Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A quality-based approach to estimating quantitative elasticities for differentiated products: an application to retail milk demand
Date
2015-09-01
Author
Gülseven, Osman
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
224
views
0
downloads
Cite This
This article introduces the Hedonic Metric (HM) approach as an original method to model the demand for differentiated products using qualitative attributes. Our approach is based on a two-stage estimation procedure that utilizes qualitative characteristics of products. First, we create an n-dimensional hedonic space based on the qualitative information available to consumers. Next, we allocate the differentiated products into this space and estimate the quantitative demand elasticities for these products using qualitative factor distances. What distinguishes our model from traditional demand estimation models is the way we link elasticities with products' qualitative attributes. Moreover, in traditional demand systems, the number of estimated parameters increases exponentially with the number of variables included in the model. Our model significantly reduces the number of parameters to be estimated, thereby making it possible to estimate large number of differentiated products in a single demand system.
Subject Keywords
Hedonic Metrics
,
Qualitative Analysis
,
Distance Metrics
,
Rotterdam Model
,
Differentiated Products
,
Milk Demand
URI
https://hdl.handle.net/11511/36378
Journal
QUALITY & QUANTITY
DOI
https://doi.org/10.1007/s11135-014-0094-8
Collections
Department of Economics, Article
Suggestions
OpenMETU
Core
Integrating multi-period quantity flexibility contracts with a capacitated production and inventory planning
Kayhan, Mehmet; Kayalıgil, Sinan; Department of Industrial Engineering (2008)
This research introduces a general approach for integrating a probabilistic model of the changes in the committed orders with an analytical model of production and inventory planning under multi-period Quantity Flexibility contracts. We study a decentralized structure where a capacitated manufacturer, capable of subcontracting, serves multiple contract buyers who actually perform forecasts on a rolling horizon basis. We model the evolution of buyers' commitments as a multiplicative forecast evolution proces...
A new approach to neural trip distribution models: NETDIM
Tapkin, Serkan; Akyilmaz, Ozdemir (Informa UK Limited, 2009-01-01)
This paper develops and presents a new neural network approach to model trip distribution, which is one of the important phases of conventional four-step travel demand modelling. The trip distribution problem has been investigated using back-propagation artificial neural networks in a number of studies and it was concluded that back-propagation artificial neural networks underperform when compared to traditional models. Such underperformance is due to the thresholding of the linearly combined inputs by util...
An Interactive approach to two-response product and process design optimization with statistical inferences
Özateş, Melis; Köksal, Gülser; Köksalan, Murat; Department of Industrial Engineering (2015)
In this study, an interactive approach has been developed for two-response product and process design optimization problems treating the single response problems as a special case. This approach considers preferences of the decision maker explicitly and the correlation between the responses. It uses a predefined set of objectives that are commonly encountered in the literature and industrial applications. However, instead of presenting all objective values at each iteration, a set of performance measures ar...
An Objective Methodology For Merging Satellite And Model Based Soil Moisture Products
Yılmaz, Mustafa Tuğrul; Anderson, Martha; Hain, Chris (2012-04-19)
An objective methodology that does not require any user-defined parameter assumptions is introduced to obtain an improved soil moisture product along with associated uncertainty estimates. This new product is obtained by merging model-, thermal infrared remote sensing-, and microwave remote sensing-based soil moisture estimates in a least squares framework where uncertainty estimates for each product are obtained using triple collocation. The merged anomaly product is validated against in situ based soil mo...
A NEW HEURISTIC APPROACH FOR THE MULTIITEM DYNAMIC LOT-SIZING PROBLEM
KIRCA, O; KOKTEN, M (Elsevier BV, 1994-06-09)
In this paper a framework for a new heuristic approach for solving the single level multi-item capacitated dynamic lot sizing problem is presented. The approach uses an iterative item-by-item strategy for generating solutions to the problem. In each iteration a set of items are scheduled over the planning horizon and the procedure terminates when all items are scheduled. An algorithm that implements this approach is developed in which in each iteration a single item is selected and scheduled over the planni...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. Gülseven, “A quality-based approach to estimating quantitative elasticities for differentiated products: an application to retail milk demand,”
QUALITY & QUANTITY
, pp. 2077–2096, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36378.