Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements. Issue 3 (4th May 2018)
- Record Type:
- Journal Article
- Title:
- Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements. Issue 3 (4th May 2018)
- Main Title:
- Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements
- Authors:
- Klumpp, Matthias
- Abstract:
- ABSTRACT: Increasing application areas and depths of autonomous systems in logistics provide a new level of challenge for the analysis and design of human–machine interaction concepts. Due to scarce high-skilled personnel in several regions and the objectives of efficiency and sustainability improvement, logistics operators have to pursue technological progress like automation with all means. In order to distinguish between more or less performing human–artificial collaboration systems in logistics ex ante for investment decision purposes, a multi-dimensional conceptual framework is developed. A comprehensive case study regarding automated truck driving in logistics is provided in order to test the concept concerning practical implications. Results include the notion of four distinctive and increasing resistance levels before finally an efficient 'trusted' collaboration between human operators and artificial intelligence systems can be achieved. This is important for the design of many automated systems in logistics, among others for driving and piloting professions regarding autonomous driving supervision.
- Is Part Of:
- International journal of logistics. Volume 21:Issue 3(2018)
- Journal:
- International journal of logistics
- Issue:
- Volume 21:Issue 3(2018)
- Issue Display:
- Volume 21, Issue 3 (2018)
- Year:
- 2018
- Volume:
- 21
- Issue:
- 3
- Issue Sort Value:
- 2018-0021-0003-0000
- Page Start:
- 224
- Page End:
- 242
- Publication Date:
- 2018-05-04
- Subjects:
- Automation in logistics -- trusted collaboration human–artificial performance analysis -- acceptance model -- autonomous driving -- human–machine interaction
Business logistics -- Periodicals
658.005 - Journal URLs:
- http://www.tandfonline.com/ ↗
- DOI:
- 10.1080/13675567.2017.1384451 ↗
- Languages:
- English
- ISSNs:
- 1367-5567
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.321700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14532.xml