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Simona Elena Dragomirescu,Daniela Cristina Solomon
One of the most important stages in the budget drafting process is the sales forecasting. As a matter of fact, the sales affect the whole activity of a company, their variation being considered the main risk factor for the performance and the financial p...
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Tian Luo, Daofang Chang and Zhenyu Xu
Accurate sales forecasting can provide a scientific basis for the management decisions of enterprises. We proposed the xDeepFM-LSTM combined forecasting model for the characteristics of sales data of apparel retail enterprises. We first used the Extreme ...
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Konstantinos P. Fourkiotis and Athanasios Tsadiras
In today?s evolving global world, the pharmaceutical sector faces an emerging challenge, which is the rapid surge of the global population and the consequent growth in drug production demands. Recognizing this, our study explores the urgent need to stren...
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Patrícia Ramos, José Manuel Oliveira, Nikolaos Kourentzes and Robert Fildes
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Patrícia Ramos and José Manuel Oliveira
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Chandadevi Giri and Yan Chen
Compared to other industries, fashion apparel retail faces many challenges in predicting future demand for its products with a high degree of precision. Fashion products? short life cycle, insufficient historical information, highly uncertain market dema...
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Linda Eglite,Ilze Birzniece
Pág. 53 - 62
This systematic literature review examines the deep learning (DL) models for retail sales forecast. The accuracy of a retail sales forecast is a prevalent force for uninterrupted business operations. Accuracy for retailers means limiting supply chain and...
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Lorenzo Menculini, Andrea Marini, Massimiliano Proietti, Alberto Garinei, Alessio Bozza, Cecilia Moretti and Marcello Marconi
Setting sale prices correctly is of great importance for firms, and the study and forecast of prices time series is therefore a relevant topic not only from a data science perspective but also from an economic and applicative one. In this paper, we exami...
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Daniella Frias,Carolina Cavour Siqueira Muniz,Pedro Senna Vieira,Dominique Souza Sant?anna,Augusto da Cunha Reis
Pág. 1606 - 1623
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Kevin William Matos Paixão,Adriano Maniçoba da Silva
Pág. 1324 - 1340
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V. A. Hertsyk
Pág. 248 - 252
The author considers the principal methods, both qualitative and quantitative ones, as well as simulation in forecasting product sales. The author suggests a system simulation method, which will enable to obtain indexes complementing each other and will ...
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Juan Manuel García Sánchez, Xavier Vilasís Cardona and Alexandre Lerma Martín
A methodology to prove the influence of car configurator webpage data for automotive manufacturers is developed across this research. Firstly, the correlation between online data and sales is measured. Afterward, car variant sales are predicted using a s...
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Elena Anatol?evna Derunova,Irina Nikolayevna Filatova,Alexandr Sergeevich Semenov,Vladimir Alexandrovich Derunov
Pág. 112 - 118
The formation of demand forecasting models is important in understanding the transition from the raw to the innovative model of the economy. The aim of the study is to analyze and evaluate the different innovation demand forecasting models and the mathem...
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Ayesha Ubaid, Farookh Hussain and Muhammad Saqib
Demand forecasting has a pivotal role in making informed business decisions by predicting future sales using historical data. Traditionally, demand forecasting has been widely used in the management of production, staffing and warehousing for sales and m...
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Audrone Lupeikiene,Mubashrah Saddiqa
Pág. I - II
The 30th issue of CSIMQ includes four articles that cover research problems in the field of digital business systems. Two of the selected articles are systematic literature reviews, while the other two provide methodological additions to the theory. Syst...
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Hongyan Jiang, Dianjun Fang, Klaus Spicher, Feng Cheng and Boxing Li
A period-sequential index algorithm with sigma-pi neural network technology, which is called the (SPNN-PSI) method, is proposed for the prediction of time series datasets. Using the SPNN-PSI method, the cumulative electricity output (CEO) dataset, Volksw...
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Pág. 25 - 53
Decomposition regression incorporating contextual factors seems to be a natural choice for exploiting both reliability of statistical forecasting and flexibility of judgmental forecasting using contextual information. However, such a regression model suf...
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Giuseppe Giunta, Alessandro Ceppi and Raffaele Salerno
Earth system predictions, from sub-seasonal to seasonal timescales, remain a challenging task, and the representation of predictability sources on seasonal timescales is a complex work. Nonetheless, advances in technology and science have been making con...
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Treerak Kongthanasuwan, Nakarin Sriwiboon, Banpot Horbanluekit, Wasakorn Laesanklang and Tipaluck Krityakierne
The automotive and auto parts industries are important economic sectors in Thailand. With rapidly changing technology, every organization should understand what needs to be improved clearly, and shift their strategies to meet evolving consumer demands. T...
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Alireza Rezazadeh
Predicting the outcome of sales opportunities is a core part of successful business management. Conventionally, undertaking this prediction has relied mostly on subjective human evaluations in the process of sales decision-making. In this paper, we addre...
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