Temat: forecasting - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Residential electricity consumption in Poland
Autorzy:: Ropuszyńska-Surma, E.
Węglarz, M.
Tematy:: forecasting
demand forecasting
econometric model
electricity consumption
HDD index; Pokaż więcej
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:: https://bibliotekanauki.pl/articles/406401.pdf Link otwiera się w nowym oknie
Opis:: Key factors influencing electricity consumption in the residential sector in Poland have been identified. A fixed-effects model was used, which includes time effects, and a set of covariates, based on the model developed by Houthakker et al. This model estimates electricity demand by using lagged values of the dependent variable along with current and lagged values of electricity prices, and other variables that affect electricity demand such as: population, economic growth, income per capita, price of related goods, etc. The model has been identified according to the research results of the authors and those obtained by Bentzen and Engsted. The set of covariates was extended to the lagged electricity price given by a tariff (taken from two years previous to the time of interest) and heating degree days index, a very important factor in European Union countries, where the climate is temperate. The authors propose four models of residential electricity demand, for which a confidence interval of 95% has been assumed. Estimation was based on Polish quarterly data for the years 2003–2013.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: DEMAND FORECAST WITH BUSINESS CLIMATE INDEX FOR A STEEL AND IRON INDUSTRY REPRESENTATIVE
Autorzy:: Barska, Magdalena
Tematy:: demand forecasting
SARIMAX
business climate indicator; Pokaż więcej
Wydawca:: Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Powiązania:: https://bibliotekanauki.pl/articles/453455.pdf Link otwiera się w nowym oknie
Opis:: The steel and iron industry production is dedicated to serve other industries mainly. This makes the exercise of demand forecasting different than for consumer goods. The common sense says that demand fluctuations are influenced by general economic soundness. An attempt was made to address the question of improving forecast’s accuracy by adding a business cycle indicator as an input variable. The SARIMAX model was applied. Including a business climate indicator improved model’s performance, however no co integration is observed between the two series.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: The impact of stochastic lead times on the bullwhip effect – an empirical insight
Autorzy:: Nielsen, P.
Michna, Z.
Tematy:: supply chain
bullwhip effect
inventory policy
lead time demand
order-up-to-level policy
stochastic lead time
demand forecasting
lead time forecasting
lead time demand forecasting; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/407121.pdf Link otwiera się w nowym oknie
Opis:: In this article, we review the research state of the bullwhip effect in supply chains with stochastic lead times. We analyze problems arising in a supply chain when lead times are not deterministic. Using real data from a supply chain, we confirm that lead times are stochastic and can be modeled by a sequence of independent identically distributed random variables. This underlines the need to further study supply chains with stochastic lead times and model the behavior of such chains.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Demand forecasting in an enterprise – the forecasted variable selection problem
Autorzy:: Dittmann, Paweł
Sobolewski, Adam Michał
Tematy:: demand
demand forecasting
operational measures of demand; Pokaż więcej
Wydawca:: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Powiązania:: https://bibliotekanauki.pl/articles/425024.pdf Link otwiera się w nowym oknie
Opis:: Forecasting process efficiency depends – to a large extent – on the correct determination of the forecasted variable. Therefore, companies should use for sales forecasting, the variables that reflect actual consumer demand. However in practice, since demand is usually not directly observable, many operational measures of demand are used. In the manufacturing and retail enterprises, the most often used variables are historical orders, shipments, and billed sales volumes. The purpose of this paper is to characterise the effects of using as the predicted variable, different operational measures of consumer demand. Theoretical discussion is illustrated by an attempt to estimate errors in demand forecasts for Avon Cosmetics’ products that are related to changes in data used for forecasting.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Logistics management based on demand forecasting
Autorzy:: Hart, M.
Lukoszová, X.
Kubíková, J.
Tematy:: logistics management
demand forecasting
supply chain
industry; Pokaż więcej
Wydawca:: Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Powiązania:: https://bibliotekanauki.pl/articles/409312.pdf Link otwiera się w nowym oknie
Opis:: The companies of any industry are strongly affected with current globalization trend, which makes supply chain flows more and more bulky and complex. To be competitive in cost and eco-friend way under contemporary business market conditions, the companies should apply system approach of logistics management to plan, manage and control of their logistics processes. Each company’s system can be analysed and divided into essential logistics sub-systems: purchasing, production, packaging, warehousing, distribution and reverse material flow management. Thus, the system and process approach are crucial for up-to-date logistics systems or subsystems management in context of long-term sustainable growth. Any effective logistics management system should be based on sub-system of demand forecasting. Demand forecasting is increasingly getting important to make right managerial decisions. Well developed demand forecasting sub-sytem in a company is a ground for effective planning, management and control of all company’s processes then also for effective logistics or supply chain management.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Hybrid demand forecasting models: pre-pandemic and pandemic use studies
Autorzy:: Kolkova, Andrea
Rozehnal, Petr
Tematy:: forecastHybrid
demand forecasting
statistic model
neural networks; Pokaż więcej
Wydawca:: Instytut Badań Gospodarczych
Powiązania:: https://bibliotekanauki.pl/articles/22443157.pdf Link otwiera się w nowym oknie
Opis:: Research background: In business practice and academic sphere, the question of which of the prognostic models is the most accurate is constantly present. The accuracy of models based on artificial intelligence and statistical models has long been discussed. By combining the advantages of both groups, hybrid models have emerged. These models show high accuracy. Moreover, the question remains whether data in a dynamically changing economy (for example, in a pandemic period) have changed the possibilities of using these models. The changing economy will continue to be an important element in demand forecasting in the years to come. In business, where the concept of just in time already proves to be insufficient, it is necessary to open new research questions in the field of demand forecasting. Purpose of the article: The aim of the article is to apply hybrid models to bicycle sales e-shop data with a comparison of accuracy models in the pre-pandemic period and in the pandemic period. The paper examines the hypothesis that the pandemic period has changed the accuracy of hybrid models in comparison with statistical models and models based on artificial neural networks. Models: In this study, hybrid models will be used, namely the Theta model and the new forecastHybrid, compared to the statistical models ETS, ARIMA, and models based on artificial neural networks. They will be applied to the data of the e-shop with the cycle assortment in the period from 1.1. 2019 to 5.10 2021. Whereas the period will be divided into two parts, pre-pandemic, i.e. until 1 March 2020 and pandemic after that date. The accuracy evaluation will be based on the RMSE, MAE, and ACF1 indicators. Findings & value added: In this study, we have concluded that the prediction of the Hybrid model was the most accurate in both periods. The study can thus provide a scientific basis for any other dynamic changes that may occur in demand forecasting in the future. In other periods when there will be volatile demand, it is essential to choose models in which accuracy will decrease the least. Therefore, this study provides guidance for the use of methods in future periods as well. The stated results are likely to be valid even in an international comparison.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Demand forecasting: an alternative approach based on technical indicator Pbands
Autorzy:: Kolková, Andrea
Ključnikov, Aleksandr
Tematy:: demand forecasting
neural network
BATS
hybrid model
Pbands; Pokaż więcej
Wydawca:: Instytut Badań Gospodarczych
Powiązania:: https://bibliotekanauki.pl/articles/19233720.pdf Link otwiera się w nowym oknie
Opis:: Research background: Demand forecasting helps companies to anticipate purchases and plan the delivery or production. In order to face this complex problem, many statistical methods, artificial intelligence-based methods, and hybrid methods are currently being developed. However, all these methods have similar problematic issues, including the complexity, long computing time, and the need for high computing performance of the IT infrastructure. Purpose of the article: This study aims to verify and evaluate the possibility of using Google Trends data for poetry book demand forecasting and compare the results of the application of the statistical methods, neural networks, and a hybrid model versus the alternative possibility of using technical analysis methods to achieve immediate and accessible forecasting. Specifically, it aims to verify the possibility of immediate demand forecasting based on an alternative approach using Pbands technical indicator for poetry books in the European Quartet countries. Methods: The study performs the demand forecasting based on the technical analysis of the Google Trends data search in case of the keyword poetry in the European Quartet countries by several statistical methods, including the commonly used ETS statistical methods, ARIMA method, ARFIMA method, BATS method based on the combination of the Cox-Box transformation model and ARMA, artificial neural networks, the Theta model, a hybrid model, and an alternative approach of forecasting using Pbands indicator. The study uses MAPE and RMSE approaches to measure the accuracy. Findings & value added: Although most currently available demand prediction models are either slow or complex, the entrepreneurial practice requires fast, simple, and accurate ones. The study results show that the alternative Pbands approach is easily applicable and can predict short-term demand changes. Due to its simplicity, the Pbands method is suitable and convenient to monitor short-term data describing the demand. Demand prediction methods based on technical indicators represent a new approach for demand forecasting. The application of these technical indicators could be a further forecasting models research direction. The future of theoretical research in forecasting should be devoted mainly to simplifying and speeding up. Creating an automated model based on primary data parameters and easily interpretable results is a challenge for further research.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Demand forecasting in a business based on experts’ opinions – an application of weibull distributions
Autorzy:: Dittmann, Paweł
Tematy:: demand
demand forecasting
experts’ opinions
Weibull distribution applications; Pokaż więcej
Wydawca:: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Powiązania:: https://bibliotekanauki.pl/articles/424785.pdf Link otwiera się w nowym oknie
Opis:: Demand forecasts in a business may be constructed by various methods, e.g. by using Type-I formal models, or by using type-II formal models based on experts’ opinions. The experts can be the business’s managers or persons from outside of the studied business. The experts can not only construct forecasts, but also subjectively specify the probability of them coming true. In this article, the Weibull distribution is described, a distribution that may be applied in the process of constructing product demand forecasts for a business. The methodology for constructing a point forecast is explained, along with the methods for evaluating the chances of the forecast coming true and the methods for judging the probability connected with sales profitability.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Case study about economic order quantities and comparison of results from conventional EOQ model and response surface-based approach
Autorzy:: Yıldız, R.
Yaman, R.
Tematy:: economic order quantity
Pareto analysis
response surface
demand forecasting; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/406756.pdf Link otwiera się w nowym oknie
Opis:: This study involves the implementation of an economic order quantity (EOQ) model which is an inventory control method in a ceramic factory. Two different methods were applied for the calculation of EOQs. The first method is to determine EOQ values using a response surface method-based approach (RSM). The second method uses conventional EOQ calculations. To produce a ceramic product, 281 different and additive materials may be used. First, Pareto (ABC) analysis was performed to determine which of the materials have higher priority. Because of this analysis, the value of 21 items among 281 different materials and additives were compared to the ratio of the total product. The ratio was found to be 70.4% so calculations were made for 21 items. Usage value for every single item for the years 2011, 2012, 2013 and 2014, respectively, were obtained from the company records. Eight different demand forecasting methods were applied to find the amount of the demand in EOQ. As a result of forecasting, the EOQ of the items were calculated by establishing a model. Also, EOQ and RSM calculations for the items were made and both calculation results were compared to each other. Considering the obtained results, it is understood that RSM can be used in EOQ calculations rather than the conventional EOQ model. Also, there are big differences between the EOQ values which were implemented by the company and the values calculated. Because of this work, the RSM-based EOQ approach can be used to decide on the EOQ calculations as a way of improving the system performance.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Shop floor-level control of manufacturing companies: an interview study in Finland
Autorzy:: Tokola, H.
Järvenpää, E.
Salonen, T.
Lanz, M.
Koho, M.
Niemi, E.
Tematy:: demand forecasting
shop floor control
production flexibility
inventory control
interview; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/407355.pdf Link otwiera się w nowym oknie
Opis:: This paper publishes the results of interviews regarding shop-floor-level control of 18 Finnish manufacturing companies. The interviews had 17 open questions relating to demand characteristics, shop floor-level control issues, production flexibility, inventory control, and potential development areas. In order to get insights from the interviews, this paper analyses the answers from the interviews and categorises them into typical answers. The companies that were interviewed are also categorised as small companies with their own end products, subcontractors, or large companies with their own end products, and the emphasis of the analysis is on how companies differ in their shop floor-level control. The results show that different types of companies have different characteristics. Small companies are characterised by constant workflow, seasonal trends in demand, and the use of forecasts. Subcontractors have great daily variation in their demand and processing times. Large companies tend to focus on inventory issues.
Dostawca treści:: Biblioteka Nauki

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