Recent advances in modeling and forecasting Kaiyu : tools for predicting and verifying the effects of urban revitalization policy / Saburo Saito, Kenichi Ishibashi, Kosuke Yamashiro, editors.
Saitō, Saburō, editor.; Ishibashi, Ken'ichi, editor.; Yamashiro, Kosuke, editor.
2023
QA274.7
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Title
Recent advances in modeling and forecasting Kaiyu : tools for predicting and verifying the effects of urban revitalization policy / Saburo Saito, Kenichi Ishibashi, Kosuke Yamashiro, editors.
ISBN
9789819912414 (electronic bk.)
9819912415 (electronic bk.)
9789819912407
9819912407
DOI
https://doi.org/10.1007/978-981-99-1241-4
Published
Singapore : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (xvii, 616 pages) : illustrations.
Item Number
10.1007/978-981-99-1241-4 doi
Call Number
QA274.7
Dewey Decimal Classification
519.2/33
Summary
This book is the first comprehensive presentation of a Kaiyu Markov model with covariates and a multivariate Poisson model with competitive destinations. These two models are core techniques when the authors and colleagues conduct their Kaiyu studies. The two models are usually used to forecast the effects of specific urban redevelopment on both the number of visitors and consumer shop-around or Kaiyu movements. Their Kaiyu studies originated from the constructions of a Kaiyu Markov model and the disaggregated hierarchical decision Huff model almost simultaneously around the early 1980s. This book retrospectively reviews how these models have evolved from the start to the present state, and previews the ongoing efforts to make further extensions of these models. The extension of the Huff model started from the disaggregated hierarchical decision Huff model with shop-arounds. In retrospect, the model formulated the consumers simultaneous choice of destinations as a joint probability. The mechanism to determine this joint probability was a recursive conditional probability system. Now the Huff model has shifted from joint probability to multivariate frequency Poisson with competitive destinations. On the other hand, the Kaiyu Markov model started from a descriptive model. Because it cannot forecast changes in shop-arounds or consumer Kaiyu behaviors, the Kaiyu Markov model with covariates was developed in which entrance and shop-around choice probabilities are explained by the respective two logit models with covariates such as distances and shop-floor areas. The noticeable point is that it can explain consumers probability of quitting their shop-arounds. Thus, the model enables one to evaluate the effects of urban revitalization policy that promotes consumers shop-arounds or Kaiyu behaviors. Furthermore, if the Kaiyu Markov model can estimate the actual numbers of flows of consumers shop-arounds among shopping sites, the corresponding money flows also can be estimated as economic effects. This book discusses from scratch the evolution of all these topics. Thus this book provides the basics of the Kaiyu Markov model, a tutorial for the theory and estimation of the conditional logit model, and a chapter serving as a practical research manual for forecasting changes caused by urban development based on consumers Kaiyu behaviors.
Note
Includes index.
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Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Saitō, Saburō, editor.
Ishibashi, Ken'ichi, editor.
Yamashiro, Kosuke, editor.
Series
New frontiers in regional science: Asian perspectives ; v. 36.
Available in Other Form
Recent advances in modeling and forecasting Kaiyu.
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Chapter 1. A disaggregate hierarchical decision Huff model incorporating consumer Kaiyu choices among shopping sites
Chapter 2. A dynamical Huff model: Computing the competitive equilibrium distribution of shop floor areas over a city center commercial district using the Fixed-Point Algorithm
Chapter 3. Kaiyu Markov model and evaluation of retail spatial structures
Chapter 4. Basics of Kaiyu Markov models: Reproducibility theoremsa validation of infinite Kaiyu representation
Chapter 5. Kaiyu Markov Model with Covariates to Forecast the Change of Consumer Kaiyu Behaviors caused by a Large-Scale City Center Retail Redevelopment
Chapter 6. Estimation of Disaggregate Huff and Kaiyu Markov Model: A Lecture Note on Conditional Logit Model
Chapter 7. A Disaggregate Kaiyu Markov Model to Forecast the Sales of Retail Establishments based on the Consumers Frequency of Visits
Chapter 8. How Would the Kyushu Super-Express Railway Opening Change the Flow of Tourists from the Kansai Region within the Kyushu Wide Area, Japan? : A Micro Behavior Analysis of the Destinations Hub Function
Chapter 9. A Micro Behavior Approach to Estimating and Forecasting the Intervening Opportunity Effects with a Multivariate Poisson Model: A Case for the New Terminal Complex of Kyushu Super-Express Railway, JR Hakata City
Chapter 10. How would the opening of JR Hakata City, a new terminal complex of the Kyushu super-express railway, change the number of visitors, retail sales, and consumers Kaiyu flows in the city center commercial district of Fukuoka City?
Chapter 11. How Many Customers Would be Brought Back from Suburban Shopping Malls to the City Center by Redeveloping the City Center Station Building, JR Oita City, Japan?: A Multivariate Poisson Model with Competitive Destinations
Chapter 12. An Opportunity Cost Approach to Valuation of the River in a City Center Retail Environment: Another Application of Kaiyu Markov Model
Chapter 13. Extraction of Long Sightseeing Kaiyu Routes in the Kyushu Wide Region, Japan
Chapter 14. A Bayesian Network Model of Consumers Kaiyu Behaviors.

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