A neural network approach to predicting price negotiation outcomes in business-to-business contexts

Moosmayer, Dirk C.; Chong, Alain Yee‐Loong; Liu, Martin; Schuppar, Bjoern

doi:10.1016/j.eswa.2012.12.018

Cited by 46 publications

(25 citation statements)

References 68 publications

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“…Neural network can detect complex non-linear relations and all possible interactions that are not pre-defined, thus the studying of independent and dependent variables is not limited by hypothesised relationships (Sargent 2001;Moosmayer et al 2013;Teo et al 2015). Also, neural network is non-parametric model.…”

Section: Neural Networkmentioning

confidence: 98%

Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews

Chong

Ch’ng

Liu

et al. 2015

International Journal of Production Research

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161

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This study aims to investigate the contributions of online promotional marketing and online reviews as predictors of consumer product demands. Using electronic data from Amazon.com, we attempt to predict if online review variables such as valence and volume of reviews, the number of positive and negative reviews, and online promotional marketing variables such as discounts and free deliveries, can influence the demand of electronic products in Amazon.com. A Big Data architecture was developed and Node.JS agents were deployed for scraping the Amazon.com pages using asynchronous Input/Output calls. The completed Web crawling and scraping data-sets were then preprocessed for Neural Network analysis. Our results showed that variables from both online reviews and promotional marketing strategies are important predictors of product demands. Variables in online reviews in general were better predictors as compared to online marketing promotional variables. This study provides important implications for practitioners as they can better understand how online reviews and online promotional marketing can influence product demands. Our empirical contributions include the design of a Big Data architecture that incorporate Neural Network analysis which can used as a platform for future researchers to investigate how Big Data can be used to understand and predict online consumer product demands.

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Section: Neural Networkmentioning

confidence: 98%

Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews

Chong

Ch’ng

Liu

et al. 2015

International Journal of Production Research

Self Cite

161

View full text Add to dashboard Cite

show abstract

“…En [50] la red neuronal fue integrada con un algoritmo de optimización basado en colonias de hormigas, mostrando mejores resultados que una red neuronal convencional. En [52] los resultados de la red neuronal fueron comparados con un análisis de regresión, mostrando que la red neuronal tiene un error estándar inferior.…”

Section: Implementación Y Resultados De Redes Neuronalesunclassified

“…Por otra parte, en [52] se utilizó una red neuronal con el objeto de predecir el precio de reserva del vendedor, precio objetivo y la oferta inicial. De esta manera se apoyaría a los procesos de negociación de precios entre vendedores y compradores.…”

Section: Procesos Scor Y Redes Neuronalesunclassified

Aplicaciones de inteligencia artificial en procesos de cadenas de suministros: una revisión sistemática

Ahumada

2016

Ingeniare. Rev. chil. ing.

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RESUMENUna cadena de suministro (SC) es una red de empresas que producen, venden y entregan un producto o servicio a un segmento de mercado predeterminado. No solo incluye a los fabricantes y proveedores, sino que también a transportistas, almacenes, minoristas y los propios clientes, entre otros. Debido al avance tecnológico, específicamente en áreas como las comunicaciones, procesamiento computacional, gestión y almacenamiento de información, es posible apoyar a la administración de cadenas de suministros pudiendo hacerla mas eficiente. En este contexto, la inteligencia artificial (IA) ha sido aplicada en diferentes procesos de SC pero no hay conocimiento especifico sobre cuáles técnicas de IA están siendo aplicadas (o no) en los procesos de la SC o cuáles actividades de la SC están siendo apoyadas (o no) con técnicas de IA. Con base a lo anterior, el objetivo de este trabajo fue establecer de forma empírica el aporte de la IA en procesos de la SC, para luego establecer actividades de investigación a realizarse en el futuro. Para lograr esto, se realizó una revisión sistemática considerando el modelo SCOR como referencia para procesos de una SC. Los principales resultados indican que los algoritmos genéticos y los agentes inteligentes son las técnicas más investigadas para procesos de la SC relacionados con la planificación y, en menor medida, a procesos relacionados con la entrega de productos. Además, existe una tendencia a incluir la incertidumbre como trabajo futuro en diferentes técnicas de IA de manera que los modelos se acerquen más a la realidad.Palabras clave: Inteligencia artificial, modelo SCOR, revisión sistemática, cadena de suministros. ABSTRACT A supply chain (SC) is a network of companies that produce

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“…When sequence has the higher self correlation, applying time series forecasting model to forecast will achieve good results. Durbin-Watson method is commonly used as inspection methods [4] [5]. Self correlation of data can be obtained using Matlab software [6].…”

Section: A Data Acquisition and Preprocessingmentioning

confidence: 99%

Prediction of Short Term Exchange Rate Using BP Neural Network

Liu¹

2017

Proceedings of the 2017 International Conference on Education Science and Economic Management (ICESEM 2017)

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Abstract-Exchange rate prediction accuracy is often about the survival of an enterprise or even national economic environment security. The effect of predicting the short-term exchange rate with general statistical method is not ideal. This paper proposed a multi-layer BP neural network model to predict short-term exchange rate. We conducted simulation experiments in Matlab 2010b, using data from China Merchants Bank foreign exchange market analysis software V2.8. The results show a better goodness of fit. It indicates that BP neural network can be of practical use in predicting short term exchange rate with high rate of accuracy.

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A neural network approach to predicting price negotiation outcomes in business-to-business contexts

Cited by 46 publications

References 68 publications

Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews

Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews

Aplicaciones de inteligencia artificial en procesos de cadenas de suministros: una revisión sistemática

Prediction of Short Term Exchange Rate Using BP Neural Network

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