Institut für Wirtschaftsinformatik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/17752

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Blockchain technology application domains along the e-commerce value chain - a qualitative content analysis of news articles
(2024) Witt, Josepha; Schoop, Mareike; Gai, Keke; Zhu, Liehuang
Blockchain Technology (BCT) offers several possible applications in the field of electronic commerce (e-commerce), such as decentralised marketplaces or payments in cryptocurrencies. Even though these applications of BCT have already been explored in the academic literature, a comprehensive collection along the whole e-commerce value chain is still missing. Furthermore, the existing comprehensive reviews are based on the academic literature whilst the evolution and further development of BCT is highly driven by practitioners. Therefore, we aim to understand how and why BCT is used in e-commerce based on a qualitative content analysis of news articles, i.e., we apply scientific methods to content which reports the latest developments in the field. As a result, we describe the multiple application domains of BCT along the e-commerce value chain. Subsequently, we discuss the main underlying principles of BCT usage across all the value chain steps.
Cost-neutral reduction of infection risk in picker-to-parts warehousing systems
(2023) Löffler, Maximilian; Schneider, Michael; Žulj, Ivan
The rapid and severe outbreak of COVID-19 caused by SARS-CoV-2 has heavily impacted warehouse operations around the world. In particular, picker-to-parts warehousing systems, in which human pickers collect requested items by moving from picking location to picking location, are very susceptible to the spread of infection among pickers because the latter generally work close to each other. This paper aims to mitigate the risk of infection in manual order picking. Given multiple pickers, each associated with a given sequence of picking tours for collecting the items specified by a picking order, we aim to execute the tours in a way that minimizes the time pickers simultaneously spend in the same picking aisles, but without changing the distance traveled by the pickers. To achieve this, we exploit the degrees of freedom induced by the fact that picking tours contain cycles which can be traversed in both directions, i.e., at the entry to each of these cycles, the decision makers can decide between the two possible directions. We formulate the resulting picking tour execution problem as a mixed integer program and propose an efficient iterated local search heuristic to solve it. In extensive numerical studies, we show that an average reduction of 50% of the total temporal overlap between pickers can be achieved compared to randomly executing the picking tours. Moreover, we compare our approach to a zone picking approach, in which infection risk between pickers can be almost eliminated. However, compared to our approach, the results show that the zone picking approach increases the makespan by up to 1066%.
Gamification of electronic negotiation training: Effects on motivation, behaviour and learning
(2022) Schmid, Andreas; Schoop, Mareike
Organisations are involved in various types of negotiation. As digitalisation advances, such business negotiations are to a large extent electronic negotiations. Consequently, dedicated training for such electronic negotiations is important for mastering negotiation skills. We designed a gamified negotiation system used in e-negotiation training to increase participants’ motivation, engagement, use of the system’s negotiation support features and to improve their decision making. The quantitative evaluation using students as subjects shows higher motivation, engagement and better system and decision-making skills for participants in the gamified training compared to a conventional training. Furthermore, female participants show higher engagement in the gamified training than males. An analysis of the individual elements in the system provides insights into participants’ perceptions and shows that the inclusion of a domain-specific feedback element yields motivational results that are almost similar compared to those using traditional game elements. Organisations can employ the designed artefact for fundamental and effective e-negotiation training.
Opportunities and challenges of blockchain technology for negotiation support systems
(2025) Witt, Josepha; Schoop, Mareike; Knaus, Konstantin
Blockchain Technology (BCT) is the backbone of the next generation of the internet and thus affects how electronic business (e-business) is conducted. While the usage of BCT for the initiation and transaction phases in e-business has been studied, the negotiation aspect has not been considered in a comprehensive manner. The current literature on the utilisation of BCT in electronic negotiations (e-negotiations) primarily focuses on autonomous agents and lacks research on the support of e-negotiations conducted by human negotiators using negotiation support systems (NSSs). This results in the issue that the consequences of a transition to Web3.0-based NSSs are unclear, while other areas of e-business already apply Web3.0 technologies. We address this lack of knowledge following a design-oriented approach in three steps exploring the opportunities and challenges of using BCT for e-negotiations via NSSs. Firstly, the well-established negotiation support system Negoisst is extended by BCT features resulting in the development of a Web3.0-based NSS called NegoisstBCT to demonstrate the technical feasibility of this approach. Secondly, the potential opportunities and challenges of a Blockchain-based NSS are analysed referring to its technical architecture. Thirdly, a generalised view of the application of Web3.0-based NSSs in different settings is taken, discussing future research on BCT in e-negotiations. The present research thus fosters the application of Blockchain-based NSSs in e-negotiations and of NSSs in BCT application areas.
Pattern labelling of business communication data
(2022) Kaya, Muhammed-Fatih
Systematic pattern recognition as well as the corresponding description of determined patterns entail numerous challenges in the application context of high-dimensional communication data. These can cause increased effort, especially with regard to machine-based processing concerning the determination of regularities in underlying datasets. Due to the increased expansion of dimensions in multidimensional data spaces, determined patterns are no longer interpretable by humans. Taking these challenges into account, this paper investigates to what extent pre-defined communication patterns can be interpreted for the application area of high-dimensional business communication data. An analytical perspective is considered by taking into account a holistic research approach and by subsequently applying selected Machine Learning methods from Association Rule Discovery, Topic Modelling and Decision Trees with regard to the overall goal of semi-automated pattern labelling. The results show that meaningful descriptions can be derived for the interpretation of pre-defined patterns.

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