The impact of three forecasting methods on the value of vendor managed inventory

2016 ◽  
Author(s):  
Zainab Belalia ◽  
Fouzia Ghaiti
Keyword(s):  
Vendor Managed Inventory ◽  
Forecasting Methods ◽  
The Impact

scholarly journals Statistical Modeling and Prediction for Tourism Economy Using Dendritic Neural Network

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Ying Yu ◽  
Yirui Wang ◽  
Shangce Gao ◽  
Zheng Tang
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Rapid Development ◽  
Seasonal Trend ◽  
Moving Averages ◽  
Forecasting Methods ◽  
Tourism Economy ◽  
The Impact ◽  
D Model

With the impact of global internationalization, tourism economy has also been a rapid development. The increasing interest aroused by more advanced forecasting methods leads us to innovate forecasting methods. In this paper, the seasonal trend autoregressive integrated moving averages with dendritic neural network model (SA-D model) is proposed to perform the tourism demand forecasting. First, we use the seasonal trend autoregressive integrated moving averages model (SARIMA model) to exclude the long-term linear trend and then train the residual data by the dendritic neural network model and make a short-term prediction. As the result showed in this paper, the SA-D model can achieve considerably better predictive performances. In order to demonstrate the effectiveness of the SA-D model, we also use the data that other authors used in the other models and compare the results. It also proved that the SA-D model achieved good predictive performances in terms of the normalized mean square error, absolute percentage of error, and correlation coefficient.

scholarly journals Evaluación de riesgo de cambio, caso de aplicación en empresa importadora

2021 ◽  
Author(s):  
Sindy Viviana Giraldo Arcila ◽  
Juliana López Restrepo
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Quantitative Analysis ◽  
Case Studies ◽  
Great Part ◽  
Exchange Rate Risk ◽  
Forecasting Methods ◽  
Black Scholes ◽  
The Impact ◽  
A Company

This applied investigation had as objective to establish a shortterm financial cover to control the impact of loss on profits due to the exchange rate risk on the COP/USD ratio, in a company dedicated to the import and marketing of tires in Colombia. For the above, it was necessary to carry out a quantitative analysis between the options and forward coverage, requiring the use of the Black Scholes technique for the calculation of the premium; Likewise, it was necessary to simulate through different forecasting methods to choose the lowest RMSE error, presented as a result the time series which was used to project the future behavior of the dollar through the Risk Simulator software. Finally, it was evident that a great part of the background for the present investigation is of a qualitative type, some of the existing quantitative origin are not focused on case studies; otherwise, the results obtained allowed to demonstrate that the best coverage is the purchase of the Call in The Money ...

scholarly journals Pengurangan Efek Bullwhip Pada Vendor Tunggal dan Eceran Multi Di PT. XYZ

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Meilita Tryana Sembiring ◽  
Feby Sanna Sibarani
Keyword(s):  
Supply Chain ◽  
Moving Average ◽  
Linear Method ◽  
Bullwhip Effect ◽  
Exponential Smoothing ◽  
Glass Bottle ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
The Impact ◽  
A Company

PT. XYZ merupakan perusahaan yang bergerak dalam produksi produk – produk olahan teh. Perusahaan telah memproduksi berbagai varian the yakni bentuk mau pun jenis teh. Objek penelitian ini ialah the dalam kemasan botol kaca dengan ukuran 220 ml. Ukuran the tersebut dipilih berdasarkan akumulasi dari penjualan the tertinggi. Terdapat perbedaan pada prediksi jumlah produksi yang akan dilakukan. Prediksi jumlah produksi dapat dilakukan dengan melakukan peramalan permintaan serta penggunaan metode yang tepat. Rantai pasok yang diteliti pada PT. XYZ terdiri atas Manufaktur (Vendor), Kantor Penjualan, dan Dister. Awalnya peramalan dilakukan pada masing – masing level rantai pasok dengan metode peramalan yang berbeda – beda. Maka, diperlukan penyeragaman metode peramalan pada masing – masing pelaku rantai pasok. Berdasarkan pengujian metode peramalan yang dilakukan yakni metode Linear, Exponential Smoothing, Moving Average, dan Winter’sMethod. Diperoleh bahwa error terkecil terdapat pada metode peramalan Winter’s Method dengan parameter Level sebesar 0,5, Trend sebesar 0,2 dan Seasonal sebesar 0,6. Parameter error yang digunakan ialah MAPE, MAD, dan MSD. Hasil penelitian menunjukkan bahwa penggunaan metode peramalan yang tepat akan mengurangi dampak dari bullwhip effect yang terjadi pada PT. XYZ.   PT. XYZ is a company engaged in the production of processed tea products. The company has produced various variants of tea, that is the shape and type of tea. The object of this research is the 220 ml glass bottle packaging. The size of the tea is chosen based on the accumulation of the highest tea sales. There is a difference in the prediction of the amount of production to be carried out. Prediction of the amount of production can be done by forecasting demand and using appropriate methods. The supply chain studied at PT. XYZ consists of Manufacturing (Vendors), Sales Offices, and Disters. Initially forecasting is done at each level of the supply chain with different forecasting methods. Therefore, uniform forecasting methods are needed for each supply chain actor. Based on testing the forecasting method that is done namely the Linear method, Exponential Smoothing, Moving Average, and Winter’s Method. Obtained that the smallest error is found in the Winter’s Method forecasting method with a Level parameter of 0.5, a Trend of 0.2 and a Seasonal of 0.6. The error parameters used are MAPE, MAD, and MSD. The results showed that the use of appropriate forecasting methods would reduce the impact of the bullwhip effect that occurred at PT. XYZ

scholarly journals Differences in Tourist Behaviors across the Seasons: The Case of Northern Indiana

2019 ◽  
Vol 11 (16) ◽  
pp. 4351
Author(s):  
Yeongbae Choe ◽  
Hany Kim ◽  
Hyo-Jae Joun
Keyword(s):  
Tourism Demand ◽  
Aggregate Level ◽  
Essential Factor ◽  
Related Factors ◽  
Seasonal Differences ◽  
Individual Level ◽  
Travel Experience ◽  
Forecasting Methods ◽  
Tourism Studies ◽  
The Impact

Seasonality is an essential factor influencing tourism demand and traveler behavior at the destination. As such, seasonality (i.e., the influx of tourists) needs to be managed by destination marketing organizations. Most tourism studies have focused mainly on the forecasting methods/metrics and the effect of seasonality at the aggregate level rather than understanding seasonal differences in the nature of the traveler and travel experience. The purpose of this study is to understand seasonality at both the aggregate market level and individual traveler level. As such, this study first utilizes the concept of the gravity model to understand seasonality in the number of inquiries through an official website. This study, then, uses seemingly unrelated regressions to estimate simultaneously the effect of various trip-related factors on overall trip expenditures and the length of the trip. The results show that the impact of seasonality on aggregated demand is surprisingly consistent across the seasons; however, individual-level analyses indicate that traveler behavior and travelers’ responses to advertising differ significantly across seasons. Thus, destination marketers need to understand the nature of seasonality of their specific markets more accurately to provide appropriate tourism products/services to their current and potential travelers.

scholarly journals Forecasting Techniques and Accuracy of Performance Forecasting

2016 ◽  
Vol 7 (2) ◽  
pp. 813-820
Author(s):  
E. W. Chindia
Keyword(s):  
Organizational Performance ◽  
Return On Assets ◽  
Manufacturing Operations ◽  
Forecasting Methods ◽  
Performance Forecasting ◽  
Return On Sales ◽  
Combined Forecasting ◽  
The Impact ◽  
Structured Questionnaire ◽  
Forecasting Techniques

This article explores the impact of the different forecasting methods (FMs) on the accuracy of performance forecasting (APF) in large manufacturing firms (LMFs), in Kenya. The objective of the study was to assess if the different forecasting methods have an influence on any of the aspects of measures of APF. APF, in manufacturing operations, is seldom derived accurately. However, LMFs tend to hire skilled forecasters, to a great extent, to ensure APF when preparing future budgets. The different types of forecasting techniques have been known to influence the behavior of operations resulting in the formulation of either accurate or inaccurate forecasts resulting in either adverse or favorable organizational performance. The study used the three known forecasting methods, objective, subjective and combined forecasting techniques against measures of APF, expected value, growth in market share, return on assets and return on sales. Regression analysis was used applying data collected through a structured questionnaire administered among randomly selected LMFs. Results indicated that there was evidence that APF is influenced by each of the forecasting methods in different ways. 

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