Finding Competitive Price Yu Peng(hong Kong University of Science and Technology Raymond Chi-Wing Wong(Hong Kong University of Science and Technology Presented by Ted Prepared by Raymond Chi-Wing Wong
1 Finding Competitive Price Yu Peng (Hong Kong University of Science and Technology) Raymond Chi-Wing Wong (Hong Kong University of Science and Technology) Presented by Ted Prepared by Raymond Chi-Wing Wong
Outline 1 Introduction 2. Problem definition 3. Algorithm Spatial approach 4. Discussion 5. Empirical Study 6. Related work 7. Conclusion
Outline 1. Introduction 2. Problem Definition 3. Algorithm ◼ Spatial Approach 4. Discussion 5. Empirical Study 6. Related Work 7. Conclusion 2
1 Introduction Consider that a customer looks for a hotel near to sea World hotels H= thi, h2, h3, h4 A={a1} attraction-site(e. g. Sea World) Spatial layout Price Decision-Making table Hotel Distance-to- Price() Hotel Prices) SeaWorld (km) 100 3.0 250 1.0 250 h3200h3 4.0 200 220 2.5 220 According to the spatial layout and the price information we can generate a decision table
1. Introduction Hotel Price ($) h1 100 h2 250 h3 200 h4 220 3 H = {h1 , h2 , h3 , h4} A = {a1} hotels attraction-site (e.g., Sea World) h4 a1 h2 h3 h1 Spatial Layout Price Hotel Distance-toSeaWorld (km) Price ($) h1 3.0 100 h2 1.0 250 h3 4.0 200 h4 2.5 220 Decision-Making Table According to the spatial layout and the price information, we can generate a decision table. Consider that a customer looks for a hotel near to Sea World 3
1 Introduction Consider that a customer looks for a hotel near to sea World hotels H= thi, h2, h3, h4 A={a1} attraction-site(e. g. Sea World) Spatial Layout Price Decision-Making table Hotel Distance-to- Price() Hotel Price (S h SeaWorld (km) 100 3.0 100 250 1.0 250 a 200 4.0 200 220 2.5 220 h, dominates h3(since h, is better than h in terms of distance-to SeaWorld and Price)
1. Introduction Hotel Price ($) h1 100 h2 250 h3 200 h4 220 4 H = {h1 , h2 , h3 , h4} A = {a1} hotels attraction-site (e.g., Sea World) h4 a1 h2 h3 h1 Spatial Layout Price Hotel Distance-toSeaWorld (km) Price ($) h1 3.0 100 h2 1.0 250 h3 4.0 200 h4 2.5 220 Decision-Making Table Consider that a customer looks for a hotel near to Sea World h1 dominates h3 (since h1 is better than h3 in terms of Distance-toSeaWorld and Price)
1 Introduction Consider that a customer looks for a hotel near to sea World hotels H= thi, h2, h3, h4 A={a1} attraction-site(e. g. Sea World) Spatial Layout Price Decision-Making table Hotel Distance-to- Price() Hotel Price (S h SeaWorld (km) 100 3.0 100 50 1.0 250》 a 200 h3 4.0 200 220 2.5 220 h, does not dominate h3(since h has a shorter distance to-SeaWorld than h3 but h 2 has a higher price than h3) 5
1. Introduction Hotel Price ($) h1 100 h2 250 h3 200 h4 220 5 H = {h1 , h2 , h3 , h4} A = {a1} hotels attraction-site (e.g., Sea World) h4 a1 h2 h3 h1 Spatial Layout Price Hotel Distance-toSeaWorld (km) Price ($) h1 3.0 100 h2 1.0 250 h3 4.0 200 h4 2.5 220 Decision-Making Table Consider that a customer looks for a hotel near to Sea World h2 does not dominate h3 (since h2 has a shorter Distanceto-SeaWorld than h3 but h2 has a higher price than h3 .)