This paper presented a method for using direct and indirect data gathered by different online and offline products, in the form of answers, previous history and ratings from tourists for the purpose of trip planning. The objective of is to aid rational and informed decision making in choosing the optimum/ near optimum itinerary based on heuristics and decision theory rather than rules of thumb, long search processes and consultation periods. The limitation of this paper is that the distributions of the user ratings data is not known, and is only assumed to be accurate or consistent. Moreover, not enough data is available for all users as of now, and we assume that as more data is generated, the more accurately we would be able to provide personalized
itinerary recommendations. Future work includes the gathering of more relevant data, developing strategies to estimate the utility functions and scaling coefficients (constants) for individuals), validation of results in comparison with currently used methods and extending the research to group travel.
For tourism companies, this model can help them reduce costs, improve profitability, increase the quality of offerings and so on. For tourists, this will help them derive most value out of their time and for the tourism corporations, organizations and bureaus this would be an entry into the future of the personalized tourism industry and development of tourist attractions.
There are a few conceivable challenges in implementing such a system. The first being privacy protection which makes it critical to have the customer’s consent for gathering data and
protecting this data as well as deciding what level of privacy is to be in place for a sustainable, accurate and non-intrusive use of technology. This can also be an opportunity for third party companies to use this data and create a hub for stakeholders of the tourism industry to study it
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and utilize in designing and managing tourism products. The other challenges are to do with the cost and profitability of offering a tool as well as resistance of the current stakeholders to change.
As we move to an even more connected world with the exponential growth of relevant and irrelevant data and the number of connected products and services in an individual’s life keeps increasing, this tool can enable fit right into the system making travel experiences more efficient and meaningful.
34 References
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