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Auflistung nach Autor:in "Flath, Christoph M."

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  • Zeitschriftenartikel
    Call for Papers, Issue 1/2024
    (Business & Information Systems Engineering: Vol. 64, No. 4, 2022) Lin, Jerry Chun-Wei; Srivastava, Gautam; Zhang, Yu-Dong; Flath, Christoph M.
  • Zeitschriftenartikel
    Challenges and Outcomes Using Big Data as a Service
    (Business & Information Systems Engineering: Vol. 66, No. 1, 2024) Srivastava, Gautam; Flath, Christoph M.; Lin, Jerry Chun-Wei; Zhang, Yu-Dong
  • Zeitschriftenartikel
    Predictive End-to-End Enterprise Process Network Monitoring
    (Business & Information Systems Engineering: Vol. 65, No. 1, 2023) Oberdorf, Felix; Schaschek, Myriam; Weinzierl, Sven; Stein, Nikolai; Matzner, Martin; Flath, Christoph M.
    Ever-growing data availability combined with rapid progress in analytics has laid the foundation for the emergence of business process analytics. Organizations strive to leverage predictive process analytics to obtain insights. However, current implementations are designed to deal with homogeneous data. Consequently, there is limited practical use in an organization with heterogeneous data sources. The paper proposes a method for predictive end-to-end enterprise process network monitoring leveraging multi-headed deep neural networks to overcome this limitation. A case study performed with a medium-sized German manufacturing company highlights the method’s utility for organizations.
  • Zeitschriftenartikel
    The Economics of Multi-Hop Ride Sharing
    (Business & Information Systems Engineering: Vol. 57, No. 5, 2015) Teubner, Timm; Flath, Christoph M.
    Ride sharing allows to share costs of traveling by car, e.g., for fuel or highway tolls. Furthermore, it reduces congestion and emissions by making better use of vehicle capacities. Ride sharing is hence beneficial for drivers, riders, as well as society. While the concept has existed for decades, ubiquity of digital and mobile technology and user habituation to peer-to-peer services and electronic markets have resulted in particular growth in recent years. This paper explores the novel idea of multi-hop ride sharing and illustrates how information systems can leverage its potential. Based on empirical ride sharing data, we provide a quantitative analysis of the structure and the economics of electronic ride sharing markets. We explore the potential and competitiveness of multi-hop ride sharing and analyze its implications for platform operators. We find that multi-hop ride sharing proves competitive against other modes of transportation and has the potential to greatly increase ride availability and city connectedness, especially under high reliability requirements. To fully realize this potential, platform operators should implement multi-hop search, assume active control of pricing and booking processes, improve coordination of transfers, enhance data services, and try to expand their market share.
  • Zeitschriftenartikel
    Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems
    (Business & Information Systems Engineering: Vol. 61, No. 1, 2019) 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 established retail environments is challenging as architectural constraints, well-established customer processes, and customer expectations regarding privacy and convenience impose limits on system design. To overcome these challenges, the authors design an IT artifact that leverages an RFID sensor infrastructure and software components (data processing and prediction routines) to jointly address the central problems of detecting purchases in a reliable and timely fashion and assigning these purchases to individual shopping baskets. The system is implemented and evaluated in a research laboratory under real-world conditions. The evaluation indicates that shopping baskets can indeed be detected reliably (precision and recall rates greater than 99%) and in an expeditious manner (median detection time of 1.03 s). Moreover, purchase assignment reliability is 100% for most standard scenarios but falls to 42% in the most challenging scenario.
  • Zeitschriftenartikel
    Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems
    (Business & Information Systems Engineering: Vol. 61, No. 1, 2019) 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 established retail environments is challenging as architectural constraints, well-established customer processes, and customer expectations regarding privacy and convenience impose limits on system design. To overcome these challenges, the authors design an IT artifact that leverages an RFID sensor infrastructure and software components (data processing and prediction routines) to jointly address the central problems of detecting purchases in a reliable and timely fashion and assigning these purchases to individual shopping baskets. The system is implemented and evaluated in a research laboratory under real-world conditions. The evaluation indicates that shopping baskets can indeed be detected reliably (precision and recall rates greater than 99%) and in an expeditious manner (median detection time of 1.03 s). Moreover, purchase assignment reliability is 100% for most standard scenarios but falls to 42% in the most challenging scenario.
  • Zeitschriftenartikel
    Welcome to the Era of ChatGPT et al.
    (Business & Information Systems Engineering: Vol. 65, No. 2, 2023) Teubner, Timm; Flath, Christoph M.; Weinhardt, Christof; Aalst, Wil; Hinz, Oliver