Recent Advances in Modeling and Forecasting Kaiyu : Tools for Predicting and Verifying the Effects of Urban Revitalization Policy

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 theorems—a 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 Destination’s 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.