On the Suitability of Econometric Demand Models in Design for Market Systems

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
Bart D. Frischknecht ◽  
Katie Whitefoot ◽  
Panos Y. Papalambros
Keyword(s):  
Predictive Validity ◽  
Revealed Preference ◽  
Demand Model ◽  
Design Studies ◽  
Automotive Market ◽  
Systems Research ◽  
Model Form ◽  
Design Variables ◽  
Demand Models ◽  
Design For Market Systems

A goal of design for market systems research is to predict demand for differentiated products so that counterfactual experiments can be performed based on design changes. We review conventional methods and propose an additional method to evaluate the suitability of econometric demand models estimated from revealed preference data for use in product design studies. We evaluate one demand model form from literature and two newly constructed forms for new vehicle demand along existing metrics of fit and predictive validity as well as a newly developed metric of proportional substitution sensitivity. We show that a model that includes horizontally differentiated preferences for size performs better under metrics of fit and predictive validity but that no model relaxes the IIA property satisfactorily to avoid exploitation by design optimization. We conduct design studies separately, applying each demand model form assuming the automotive market is in Bertrand–Nash price equilibrium. Results illustrate that the influence of the demand model form on the optimum in terms of design variables and expected firm profit is significant.

Methods for Evaluating Suitability of Econometric Demand Models in Design for Market Systems

2009 ◽  
Author(s):  
Bart Frischknecht ◽  
Katie Whitefoot ◽  
Panos Papalambros
Keyword(s):  
Product Design ◽  
Consumer Demand ◽  
Ideal Point ◽  
Future Research ◽  
Demand Model ◽  
Automotive Market ◽  
Systems Research ◽  
Demand Models ◽  
Functional Forms ◽  
Design For Market Systems

This paper articulates some of the challenges for what has been an implicit goal of design for market systems research: To predict demand for differentiated products so that counterfactual experiments can be performed based on changes to the product design (i.e., attributes). We present a set of methods for examining econometric models of consumer demand for their suitability in product design studies. We use these methods to test the hypothesis that automotive demand models that allow for nonlinear horizontal differentiation perform better than the conventional functional forms, which emphasize vertical differentiation. We estimate these two forms of consumer demand in the new vehicle automotive market, and find that using an ideal-point model of size preference rather than a monotonic model has model fit but different attribute substitution patterns. The generality of the evaluation methods and the range of demand model issues to be explored in future research are highlighted.

Regional Bicycle Network Evaluation and Strategic Planning: A Quantitative Methodological Approach Despite Limited Data Sources for Cycling

2021 ◽  
pp. 036119812110288
Author(s):  
Alex van Dulmen ◽  
Martin Fellendorf
Keyword(s):  
Travel Demand ◽  
Choice Model ◽  
Methodological Approach ◽  
Data Availability ◽  
Data Sources ◽  
Test Case ◽  
Demand Model ◽  
Limited Data ◽  
Demand Models ◽  
Bicycle Infrastructure

In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.

scholarly journals ANALISIS POLA KONSUMSI DAN MODEL PERMINTAAN IKAN MENURUT KARAKTERISTIK RUMAH TANGGA DI INDONESIA

2018 ◽  
Vol 13 (1) ◽  
pp. 73 ◽  
Author(s):  
Freshty Yulia Arthatiani ◽  
Nunung Kusnadi ◽  
Harianto Harianto
Keyword(s):  
Fish Consumption ◽  
Income Elasticity ◽  
Fish Distribution ◽  
Consumption Patterns ◽  
Demand System ◽  
Coefficient Of Determination ◽  
Almost Ideal Demand System ◽  
Demand Model ◽  
Demand Models ◽  
The Government

ABSTRAKTujuan penelitian ini adalah untuk mendeskripsikan pola konsumsi ikan di Indonesia dan mengidentifikasi faktor-faktor yang mempengaruhi permintaan ikan menurut karakteristik rumah tangga di Indonesia. Penelitian ini menggunakan data SUSENAS yang dilaporkan oleh Badan Pusat Statistik pada bulan Maret 2016. Pola konsumsi ikan dianalisis menggunakan statistik deskriptif dan model permintaan ikan dianalisis dengan menggunakan pendekatan model Linnear Approximation Almost Ideal Demand System (LA/AIDS). Hasil riset menunjukkan bahwa pola konsumsi rumah tangga di Indonesia dikelompokkan menjadi konsumsi ikan air laut segar sebesar 22.10 kg/kapita/tahun, ikan air tawar/payau segar sebesar 16.75 kg/kapita/tahun, udang segar sebesar 9.58 kg/kapita/tahun dan ikan olahan sebesar 4.22 kg/kapita/tahun. Dugaan model permintaan memberikan hasil cukup baik dengan 82.15% dari semua peubah berpengaruh signifikan terhadap fungsi permintaan kelompok ikan dan koefisien determinasi sebesar 27.06%. Nilai elastisitas pendapatan mengindikasikan bahwa seluruh kelompok ikan merupakan barang normal dan ikan olahan cenderung inelastis, sedangkan dari nilai elastisitas harga menunjukkan tanda negatif yang sesuai dengan teori ekonomi. Nilai elastisitas silang antar kelompok ikan menunjukkan hubungan yang bervariasi antar kelompok. Implikasi kebijakan yang dapat disarankan untuk meningkatkan konsumsi ikan segar adalah dengan peningkatan ketersediaan ikan melalui kebijakan peningkatan produksi dan peningkatan efektifitas distribusi ikan. Kebijakan promosi dan edukasi masih diperlukan untuk meningkatkan konsumsi ikan olahan karena sifatnya yang inelastis  terhadap perubahan harga dan pendapatan.Title: Analysis of Fish Consumption Patterns and Fish Demand Model Based on Household’s Characteristics in IndonesiaABSTRACTThis study aims to describe the pattern of fish consumption in Indonesia and to identify factors affecting household’s fish demand in Indonesia as well as estimating the elasticities of income and price. The data analyzed were mainly obtained from the SUSENAS Database-a nation social economy survey  conduct by the Indonesian Bureau of Statistic (BPS- during march 2016. Fish consumption patterns were analyzed using descriptive statistical analysis, while fish demand models were analyzed by Linnear Approximation Almost Ideal Demand System (LA/AIDS). Research shows that household consumption patterns in Indonesia are grouped into consumption of marine fish at 22.10 kg / capita / year, freshwater/brackish fish at 16.75 kg / capita / year, fresh shrimp at 9.58 kg / capita / year and processed fish amounted to 4.22 kg / capita / year. The estimation of the demand model gives quite good results with82,15% of all variables have a significant effect on the demand function of fish groups and the coefficient of determination is 27.06%. The value of income elasticity showed that all fish groups are normal goods and were negatively related to prices. The cross elasticities showed variation relationship between fish groups. With such result, in order for the government to be able to push the fish consumption level furtherwould require an increasing fish availbility through policies to increase production and effectiveness of fish distribution for fresh fish. Meanwhile education and promotion policies are necessary to increase consumption of processed fish because of their inelastic demand for changes in prices and income.

scholarly journals Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows

2019 ◽  
Author(s):  
Crispin H. V. Cooper ◽  
Ian Harvey ◽  
Scott Orford ◽  
Alain J. F. Chiaradia
Keyword(s):  
Network Analysis ◽  
Shortest Path ◽  
City Centre ◽  
Demand Model ◽  
Railway Stations ◽  
Spatial Design ◽  
Demand Models ◽  
Directional Change ◽  
Spatial Network Analysis ◽  
Changes Over Time

AbstractPredicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for environmental, social and economic sustainability. We present longitudinal evaluation of a model of the effect of urban environmental layout change in a city centre (Cardiff 2007–2010), on pedestrian flows. Our model can be classed as regression based direct demand using Multiple Hybrid Spatial Design Network Analysis (MH-sDNA) assignment, which bridges the gap between direct demand models, facility-based activity estimation and spatial network analysis (which can also be conceived as a pedestrian route assignment based direct demand model). Multiple theoretical flows are computed based on retail floor area: everywhere to shops, shop to shop, railway stations to shops and parking to shops. Route assignment, in contrast to the usual approach of shortest path only, is based on a hybrid of shortest path and least directional change (most direct) with a degree of randomization. The calibration process determines a suitable balance of theoretical flows to best match observed pedestrian flows, using generalized cross-validation to prevent overfit. Validation shows that the model successfully predicts the effect of layout change on flows of up to approx. 8000 pedestrians per hour based on counts spanning a 1 km2 city centre, calibrated on 2007 data and validated to 2010 and 2011. This is the first time, to our knowledge, that a pedestrian flow model with assignment has been evaluated for its ability to forecast the effect of urban layout changes over time.

scholarly journals Addressing Household Income Distribution in Air Travel Demand Models: Case Study of the Baltimore–Washington Region

2019 ◽  
Vol 2673 (1) ◽  
pp. 491-502 ◽  
Author(s):  
Geoffrey D. Gosling ◽  
David Ballard
Keyword(s):  
Income Distribution ◽  
Household Income ◽  
Travel Demand ◽  
Metropolitan Region ◽  
Annual Data ◽  
Demand Model ◽  
Passenger Demand ◽  
Average Household Income ◽  
Demand Models ◽  
The Future

The paper describes the development of an air passenger demand model for the Baltimore–Washington metropolitan region that was undertaken as part of a recently concluded ACRP project that explored the use of disaggregated socioeconomic data in air passenger demand studies. The model incorporated a variable reflecting the change in household income distribution, together with more traditional aggregate causal variables: population, employment, average household income, and airfares as measured by the average U.S. airline yield, as well as several year-specific dummy variables. The model was estimated on annual data for the period 1990 to 2010 and obtained statistically significant estimated coefficients for all variables, including both the average household income and the household income distribution variable. Including household income distribution in the model resulted in a significant change to the estimated coefficient for average household income, giving a much higher estimated elasticity of demand with respect to average household income compared with a model that does not consider changes in household income distribution. This has important implications for the use of such demand models for forecasting, as household income distribution and average household income may change in the future in quite different ways, which would affect the future levels of air passenger travel projected by the models.

Transferability of aggregate intercity total demand models

1995 ◽  
Vol 22 (2) ◽  
pp. 283-291
Author(s):  
Amal S. Kumarage ◽  
S. C. Wirasinghe
Keyword(s):  
Sri Lanka ◽  
Public Transportation ◽  
Travel Demand ◽  
Contextual Factors ◽  
Demand Model ◽  
Aggregate Model ◽  
Demand Models ◽  
Intercity Travel ◽  
Model Transfer ◽  
Contextual Characteristics

Over the last 15 years, extensive research has been done on the transferability of travel demand models. However, much of this work has been concentrated towards investigating the transferability of disaggregate mode choice models. The transferability of an aggregate total demand model for intercity travel is examined. Model transfer is possible only when a number of preconditions for transferability are satisfied. One of the principal obstacles to the successful transfer of intercity demand models is the inability to overcome the contextual differences between calibration and application. Here, the components of the intercity total demand model are separated into exogenous and intrinsic (contextual) factors. The latter is thereafter classified as being either transferable or nontransferable. It is shown that transferable attributes can accompany a model during transfer. Nontransferable attributes, on the other hand, will free the model of city or city-pair specific contextual characteristics which should not be transferred to other city pairs. The issues involved in transferring an aggregate model are also investigated. Aggregate data on interdistrict travel by public transportation in Sri Lanka have been used to successfully calibrate a total demand model with a number of transferable and nontransferable attributes that represent both temporal and spatial contextual factors. It is shown that the forecasting ability of this model is far superior to a counterpart model without the intrinsic variables. Key words: travel demand, aggregate, forecasting, transferability, intercity, Sri Lanka.

scholarly journals Hexagonal Zones in Transport Demand Models

2020 ◽  
Author(s):  
Jacek Chmielewski ◽  
Jan Kempa
Keyword(s):  
Objective Assessment ◽  
Transport Infrastructure ◽  
Transport Systems ◽  
Main Role ◽  
Demand Model ◽  
Hexagonal System ◽  
Demand Models ◽  
Transport Analysis ◽  
High Level ◽  
Investment Intentions

Planning the development of transport systems, as well as assessing the effects of investment activities in the field of spatial development requires the use of appropriate IT tools enabling an objective assessment of investment intentions. In the field of transport analysis, one such tool is a transport demand model. Reproduction of transport-related processes is the main role of such transport demand model. This applies to both the transport of people and goods, and includes both residential travel and visitors travelling to and within the study area. The description of the process of creation and implementation of transport demands is usually based on the assumptions in the field of places of generation and absorption of travel - i.e. sources and destinations of travel. The generalization of the mathematical description of this phenomenon introduced the concept of transport zones, which are separated homogeneous areas of the study area, as sources and destinations of trips. Practice in the construction and use of transport models indicates that the problem of  defining transport zones requires further investigation. Increasingly extensive transport infrastructure data collected in open databases (such as OpenStreets) are encouraging a change in the approach to the problems of constructing transport zones. The current solutions are characterized by a high level of generalization of sources and destinations rather than detailed transport analysis. This article presents the author’s method of dividing the study areas into transport zones based on a uniform hexagonal system, explaining the basic assumptions and evaluating the pros and cons of this proposed system. Keywords: Transport, Demand models, Algorithms

The Effect of Site Congestion on Valuing Freshwater Fishing for Urban Residents

2019 ◽  
Vol 06 (04) ◽  
pp. 1950008 ◽  
Author(s):  
Richard T. Melstrom ◽  
Taylor Welniak
Keyword(s):  
Instrumental Variables ◽  
Choice Model ◽  
Revealed Preference ◽  
Recreation Demand ◽  
Oklahoma City ◽  
Weight Of Evidence ◽  
Urban Residents ◽  
Demand Models ◽  
A Site ◽  
Congestion Effects

This paper provides evidence that welfare estimates from recreation demand models can be severely biased if the model omits congestion effects. Congestion effects arise when crowding at popular sites lowers site values. Measuring the effect of congestion is complicated by a well-known endogeneity problem in revealed preference data. We study congestion effects in a sample of licensed anglers in Oklahoma City. We develop a site choice model of freshwater fishing, and correct for endogenous congestion using an instrumental variables strategy. Our results add to the growing weight of evidence that ignoring congestion leads to estimates that understate the value of individual sites and site amenities.

Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?

2019 ◽  
Vol 26 (3) ◽  
pp. 461-474
Author(s):  
Tzu-Ming Liu
Keyword(s):  
Word Of Mouth ◽  
Habit Formation ◽  
Critical Role ◽  
Tourism Demand ◽  
Demand Model ◽  
Dynamic Panel Model ◽  
Empirical Results ◽  
Demand Models ◽  
Lagged Dependent Variable ◽  
Time Lagged

The effects of habit formation/persistence (HFP) and word of mouth (WOM) each play a critical role in influencing tourists’ decisions regarding whether to visit tourism destinations and therefore tourism policies and tourism management resource allocations. Nevertheless, in previous tourism demand studies, the two effects have been represented by the same time-lagged dependent variable, which makes the variable have an ambiguous meaning and biases the empirical results. The purpose of this study is to solve the ambiguity of a lagged dependent variable in tourism demand. We used economic theories regarding internal habits and external habits to clarify the meanings of HFP and WOM and revised the tourism demand model into a spatial dynamic panel model (SDPM). The empirical results suggested that an SDPM is a more accurate model for modeling tourism demand. The effects of variables in an SDPM are more consistent with theoretical expectations.

scholarly journals Development of Parking Demand Model for Private Hospital in Developing Country (Case Study of Denpasar City, Indonesia)

2017 ◽  
Vol 10 (5) ◽  
pp. 52 ◽  
Author(s):  
Putu Alit Suthanaya
Keyword(s):  
Motor Vehicle ◽  
Population Increase ◽  
Annual Growth Rate ◽  
Demand Model ◽  
Private Hospitals ◽  
The Road ◽  
Motor Cycle ◽  
Demand Models ◽  
Class 1 ◽  
Parking Demand

Denpasar City is the capital of Bali Province and the center of activities in Bali, Indonesia. The population continue to increase with the annual growth rate of 2%. As the number of population increase, the number of facilities including health facility also continue to increase. The traffic volume is predominated by private motor vehicle (where 80% is motor cycle) as lack of public transport service available. The trip attraction to hospital increases, however parking spaces provided are very limited. As the results the visitors usually park their vehicles on street around the hospital. This has caused a significant reduction in the road capacity. Therefore, it is required to accurately estimate parking demand both for car and motor cycle. The objectives of this study are to analyze parking characteristics and to develop parking demand models for car and motor cycle. Five private hospitals were considered in this study. Parking data were collected and used to model parking demand based on simple and multiple liner regression models. The results of this study indicated that the parking index for all private hospitals has exceeded 1. The number of beds for room class 1 was found to be the main predictor for parking demand for car. However, the number of hospital’s employees was found to be the best predictor for parking demand for motor cycle. 

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