Download or read book How Artificial Intelligence Measures Traveller Needs written by Johnny Ch Lok and published by . This book was released on 2019-11-21 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: I shall explain how (AI) big data gathering technology can provide travelling businesses with better-informed decisions to drive top-line growth, deliver meaningful experience for travelling customers and smooth their path along the travelling consumer journey. The widely understood definition of (AI) involves the ability of machines or computers to learn human thinking, reasoning and decision-making abilities. So, such as (AI) learning machine system can attempt to learn travelling consumer's travel destination or travel package thinking, judgement of their reasons why they choose to go to the destination to travel or why they choose to buy the travel package and learn how and why they make their past travelling decisions from their past travel big data gathering.A Narrative science study in 2015 year identified that (AI) was being used primarily in voice recognition, machine learning virtual assistants and decision support. This study also highlighted the many branches of (AI) and that techniques and their definition are used interchangeably. It is possible that (AI) can be used to gather big data, then to analyze to help travel businesses to predict travelling consumer travel destination and travel package choice behaviors. For example, one of the most common techniques is traveler machine learning, where algorithms are used to perform tasks by learning from the airline or travel agent whose past all travelers' travelling destination choice and travel package choice historical data. However, during 2017 year, search engines will begin to find what additional factors can influence past traveler personal travelling destination and travelling package travelling behavioral data into prediction of future travelling customer behavioral results, such as the online traveler (user's) history of travelling data searches, such as anywhere are the most popular travelling locations or travelling destinations and previously captures conservations. Artificial intelligence will use this past travelling destinations and travelling package information to power predictive search results, e.g. predictive future travelling consumer's choice behavioral processing for where will be their preferable travelling destination choice and how to design travelling package to satisfy future travelling clients' needs.

Download or read book Artificial Intelligence Brings Social Influences written by Johnny Ch Lok and published by Independently Published. This book was released on 2021-03-25 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to apply (AI) big data 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. 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?Social psychology is concerned with gaining insight into the psychological of socially relevant behaviors and the processes. For instance, on a global level bad influence to global warming, it influences some countries extreme cold or hot bad climate changing occurrence, then it ought influence some travelers' behavioral decision to change their mind to choose some countries to go to travel at the moment which do not occur extreme hot or cold climate ( temperature). e.g. above than 40 degree in summer or below than 0 degree in winter. Due to the extreme climate changing environment in the countries, it will cause them to feel uncomfortable to play during their trips. So, the global warming causes to climate changing factor will influence the numbers of travel consumption to be reduced possibly.

Download or read book Robots Artificial Intelligence and Service Automation in Travel Tourism and Hospitality written by Stanislav Ivanov and published by Emerald Group Publishing. This book was released on 2019-10-14 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using a combination of theoretical discussion and real-world case studies, this book focuses on current and future use of RAISA technologies in the tourism economy, including examples from the hotel, restaurant, travel agency, museum, and events industries.

Download or read book Artificial Intelligence and Machine Learning in the Travel Industry written by Ben Vinod and published by Springer Nature. This book was released on 2023-05-26 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high. The contributions in this book, originally published as a special issue for the Journal of Revenue and Pricing Management, showcase the breadth and scope of the technological advances that have the potential to transform the travel experience, as well as the individuals who are already putting them into practice.

Download or read book Artificial Intelligence Predicts Traveller Behavioral Tool written by Johnny Ch Lok and published by . This book was released on 2020-02-16 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can ARTIFICIAL INTELLIGENT online tourism sale channel influence traveling consumption of behavior?Nowadays, internet is popular, it seems that booking air ticket behavior of using internet is predicted to influence overall tourism air tickets payment method. Tourism industry has grown in the previous several decades. Despite its global impact, questions related to better understanding of tourists and whose habits. Using online travel air ticket booking benefits include booking electronic air tickets can be made from entering any electronic travel agents websites in the short time and electronic travel ticket payers do not need leave home, who can pay visa card to pre booking any electronic travel ticket from online channel conveniently.3.5How can 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 behavioral consumption nowadays. Any travel package products can be sold from websites to attract travelers to choose to pre-book 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 it adapts to high 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 behavioral 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 tourism agents want to keep competitive ability in tourism industry for long term.What is actively based patterns of urban population of travel behavioral prediction method?

Download or read book Artificial Intelligence Predicts Traveller Behaviors written by Johnny Ch LOK and published by . This book was released on 2019-09-06 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 tourism agents want to keep competitive ability in tourism industry for long term.3.6What is actively based patterns of urban population of travel behavioral prediction method? Actively based patterns of urban population. It is a method of motivational framework means in which societal constraints and inherent individual motivations interact to shape activity participation patterns. It can be used to predict one city or urban the numbers of travel demand in the year. It has two elements: First, capability constraints refer to constraints are imposed by biological needs, such as eating and sleeping and/or resources, such as income, availability of cars etc. to undertake the urban or city's family activities in the year. Second, coupling constraints define where, when and the duration of planning activities that are to be pursued with other individuals. So, this method needs to gather information ( data) to get the relationship between activities, travel and spending work time and space time to evaluate whether there are how many families who have real needs to spend time to go to travel in the year.3.7What is trip based versus activity based approaches? What is trip based versus activity based approaches? The fundamental difference between the trip-based and activity based approaches is that the former approach directly focuses on trips without explicit recognition of the motivation or reason for the trips and travel. The activity based approach , on the other hand, views travel as a demand derived from the need to pursue travel activities. So, it is better understand the individual or family behavior basis for individual or family travelling decision regarding participation in travelling activities in certain places or cities or countries at given times and hence the resulting travel needs. This behavioral basis includes all the factors that influence the why, how, when and where of performed activities and resulting individuals and household, the cultural/social norms of the community and the travel surrounding environment.

Download or read book How Artificial Intelligence Influences Online Book And written by Johnny Ch Lok and published by . This book was released on 2020-06-26 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: How artificial intelligence can raise office efficiency to bring benefits to online tourism and publish industries ?Artificial Intelligence is already impacting every industry through automation and machine learning, bringing concerns that AI is on the fast track to replacing many jobs. But these fears aren't new, says Dan Jackson, director of Enterprise Technology at Crestron, a company that designs workplace technology. "I'd argue this is no different than when we moved from an agricultural to an industrial economy at the turn of the last century. The percentage of people working in agriculture significantly decreased, and it was a big shift, but we still have plenty of jobs 100 years later," he says. Anytime society experiences a major technological advancement, we need to be prepared for it to change the way we live and work. It's hard to imagine what the future of jobs will look like with AI, but that future exists. And optimists suggest that, like the sewing machine to the textile industry, AI will make us better, more efficient and faster workers. In fact, many experts agree that AI has the potential to eliminate mundane, administrative work, while we will always rely on human workers to be empathetic, collaborative, creative and strategic. But it's impact on any industry lies in the hands of the business leaders who are responsible for adopting AI strategies. ⦁Training presents challengesA recent study of 1,000 global companies by Accenture found that AI is already creating three new categories of jobs: trainers, explainers and sustainers. Trainers are the people who teach AI systems how to act -- whether it's language, human behavior or the intricacies of human interaction. Explainers are the liaison between technology and business leaders, providing more insight and clarity into machine learning for the non-tech workers. Sustainers are the workers required to maintain AI systems and troubleshoot any potential issues. Some jobs were highly technical and required advanced degrees, but other roles demanded innately human things such as empathy and interaction. Downstream jobs, such as those in sales, marketing, or service will change to take advantage of the insights from AI, but many of the core skills will remain. However, it might sound like any job related to AI will require years of technical knowledge, but that isn't the case. We've already seen a shift in tech hiring -- companies often need highly specific skill sets that are hard to find in potential candidates. As a result, more businesses are hiring employees with the right soft skills, and then training them in technical skills. Internet negative influences to travel agentsAlthough, on the one hand, internet creates offline travel agents to use websites to help them to sell electronic air ticket or travel related products, such as prebooking hotel rooms, restaurants, transportation tools etc. travel service. However, on the other hand, internet also brings travel agencies competitive disadvantage with regad to suppliers' direct websites, when airlines are able to control seat availability and prices. Indeed internet cause the decision is made by the airlines to reduce and/or eliminate travel agency commission has led them to use technology that many of their distrust or are not inclined to use, and to compare prices and travel schedules constantly. As a result of this travel sale service environment, traditional offline travel agencies are at a competitive disadvantage with regard to online travel agencie and to airline carriers, which have developed their own direct websites where they are able to control seat availability and prices.

Download or read book THE RISE OF ARTIFICIAL INTELLIGENCE HOW IT WILL TRANSFORM OUR LIVES written by John Lyndon and published by John Lyndon. This book was released on 2023-08-07 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: ABOUT THIS BOOK In recent years, the world has witnessed a remarkable surge in technological advancements, and at the forefront of this wave is the rapid development and integration of artificial intelligence (AI). From self-driving cars to personalized virtual assistants, AI has permeated various aspects of our lives, reshaping industries, transforming economies, and challenging our understanding of what is possible. “The Rise of Artificial Intelligence and How It Will Transform Our Lives” is a groundbreaking exploration of the transformative power of AI and its far-reaching implications for society. In this book, we delve into the vast potential of AI, examining its impact across diverse domains, from healthcare and education to business and governance. We seek to demystify this complex field and provide readers with a comprehensive understanding of how AI is poised to reshape our world. Whether you are an AI enthusiast, a curious skeptic, or simply someone intrigued by innovative technologies, “The Rise of Artificial Intelligence & How It Will Transform Our Lives” is an essential read that will leave you enlightened, informed, and inspired to shape a future where artificial intelligence truly augments the human experience. Join us as we embark on a compelling odyssey into the heart of AI, charting a course toward a world where the realms of science fiction become awe-inspiring reality.

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 Big Data Travelling Consumption Prediction written by Johnny Ch LOK and published by . This book was released on 2018-06-16 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: PrepareThis 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 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 Artificial Intelligence Improves Service Performance written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-11-29 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to apply (AI) technology to improve service performance to satisfy US tourism consumers needsNowadays, tourism industry is every country's main leisure income. Every country will need have itself unique tourism features to attract travellers to go to travel easily. So, attractive unique tourism features can persuade different countrues travellers choose to go to itself country to travel more easily. I shall recommend what factors can influence global travelling consumers choose to go to US travel more easily. The travelling strategies can attempt to be implemented as below: Firstly, US tourism leisure providers ( travel agents) need to know what different countries' tourism consumers why and how to persuade them to feel US anywhere places are valuable to go to travel, what can attract them in these places, for Chinese travellers case example, what Chinese like to play when they choose to go to any one of the US domestic travelling placs. So, the US tourism leisure providers need to define the Chinese tourism consumers' tourism acts, attitude and travelling decisions regarding choosing, buying and consuming tourism products and tourism services and also its past consumer tourism reaction. Due to different countries' tourism consumers who have different tourism leisure needs, e.g. Chinese young age travellers prefer to choose to tourism package arrangement, who only like to buy air tickets and arrange their travelling journeys, e.g. they can choose where they will live and anywhere they choose to travel. So, US tourism service providers only concentrate on introducing anywhere US places valuable to let them to travel, calculating every journey transportation cost, and living and eating cost to let Chinese young tourism consumers to know. Otherwise, Chinese old age tourism consumers prefer to the US tourism service providers can arrange whole tourism journey to help them to reduce their worries about paying how much rent to live hotels, transportation costs in US anywhere journeys. Due to US is a large area country, many Chinese will feel worry about how to catch the bus, ferry, domestic air place, taxt, train, tram etc. transportation to go to any US domestic tourism places to pay the cheaper cost as well as how to find the reasonable price of hotels to live as well as how to choose the most valuable travelling places to travel and US anywhere touism places can be exciting and comfortable and enjoyable tourism leisure feeling in their whole US tourism journeys.In special, the Chinese old age tourism consumers must consider above these challenges, they must need the US tourism leisure provider ensures to help them to arrange all their US tourism journey needs, then they will reduce worry to choose who is the best tourism leisure service provider if the US travel service provider can solve above all challenges for their US domestic journeys. So, the US doemstic tourism leisure arrangement service market competition is serious. Every US domestic tourism leisure provider needs have unique travelling leisure arrangement to attract them.Secondly, US tourism service providers need to attempt to find different countries' tourism consumers' tourism leisure needs and how they make travelling journey decision processes because it can assist marketing manger to improve his/her own decision making process to forecast future different countries' tourism consumers' behaviors and to have a real and objective image of the country's general tourism consumer tourism leisure and tourism journey arrangement demands.Hence, US tourism leisure service providers need to spend time to gather past different countries' tourism journeys arrangement tourism experience to develop new tourism products and services . It will include these questions for each country's travelling consumers' demands, such as below: Who is important in the whole travelling journey arrangement decision making final tourism consumer?

Download or read book AI Innovations for Travel and Tourism written by Correia, Ricardo and published by IGI Global. This book was released on 2024-06-05 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tourism industry faces pressing challenges amidst the integration of artificial intelligence (AI) technologies. It is necessary to address the lack of a comprehensive understanding of AI's impact on the sector, emphasizing its role in reshaping the travel ecosystem, enhancing customer experiences, and optimizing operational efficiency. Ethical considerations surrounding AI implementation in tourism must be thoroughly examined to guide responsible technology use. AI Innovations for Travel and Tourism illuminates how AI revolutionizes travel ecosystems, beginning with an insightful introduction to AI's impact on tourism, laying the groundwork for a nuanced understanding of its transformative potential. Delving into personalized travel planning, the book navigates the reader through the intricacies of AI-enhanced destination recommendations, digging into how these technologies redefine the travel experience. Smart booking systems and travel experiences demonstrate how AI streamlines operations and raises customer satisfaction. This book is ideal for tourism scholars, educators, students, researchers, and industry professionals.

Download or read book AI Infused Test Automation Revolutionizing Software Testing through Artificial Intelligence written by Anup Sahoo and published by OrangeBooks Publication. This book was released on 2023-11-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI-Infused Test Automation: Revolutionizing Software Testing through Artificial Intelligence is an enlightening book that explores the transformative power of AI in software testing. It covers a wide range of AI-driven techniques, tools, and practices, providing readers with a comprehensive understanding of how AI has revolutionized the field. The book inspires readers to embrace AI and leverage its capabilities to enhance test case generation, bug detection, performance testing, and test management. With AI, readers can achieve higher productivity, improved software quality, and enhanced customer satisfaction. This book catalyzes readers to embark on their AI-infused testing journey, driving innovation and shaping the future of software testing.

Download or read book How Artificial Intelligence Predicts Traveller Behavior written by Johnny Ch Lok and published by . This book was released on 2020-10-11 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether AI can predict climate change to influence travelling behaviours.The flexibility of human travelling behavior is at least the result of one such mechanism, our ability to travel mentally in time and entertain potential future. Understanding of the impacts is holidays, particularly those involving travel. Using focus groups research to explores tourists' awareness of the impacts of travel own climate change, examines the extent to which climate change features in holiday travel decisions and identifies some of the barriers to the adoption of less carbon intensive tourism practices. The findings suggest many tourists don't consider climate change when planning their holidays. The failure of tourists to engage with the climate change to impact of holidays, combined with significant barriers to behavioral change, presents a considerable challenge in the tourism industry.Tourism is a highly energy intensive industry and has only recently attracted attention as an important contributions to climate change through greenhouse gas emissions. It has been estimated that tourism contributes 5% of global carbon dioxide emissions. There have been a number of potential changes proposed for reducing the impact of air travel on climate change. These include technological changes, market based changes and behavioral changes. However, the role that climate change plays in the holiday and travel decisions of global tourists. How the global tourists of the impacts travel has on climate change to establish the extent to which climate change, considerations features in holiday travel decision making processes and to investigate the major barriers to global tourists adopting less carbon intensive travel practices. Whether tourists will aware the impacts that their holidays and travel have on climate changes.When, it comes to understand indvidual traveler's behavioral change, wide range of conceptual theories have been developed, utilizing various social, psychological, subjective and objective variables in order to model travel consumption behavior. These theories of travel behavioral change operate at a number of different levels, including the individual level, the interpersonal level and community level. Whether pro-environmental behavior can be used to predict travel consumption behavior in a climate change. However, the question of what determines pro-environmental behavior in such a complex one that it can not be visualized through one single framework or diagram.Despite the potentially high risk scenario for the tourism industry and the global environment, the tourism and climate change ought have close relationship. Whether what are the important factors and variables which can limit tourism? e.g. money, time, family problem, extreme hot or cold weather change, air ticket price, journey attraction etc. variable factors. Mention of holidays and travel were deliberately avoided in the recruitment process, so as not to create a connection factor to influence traveler's individual mind. However, the dismissal of alternative transportation modes can be conceived as either a structural barrier, in the sense that flying is perhaps the only realistic option to reach long-haul holiday destination, or a perceived behavioral control barriers in that an individual perceives flying as the only option open to whom. The transportation tool factor will be depend to extent on the distance to the destination. This can also be interpreted in a social perspective as an intention with the resources available where much international tourism is structured around flying. To

Download or read book The Ethical Frontier of AI and Data Analysis written by Kumar, Rajeev and published by IGI Global. This book was released on 2024-03-04 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the advancing fields of artificial intelligence (AI) and data science, a pressing ethical dilemma arises. As technology continues its relentless march forward, ethical considerations within these domains become increasingly complex and critical. Bias in algorithms, lack of transparency, data privacy breaches, and the broader societal repercussions of AI applications are demanding urgent attention. This ethical quandary poses a formidable challenge for researchers, academics, and industry professionals alike, threatening the very foundation of responsible technological innovation. Navigating this ethical minefield requires a comprehensive understanding of the multifaceted issues at hand. The Ethical Frontier of AI and Data Analysis is an indispensable resource crafted to address the ethical challenges that define the future of AI and data science. Researchers and academics who find themselves at the forefront of this challenge are grappling with the evolving landscape of AI and data science ethics. Underscoring the need for this book is the current lack of clarity on ethical frameworks, bias mitigation strategies, and the broader societal implications, which hinder progress and leave a void in the discourse. As the demand for responsible AI solutions intensifies, the imperative for this reliable guide that consolidates, explores, and advances the dialogue on ethical considerations grows exponentially.

Download or read book The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations written by Alhamzah Alnoor and published by Emerald Group Publishing. This book was released on 2024-07-09 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume takes the reader through the origins of regenerative tourism and how artificial intelligence can be utilised to develop and maintain green tourism. Chapters examine everything from marketing, data mapping, employment opportunities, cultural issues as well as what the future holds for tourism to give back to countries.

Download or read book Artificial Intelligent Future Development written by Johnny Ch Lok and published by . This book was released on 2019-07-25 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why does travelling market seem to similar to vehicle market which can apply (AI) learning tool to predict travellingconsumer behaviors?Artificial intelligence refers to complex in vehicle market and travelling entertainment market which is very seem to be applied to predict consumer behaviors.(AI) machine learning that posses the same characteristics of human intelligence and that have all our sense, all our reason and think just like human vehicle buyer who prefer vehicle purchase choice or travelling consumer who prefer travelling package or travelling destination and airline choice. Besides, machine learning is the practice of using algorithms to collect and examine data, learn from it, and then make a determination or prediction about something in the world. So, it can be attempted to gather data concerns that travelling consumer past travelling destination choice and air ticket price choice and different travelling package, e.g. high, middle, or low class hotel and foods supply and entertainment places choice in their past travelling journeys.The machine is " trained" using large amounts of data and algorithms that give it the ability to learn how to automatically perform a task with increasing accuracy. Otherwise, deep learning is primarily based on artificial neural networks inspired by our understanding of the biology of human's brains. Thus, (AI) big data can gather all these past traveler consumption behavioral choice data to make reference to analyze whether how many travelers will choose to go to the specific travelling destination in any time by the past traveler number record to different travelling destinations, then it can gather the past air ticket sale price to different destinations and past travelling package design to different destinations in order to analyze whether it is the cheap airline ticket price factor or attractive travelling package factor or attractive travelling entertainment etc. in order to predict which factor is the most potential influential factor to they choose to go to the destination to travel in different time within one year. Then, traveler agent or airline can collect these big data to judge how to design their package to attract travelers to go to anywhere to travel or what the main factor influence most of them to choose to visit the destination to travel.For example, travel agents or airlines can apply "Deep learning" breaks down tasks in ways that enables machines to assist them to predict when travelling consumer choice will be changed and why their travelling choice will change and how their travelling choice will change with increasingly complex tasks. So, such as why (AI) technology can be applied to predict how travelling consumer behavior changes to bring to judge whether anywhere will be many travelling consumers who will prefer to choose travelling hot destinations next year or next month. Then, travel agents and airlines can gather overall past travelling consumer data to analyze and conclude the more accurate prediction of different travelling destinations to the number of traveler. Then, they can choose how much air ticket price is more reasonable to charge to the travelling destination or how to design the travelling package which can bring more attractive to the prediction number of different travelling destination travelers in order to achieve to raise the different travelling destination number next year. Thus, (AI) big data machine learning can help airlines or travel agents to solve how to design any attractive travelling package challenge.