S. (2017). Generating Tourists’ Loyalty in Destinations through Mass Customization, Applied Ordered Logistic Regression. 관광연구, 32(8), 213-230.

 

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