Research Repository

See what's under the surface

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

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

Authors

Dirk C. Moosmayer

Alain Yee Loong Chong

Martin J. Liu

Bjoern Schuppar

Abstract

Price premiums are a key profit driver for long-term business relationships. For sellers in business-to-business (B2B) relationships, it is important to have appropriate strategies to negotiate price increases without trading off the relationships with their buyers. This paper aims to understand the annual price negotiation processes of companies by predicting whether a seller’s reservation price, target price, and initial offer positively affect the price negotiation outcome between the sellers and buyers. Data from 284 B2B relationships of a chemicals supplier based in Germany was used to examine our research model. In order to capture the non-linear decisions that are involved in price negotiations and to address collinearity among negotiations’ determinants, neural network analysis was used to predict the factors that influence price negotiation outcome. The neural network model was then compared with the results from regression analysis. Compared to regression analysis, the neural network has a lower standard error, and it showed that target price played a more important role in B2B price negotiations. The neural network was also able measure non-linear, non-compensatory decisions that are involved in price negotiations. The results imply that neural networks should be more widely used by researchers to address the threats that multi-collinearity poses. For companies, the results imply that price targets should be actively managed, e.g. through clear financial aims or through seminars aiming to help sales personnel to establish more challenging negotiation aims.

Journal Article Type Article
Publication Date Jun 15, 2013
Journal Expert Systems with Applications
Print ISSN 0957-4174
Electronic ISSN 0957-4174
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 40
Issue 8
Institution Citation Moosmayer, D. C., Chong, A. Y. L., Liu, M. J., & Schuppar, B. (2013). A neural network approach to predicting price negotiation outcomes in business-to-business contexts. Expert Systems with Applications, 40(8), doi:10.1016/j.eswa.2012.12.018
DOI https://doi.org/10.1016/j.eswa.2012.12.018
Keywords Business-to-business marketing; Price negotiation; Neural network; Regression analysis
Publisher URL http://www.sciencedirect.com/science/article/pii/S0957417412012596
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

Files

A neural network approach to predicting price negotiation outcomes in business-to-business contexts.pdf (604 Kb)
PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0



Downloadable Citations