Big Data Prediction Traveller Behavior

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Big Data Prediction Traveller Behavior

Author : Johnny Ch Lok
Publisher :
ISBN 13 : 9781710419344
Total Pages : 130 pages
Book Rating : 4.4/5 (193 download)

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Book Synopsis Big Data Prediction Traveller Behavior by : Johnny Ch Lok

Download or read book Big Data Prediction Traveller Behavior written by Johnny Ch Lok and published by . This book was released on 2019-11-22 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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?

Big Data Analytics for the Prediction of Tourist Preferences Worldwide

Author : N. Padmaja
Publisher : Emerald Group Publishing
ISBN 13 : 1835493386
Total Pages : 145 pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis Big Data Analytics for the Prediction of Tourist Preferences Worldwide by : N. Padmaja

Download or read book Big Data Analytics for the Prediction of Tourist Preferences Worldwide written by N. Padmaja and published by Emerald Group Publishing. This book was released on 2024-02-22 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics for the Prediction of Tourist Preferences Worldwide explores the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner.

Artificial Intelligence Big Data Travelling Consumption: Prediction Story

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781799117001
Total Pages : 108 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Artificial Intelligence Big Data Travelling Consumption: Prediction Story by : Johnny Ch Lok

Download or read book Artificial Intelligence Big Data Travelling Consumption: Prediction Story written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-03-08 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future travel consumption behaviorCan (AI) big data gathering tool predict traveller individual habitual behaviour, e.g. renting travel transportation tools ?Can (AI) big data gathering tool can predict past traveller destination and travelling package choice habit and it can be intended to predict of future traveller behavior to people are creatures of habits judgement of future anywhere travelling destination choice next year or next month or next half year destination prediction ? Many of human's everyday goal-directed behaviors are performed in a habitual fashion, the transportation made and route one takes to work, one's choice of breakfast. Habits are formed when using the some behavior frequently and a similar consistency in a similar context for the some purpose whether the individual past travel consumption model will be caused a habit to whom. e.g. choosing whom travel agent to buy air ticket or traveling package; choosing the same or similar countries' destinations to go to travel; choosing the business class or normal (general) class of quality airlines to catch planes. Does habitual rent traveling car tools use not lead to more resistance to change of travel mode? It has been argued that past behavior is the best predictor of future behavior to travel consumption. If individual traveler's past consumption behavior was always reasoned, then frequency of prior travel consumption behavior should only have an indirect link to the individual traveler's behavior. It seems that renting travel car tools to use is a habit example. So, a strong rent traveling car tools useful habit makes traveling mode choice. People with a strong renting of traveling car tools of habit should have low motivation to attend to gather any information about public transportation in their choice of travelling country for individual or family or friends members during their traveling journeys. Even when persuasive communication changes the traveler whose attitudes and intention, in the case of individual traveler or family travelers with a strong renting travel car tools habit. It is difficult to change whose travel behaviors to choose to catch public transportation in whose any trips in any countries. However, understanding of travel behavior and the reasons for choosing one mode of transportation over another. The arguments for rent traveling car tools to use, including convenience, speed, comfort and individual freedom and well known. Increasingly, psychological factors include such as, perceptions, identity, social norms and habit are being used to understand travel mode choice. Whether how many travel consumers will choose to rent traveling car tools during their trips in any countries. It is difficult to estimate the numbers. As the average level of renting travel car tools of dependence or attitudes to certain travel package policies from travel agents. Instead different people must be treated in different ways because who are motivated in different ways and who are motivated by different travel package policies ways from travel agents.In conclusion, the factors influence whose traveler's individual traveller destination choice behavior The factors include either who chooses to rent traveling car tools or who chooses to catch public transportation when who individual goes to travel in alone trip or family trip. It include influence mode choice factors, such as social psychology factor and marketing on segmentation factor both to influence whose transportation choice of behavior in whose trip. So, (AI) big data can be attempted to gather past traveller transportatin tool choice, rent travelling car tools choice or catching public transportation tools choice to predict where destinaton can provide what kind of transportation tool to attract many travellers to choose to go to the place to travel.

Big Data Analytics for the Prediction of Tourist Preferences Worldwide

Author : N. Padmaja
Publisher : Emerald Group Publishing
ISBN 13 : 1835493408
Total Pages : 116 pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis Big Data Analytics for the Prediction of Tourist Preferences Worldwide by : N. Padmaja

Download or read book Big Data Analytics for the Prediction of Tourist Preferences Worldwide written by N. Padmaja and published by Emerald Group Publishing. This book was released on 2024-02-22 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics for the Prediction of Tourist Preferences Worldwide explores the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner.

Artificial Intelligence Big Data Travelling Consumption Prediction

Author : Johnny Ch LOK
Publisher :
ISBN 13 : 9781983185939
Total Pages : 129 pages
Book Rating : 4.1/5 (859 download)

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Book Synopsis Artificial Intelligence Big Data Travelling Consumption Prediction by : Johnny Ch LOK

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: Chapter twoHow can apply (AI) to provide travelling businesses with better-informed decisions ?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.

Is Artificial Intelligence The Best Traveler Behavior Prediction Tool

Author : John Lok
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (873 download)

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Book Synopsis Is Artificial Intelligence The Best Traveler Behavior Prediction Tool by : John Lok

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.

Advances in Computational and Bio-Engineering

Author : S. Jyothi
Publisher : Springer Nature
ISBN 13 : 3030469433
Total Pages : 488 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Advances in Computational and Bio-Engineering by : S. Jyothi

Download or read book Advances in Computational and Bio-Engineering written by S. Jyothi and published by Springer Nature. This book was released on 2020-07-06 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes.

Artificial Intelligence Big Data Gathering Consumer Behavior Prediction

Author : Johnny Ch Lok
Publisher :
ISBN 13 : 9781723986512
Total Pages : 734 pages
Book Rating : 4.9/5 (865 download)

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Book Synopsis Artificial Intelligence Big Data Gathering Consumer Behavior Prediction by : Johnny Ch Lok

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.

Big Data and Innovation in Tourism, Travel, and Hospitality

Author : Marianna Sigala
Publisher : Springer
ISBN 13 : 9811363390
Total Pages : 223 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Big Data and Innovation in Tourism, Travel, and Hospitality by : Marianna Sigala

Download or read book Big Data and Innovation in Tourism, Travel, and Hospitality written by Marianna Sigala and published by Springer. This book was released on 2019-02-26 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together multi-disciplinary research and practical evidence about the role and exploitation of big data in driving and supporting innovation in tourism. It also provides a consolidated framework and roadmap summarising the major issues that both researchers and practitioners have to address for effective big data innovation. The book proposes a process-based model to identify and implement big data innovation strategies in tourism. This process framework consists of four major parts: 1) inputs required for big data innovation; 2) processes required to implement big data innovation; 3) outcomes of big data innovation; and 4) contextual factors influencing big data exploitation and advances in big data exploitation for business innovation.

Management Science in Hospitality and Tourism

Author : Muzaffer Uysal
Publisher : CRC Press
ISBN 13 : 1315356171
Total Pages : 336 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Management Science in Hospitality and Tourism by : Muzaffer Uysal

Download or read book Management Science in Hospitality and Tourism written by Muzaffer Uysal and published by CRC Press. This book was released on 2017-03-03 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Management Science in Hospitality and Tourism is a timely and unique book focusing on management science applications. The first section of the book introduces the concept of management science application in hospitality and tourism and related issues to set the stage for subsequent sections. Section II focuses on management science applications with conceptual pieces, empirical applications, and best practices with examples coming from different parts of the world and settings. The last section ends with a chapter focusing on challenges and future research directions. This book goes beyond revenue management topics and presents a broad range of topics in management science applications as they relate to hospitality and tourism cases. Researchers and students in hospitality and tourism will find this book very useful since it contains chapters on data analytics, e-commerce and technology, revenue and yield management, optimization methods, resource allocation, goal programming, dynamic programming, Markov chain models, trends analysis and detection, measuring potential and attractiveness in tourism development, performance measures and use of indices in hospitality and tourism, and more. There is a heightened interest in these areas of business applications in today’s data-driven business environment, and this book addresses that interest. This book is the only comprehensive text on management science applications in hospitality and tourism. It will help managers and hospitality and tourism students as future managers to develop an in-depth understanding of the importance of data analysis, interpretation, and generating information, and intelligence for decision making. It covers a broad range of applications representing different geographic regions of the world.

Artificial Intelligence Predicts Traveller Behaviors?

Author : Johnny Ch Lok
Publisher :
ISBN 13 : 9781691393756
Total Pages : 188 pages
Book Rating : 4.3/5 (937 download)

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Book Synopsis Artificial Intelligence Predicts Traveller Behaviors? by : Johnny Ch Lok

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 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can apply (AI) big data gathering method predict senior age will be main travelling target? In the past, Germany government had established tourism survey analysis to analyze survey data in order to arrive at reliable conclusions on future trends in travel behavior. To aim to find how demographic change will influence the tourism market and how the industry can adapt to those changes. The travel analysis provided data on tourism consumer behavior, including attitudes, motives and intentions. Since, 1970 year, it is based on a random sample, representative for the population in private households aged 14 years or older. Then, a continuous high scientific standard combined with a national and international users makes the travel analysis a useful tool and reliable source for tourism industry and policy decisions. It aimed to gather statistical data. e.g. on the age structure and on demographic trends, quantitative and qualitative analysis with time series data from the travel analysis. It shows e.g. not only the future volume, quite different from today's seniors, or how who will travel of family holidays will change, e.g. single parents of low, but grandparents of growing significance for tourism. Demographic change is said to be one of the important drivers for new trends in consumer traveling change behavior in most European countries ( e.g. Lind 2001). Because the growing number of senior citizens in the European Union and other industrialized countries, such as the USA and Japan, looks to become one of the major marketing challenges for the tourism industry. United Nations statistics predict that the share of people being 60 age or older will grow dramatically in the coming future, and is expected to rise from 10 percent of the world population in 2000 year to more than 20 percent in 2050 year ( United Nations Population Division, 2001). From its statistic, some data showed that travel propensity increased throughout life until the age of about 50 years of age and was then kept stable until very late in life 75 age. The most important results is that the travel propensity when getting older is not going down between 65 and 75 age of course, the overall development of this variable is influenced by a lot of other factors which are responsible for quite a variation over time. It is now possible to suggest that the general pattern of travel propensity is one of the key indicators for holiday life cycle travel behavior, includes three stages. The growth stage tends to increase from early adult hood until 45 age old or when reaching some 80%. The next stage is stabilization from the ages of around 50 age, until 75 age old, starting with a lower increase. Finally, the decrease stage is a slight decrease occurs once people reach the more advanced age of 75 age to 85 age old ( Lohmann & Danielsson 2001). So, it seems Germany government tourism prediction to future travelers' behavior indicated these findings, such as on how future senior generations will travel, who had used survey data to examine the patterns of travel behavior of a generation getting older and applied the findings to draw conclusions on the future. Also, it predicted that on the future of family trips, family segmentation will be the travel behavior patterns in the future. These findings together with the statistical data on demographic change allowed for a better understanding of the coming tends in family holidays. It's aim developed in consumer behavior related to demographic change and predicted what will happen future of tourism one had to consider other influences and drivers as well, for example, trends on the supply side. e.g. low cost airlines or in travelling consumption behavior in general whether how the past may provide a key to predict travel patterns of senior citizens to the future.

Marketing and Big Data Analytics in Tourism and Events

Author : Hashem, Tareq Nael
Publisher : IGI Global
ISBN 13 :
Total Pages : 313 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Marketing and Big Data Analytics in Tourism and Events by : Hashem, Tareq Nael

Download or read book Marketing and Big Data Analytics in Tourism and Events written by Hashem, Tareq Nael and published by IGI Global. This book was released on 2024-05-06 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the digital age, the tourism industry faces the challenge of effectively marketing destinations amidst a sea of competition and information. Marketing Information Systems (MkIS) and Big Data Analytics (BDA) hold immense potential. Yet, many organizations need help harnessing their power efficiently. Marketing and Big Data Analytics in Tourism and Events offer a comprehensive solution, deep-dive into integrating MkIS and BDA as a strategic approach to revolutionizing tourism marketing. The book aims to bridge the gap between theory and practice by examining the complexities and nuances of MkIS and BDA in promoting tourist destinations. It provides actionable insights and practical strategies for leveraging these technologies effectively. Readers will understand how AI-driven MkIS and BDA can enhance marketing campaigns, improve customer experiences, and drive business growth in the tourism sector.

Spatial Big Data, BIM and advanced GIS for Smart Transformation

Author : Sara Shirowzhan
Publisher : MDPI
ISBN 13 : 3039360302
Total Pages : 166 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Spatial Big Data, BIM and advanced GIS for Smart Transformation by : Sara Shirowzhan

Download or read book Spatial Big Data, BIM and advanced GIS for Smart Transformation written by Sara Shirowzhan and published by MDPI. This book was released on 2020-12-02 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a range of topics including selective technologies and algorithms that can potentially contribute to developing an intelligent environment and smarter cities. While the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers, before the project is approved. This book also presents an agenda for future investigations to address the need for advanced tools such as mobile scanners, Geospatial Artificial Intelligence, Unmanned Aerial Vehicles, Geospatial Augmented Reality apps, Light Detection, and Ranging in smart cities. Some of selected specific tools presented in this book are as a simulator for improving the smart parking practices by modelling drivers with activity plans, a bike optimization algorithm to increase the efficiency of bike stations, an agent-based model simulation of human mobility with the use of mobile phone datasets. In addition, this book describes the use of numerical methods to match the network demand and supply of bicycles, investigate the distribution of railways using different indicators, presents a novel algorithm of direction-aware continuous moving K-nearest neighbor queries in road networks, and presents an efficient staged evacuation planning algorithm for multi-exit buildings.

Analytics in Smart Tourism Design

Author : Zheng Xiang
Publisher : Springer
ISBN 13 : 3319442635
Total Pages : 307 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Analytics in Smart Tourism Design by : Zheng Xiang

Download or read book Analytics in Smart Tourism Design written by Zheng Xiang and published by Springer. This book was released on 2016-10-12 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting edge research on the development of analytics in travel and tourism. It introduces new conceptual frameworks and measurement tools, as well as applications and case studies for destination marketing and management. It is divided into five parts: Part one on travel demand analytics focuses on conceptualizing and implementing travel demand modeling using big data. It illustrates new ways to identify, generate and utilize large quantities of data in tourism demand forecasting and modeling. Part two focuses on analytics in travel and everyday life, presenting recent developments in wearable computers and physiological measurement devices, and the implications for our understanding of on-the-go travelers and tourism design. Part three embraces tourism geoanalytics, correlating social media and geo-based data with tourism statistics. Part four discusses web-based and social media analytics and presents the latest developments in utilizing user-generated content on the Internet to understand a number of managerial problems. The final part is a collection of case studies using web-based and social media analytics, with examples from the Sochi Olympics on Twitter, leveraging online reviews in the hotel industry, and evaluating destination communications and market intelligence with online hotel reviews. The chapters in this section collectively describe a range of different approaches to understanding market dynamics in tourism and hospitality.

Big Data and Mobility as a Service

Author : Haoran Zhang
Publisher : Elsevier
ISBN 13 : 0323901700
Total Pages : 308 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Big Data and Mobility as a Service by : Haoran Zhang

Download or read book Big Data and Mobility as a Service written by Haoran Zhang and published by Elsevier. This book was released on 2021-10-01 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data and Mobility as a Service explores MaaS platforms that can be adaptable to the ever-evolving mobility environment. It looks at multi-mode urban crowd data to assess urban mobility characteristics, their shared transportation potential, and their performance conditions and constraints. The book analyzes the roles of multimodality, travel behavior, urban mobility dynamics and participation. Combined with insights on using big data to analyze market and policy decisions, this book is an essential tool for urban transportation management researchers and practitioners. Summarizes current fundamental MaaS technologies Shows how to utilize anonymous big data for transportation analysis and problem-solving Illustrates, with data-enabled shared transportation service examples from different countries, the similarities and differences within a global urban mobility framework

Data-Driven Solutions to Transportation Problems

Author : Yinhai Wang
Publisher : Elsevier
ISBN 13 : 0128170271
Total Pages : 299 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Data-Driven Solutions to Transportation Problems by : Yinhai Wang

Download or read book Data-Driven Solutions to Transportation Problems written by Yinhai Wang and published by Elsevier. This book was released on 2018-12-04 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. Synthesizes the newest developments in data-driven transportation science Includes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed Useful for both theoretical and technically-oriented researchers

Artificial Intelligence Predicts Marketing Behavior

Author : Johnny Ch Lok
Publisher :
ISBN 13 :
Total Pages : 182 pages
Book Rating : 4.5/5 (851 download)

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Book Synopsis Artificial Intelligence Predicts Marketing Behavior by : Johnny Ch Lok

Download or read book Artificial Intelligence Predicts Marketing Behavior written by Johnny Ch Lok and published by . This book was released on 2020-12-22 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can apply (AI) to provide travelling businesses with better-informed decisions 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.Predictive search will improve the quality of online travelling search results, and provide new insights into travelling consumers' travelling destination and package behavior and the moments which matter to them. Search will give recommendation into tailored how travelling consumer individual travelling destination choice in travelling decision making process. Several of the largest online platforms already use (AI) travelling machine learning to improve predictive travelling consumer behavioral search results. For example, Google's rank brain technology adds research by understanding the context in which the travelling consumer has entered it. Over time, rank brain will learn further from user behaviors Amazon's DSSTNE ( pronouned destiny) learns from shoppers' purchasing habits and consumption behavior to offer better product recommend actions, which Amazon can offer before a consumer has entered anything into the search bar. Such as (AI) big data can gather past online travelers' e-ticket purchase transactions to conclude that online traveler's travelling choice habits and online traveler consumption behavior to offer better travelling destinations and travelling package opinions to travel agents or airlines. However, this technology is not independent of human input. For example, Google engineers will periodically retain the rank brain system to improve the models it uses.