نتایج جستجو برای: competitive pricing

تعداد نتایج: 119772  

Journal: :Int. J. Game Theory 2013
Julio González-Díaz Ron Siegel

Bulow and Levin’s (2006) “Matching and Price Competition” studies a matching model in which hospitals compete for interns by offering wages. We relax the assumption of symmetric linear costs and compare the pricing equilibrium that results to the firm-optimal competitive equilibrium. With linear and asymmetric costs, competition in the pricing equilibrium may not be localized, but all other qua...

Journal: :International Journal of Academic Research in Business and Social Sciences 2020

Journal: :Review of Economic Studies and Research "Virgil Madgearu" 2021

The article offer a critical perspective of several elements and some associated indicators used in characterizing estimating the intensity competition (i.e., extent to which mutual pressure rivals is exerted on market). We focus pricing policies firms its impact expected responses from competitors. Influences substitutes overall production capacity surplus are also analyzed.

Journal: :Journal of Applied Business Research (JABR) 2011

Journal: :Journal of Revenue and Pricing Management 2022

Abstract Past reviews of studies concerning competitive pricing strategies lack a unifying approach to interdisciplinarily structure research across economics, marketing management, and operations. This academic void is especially unfortunate for online markets as they show much higher dynamics compared their offline counterparts. We review 132 articles on posted goods either e-tail or in gener...

1994
Baruch Awerbuch Yossi Azar

The standard setting for competitive analysis of online algorithms assumes that on-line algorithm knows the past (but not future) inputs, and can optimize its performance by \learning" from mistakes of the past. This framework cannot capture some of the real-life online decision-making, which takes place without full knowledge of past and present inputs. Instead, online algorithm only knows a f...

1995
Baruch Awerbuch Yossi Azar

The standard setting for competitive analysis of online algorithms assumes that on-line algorithm knows the past (but not future) inputs, and can optimize its performance by \learning" from mistakes of the past. This framework cannot capture some of the real-life online decision-making, which takes place without full knowledge of past and present inputs. Instead, online algorithm only knows a f...

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