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Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems 

Business & Information Systems Engineering: Vol. 61, No. 1 Hauser, Matthias; Günther, Sebastian A.; Flath, Christoph M.; Thiesse, Frédéric
Automated checkout systems promise greater sales due to an improved customer experience and cost savings because less store personnel is needed. The present design-oriented IS research study is concerned with an automated checkout solution in fashion retail stores. The implementation of such a cyberphysical system in ...

Hybrid Intelligence 

Business & Information Systems Engineering: Vol. 61, No. 5 Dellermann, Dominik; Ebel, Philipp; Söllner, Matthias; Leimeister, Jan Marco

Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems 

Business & Information Systems Engineering: Vol. 61, No. 1 Hauser, Matthias; Günther, Sebastian A.; Flath, Christoph M.; Thiesse, Frédéric
Automated checkout systems promise greater sales due to an improved customer experience and cost savings because less store personnel is needed. The present design-oriented IS research study is concerned with an automated checkout solution in fashion retail stores. The implementation of such a cyberphysical system in ...

Designing Business Analytics Solutions 

Business & Information Systems Engineering: Vol. 62, No. 1 Nalchigar, Soroosh; Yu, Eric
The design and development of data analytics systems, as a new type of information systems, has proven to be complicated and challenging. Model based approaches from information systems engineering can potentially provide methods, techniques, and tools for facilitating and supporting such processes. The contribution of ...

An ETA Prediction Model for Intermodal Transport Networks Based on Machine Learning 

Business & Information Systems Engineering: Vol. 62, No. 5 Balster, Andreas; Hansen, Ole; Friedrich, Hanno; Ludwig, André
Transparency in transport processes is becoming increasingly important for transport companies to improve internal processes and to be able to compete for customers. One important element to increase transparency is reliable, up-to-date and accurate arrival time prediction, commonly referred to as estimated time of arrival ...

Watch Me Improve—Algorithm Aversion and Demonstrating the Ability to Learn 

Business & Information Systems Engineering: Vol. 63, No. 1 Berger, Benedikt; Adam, Martin; Rühr, Alexander; Benlian, Alexander
Owing to advancements in artificial intelligence (AI) and specifically in machine learning, information technology (IT) systems can support humans in an increasing number of tasks. Yet, previous research indicates that people often prefer human support to support by an IT system, even if the latter provides superior ...

Not All Doom and Gloom:ÿHow Energy-Intensive and Temporally Flexible Data Center Applications May Actually Promote Renewable Energy Sources (**encoding or data invalid**) 

Business & Information Systems Engineering: Vol. 63, No. 3 Fridgen, Gilbert; Körner, Marc-Fabian; Walters, Steffen; Weibelzahl, Martin
To achieve a sustainable energy system, a further increase in electricity generation from renewable energy sources (RES) is imperative. However, the development and implementation of RES entail various challenges, e.g., dealing with grid stability issues due to RES? intermittency. Correspondingly, increasingly volatile ...

Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction 

Business & Information Systems Engineering: Vol. 63, No. 3 Kratsch, Wolfgang; Manderscheid, Jonas; Röglinger, Maximilian; Seyfried, Johannes
Predictive process monitoring aims at forecasting the behavior, performance, and outcomes of business processes at runtime. It helps identify problems before they occur and re-allocate resources before they are wasted. Although deep learning (DL) has yielded breakthroughs, most existing approaches build on classical ...

AI Startup Business Models 

Business & Information Systems Engineering: Vol. 64, No. 1 Weber, Michael; Beutter, Moritz; Weking, Jörg; Böhm, Markus; Krcmar, Helmut
We currently observe the rapid emergence of startups that use Artificial Intelligence (AI) as part of their business model. While recent research suggests that AI startups employ novel or different business models, one could argue that AI technology has been used in business models for a long time already—questioning the ...

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Author

Flath, Christoph M. (2)Günther, Sebastian A. (2)Hauser, Matthias (2)Thiesse, Frédéric (2)Adam, Martin (1)Balster, Andreas (1)Benlian, Alexander (1)Berger, Benedikt (1)Beutter, Moritz (1)Böhm, Markus (1)... View More

Subject

Machine learning (9)
Artificial intelligence (3)Automated checkout systems (2)Cyberphysical systems (2)Design-oriented IS research (2)Digital innovation (2)Internet of things (2)Radio frequency identification (2)Retail industry (2)Advice taking (1)... View More

Date Issued

2019 (3)2021 (3)2020 (2)2022 (1)

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No (9)

About uns | FAQ | Help | Imprint | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.