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Artificial Intelligence Big Data Gathering Consumer Behavior Prediction

Artificial Intelligence Big Data Gathering Consumer Behavior Prediction

          
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About the Book

How to analyze activity based travel demand ? Nowadays, human are concerning the traffic congestion and air quality deterioration, the supply oriented focus of transportation planning has expanded to include how to manage travel demand within the available transportation supply. Consequently, there has been an increasing interest in travel demand management strategies, such as congestion pricing that attempts to change aggregate travel demand. The prediction aggregate level, long term travel demand to understanding disaggregate level ( i.e. individual levels ) behavioral responses to short term demand policies, such as ride sharing incentives, congestion pricing and employer based demand management schemes, alternate work schedules, telecommuting limitation of travel agent traditionally work nature shall influence oriented trip based travel modelling passenger travel demand indirectly.Finally, online travel purchase will be popular to influence the number of travel behavioural consumption nowadays. Any travel package products can be sold from websites to attract travellers to choose to prebook air ticket for any trips conveniently. In the past ten years, the internet has become the predominant carrier of all types of information and transactions. Regarding travel decisions, internet has also become an important sales channels for the travel industry, because it is associated with comparably lower distribution and sales costs, but also because ir adapts to hign supply and demand dynamics in this industry. Consequently, the travel and tourism industry tries to increase the internet sale specific share of sales volumes. So, internet sale channel has changed travel consumption behavioural pattern and characteristics and travel experience. For example, Switzerland has one of the highest population-to-computer ratio in Europe. It is also one of the most highly internet penetrated countries in terms of use of the WWW on a day-to-day basis, with more than 75 percent of the population older than 14 years using the WWW daily ( ICT, 2005).The reason of booking online tourism may include: convenience, fast transaction, finding traveling package choice easily, more airline seats available. So, online booking tourism will influence the traditional tourism agents visiting of sales and air tickets and travelling package numbers to be decreased. Finally, the online booking tourism market shares will be expanded to more than traditional tourism agents visits sale market in the future one day. So, the travel agents who still use the traditional tourism visiting sale channel which ought raise whose features to compare to differ to online tourism sale channel if these traditional touriam agents want to keep competitive ability in tourism industry for long term.


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Product Details
  • ISBN-13: 9781723986512
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 734
  • Spine Width: 49 mm
  • Width: 203 mm
  • ISBN-10: 1723986518
  • Publisher Date: 24 Sep 2018
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Weight: 1989 gr


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