Параметры публикации

Тип публикации: 

Статья в журнале/сборнике


Megapolis Tourism Development Strategic Planning with Cognitive Modelling Support


Print ISBN 978-981-15-0636-9 / Online ISBN 978-981-15-0637-6



Наименование источника: 

  • Advances in Intelligent Systems and Computing

Обозначение и номер тома: 

Vol. 1041


  • Singapore


  • Springer Nature Singapore Pte Ltd

Год издания: 



The strategic planning of the megapolis tourism development is the process that has to take into account hundreds of factors. Some of the factors cannot be calculated or do not have statistic history. Some of the factors are latent or incorrect. The long-term strategic planning usually includes a short-term action planning. In this case, experts are creating cognitive models that take into consideration non-formalized cognitive semantics. The modelling shows that small change in resource allocation or some mistakes in decision-making can be the reason not to achieve the goals and can replace the optimistic scenario of tourism development by a pessimistic one. The cognitive models could be improved by mapping on the relevant Big Data. The special author’s approach to make the process of tourism strategic decision-making convergent was applied. This paper addresses the issue of using convergent approach to megapolis tourism development strategic planning with a lot of focus groups and cognitive modelling. The inverse problem solving with genetic algorithm helped to find effective strategic decisions and reduce risks of decision-making. For taking into account non-quantitative factors, it is suggested using networked expertise. The convergent approach with cognitive modelling was applied for creating the megapolis tourism development strategic plan for the megapolis. It helps to find the multiplying events and prioritize strategic directions for tourism development.

Библиографическая ссылка: 

Райков А.Н. Megapolis Tourism Development Strategic Planning with Cognitive Modelling Support // Advances in Intelligent Systems and Computing. 2020. Vol. 1041. С. https://link.springer.com/chapter/10.1007/978-981-15-0637-6_12.