Role of Spatial Demand on Outlet Location and Pricinig (Record no. 30462)
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000 -LEADER | |
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fixed length control field | 01962pab a2200205 454500 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 140923b0 xxu||||| |||| 00| 0 eng d |
040 ## - CATALOGING SOURCE | |
Transcribing agency | Welingkar Institute of Management Development & Research, Mumbai |
Original cataloging agency | Welingkar Institute of Management Development & Research, Mumbai |
041 ## - LANGUAGE CODE | |
Language code of text/sound track or separate title | ENG |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | |
Item number | Dua |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Duan Jason A |
245 ## - TITLE STATEMENT | |
Title | Role of Spatial Demand on Outlet Location and Pricinig |
250 ## - EDITION STATEMENT | |
Edition statement | 2 |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Place of publication, distribution, etc. | |
Name of publisher, distributor, etc. | April 2009 |
Date of publication, distribution, etc. | 0 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 260-278 Pp. |
490 ## - SERIES STATEMENT | |
Volume/sequential designation | XLVI |
520 ## - SUMMARY, ETC. | |
Summary, etc. | In this article, the authors consider the problem of outlet pricing and location in the context of unobserved spatial demand. The analysis constitutes a scenario in which capacity-constrained firms set prices conditional on their location, demand, and costs. This enables firms to develop maps of latent demand patterns across the market in which they compete. The analysis further suggests locations for additional outlets and the resultant equilibrium effect on profits and prices. Using Bayesian spatial statistics, the authors apply their model to seven years of data on apartment location and prices in Roanoke, Va. They find that spatial covariation in demand is material in outlet choice; the 95% spatial decay in demand extends 3.6 miles in a region that measures slightly more than 9.5 miles. They also find that capacity constraints can cost complexes upward of $100 per apartment. As they predict, price elasticities and costs are biased downward when spatial covariance in demand is ignored. Costs are biased upward when capacity constraints are ignored. Using the analysis to suggest locations for entry, the authors find that properly accounting for spatial effects and capacity constraints leads to an entry recommendation that improves profitability by 66% over a model that ignores these effects. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Outlet Location, Pricinig |
856 ## - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="http://192.168.6.13/libsuite/mm_files/Articles/AR10639.pdf">http://192.168.6.13/libsuite/mm_files/Articles/AR10639.pdf</a> |
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) | |
a | 31924 |
Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Date acquired | Cost, normal purchase price | Total Checkouts | Full call number | Barcode | Date last seen | Cost, replacement price | Price effective from | Koha item type |
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Main Library | Main Library | 18/05/2009 | 0.00 | Dua | AR10639 | 23/09/2014 | 0.00 | 23/09/2014 | Articles |