Download or read book Prediction Artificial Intelligent Travel Health Education Transportation Space Exploration Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-09-04 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction I write this book aims to let readers to feel that future artificial intelligent (AI) technology whether it could be applied to which aspects to satisfy our life need. I shall concentrate on predicting (AI) technology can be applied to these several aspects: education, business, transportation, space tourism, medical health these five aspects. This is my opinion, it is not absolute true. However, I shall follow our nowadays (AI) technological development trend to explain how I predict how (AI) technology will be invented to applied to these five aspects to satisfy consumer individual and businessman individual both needs, even I shall explain how to (AI) tool to predict consumer behavior in psychological function successfully. First part, I shall explain how and why (AI) technology can be applied to space exploration missions and space tourism development. Will artificial intelligent space exploration bring long term economic, entertainment and technological benefits? What factors will apply (AI) technology to assist space tourism leisure development? How to apply (AI) technology to solve any challenges during space travelling boats fly to space to encounter sudden accident. This part concerns whether artificial intelligent technology can be used in future space development. Firstly, I shall explain how human can apply artificial intelligent technology to space development which aspects. Then, I shall indicate how scientists need to follow what steps in order to achieve (AI) space robotic technology can be used in space technology to develop more successful. In this part, I shall also explain what benefits or strengths that (AI) space robotic technology can bring to assist space development as well as what disadvantages or weaknesses if (AI) space robotic technology can not be used to assist space development. I shall conclude whether (AI) space robotic technology will be real one tool which can assist space development, when human chooses to adapt to work and live and space tourism entertainment activities with (AI) space robots together in our future (AI) space robotic technological societies. Second part, I shall explain how future (AI) technology can be applied to business and health service aspect. The research questions: Can AI grow productivity? If AI can grow productivity, how can it raise ? If productivity raised, can it raise economic development ? How will (AI) influence human job change? Advances in artificial intelligence (AI) technology is for the progress in critical areas, such as health, education, energy, economy inclusion, social welfare and the environment. Thus, it brings this question: Which (AI) workers be instead of traditional human workers in these different new markets? In recent years, machines had been used to be human's tasks in the performance of certain tasks related to intelligence, such as aspects of image recognition. Experts also forecast that rapid progress in the field of specialized artificial intelligence will continue. Then, it also brings this question: Does (AI) exceed that of human performance on more and more tasks? If it is truth, will some of human jobs to be disappeared? (AI) will be instead of human some simple jobs, then unemployment rate to the low skillful and low educated workers will be increased.

Download or read book Prediction Artificial Intelligent Travel Health Education Transportation Space Exploration written by Johnny Ch LOK and published by . This book was released on 2018-08-23 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction I write this book aims to let readers to feel that future artificial intelligent (AI) technology whether it could be applied to which aspects to satisfy our life need. I shall concentrate on predicting (AI) technology can be applied to these several aspects: education, business, transportation, space tourism, medical health these five aspects. This is my opinion, it is not absolute true. However, I shall follow our nowadays (AI) technological development trend to explain how I predict how (AI) technology will be invented to applied to these five aspects to satisfy consumer individual and businessman individual both needs, even I shall explain how to (AI) tool to predict consumer behavior in psychological function successfully. First part, I shall explain how and why (AI) technology can be applied to space exploration missions and space tourism development. Will artificial intelligent space exploration bring long term economic , entertainment and technological benefits? What factors will apply (AI) technology to assist space tourism leisure development? How to apply (AI) technology to solve any challenges during space travelling boats fly to space to encounter sudden accident. This part concerns whether artificial intelligent technology can be used in future space development. Firstly, I shall explain how human can apply artificial intelligent technology to space development which aspects. Then, I shall indicate how scientists need to follow what steps in order to achieve (AI) space robotic technology can be used in space technology to develop more successful. In this part, I shall also explain what benefits or strengths that (AI) space robotic technology can bring to assist space development as well as what disadvantages or weaknesses if (AI) space robotic technology can not be used to assist space development. I shall conclude whether (AI) space robotic technology will be real one tool which can assist space development, when human chooses to adapt to work and live and space tourism entertainment activities with (AI) space robots together in our future (AI) space robotic technological societies. Second part, I shall explain how future (AI) technology can be applied to business and health service aspect. The research questions: Can AI grow productivity? If AI can grow productivity, how can it raise ? If productivity raised, can it raise economic development ? How will (AI) influence human job change? Advances in artificial intelligence (AI) technology is for the progress in critical areas, such as health, education, energy, economy inclusion, social welfare and the environment. Thus, it brings this question: Which (AI) workers be instead of traditional human workers in these different new markets? In recent years, machines had been used to be human's tasks in the performance of certain tasks related to intelligence , such as aspects of image recognition. Experts also forecast that rapid progress in the field of specialized artificial intelligence will continue. Then, it also brings this question: Does (AI) exceed that of human performance on more and more tasks? If it is truth, will some of human jobs to be disappeared? (AI) will be instead of human some simple jobs, then unemployment rate to the low skillful and low educated workers will be increased.

Download or read book Prediction Artificial Intelligent Travel Health Education Transportation Spa written by Johnny Ch Lok and published by Createspace Independent Publishing Platform. This book was released on 2018-09-04 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: I write this book aims to let readers to feel that future artificial intelligent (AI) technology whether it could be applied to which aspects to satisfy our life need. I shall concentrate on predicting (AI) technology can be applied to these several aspects: education, business, transportation, space tourism, medical health these five aspects. This is my opinion, it is not absolute true. However, I shall follow our nowadays (AI) technological development trend to explain how I predict how (AI) technology will be invented to applied to these five aspects to satisfy consumer individual and businessman individual both needs, even I shall explain how to (AI) tool to predict consumer behavior in psychological function successfully. First part, I shall explain how and why (AI) technology can be applied to space exploration missions and space tourism development. Will artificial intelligent space exploration bring long term economic , entertainment and technological benefits? What factors will apply (AI) technology to assist space tourism leisure development? How to apply (AI) technology to solve any challenges during space travelling boats fly to space to encounter sudden accident. This part concerns whether artificial intelligent technology can be used in future space development. Firstly, I shall explain how human can apply artificial intelligent technology to space development which aspects. Then, I shall indicate how scientists need to follow what steps in order to achieve (AI) space robotic technology can be used in space technology to develop more successful. In this part, I shall also explain what benefits or strengths that (AI) space robotic technology can bring to assist space development as well as what disadvantages or weaknesses if (AI) space robotic technology can not be used to assist space development. I shall conclude whether (AI) space robotic technology will be real one tool which can assist space development, when human chooses to adapt to work and live and space tourism entertainment activities with (AI) space robots together in our future (AI) space robotic technological societies.

Download or read book Learning Big Data Gathering to Predict Travel Industry Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-10-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter ThreeMain barriers influence artificial intelligent travelling consumer behavioral predictionIn future, it is possible that these barriers will influence how to apply (AI technology) to predict travelling consumer behavior in success. The barriers may include: Lacking of a (AI) digital data gathering vision and strategy, lacking of efficient workforce readiness, (AI) technology constraints., non reaching (AI) consumer behavioral prediction mature stage, time and money and resource constraints, law and regulations prohibition to develop (AI) consumer behavioral prediction bug data gather technology.However, the recommendation of solutions to attack the barriers to influence artificial intelligence consumer behavioral prediction not success, it may include gaining employee buy in to participate and develop (AI) consumer behavioral prediction technology, making customer experience to a concern (AI) big data gather questionnaire investigation, providing compensation, training to employees in order to achieve (AI) travelling consumer behavioral big data questionnaire investigation research digital technological goals and strategy, task senior leaders manage any (AI) digital big data gather technology changes, putting policies and (AI) big data gather digital technology in place to support a fully remote, flexible workforce in any (AI) digital big data gather questionnaires research projects, teaching all employees how to code/understand (AI) big data gather consumer behavioral prediction software development, appointing a chief (AI) officer to manage any (AI) big data gather customer behavioral prediction projects and automate everything and encourage customers to attempt experience to self-service and (AI) big data gather questionnaire research to earn beneficial consumption aim after they gave feedback to any (AI) digital questionnaire researches. So, in the future, the (AI) digital big data questionnaire researches can include these industries surveyed, such as automat m financial services, public healthcare, private healthcare, technology, telecoms, insurance, life sciences, manufacturing, media and entertainment, oil and gas, retail and consumer products etc. Hence, in the future, any of these industries can attempt to apply (AI) digital big data gather technology to predict how and why consumer behaviors will change in order to avoid reducing consumer number threat occurrence.

Download or read book Artificial Intelligence Technology Predicts Travel Consumption Market written by Johnny Ch Lok and published by . This book was released on 2018-07-20 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has these two research questions need to be answered?(1) Can apply (AI) learning machine predict travelling consumer behavior?(2) Can (AI) big data gathering learning machine be replaced to human travelling marketing research method, e.g. survey or traveler psychological and travelling marketing research or travelling environment micro and macro economic human judgement of traveler consumption behavior prediction methods to predict travelling consumer behaviors more accurate?

Download or read book Artificial Intelligence Big Data Gathering Consumer Behavior Prediction written by Johnny Ch Lok and published by . This book was released on 2018-09-24 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence Big Data Travelling written by Johnny Ch LOK and published by . This book was released on 2018-06-17 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book indicates whether human technological AI (big data gathering tool) which can be applied to predict when, how and why consumer behavior will change. Does it is science story or actual fact to be applied in our future business society. Parent can learn their children to make judgement whether our future society will be either assistance by AI technological development absolutely or AI is only science story product. This book has these two research questions need to be answered?(1) Can apply (AI) learning machine predict travelling consumer behavior?(2) Can (AI) big data gathering learning machine be replaced to human travelling marketing research method, e.g. survey or traveler psychological and travelling marketing research or travelling environment micro and macro economic human judgement of traveler consumption behavior prediction methods to predict travelling consumer behaviors more accurate? Nowadays, many airline firms or travelling agents hope to apply different methods to predict travelling consumer behaviors in order to know what will be future next month, even next year travelling market destination choice and travelling package design preferable choice activities and travelling consumers travelling packages or travelling destination taste changes to help them to choose to implement what kinds of travelling marketing strategies or what are travelling packages or airline ticket prices more reasonable or more accurate range price level to attract travelers choose to the airline or travel agent to buy paper or e- ticket or help them to arrange travel package more attractive. Hence, if the travel agent or airline can apply the most suitable travelling consumer behavioral prediction method to predict how and the reasons why future travelling consumers' choice will be changed to influence their frequent travelling destination or travelling package choice. It will have more beneficial intangible advantages to compare the non-predictive travelling consumer behavioral variable changes travel agents or airlines, e.g. what will be the hot travel entertainment destinations and tangible advantages, what are the most suitable airline and hotel reasonable price range level to attract many travelers to choose to find the airline or travel agent to help them to buy air ticket or they ought know how to design their arrange travel package which will be accepted more popular for next or next year travelling customer's hot needs .Otherwise, if they applied the inaccurate traveler consumer behavioral prediction market research methods, e.g. survey, telephone questionnaire to predict how their consumers' behavioral changes. It will waste their time and money to attempt to make wrong travelling hot destinations and travelling package design to make unattractive travelling market strategy to cause travelling customer number to be reduced. In my this book, I concentrate on explain why artificial intelligence (AI) big data gathering tool will be one kind of good traveler consumer behavioral prediction tool to be chose to apply to predict traveler consumer consumption behavior concerns when and why and how their travelling behavior will change. I shall indicate some cases examples to give reasonable evidences to analyze whether (AI) big data gathering tool will be one kind suitable tool to be applied to predict when and how and why travelling consumer behavioral changes. If (AI) big data can be one kind tool to attempt to be applied to predict when and how and why travelling consumer behavioral changes. Will it make more accurate to compare other kinds of methods to predict travelling consumer behaviors, e.g. survey, telephone questionnaire? Does it have weaknesses to be applied to predict travelling consumer behaviors, instead of strengths?

Download or read book Prediction Artificial Intelligence Consumer Behavioral Trend written by Johnny Ch Lok and published by Createspace Independent Publishing Platform. This book was released on 2018-01-28 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, I shall give actual data to predict what the future (AI) products development trend is. Giving my opinions to predict how (AI) consumers' choices are more absolutely. I shall concern travel, education, transportation, financial , hospital, administrative service etc. different job natures to indicate how to apply (AI) products to assist these industries more beneficial.

Download or read book Artificial Intelligence Big Data Travelling Consumption Prediction written by Johnny Ch Lok and published by Createspace Independent Publishing Platform. This book was released on 2018-06-10 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, many airline firms or travelling agents hope to apply different methods to predict travelling consumer behaviors in order to know what will be future next month, even next year travelling market destination choice and travelling package design preferable choice activities and travelling consumers travelling packages or travelling destination taste changes to help them to choose to implement what kinds of travelling marketing strategies or what are travelling packages or airline ticket prices more reasonable or more accurate range price level to attract travelers choose to the airline or travel agent to buy paper or e- ticket or help them to arrange travel package more attractive. Hence, if the travel agent or airline can apply the most suitable travelling consumer behavioral prediction method to predict how and the reasons why future travelling consumers' choice will be changed to influence their frequent travelling destination or travelling package choice. It will have more beneficial intangible advantages to compare the non-predictive travelling consumer behavioral variable changes travel agents or airlines, e.g. what will be the hot travel entertainment destinations and tangible advantages, what are the most suitable airline and hotel reasonable price range level to attract many travelers to choose to find the airline or travel agent to help them to buy air ticket or they ought know how to design their arrange travel package which will be accepted more popular for next or next year travelling customer's hot needs .Otherwise, if they applied the inaccurate traveler consumer behavioral prediction market research methods, e.g. survey, telephone questionnaire to predict how their consumers' behavioral changes. It will waste their time and money to attempt to make wrong travelling hot destinations and travelling package design to make unattractive travelling marketing strategy to cause travelling customer number to be reduced. In my this book, I concentrate on explain why artificial intelligence (AI) big data gathering tool will be one kind of good traveler consumer behavioral prediction tool to be chose to apply to predict traveler consumer consumption behavior concerns when and why and how their travelling behavior will change. I shall indicate some cases examples to give reasonable evidences to analyze whether (AI) big data gathering tool will be one kind suitable tool to be applied to predict when and how and why travelling consumer behavioral changes. If (AI) big data can be one kind tool to attempt to be applied to predict when and how and why travelling consumer behavioral changes. Will it make more accurate to compare other kinds of methods to predict travelling consumer behaviors, e.g. survey, telephone questionnaire? Does it have weaknesses to be applied to predict travelling consumer behaviors, instead of strengths? Can it be applied to predict travelling consumer behaviors depending on any situations or only some situations? Finally, I believe that any readers can find answers to answer above these questions in this book.

Download or read book Can Apply Artificial Intelligent Tourism Behavioral Prediction Tool written by Johnny Ch Lok and published by . This book was released on 2019-05-25 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: When (AI) big data gather past every country traveler number who chose to go to which countries to travel in order to judge where destinations will be the country travelers' travelling choice destinations in the future.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. Hence, (AI) big data can gather past different countries' climate changing data, transportation tool changing data, destination scene environment changing etc. different data to give opinions to travelling businesses whether any country's these above factors will influence about how many traveler number will be increase or decrease in the future.2.3Why can expectation, motivation and attitude factor influence travelling behavior?

Download or read book Artificial Intelligent Travelling Behavioral Predictive Tool written by Johnny Ch LOK and published by . This book was released on 2018-12-10 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligent Consumer Behavioral Predictive Tool written by Johnny Ch LOK and published by . This book was released on 2018-10-20 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligent Data Gathering Tool Predicts Travel Industry Consumer Behavior written by Johnny Ch LOK and published by . This book was released on 2018-10-13 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The challenges of (AI) big data gather shapingthe future of retail for consumer industriesThe future of retail for consumer industries' (AI) big data gather challenges are similar to future travelling industry's entertainment consumption challenges. Another challenge of (AI) big data gather is that how to shape the consumer behavior to let business owner to feel or know oe predict. It means that how it express it's conclusion or opinion for every consumer behavior after it had gather all big data in any data gather period, e.g. three months, half year or one year consumer shopping model data gather period.Because every kind of industry, consumers will continue to demand price and quality change , with a wide range of convenient fulfilment options among of different kinds of products or services supply. Overall, the (AI) big data gather procedure gives opinion concerns every time retail experience will become more exciting, simple and convenient, depending on the consumer's ever-changing needs. So, I believe that (AI) big data gather every conclusion or result will be different, due to consumer's price and quality demand will often change to every kind of product or service supply in retail industry. So, how to shape (AI) big data gathering's analytical conclusion or result more clear. I shall recommend organizations need to build great understanding of and a stronger connection to increasingly empowered consumers before they plan and implement how to apply (AI) big data gather tool to predict consumer behavior as below:Firstly, (AI) is empowered by technology, the consumer is redefining value. The traditional measures of cost, choice and convenience are still relevant, but not control and experience are also important. Globally, consumers have access to more than 2 billion different products choice by a wide range of traditional competitors and dynamic new entrants, all experimenting with new business models and methods of client engagement. As choice increases, loyalty becomes more difficult familiarity and the consumer becomes more empowered. Businesses will have no choice and constantly innovate and disrupt themselves by meeting new technologies of high standards and expectations of consumers. So, (AI) data gather tool will need to follow different target group of consumers' needs to follow their different kinds of product design or style choice preferable to gather data in order to conclude the different target groups of consumer behavior to give opinion more clear and accurate to let businessmen to understand more clear how its customers' behavioral choice trend in the future half month, even to two years period.Secondly, businessmen need to adopt changing technologies rapidly. Technology will be the key driver of this retail industry. Industry participants will only success if they have a clear prediction to focus on how to using technology to increase the value added to consumers. They must , however, do so will I realistic assessment of their costs and benefits. Hence, (AI) big data gather technological tools will need to design to help them to gather data efficiently by these ways, such as the internet of things ( IOT), artificial intelligence (AI) machine learning, augmented reality (AR)/virtual reality (VR), digital traceability. So, future (AI) big data gather tool are predicted to be most influential customer behavioral positive emotion changing tool for retail , due to their widespread applications , ability to drive efficiencies and impact on labor in order to impact consumer behavior changing effort from negative emotion to positive.

Download or read book Is Artificial Intelligence The Best Traveler Behavior Prediction Tool written by John Lok and published by . This book was released on 2022-06-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 individual 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 researches how to apply big data 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 assist 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.

Download or read book Artificial Intelligence Predicts Consumer Behavioral Tool Business Journey written by Johnny Ch LOK and published by . This book was released on 2018-11-23 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: PrepareThis AI science fiction brings readers to image whether what are influenced by artificial intelligent big data gathering tool if it can be invented to replace human marketing research method to predict when, how and why consumer behaviors changes successfully. This book let readers to image themselve are such consumer behavior predictive professional how to apply AI tool to predict customer behavior changes for themselve example product industries in this consumer behavioral predictive journey.This book has these two research questions need to be answered?(1)Can apply (AI) learning machine predict consumer behaviors?(2)Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate?Nowadays, many businessmen or marketing research professional hope to apply different methods to predict consumer behaviors in order to know what will be future market activities and market changes to help them to choose to implement what kinds of 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 consumer behavioral changes to influence whose behavioral consumption to the manufacturer products sale within one to two years short term or three to five years middle term, even above five years long term business plans.Hence, if the product manufacturers can apply the most suitable consumer behavioral prediction method to predict how consumers' choice will be changed to influence their products sale easily. It will have more beneficial intangible and tangible advantages to achieve the their product easier sale aim to ensure their businesses' future market share to be increased more easier to their countries' choice target sale markets. Otherwise, if they applied the inaccurate consumer behavioral prediction methods to predict how their consumers' behavioral changes wrongly. Then, it will influence their market shares to be same level, even it will decrease their market shares, when their consumer behavioral prediction inaccurately.In my this book, I concentrate on indicate whether any artificial intelligence (AI) tools will be one kind of good consumer behavioral prediction method to be choose to apply to predict consumer behaviors. I shall indicate some examples, cases to give reasonable evidences to analyze whether (AI) tools will be one kind suitable tool to be applied to predict when and how consumer behavioral changes. If (AI) can be one kind tool to attempt to be applied to predict when and how consumer behavioral changes. Will it replace other kinds of methods to predict consumer behaviors? Does it have weaknesses to be applied to predict consumer behaviors, instead of strengths? Can it be applied to predict consumer behaviors depending on any situations of only some situation? Finally, I believe that any readers can find answers to answer above these questions in this book.

Download or read book Artificial Intelligence Predicts Traveller Behaviors written by Johnny Ch Lok and published by . This book was released on 2019-07-03 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: What methods can predict future travel behavioural consumptionHow to use qualitative of travel behavioural method to predict future travel consumption. I also suggest to use qualitative of travel behavioural method to predict future travel consumption. Methods such as focus groups interviews and participant observer techniques can be used with quantitative approaches on their own to fill the gaps left by quantitative techniques. These insights have contributed to the development of increasingly sophisticated models to forecast travel behavior and predict changes in behavior in response to change in the transportation system. First, survey methods restrict not only the question frame but the answer frame as well, anticipating the important issues and questions and the responses. However, these surveys methods are not well suited to exploratory areas of research where issues remain unidentified and the researched seek to answer the question "why?". Second, data collection methods using traditional travel diaries or telephone recruitment can under represent certain segments of the population, particularly the older persons with little education, minorities and the poor. Before the survey, focus group for example can be used to identify what socio-demographic variables to include in the survey, how best to structure the diary, even what incentives will be most effective in increasing the response rate. After the survey, focus, focus groups can be used to build explanations for the survey results to identify the "why" of the results as well as the implications. One Asia Pacific survey research result was made by tourism market investigation before. It indicated the travel in Asia Pacific market in the past, had often been undertaken in large groups through leisure package sold in bulk, or in large organized business groups, future travelers will be in smaller groups or alone, and for a much wider range of reasons. Significant new traveler segments, such as female business traveler. The small business traveler and the senior traveler, all of which have different aspirations and requirements from the travel experience. Moreover, Asia tourism market will start to exist behaviors in the adoption of newer technologies, a giving the traveler new ways to manage the travel experience, creating new behaviors. This with provide new opportunities for travel providers. The use of mobile devices, smartphones, tablets etc. and social media are the obvious findings to become an integral part of the travel experience. Thus, quality method can attempt to predict Asia Pacific tourism market development in the future. However, improving the predictive power of travel behavior models and to increase understanding travel behavior which lies in the use of panel data( repeated measures from the same individuals). Whereas, cross-sectional data only reveal inter-individual differences at one moment in time, panel data can reveal intra-individual changes over time. In effect, panel data are generally better suited to understand and predict ( changes in ) travel behavior. However, a substantial proportion was also observed to transition between very different activity/travel patterns over time, indicating that from one year to the next, many people renegotiated their activity/travel patterns.

Download or read book Artificial Intelligent written by Johnny Ch LOK and published by . This book was released on 2018-05-06 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter One How artificial intelligent vehicle may interact intelligent transportation tools Can artificial intelligence (AI) and machine learning (ML) be used in the search for new " consumption" behavioral type variables that affect consumer individual or transportation service organization individual different transportation tools choices, such as road or sea or sky transportation tools? Can artificial intelligent vehicle may interact intelligent transportation tools market development? Consumers usually have bargaining and on risk choice when they are already shopping, such as who need to accept to use any (AI) new technological products to replace human traditional behaviors, such as intelligent non-manual driving transportation market, e.g. cars are needed to be driven by human drivers on road, but it has bargaining and on risky choice, when non-manual (AI) vehicle buyers who need to depend on non-manual artificial intelligent (ML) system assists them to drive their cars on the roads. So, any non-manual driving auto car buyers must need to believe (AI) non-manual driving vehicles (ML) systems can make accurate driving judgement to reduce or avoid any traffic accident occurrences more than human drivers' driving judgement when the (ML) systems are driving their cars on the roads. Then the intelligent vehicle manufacturers will have possible to sell their non-manual driving vehicles success. This is the first reason or idea influences consumer individual choice to buy any kinds of (AI) non-manual driving vehicles, when consumers believe (ML) systems are more safe and make more accurate judgement to compare human or computer systems, when they are sitting in one non-manual auto driving vehicle on the road. The another second reason or idea is that some common limits on driving consumer prediction might be understood as the kinds of errors made by poor implementation of machine learning. Supposing driving consumers believe (AI) machine learning ability is worse to compare to human learning ability. It will also influence driving consumers do not accept to use any (AI) non-manual auto driving vehicles to replace every driver is essential on driving by himself/herself on the road. The third idea or reason is that it is important to influence driving customers believe how (AI) non-manual auto driving technology is used in them can both overcome and exploit human driving skill and safe limits and raise more auto driving safe judgement to compare human driving safe judgement. However, how to predict any kinds of (AI) non-manual driving vehicles future consumption effort, due to different kinds of (AI) non-manual driving transportation vehicles which have different unique functions and designs to be used by different kinds of road transportation or driving demand of consumers. For example, lorry drivers need non-manual intelligent system can help them to drive fast, but safe to assist them to transport cargo to arrive destinations from their factories or offices. Otherwise, private car driver expects whose (AI) non-manual driving vehicle can auto drive to send to whom to arrive destination in safe way and non-too fast and non-too slow speed in order to avoid accident occurrences. So, a different road intelligent consum