scholarly journals Pricing strategy and product substitution of bullwhip effect in dual parallel supply chain: aggravation or mitigation?

2021 ◽  
Author(s):  
Junhai Ma ◽  
Wandong Lou ◽  
Zongxian Wang
Keyword(s):  
Supply Chains ◽  
Negative Impact ◽  
Autoregressive Process ◽  
Bullwhip Effect ◽  
Pricing Strategy ◽  
Product Substitution ◽  
Vector Autoregressive ◽  
Substitutable Products ◽  
Pricing Decision ◽  
Vector Autoregressive Process

The bullwhip effect (BE) affects not only the revenue of the retailer but also the revenue of the manufacture. Thus, a lot of retailers and manufacturers aim to attenuate the negative impact of the BE. In this research, two parallel supply chains distributing two substitutable products with price-sensitive demands are considered, the order-up-to inventory policy, as well as the MMSE forecasting method, are employed by retailers in these chains. The retailer’s price-setting follows the first-order vector autoregressive process, suggesting that its pricing decision depends on its previous price as well as its rival’s price, owing to the BE. The analytical expression of the BE is calculated by the statistical method. Besides, the effects of pricing strategy and product substitution on the BE are studied through simulation. A conclusion can be drawn that the BE of the two parallel supply chains will be affected by lead time, product substitution rate, and pricing coefficient. Of particular interest is that the BE can be efficiently alleviated by adopting a price strategy with many correlations and a small coefficient of autocorrelation.

Some ARMA models for dependent sequences of poisson counts

1988 ◽  
Vol 20 (4) ◽  
pp. 822-835 ◽  
Author(s):  
Ed Mckenzie
Keyword(s):  
Asymptotic Behaviour ◽  
Discrete Time ◽  
Joint Distribution ◽  
Autoregressive Process ◽  
Two Dimensional ◽  
Arma Models ◽  
Time Reversibility ◽  
Vector Autoregressive ◽  
Arma Processes ◽  
Vector Autoregressive Process

A family of models for discrete-time processes with Poisson marginal distributions is developed and investigated. They have the same correlation structure as the linear ARMA processes. The joint distribution of n consecutive observations in such a process is derived and its properties discussed. In particular, time-reversibility and asymptotic behaviour are considered in detail. A vector autoregressive process is constructed and the behaviour of its components, which are Poisson ARMA processes, is considered. In particular, the two-dimensional case is discussed in detail.

scholarly journals Justification of Wold’s Theorem and the Unbiasedness of a Stable Vector Autoregressive Time Series Model Forecasts

2017 ◽  
Vol 6 (2) ◽  
pp. 1
Author(s):  
Iberedem A. Iwok
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Autoregressive Process ◽  
Time Series Model ◽  
Average Process ◽  
Moving Average Process ◽  
Autoregressive Time Series ◽  
Vector Autoregressive ◽  
Vector Autoregressive Process ◽  
Vector Time Series

In this work, the multivariate analogue to the univariate Wold’s theorem for a purely non-deterministic stable vector time series process was presented and justified using the method of undetermined coefficients. By this method, a finite vector autoregressive process of order  [] was represented as an infinite vector moving average () process which was found to be the same as the Wold’s representation. Thus, obtaining the properties of a  process is equivalent to obtaining the properties of an infinite  process. The proof of the unbiasedness of forecasts followed immediately based on the fact that a stable VAR process can be represented as an infinite VEMA process.

Coordinating of multi-echelon supply chains through the generalized (R, S) policy

SIMULATION ◽  
2020 ◽  
Vol 96 (9) ◽  
pp. 767-778 ◽  
Author(s):  
Ahmed Shaban ◽  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Massimo Tronci
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information Sharing ◽  
Negative Impact ◽  
Bullwhip Effect ◽  
Coordination Mechanism ◽  
Chain Model ◽  
Demand Forecast ◽  
Modeling Methodology ◽  
Information Demand

Numerous studies have confirmed the negative impact of the lack of coordination on supply chain performance. In particular, the lack of coordination leads to the bullwhip effect, which has severe impacts on supply chain stability. This paper evaluates a proposed coordination mechanism that allows a decentralized information sharing in multi-echelon supply chains. The proposed mechanism “Info-Smooth” utilizes the ordering rule of the generalized (R, S) policy in which a replenishment order can be transferred to upstream echelons including two pieces of information (demand forecast and inventory balance). As the generalized (R, S) can allow order smoothing, Info-Smooth combines the power of both information sharing and order smoothing. A simulation modeling methodology is employed to investigate the effectiveness of Info-Smooth in a multi-echelon supply chain. The factorial design results have shown that Info-Smooth is successful in mitigating the bullwhip effect whilst keeping acceptable inventory stability, compared to the traditional supply chain model.

IDENTIFICATION AND DICHOTOMIZATION OF LONG- AND SHORT-RUN RELATIONS OF COINTEGRATED VECTOR AUTOREGRESSIVE MODELS

2001 ◽  
Vol 17 (5) ◽  
pp. 889-912 ◽  
Author(s):  
Cheng Hsiao
Keyword(s):  
Prior Information ◽  
Autoregressive Process ◽  
Rank Condition ◽  
Vector Autoregressive ◽  
Long Run ◽  
Vector Autoregressive Process ◽  
Short Run ◽  
Cowles Commission ◽  
Necessary And Sufficient ◽  
The Relationship

We show that the usual rank condition is necessary and sufficient to identify a vector autoregressive process whether the variables are I(0) or I(d) for d = 1,2,.... We then use this rank condition to demonstrate the interdependence between the identification of short-run and long-run relations of cointegrated process. We find that both the short-run and long-run relations can be identified without the existence of prior information to identify either relation. But if there exists a set of prior restrictions to identify the short-run relation, then this same set of restrictions is sufficient to identify the corresponding long-run relation. On the other hand, it is in general not possible to identify the long-run relations without information on the complete structure. The relationship between the identification of a vector autoregressive process and a Cowles Commission dynamic simultaneous equations model is also clarified.

SOME PROPERTIES OF VECTOR AUTOREGRESSIVE PROCESSES WITH MARKOV-SWITCHING COEFFICIENTS

2000 ◽  
Vol 16 (1) ◽  
pp. 23-43 ◽  
Author(s):  
Minxian Yang
Keyword(s):  
Markov Switching ◽  
Sufficient Conditions ◽  
Autoregressive Process ◽  
Nonlinear Process ◽  
Vector Autoregressive ◽  
Second Moments ◽  
Large Numbers ◽  
Vector Autoregressive Process ◽  
Short Run ◽  
Stationarity Conditions

Some statistical properties of a vector autoregressive process with Markov-switching coefficients are considered. Sufficient conditions for this nonlinear process to be covariance stationary are given. The second moments of the process are derived under the conditions. The autocovariance matrix decays at exponential rate, permitting the application of the law of large numbers. Under the stationarity conditions, although sharing the “mean-reverting” property with conventional linear stationary processes, the process offers richer short-run dynamics such as conditional heteroskedasticity, asymmetric responses, and occasional nonstationary behavior.

Sign in / Sign up

Export Citation Format

Share Document