Higher Minimum Quality Standards and Redistributive Effects on Consumer Welfare

Kotschedoff, Marco J.W.; Pachali, Max J.

doi:10.1287/mksc.2019.1172

Cited by 16 publications

(3 citation statements)

References 51 publications

(67 reference statements)

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“…Consumer welfare is traditionally measured by consumers' surplus (Sarkar, 2016). Referring to the literature (Yu et al, 2018;Nagurney et al, 2019;Gui et al, 2019;Kotschedoff and Pachali, 2020), we construct the consumer welfare function as:…”

Section: Consumers' Welfare Functionmentioning

confidence: 99%

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Optimal service quality and pricing for App service supply chain with network externality based on four different scenarios

Xing

Wang

Yao

2022

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PurposeThe paper aims to investigate the optimal service quality and pricing for a mobile application (App) service supply chain (SSC) and analyze the impact of network externality on App SSC members' utilities. After that, the corresponding management inspirations and suggestions are put forward.Design/methodology/approachThe paper developed a SSC consisted of an App service supplier and an App service operator. Our models aim to maximize the SSC members' utilities. By utilizing the game theory, equilibrium solutions are obtained. Numerical examples are used to manifest the impact of parameters on decisions by Matlab. Some management enlightenment could be obtained by comparison analysis.FindingsCooperating with an App service operator that asks for a lower revenue sharing ratio will enable the App service supplier to have sufficient funds to provide high-quality update service. With the increase of network externality, adopting a high-quality service strategy can bring higher utility to the App service operator and users. Pouring attention into consumer welfare moderately will improve the App service supplier's utility. Scenario CRS can achieve a win–win goal for App SSC members and consumers.Originality/valueThe innovations of this paper are as follows: Firstly, the authors investigate the optimal service quality and pricing for the App SSC, which has been discussed little in previous literature. Secondly, the authors discuss how network externality and enterprises' attention to consumer welfare affect the optimal decisions and utilities of App service supply chain members. Thirdly, this paper considers four different circumstances and determines the optimal operation scenario for App SSC through comparative analysis.

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Section: Consumers' Welfare Functionmentioning

confidence: 99%

“…, 2019; Gui et al. , 2019; Kotschedoff and Pachali, 2020), we construct the consumer welfare function as:…”

Section: Model Description and Notationsmentioning

confidence: 99%

Optimal service quality and pricing for App service supply chain with network externality based on four different scenarios

Xing

Wang

Yao

2022

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“…Many of the above papers emphasize the uneven impact of a regulation across different segments of consumers. Kotschedoff and Pachali (2020), in their study of animal welfare standards in egg farming, show that high-income households are likely to gain most. In particular, high-income households have higher willingness-to-pay for animal welfare in their food and therefore benefit most from the falling price of higher-quality eggs.…”

Section: Distributional Impactmentioning

confidence: 99%

Introduction to the Special Issue on Consumer Protection

2020

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Please scroll down for article-it is on subsequent pages With 12,500 members from nearly 90 countries, INFORMS is the largest international association of operations research (O.R.) and analytics professionals and students. INFORMS provides unique networking and learning opportunities for individual professionals, and organizations of all types and sizes, to better understand and use O.R. and analytics tools and methods to transform strategic visions and achieve better outcomes. For more information on INFORMS, its publications, membership, or meetings visit http://www.informs.org

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How to generalize from a hierarchical model?

Pachali

Kurz²,

Otter

2020

Quant Mark Econ

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Models of consumer heterogeneity play a pivotal role in marketing and economics, specifically in random coefficient or mixed logit models for aggregate or individual data and in hierarchical Bayesian models of heterogeneity. In applications, the inferential target often pertains to a population beyond the sample of consumers providing the data. For example, optimal prices inferred from the model are expected to be optimal in the population and not just optimal in the observed, finite sample. The population model, random coefficients distribution, or heterogeneity distribution is the natural and correct basis for generalizations from the observed sample to the market. However, in many if not most applications standard heterogeneity models such as the multivariate normal, or its finite mixture generalization lack economic rationality because they support regions of the parameter space that contradict basic economic arguments. For example, such population distributions support positive price coefficients or preferences against fuel-efficiency in cars. Likely as a consequence, it is common practice in applied research to rely on the collection of individual level mean estimates of consumers as a representation of population preferences that often substantially reduce the support for parameters in violation of economic expectations. To overcome the choice between relying on a mis-specified heterogeneity distribution and the collection of individual level means that fail to measure heterogeneity consistently, we develop an approach that facilitates the formulation of more economically faithful heterogeneity distributions based on prior constraints. In the common situation where the heterogeneity distribution comprises both constrained and unconstrained coefficients (e.g., brand and price coefficients), the choice of subjective prior parameters is an unresolved challenge. As a solution to this problem, we propose a marginal-conditional decomposition that avoids the conflict between wanting to be more informative about constrained parameters and only weakly informative about unconstrained parameters. We show how to efficiently sample from the implied posterior and illustrate the merits of our prior as well as the drawbacks of relying on means of individual level preferences for decision-making in two illustrative case studies.

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Higher Minimum Quality Standards and Redistributive Effects on Consumer Welfare

Cited by 16 publications

References 51 publications

Optimal service quality and pricing for App service supply chain with network externality based on four different scenarios

Optimal service quality and pricing for App service supply chain with network externality based on four different scenarios

Introduction to the Special Issue on Consumer Protection

How to generalize from a hierarchical model?

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