Recent Advances in Modeling and Forecasting Kaiyu

Saburo Saito, Fukuoka UniversityKenichi Ishibashi, Nagoya Sangyo UniversityKosuke Yamashiro, Fukuoka University

• 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.