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Solution model for eCommerce distribution logistics for a 3D fibre product

Joensuu, Tanja (2022)

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Joensuu, Tanja
2022
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022052211007
Tiivistelmä
B2B online sales is a phenomenon that has increased in recent years. Launching a new product using online store as sales method is not an easy task, especially when target market is abroad. Many variables need to be considered to ensure cost-effective distribution while keeping the customers satisfied. Target company for the study is piloting a new production method for a new sustainable product and required research on finding a suitable model for its distribution logistics for this new product when sales channel is an online store.

The aim was to conduct research in logistics strategies and distribution methods, and variables affecting these, to find a suitable solution model for a new product’s distribution logistics. The goal was to figure out the most suitable service model that would correlate with company’s sales strategy and customers’ expectations.

Main research question and four sub-questions were defined. Answers to these questions were obtained through literature review, which was used to form theoretical base, and qualitative research that was conducted using half-structured interviews as a research method to find correlating themes.

Results indicated that there are certain characteristics that cannot be ignored when transporting abroad from Finland. Longer lead times due to maritime transportation are unavoidable, bigger volumes increase cost-efficiency, information flow is essential for transparency and smooth operations, sustainability adds value and agility is necessary when working in eCommerce environment.

Based on the results a suggestion for solution model was proposed. Further research could be done when the actual production has been established and market predictions are easier to make to consider possible relocation of the production closer to market areas.
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