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Past Travel Behaviour Predict Future Travel Behaviour Method

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Past Travel Behaviour Predict Future Travel Behaviour Method

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Author : Johnny C. H. Lok
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-03-02

Past Travel Behaviour Predict Future Travel Behaviour Method written by Johnny C. H. Lok and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-02 with categories.

Past Travel Behaviour Predict Future Travel Behaviour Method

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Author : Johnny Ch LOK
language : en
Publisher:
Release Date : 2018-03-02

Past Travel Behaviour Predict Future Travel Behaviour Method written by Johnny Ch LOK and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-02 with categories.

I write this book aim to let readers to judge whether it is possible to predict future travel behaviour from past travel behaviour for travel agents benefits. This book is divided three parts. This book is suitable to any readers who have interest to predict any individal or family or friend groups of travel target's psychological mind to design the different suitable travel packages to satisfy their needs. In the first part, I shall explain whether it is possible to predict travel behavioural consumption from psychology view and computer statistic view. Second, I shall indicate what factors can influence travel behavioural consumption, such as climate changing, renting travel car tools choice, the country's risk and safety. Then I shall indicate psychological factor to influence travel behavioural consumption, such as: push and pull psychological factor, expectation and motivation and attitude factor. In the second part, I shall general investigating methods to predict travel behavioural consumption, such as qualitative of travel behavioural method, advanced traveler information systems (ATIS) method, online tourism sale channel method, actively based patterns of urban population of travel behavioural prediction method, trip based versus activity based approaches of method. In the final part, I shall explain why the future travel age target will be the senior age group and I shall indicate how to use psychological method to predict travel behavioral consumption.

Past Travel Behaviour Predicts Future Travel Behaviour Methods

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Author : Johnny Ch Lok
language : en
Publisher: Independently Published
Release Date : 2018-12-28

Past Travel Behaviour Predicts Future Travel Behaviour Methods written by Johnny Ch Lok and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-28 with categories.

How to determine future travel behavior from past travel experience and perceptions of risk and safety for the benefits to travel consumers? How to determine future travel behavior from past travel experience and perceptions of risk and safety for the benefits to travel consumers? Why does individual traveler avoid certain destination(s) is(are) as relevant to tourist decision making as why who chooses to travel to others. Perceptions of risk and safety and travel experience are likely to influence travel decisions. If travel agents had efforts to predict future travel behavior to guess whether travelers will feel where is(are) risk and unsafe to cause who does not choose to go to the country to travel. Then, the travel agents will avoid to choose to spend much time to design the different traveling package to attract their potential travel consumers to choose to travel. The reason is because in the case of individual traveler's tourism experience, the traveler whose past disappointment travel experience ( psychological risk) will be a serious threat to the traveler's health or life ( health, physical or terrorism risk). The past safety or unhealthy risk to the country(countries) will influence the traveler decides to choose not to go to the countries(country) to travel again in the future.What is push and pull factors to influence anytraveler who chooses where is whose preferable travelling destinationHow to predict individual traveler's behavioral intention of choosing a travel destination. Understanding why people travel and what factors influence their behavioral intention of choosing a travel destination is beneficial to tourism planning and marketing. In general, an individual's choice of a travel destination into two forces. The first force is the push factor that pushes an individual away from home and attempt to develop a general desire to go somewhere, without specifying where that may be. The other force is the pull factor that pull an individual toward in destination, due to a region-specific or perceived attractiveness of a destination. The respective push and pull factors illustrate that people travel because who are pushed by whose internal motives and pulled by external forced of a destination. However, the decision making process leading to the choice of a travel destination is a very complex process. For example, a Taiwanese traveler who might either choose new travel destination of Hong Kong or another old travel Asia destinations again or who also might choose any one of Western country, as a new travel destination. The travel agents can predict where who will have intention to choose to travel from whose past behavior and attitude, subjective and perceived behavioral control model.The factors influence where is the traveler choice, include personal safety, scenic beauty, cultural interest, climate changing, transportation tools, friendliness of local people, price of trip, trip package service in hotels and restaurants, quality and variety of food and shopping facilities and services etc. needs. So, whose factors will influence where is the individual travel's choice. It seems every traveler whose choice of travel process, will include past behavior. e.g. travelling experience, travelling habit, then to choose the best seasoned travelling action to satisfy whose travel needs. This process is the individual traveler's psychological choice process, who must need time to gather information to compare concerning of different travel packages, destination scene, climate change, transportation tools available to the destination, air ticket price etc. these factors, then to judge where is the best right destination to travel in the right time.

Can Past Travel Behaviour Predict Future Travel Behaviour

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Author : Johhy Lok
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-01-24

Can Past Travel Behaviour Predict Future Travel Behaviour written by Johhy Lok and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-24 with categories.

Can Past Travel Behaviour Predict Future Travel Behaviour

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Author : Johnny C. H. Lok LOK
language : en
Publisher:
Release Date : 2017-12-12

Can Past Travel Behaviour Predict Future Travel Behaviour written by Johnny C. H. Lok LOK and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-12 with categories.

I write this book aim to let readers to judge whether it is possible to predict future travel behaviour from past travel behaviour for travel agents benefits. This book is divided three parts. This book is suitable to any readers who have interest to predict any individal or family or friend groups of travel target's psychological mind to design the different suitable travel packages to satisfy their needs.In the first part, I shall explain whether it is possible to predict travel behavioural consumption from psychology view and computer statistic view. Second, I shall indicate what factors can influence travel behavioural consumption, such as climate changing, renting travel car tools choice, the country's risk and safety. Then I shall indicate psychological factor to influence travel behavioural consumption, such as: push and pull psychological factor, expectation and motivation and attitude factor. In the second part, I shall general investigating methods to predict travel behavioural consumption, such as qualitative of travel behavioural method, advanced traveler information systems (ATIS) method, online tourism sale channel method, actively based patterns of urban population of travel behavioural prediction method, trip based versus activity based approaches of method. In the final part, I shall explain why the future travel age target will be the senior age group and I shall indicate how to use psychological method to predict travel behavioral consumption.

Learning Big Data Gathering To Predict Travel Industry Consumer Behavior

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Author : Johnny Ch Lok
language : en
Publisher: Independently Published
Release Date : 2018-10-04

Learning Big Data Gathering To Predict Travel Industry Consumer Behavior written by Johnny Ch Lok and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-04 with Business & Economics categories.

PrepareI write this book aim to let readers to judge whether it is possible to predict future travel behaviour from past travel behaviour for travel agents benefits as well as big data gathering technology can be applied to predict travel consumption behavior if travel agents can gather any past travel consumer data to predict future travel consumption behavior from AI ( big data gathering tool). This book is suitable to any readers who have interest to predict any individal or family or friend groups of travel target's psychological mind to design the different suitable travel packages to satisfy their needs from big data gathering tool prediction method in possible.This book researchs how to apply big dta gathering tool to predict future travel consumer behavior from past travel consumer data. This book first part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes in entertainment industry, e.g. cruise travel and vehicle leisure activities. If AI, big data gathering tool can be applied to predict such as leisure market consumption behavior, it is possible that future big data gathering tool can be used to gather past travel consumer behavioral data in order to conclude more accurate information to predict future travel behavioral need changes.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict future travelling consumer behaviors from past travelling consumer behavioral data gathering?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict future travelling consumer behavioral need changes more accurate in travelling industry?This book second part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to predict why and when and how travelling consumer behavioral need changes in travelling industry. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort in travel industryNowadays, many businessmen or marketing research professional hope to apply different methods to predict travelling consumer behavioral needs in order to know what will be future travelling market activities changes to help them to choose to implement what kinds of travelling service marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how travelling consumer needs changes to influence whose travelling behavioral consumption for every travels season changes.Hence, if the travelling service providers can apply the most suitable travelling consumer service needs prediction method to predict how travelling consumers' different kinds of travelling package design needs will be changed to attract their travel journey entertainment or journey public transportation service or catching air plan etc. different kinds of travelling service choice easily.

Is Artificial Intelligence The Best Traveler Behavior Prediction Tool

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Author : John Lok
language : en
Publisher:
Release Date : 2022-06-27

Is Artificial Intelligence The Best Traveler Behavior Prediction Tool written by John Lok and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-27 with categories.

Artificial Intelligent Travelling Behavioral Predictive Tool

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Author : Johnny Ch LOK
language : en
Publisher:
Release Date : 2018-12-10

Artificial Intelligent Travelling Behavioral Predictive Tool written by Johnny Ch LOK and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-10 with categories.

I write this book aim to let readers to judge whether it is possible to predict future travel behaviour from past travel behaviour for travel agents benefits as well as big data gathering technology can be applied to predict travel consumption behavior if travel agents can gather any past travel consumer data to predict future travel consumption behavior from AI ( big data gathering tool). This book is suitable to any readers who have interest to predict any individal or family or friend groups of travel target's psychological mind to design the different suitable travel packages to satisfy their needs from big data gathering tool prediction method in possible.This book researchs how to apply big dta gathering tool to predict future travel consumer behavior from past travel consumer data. This book first part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes in entertainment industry, e.g. cruise travel and vehicle leisure activities. If AI , big data gathering tool can be applied to predict such as leisure market consumption behavior, it is possible that future big data gathering tool can be used to gather past travel consumer behavioral data in order to conclude more accurate information to predict future travel behavioral need changes.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict future travelling consumer behaviors from past travelling consumer behavioral data gathering?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict future travelling consumer behavioral need changes more accurate in travelling industry?This book second part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to predict why and when and how travelling consumer behavioral need changes in travelling industry. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort in travel industryNowadays, many businessmen or marketing research professional hope to apply different methods to predict travelling consumer behavioral needs in order to know what will be future travelling market activities changes to help them to choose to implement what kinds of travelling service marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how travelling consumer needs changes to influence whose travelling behavioral consumption for every travels season changes.

Artificial Intelligent Consumer Behavioral Predictive Tool

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Author : Johnny Ch LOK
language : en
Publisher:
Release Date : 2018-10-20

Artificial Intelligent Consumer Behavioral Predictive Tool written by Johnny Ch LOK and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-20 with categories.

PrepareI write this book aim to let readers to judge whether it is possible to predict future travel behaviour from past travel behaviour for travel agents benefits as well as big data gathering technology can be applied to predict travel consumption behavior if travel agents can gather any past travel consumer data to predict future travel consumption behavior from AI ( big data gathering tool). This book is suitable to any readers who have interest to predict any individal or family or friend groups of travel target's psychological mind to design the different suitable travel packages to satisfy their needs from big data gathering tool prediction method in possible.This book researchs how to apply big dta gathering tool to predict future travel consumer behavior from past travel consumer data. This book first part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes in entertainment industry, e.g. cruise travel and vehicle leisure activities. If AI , big data gathering tool can be applied to predict such as leisure market consumption behavior, it is possible that future big data gathering tool can be used to gather past travel consumer behavioral data in order to conclude more accurate information to predict future travel behavioral need changes.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict future travelling consumer behaviors from past travelling consumer behavioral data gathering?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict future travelling consumer behavioral need changes more accurate in travelling industry?This book second part aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to predict why and when and how travelling consumer behavioral need changes in travelling industry. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort in travel industryNowadays, many businessmen or marketing research professional hope to apply different methods to predict travelling consumer behavioral needs in order to know what will be future travelling market activities changes to help them to choose to implement what kinds of travelling service marketing strategies more accurately. The methods include economic environmental change prediction method, consumer individual psychological change prediction method, micro or macro behavioral economic environmental change prediction method, marketing environmental change prediction method etc. different kinds of methods which can be applied to predict how travelling consumer needs changes to influence whose travelling behavioral consumption for every travels season changes.

Big Data Prediction Traveller Behavior

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Author : Johnny Ch Lok
language : en
Publisher:
Release Date : 2019-11-22

Big Data Prediction Traveller Behavior written by Johnny Ch Lok and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-22 with categories.

The second reason is that on the weakness of traveler individual psychological thinking view of survey investigation. It has evidence to support the relationship between self-identify threat and resistance to change travel behavior to any travelers, controlling for whose past travelling behavior, resistance to change if a psychological phenomenon of long standing interest in many applied branches of psychology. Past travelling behavior has been acknowledged as a predictor of future action. Such as travelling behavior that is experienced as successful is likely to be repeated and may lead to habitual patterns. Some psychologists differentiate habit between two concepts, such as goal oriented and automatic oriented both. Although repeated past travelling behavior is addition goal oriented and automatic oriented. Further non-deliberative nature of habit may make appeals to judge and to predict future individual traveler's behavior accurately. However, repeated one traveler will choose the destination to repeat to travel without a necessary constraint of goal orientation and automatic oriented both. So, it seems that psychological factor can influence any individual traveler why and how who choose to decide to repeat to choose the destination to travel. So, survey investigation is only the traveler's thinking to answer the travel firm. It is not sure that the traveler's past travel experience is real answer. Otherwise, (AI) big data gathering method is computer gathering method which gather past traveler consumption actual data to analyze and conclude future traveler possible repeated travel destination choice and travel package choice more accurate.The third reason is that on the strength of (AI) big data gathering method computer statistic view to predict future traveller consumer's destination and travel package choice. It is structural equation modeling is an extremely flexible linear-in-parameters multivariate statistical modeling technique. It has been used in modeling travel behavior and values since about 1980 year. It is a software method to handle a large number of variables, as well as unobserved variables specified as linear combinations ( weighted averages) of the observed variable. Can (AI) big data gather data to predict when climate will change to influence poor travelling behaviours?

Past Travel Behaviour Predict Future Travel Behaviour Method

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