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

Author(s):  
Bart Frischknecht ◽  
Katie Whitefoot ◽  
Panos Papalambros

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.

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
Bart D. Frischknecht ◽  
Katie Whitefoot ◽  
Panos Y. Papalambros

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.


2018 ◽  
Vol 58 (4) ◽  
pp. 730
Author(s):  
R. J. Sadler ◽  
D. B. Purser ◽  
S. K. Baker

Daily food intake is the single most important factor affecting milk production by dairy cows. However, an animal’s choice of food depends not only on the nutritional characteristics of the food in question, but also on the nutritional characteristics of other available foods. Any prediction of intake should be based on the nutritional characteristics of all foods on offer. However, when the initial food-preference experiment possesses a control-specific design (i.e. experiments that include only a limited number of control foods for comparison) it is apparent that the prediction of future food choices must include the same controls as the initial experiment underpinning the prediction model. This requirement is clearly impractical. By drawing an analogy between animal food preference and economic choice, the total and relative dry matter intake of two oaten hays was modelled on their nutritive characteristics by estimating a consumer-demand model (here a generalised additive model representation of a direct bundle good model) from experimental data offering hays to lactating cows (adj-R2 > 80%; where adj-R2 is the value adjusted for the number of predictor terms in the model). To negate the problem of control-specificity, a simplex interpolation was developed to construct and test predictions of hay intake for a second food-preference experiment (adj-R2 > 53%; correlation between predictions and actual intakes = 76%). To improve prediction accuracy and avoid control-specificity, it is recommended that future preference experiments be designed to exclude control-specificity by mimicking fractional factorial designs, supported by a two-stage approach to select a cost-effective number of comparisons. Our approach to predicting food intake may be extended to a choice between more than two foods, and to combinations of foods other than oaten hays.


2019 ◽  
Vol 11 (4) ◽  
pp. 1163 ◽  
Author(s):  
Melissa Bedinger ◽  
Lindsay Beevers ◽  
Lila Collet ◽  
Annie Visser

Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.


Author(s):  
Alex van Dulmen ◽  
Martin Fellendorf

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.


2021 ◽  
Author(s):  
Emelia Delaney ◽  
Wei Liu

Abstract The aim of sustainability is to fulfil the needs of current generations without compromising the needs of future generations. It is also a rising area of concern within industry, it is therefore important that graduate designers are equipped with the skills to accommodate sustainability issues as well as demands from industry. Additionally, the product design stage during New Product Development has been identified to have the greatest impact on the sustainability of the entire product, however how educated designers are on the topic of sustainability is unclear. An initial literature review has been conducted to investigate design education on sustainability as well as teaching styles. Following this the study identifies and reviews UK Product Design courses to establish the current status of sustainability integration in higher education. The exploration into university prospectuses has found that around half of UK universities implement sustainability in some way, however there are limited courses which dedicate specific modules to sustainability. Additionally, links with industry and accreditation organizations between UK product design courses have been confirmed, but there is no definite information to suggest that the universities use this to aid in the implementation sustainability education. From this review future research directions have been outlined.


2016 ◽  
Vol 79 (1) ◽  
Author(s):  
Mohd Fahrul Hassan ◽  
Muhamad Zameri Mat Saman ◽  
Salwa Mahmood ◽  
Nik Hisyamudin Muhd Nor ◽  
Mohd Nasrull Abdol Rahman

To achieve sustainable product design, it is crucial to use sustainability assessment during the product design process. In this paper, numerous sustainability assessment methodologies in product design are reviewed. A comprehensive assessment of sustainability has been reported to present better performance for improving product sustainability. This review focused on the consideration of sustainability elements by previous researchers that have proposed integrated design tools, commercial software tools and combination both methods in supporting the methodologies. Based on this review, it can be concluded that the inclusion of sustainability performance among the assessment criteria in the design process activities is suggested as a critical point of concern which presents a challenge and is a great opportunity to develop useful guidelines or directions for industries or any product-based project so that the proposed approach will be accepted for implementation in the working environment.


2018 ◽  
Vol 13 (1) ◽  
pp. 73 ◽  
Author(s):  
Freshty Yulia Arthatiani ◽  
Nunung Kusnadi ◽  
Harianto Harianto

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.


Author(s):  
John Joe Parappallil ◽  
Novica Zarvic ◽  
Oliver Thomas

In this paper, the authors present the results of a recently performed literature analysis on the topic of Business-IT Alignment. They have thereby investigated 270 articles from the period 1993-2011 in a structured way. The articles were selected on the basis of three well-known ranking lists of publications in the Information Systems research domain. In the authors’ analysis they distinguish a context and a content point of view. The former one focuses on metadata analysis of the articles under consideration whereas the latter one uses text mining techniques to dive into the articles´ body of content. Finally, they discuss their results and present conceivable future research directions that should be tackled by alignment researchers and conclude their paper.


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