Return to search

Impact of IoT Enabled Service Solutions in the Downstream Automotive Supply Chain

The automotive industry has been an integral element of global economy for many decades and has withstood economic downturns by being able to shift their processes along with market needs. With the addition of new innovations in the field of ICT, the automotive industry has addressed the need to restructure to stay afront of customers‘ expectation. Internet of Things and Big Data have advanced to where connected solutions are possible to provide value opportunities in many industries including automotives with the entrance of connected vehicles. This thesis aims to investigate the extent that connected services could be applied to the downstream automotive supply chain as a viable long-term business solution. A door-to-door perspective was applied in order to identify the challenges and opportunities towards different stakeholders within this supply chain. Qualitative interviews were conducted with leading OEMs, Logistics Providers, NSC, and car dealers as well as quantitative analysis performed on car buying customers to gauge their opinions of connected vehicles and services. There are many opportunities for a viable connected service solution to offer additional value to each stakeholder including efficient supply chain management due to increased visibility, improved lead times, and operational effectiveness. However, with the complexity and variations in the supply chain it cannot be applied rapidly and requires all actors to agree to participation in a network that supports the IT infrastructures and fortifies information flow.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-170556
Date January 2014
CreatorsAikaterini, Micheli
PublisherKTH, Skolan för datavetenskap och kommunikation (CSC)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

Page generated in 0.0125 seconds