Moritz von Hoffen

Designing a Peer-to-Peer Sharing Service as Fuel for the Development of the Electric Vehicle Charging Infrastructure

The general public and politics discuss electric vehicles (EVs) as promising means for achieving clean, carbon-free, and sustainable individual transportation. However, an insufficient charging infrastructure hampers a rapid diffusion of EVs. At the same time, investors have refrained from developing an EV-charging infrastructure on a large scale because of the limited demand for EVs. Against this backdrop, peer-to-peer (P2P) sharing and collaborative consumption (SCC) is a promising strategy with which to address this problem. This article describes the concept of an IT-based P2P SCC service and the research activities needed for its design. We do so by introducing a novel application of the sharing economy. Our primary contribution is to take a step toward finding a solution for a problem in the EV domain that is relevant for society. A second contribution lies in the introduction and discussion of predominantly infrastructure-creating (PIC) P2P SCC services and their characteristics.

Enabling Semantically Enriched Data Analytics by Leveraging Topology-based Mobile Network Context Ontologies

The OpenMobileNetwork is an open platform that provides approximated and semantically enriched mobile network and WiFi access point topology data based on the principles of Linked Data. By making use of the data within the Linking Open Data Cloud, this platform enables the development of new and sophisticated location-based services for the end consumer that also incorporate the semantics of a location rather than plain geospatial information. More importantly, it gives mobile network operators the opportunity to exploit their asset (being their network topology) for innovative services based on semantically enriched data analytics such as identifying location hotspots or traffic heat maps. The foundation of the OpenMobileNetwork is an ontology comprising static and dynamic network context facets that describe mobile and WiFi access point networks from a topological perspective (e.g., base stations, their locations and coverage areas). Within this paper, we present this ontology in detail and demonstrate its applicability in a power management scenario for mobile networks.

Designing an Ontology-Based Web Directory for the Discovery of Sharing and Collaborative Consumption Platforms

A vast number of peer-to-peer (P2P) sharing and collaborative consumption (SCC) platforms has emerged over the last decade. These platforms allow private individuals to share their physical resources, such as vehicles, spaces, food, clothing, gear and even pets, with other private persons. The large number and diversity of the platforms make it difficult for potential peer-consumers and peer-providers to find an appropriate platform for their demands or offers. This research therefore designs an ontology-based web directory which facilitates an effective discovery of P2P SCC platforms. The paper includes three major contributions. First, we formalize concepts identified in the SCC literature by means of a description language. Second, we develop an ontology that provides a means to purposefully describe the domain of SCC platforms. Third, we describe the design of a web directory that uses the ontology to make discovering P2P SCC platforms more approachable.

Leveraging social media to gain insights into service delivery: a study on Airbnb

Consumers increasingly rely on reviews and social media posts provided by others to get information about a service. Especially in the Sharing Economy, the quality of service delivery varies widely; no common quality standard can be expected. Because of the rapidly increasing number of reviews and tweets regarding a particular service, the available information becomes unmanageable for a single individual. However, this data contains valuable insights for platform operators to improve the service and educate individual providers. Therefore, an automated tool to summarize this flood of information is needed. Various approaches to aggregating and analyzing unstructured texts like reviews and tweets have already been proposed. In this research, we present a software toolkit that supports the sentiment analysis workflow informed by the current state-of-the-art. Our holistic toolkit embraces the entire process, from data collection and filtering to automated analysis to an interactive visualization of the results to guide researchers and practitioners in interpreting the results. We give an example of how the tool works by identifying positive and negative sentiments from reviews and tweets regarding Airbnb and delivering insights into the features of service delivery its users most value and most dislike. In doing so, we lay the foundation for learning why people participate in the Sharing Economy and for showing how to use the data. Beyond its application on the Sharing Economy, the proposed toolkit is a step toward providing the research community with an instrument for a holistic sentiment analysis of individual domains of interest.

Business Development in the Sharing Economy: A Business Model Generation Framework

Recent success stories such as those of Airbnb or Uber have proved that the Sharing Economy has evolved from a niche phenomenon to an independent economic sector. Against this backdrop, it is widely recognized that business models—although a research field still based on a highly-fragmented body of knowledge—constitute one of the most important factors to create such success stories. By leveraging the extant literature, a framework for business model generation is proposed, which is specifically tailored to the domain of the Sharing Economy. Hence, this works contribution is multifaceted: Literature is synthesized to cope with the current fragmentation and used to study state-of-the-art business model (generation) approaches. Furthermore, shortcomings in the application of current business model (generation) frameworks with regard to the Sharing Economy are pointed out. The merit of this research is the presentation of a consolidated framework for business model conceptualization and generation in the Sharing Economy.

Towards an Information System for Evidence-Based Analysis of Charging Behavior, Charging Demand, and Battery Degradation of Electric Vehicles

Batteries in Electric Vehicles (EV) are subject to a degradation process that has many, yet not fully understood, influential factors. Typically, the battery is continuously monitored by a proprietary Battery Management System (BMS) which records and analyzes various key figures of the battery. Because the BMS is proprietary, the data collected throughout the lifetime of an EV and its battery cannot simply be looked into by the owner but only by the EV manufacturer and licensed service providers. Hence, the EV owner is dependent on the manufacturer to retrieve accurate data regarding the State of Health (SOH) of the battery, e.g. when selling the vehicle or when the battery needs replacement. An in-depth understanding of charging behavior and the degradation process of an EVs battery requires a vast amount of data, which is a crucial factor limiting current research. This paper proposes an information system that blends into the EV charging infrastructure and utilizes a crowdsourcing approach to collect charging transaction data. In order to identify concealed dependencies with regards to battery degradation and to identify patterns in the charging behavior, an enrichment of the raw transaction data is motivated and different information providers are discussed. This augmentation integrates environmental information from various sources such as weather and location data. On a macroscopic view, analyses could point out the correlation between weather, public events, location, and charging demand. On an individual basis, the effect of environmental impacts, charging behavior, and driving profile on battery degradation can be investigated and compared.

A METHOD FOR MEASURING USER PREFERENCES IN INFORMATION SYSTEMS DESIGN CHOICES

Information System Design (ISD) applies information technology to achieve desired ends in organizations and implies many technology choices to be made. A successful design of information systems addresses the different views of all its stakeholders in these decisions. If we consider that sub-part of an IS that is intended to assist in customer processes, a purposeful assessment of the preferences of this anonymous mass is needed. Methods of Human-Centered ISD are not sufficient in that case for that they require too close integration of the subjects; and state of the art preference measurement techniques are likely to be too time-consuming and cognitively challenging if the number of alternatives is large. Building on the Q-Methodology, originally developed to reveal subjectivity in psychology, we suggest a novel method for user preference measurement. We report on a case in which we failed by applying standard techniques for user measurement, but succeeded with Q-Sort. By means of an experiment we subsequently compare the mentioned methods and identify root causes for failure and success we experienced in the case, which for Q-Sort include short execution time, measuring many design choices at one time, satisfaction of the interviewees, and an effective IT support.

Analyzing the Applicability of the Linking Open Data Cloud for Context-Aware Services

The amount of data within the Linking Open Data (LOD) cloud is steadily increasing and resembles a rich source of information. Since Context-aware Services (CAS) can highly benefit from background information, e.g., about the environment of a user, it makes sense to leverage that enormous amount of data already present in the LOD cloud to enhance the quality of these services. Within this work, the applicability of the LOD cloud as provider for contextual information to enrich CAS is investigated. For this purpose, non-functional criteria of discoverability and availability are analyzed, followed by a presentation of an overview of the different domains covered by the LOD cloud. In order to ease the process of finding a dataset that matches the information needs of a developer of a CAS, techniques for retrieving contents of LOD datasets are discussed and different approaches to condense the dataset to its most important concepts are shown.

A Tale of Two Cities: How High Streets Can Prevail in the Digital Age

The rise of e-commerce and lately m-commerce, and the ongoing digitization have a significant impact on traditional high street retailers, who often are not able to match the prices, variety of products, and services provided online. To prevent the looming decline of high streets, retailers need to catch up and start to engage the new digital customer. This article illuminates the interplay of diverse, digital interfaces, resources and actors in the co-creation of value in high street retail. Alliances and a digital platform ecosystem are presented as forms of cooperation, where retailers join forces to provide digital touchpoints and boundary-spanning service to the customer, and also actively use customer-generated data to improve their service and strengthen the overall attractiveness of their high streets. We tell a tale of two cities—Burnsley and Beckinsdale—set in the not so distant future, where retailers have taken very different approaches to respond to the digital age.

CrowdStrom: Analysis, Design, and Implementation of Processes for a Peer-to-Peer Service for Electric Vehicle Charging

(a) Situation faced: An inadequate number of publicly available charging points is among the main reasons that consumers do not buy electric vehicles (EVs). To address this problem, we suggest a peer-to-peer (P2P) sharing approach for private charging infrastructures. We formed a joint consortium between academia and industry to design and implement a web platform and an underlying business model for an infrastructure of individually owned EV-charging stations for public use. Currently, there are no standardized processes for EV charging, so we had to look elsewhere for processes that could be adapted or partly adopted as a foundation for the proposed web platform. (b) Action taken: We interviewed representatives of seven organizations that are already operating in the domain of EV charging about the relevant business processes. Applying the BPM lifecycle (Dumas et al., Fundamentals of business process management. Springer, 2013), we analyzed the resulting as-is processes for best practices and redesigned them for the scenario of a P2P platform for EV charging. (c) Results achieved: Sixteen to-be processes that comprised registration, authentication, charging, billing, and administration were modeled in BPMN and implemented in a software prototype. The prototype and associated processes are currently being evaluated to ensure their validity and effectiveness in the target environment while the partnering utility company prepares the solution’s staged roll-out to operate their own charging stations and then open the system to other providers. (d) Lessons learned: Analyzing and then designing business processes to reach a common goal has been a unifying factor in our joint research project, where partners from industry and academia have differing backgrounds, expectations, and individual goals. BPM practices enabled the project team to create an innovative business model and corresponding business processes that will have an impact in practice.