Benchmarking Approach to Support Technology Investment Decisions: A Study of Technology Implementation in Last-mile Distribution
Pyykkö, Harri; Lauhkonen, Arttu; Hinkka, Ville; Karvonen, Hannu; Leviäkangas, Pekka (2024-05-17)
Universitas Indonesia
17.05.2024
Pyykkö, H., Lauhkonen, A., Hinkka, V., Karvonen, H., Leviäkangas, P., 2024. Benchmarking Approach to Support Technology Investment Decisions: A Study of Technology Implementation in Last-mile Distribution. International Journal of Technology. Volume 15(3), pp. 517-530
https://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons License: International Journal of Technology is licensed under a Creative Commons Attribution - NonCommercial - NoDerivs 4.0 (CC BY - NC - ND).
https://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons License: International Journal of Technology is licensed under a Creative Commons Attribution - NonCommercial - NoDerivs 4.0 (CC BY - NC - ND).
https://creativecommons.org/licenses/by-nc-nd/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202406144549
https://urn.fi/URN:NBN:fi:oulu-202406144549
Tiivistelmä
Abstract
The rapid increase in business-to-consumer online retail has challenged the existing distribution models. Seamlessly integrated, more sustainable and digitalized last-mile distribution processes are vital to meeting the requirements posed by future online retail. Investments to new and more advanced technological solutions are needed to improve the operational performance and to meet all the external requirements. The variety of available technological solutions creates a significant, multi-layered challenge to individual organizations’ ability to select the most fit-for-purpose technology for their own and their customers’ needs. This is a well-recognized issue at the front end of the innovation process and it calls for deep insight before proceeding to actual product development. This paper describes how domain-specific benchmarking can be a valid tool for increasing strategic knowledge and supporting technology investment decisions. In this research, 16 technologies and technology topics applied to distribution logistics were evaluated in terms of the technologies’ perceived feasibility. The feasibility comprised three technology dimensions – applicability, tangibility and maturity - as benchmarking indicators, chosen on the basis of literature. The demonstrated application of domain-specific benchmarking supports managerial evaluations of individual technologies, as well as enables further customizing the benchmarking indicators to be used in the proposed model.
The rapid increase in business-to-consumer online retail has challenged the existing distribution models. Seamlessly integrated, more sustainable and digitalized last-mile distribution processes are vital to meeting the requirements posed by future online retail. Investments to new and more advanced technological solutions are needed to improve the operational performance and to meet all the external requirements. The variety of available technological solutions creates a significant, multi-layered challenge to individual organizations’ ability to select the most fit-for-purpose technology for their own and their customers’ needs. This is a well-recognized issue at the front end of the innovation process and it calls for deep insight before proceeding to actual product development. This paper describes how domain-specific benchmarking can be a valid tool for increasing strategic knowledge and supporting technology investment decisions. In this research, 16 technologies and technology topics applied to distribution logistics were evaluated in terms of the technologies’ perceived feasibility. The feasibility comprised three technology dimensions – applicability, tangibility and maturity - as benchmarking indicators, chosen on the basis of literature. The demonstrated application of domain-specific benchmarking supports managerial evaluations of individual technologies, as well as enables further customizing the benchmarking indicators to be used in the proposed model.
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