scholarly journals Analysis of Asymmetric Quantity Commitment in Decentralized Supply Chains

2021 ◽  
Vol 12 (2) ◽  
pp. 83-102
Author(s):  
Zhaoqiong Qin ◽  
Wen-Chyuan Chiang ◽  
Robert Russell
Keyword(s):  
Supply Chains ◽  
Price Competition ◽  
Just In Time ◽  
Lead Times ◽  
Backward Induction ◽  
Multi Stage ◽  
Stage Game ◽  
Time Systems

Quantity commitment chosen by firms in competition has been demonstrated by previous studies to mitigate price competition. This study demonstrates that asymmetric quantity commitment can always arise when one firm (e-tailer) shortens lead times or adopts just-in-time systems to circumvent quantity commitment while another firm (retailer) does not. To study the asymmetric quantity commitment in decentralization, a multi-stage game is analyzed, and backward induction is adopted. The authors find that the retailer always adopts the quantity commitment in the decentralization to achieve a higher profit.

scholarly journals Location-Price Competition in Airline Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
H. Gao ◽  
J. Hu ◽  
V. Mazalov ◽  
A. Shchiptsova ◽  
L. Song ◽  
...  
Keyword(s):  
Price Competition ◽  
Multinomial Logit Model ◽  
Backward Induction ◽  
Response Dynamics ◽  
Demand Distribution ◽  
Second Stage ◽  
Knowing That ◽  
Price Game ◽  
Best Response ◽  
Stage Game

This paper addresses location-then-price competition in airline market as a two-stage game ofnplayers on the graph. Passenger’s demand distribution is described by multinomial logit model. Equilibrium in price game is computed through best response dynamics. We solve location game using backward induction, knowing that airlines will choose prices from equilibrium for the second-stage game. Some numerical results for airline market under consideration are presented.

scholarly journals Duopoly price competition with limited capacity

2021 ◽  
Author(s):  
A. Bërdëllima
Keyword(s):  
Price Competition ◽  
Small Firms ◽  
Common Knowledge ◽  
Limited Capacity ◽  
Equilibrium Outcome ◽  
Second Stage ◽  
Duopoly Model ◽  
Full Capacity ◽  
Stage Game ◽  
The Given

AbstractWe study a variation of the duopoly model by Kreps and Scheinkman (1983). Firms limited by their capacity of production engage in a two stage game. In the first stage they commit to levels of production not exceeding their capacities which are then made common knowledge. In the second stage after production has taken place firms simultane- ously compete in prices. Solution of this sequential game shows that the unique Cournot equilibrium outcome as in Kreps and Scheinkman is not always guaranteed. However the Cournot outcome is still robust in the sense that given sufficiently large capacities this equilibrium holds. If capacities are sufficiently small, firms decide to produce at their full capacity and set a price which clears the market at the given level of output.

DETERMINING THE NUMBER OF KANBANS IN MULTI-ITEM JUST-IN-TIME SYSTEMS

1993 ◽  
Vol 25 (1) ◽  
pp. 89-98 ◽  
Author(s):  
RONALD G. ASKIN ◽  
M. GEORGE MITWASI ◽  
JEFFREY B. GOLDBERG
Keyword(s):  
Just In Time ◽  
Time Systems

scholarly journals Learning from Mistakes: A Note on Just-in-Time Systems

1996 ◽  
Vol 44 (1) ◽  
pp. 206-214 ◽  
Author(s):  
Carlos Ocaña ◽  
Eitan Zemel
Keyword(s):  
Just In Time ◽  
Time Systems

scholarly journals Lead Times – Their Behavior and the Impact on Planning and Control in Supply Chains

2017 ◽  
Vol 8 (2) ◽  
pp. 30-40 ◽  
Author(s):  
Peter Nielsen ◽  
Zbigniew Michna ◽  
Brian Bruhn Sørensen ◽  
Ngoc Do Anh Dung
Keyword(s):  
Supply Chains ◽  
Lead Time ◽  
Large Impact ◽  
Lead Times ◽  
Stochastic Nature ◽  
Planning And Control ◽  
And Control ◽  
The Impact ◽  
Independent And Identically Distributed

AbstractLead times and their nature have received limited interest in literature despite their large impact on the performance and the management of supply chains. This paper presents a method and a case implementation of the same, to establish the behavior of real lead times in supply chains. The paper explores the behavior of lead times and illustrates how in one particular case they can and should be considered to be independent and identically distributed (i.i.d.). The conclusion is also that the stochastic nature of the lead times contributes more to lead time demand variance than demand variance.

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