Abstract
Smaller and mid-sized enterprises in the metal industry often face problems during their sourcing and procurement processes. These problems are caused by the policies of wholesalers, which optimize their business processes by passing on better, i.e. cheaper prices for bulk procurement or even just selling products only in large quantities. These policies mainly confer benefits to big companies and leading to the elimination of small customers who want to order only small amounts of a product. That is the reason why smaller and mid-sized metal enterprises must invest a lot of time to find the right suppliers and to order the right products. To save time and money, there are already a few known approaches like marketplaces and shops. However, these solutions do neither solve the problem of finding the right wholesaler nor do they automate the whole process from order to delivery. This paper focuses on an approach to simplify the sourcing and procurement processes by automating parts of it. To achieve this goal, an automated bot technology is suggested which allows for an easy search for dealers and potential suppliers. The implemented bots will be linked to a web crawler with a matching algorithm to detect relevant offers in the world wide web. All information gathered by the crawler will then be processed automatically to start a request for quotation (RFQ) process. The artificial intelligence starts the RFQ process by (1) analyzing existing offers found in the world wide web with Natural Language Processing (NLP) and (2) generating automated written requests to dealers. The algorithm will additionally help by finding other prospective buyers, i.e. other small or mid-sized companies which are interested in the same product. This enables a group of customers to perform bulk procurement together. This paper discusses the current possibilities as well as the practical implications of the suggested approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wigand, R.T.: Electronic commerce: definition, theory, and context. Inf. Soc. 13, 1–16 (1997). https://doi.org/10.1080/019722497129241
Burt, S., Sparks, L.: E-commerce and the retail process: a review. J. Retail. Cons. Serv. Nr. 10, 275–286 (2003). https://doi.org/10.1016/S0969-6989(02)00062-0
Tan, M., Teo, T.S.H.: Factors influencing the adoption of internet banking. Int. J. Electrict Commerce 2, 5–18 (1998). https://doi.org/10.1080/10864415.1998.11518312
Clement, J.: Retail e-commerce sales worldwide from 2014 to 2012 (in billion U.S.dollars). https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/ Accessed 15 July 2020
Sana Commerce: Der digitale Wandel im B2B-Einkauf - Report 2019 (2019)
Sila, I.: Factors affecting the adoption of B2B e-commercetechnologies. Electronig Comm. Res. 13, 199–236 (2013). https://doi.org/10.1007/s10660-013-9110-7
Goasduff, L.: Chatbots Will Appeal to Modern Workers - Smarter With Gartner. https://www.gartner.com/smarterwithgartner/chatbots-will-appeal-to-modern-workers/ Accessed 17 July 2020
Leung, K., Luk, C., Choy, K.L.H., Lee, C.K.: A B2B flexible pricing decision support system formanaging the request for quotation process undere-commerce business environment. Int. J. Prod. Res. 57(20), 6528–6551 (2019). https://doi.org/10.1080/00207543.2019.1566674
Volpi, M.: RFQ and Sourcing in Purchasing Process, Central In-formation Technology and Organisation (2019)
Amazon.com Inc.: Amazon Business Prime. https://www.amazon.de/businessprimeAccessed 02 Aug. 2020
ONE.Konzern Business Plattform: Willkommen auf der ONE.Konzern Business Plattform. https://www.vwgroupsupply.com/one-kbp-pub/de/kbp_public/homepage/homepage.html Accessed 02 Aug. 2020
Wer liefert was: “Wer liefert was’’ - Der führende B2B-Marktplatz [“Who supplies what” - The leading B2B Marketplace], Visable GmbH https://www.wlw.de/Accessed 02 Aug. 2020
Hevner, A. et al.: Design Science in Information Systems Research. Management Information Systems Quarterly, p. 75 (2004)
Shelar, H., Kaur, G., Heda, N., Agrawal, P.: Named entity recognition approaches and their comparison for custom ner model. Science & Technology Libraries, pp. 1–14 (2020)
Abdul-Kader, S.A.: Question answer system for online feedable new born chatbot. In: Intelligent Systems Conference, London (2017)
Dolle, N., Wilhelm, C., Rössle, M.: Applying modern text processing technologies to implement a self-learning marketplace by using cloud services as an example. Lect. Notes Netw. Syst. 117, 450–459 (2020)
Webber, J.: A Programmatic Introduction to Neo4j, Addison-Wesley Professional, pp. 217–218 (2012) https://doi.org/10.1145/2384716.2384777
Fernandes, D., Bernardino, J.: Graph Databases Comparison: AllegroGraph, ArangoDB, InfiniteGraph, Neo4J, and OrientDB. In: Conference: 7th International Conference on Data Science, Technology and Applications, pp. 373–380 (2018) https://doi.org/10.5220/0006910203730380
Li, Y., Han, P., Liu, C., Fang, B.: Automatically crawling dynamic web applications via proxy-based javascript injection and runtime analysis. In: IEEE Third International Conference on Data Science in Cyberspace (DSC), pp. 242–249 (2018) https://doi.org/10.1109/DSC.2018.00042
Orbweaver, H.Q.: RFQ Definition: How Automation Will Streamline Your Business/Orbweaver. https://www.orbweaver.com/rfq-definition-how-automation-will-streamline-your-business/ Accessed 30 Aug. 2020
Pennell, J.: Automate the RFQ Process With Laserfiche. https://www.laserfiche.com/solutionexchange/mw-industries-automated-request-quote-rfq-process-laserfiche-forms/Accessed 30 Aug. 2020
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Dolle, N., Wilhelm, C., Wergunow, A., Rössle, M., Fernandes, M., Glißmann, L. (2021). An Artificial Intelligence Based Sourcing Automation Concept for Smaller and Mid-Sized Enterprises in the Metal Industry. In: Kabashkin, I., Yatskiv, I., Prentkovskis, O. (eds) Reliability and Statistics in Transportation and Communication. RelStat 2020. Lecture Notes in Networks and Systems, vol 195. Springer, Cham. https://doi.org/10.1007/978-3-030-68476-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-68476-1_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-68475-4
Online ISBN: 978-3-030-68476-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)