The Economics of Multi-Hop Ride Sharing - Creating New Mobility Networks Through IS

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

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

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

Simulation-based Evaluation of Battery Switching Stations for Electric Vehicles

To meet future mobility challenges, major original equipment manufacturers (OEM) are pushing forward various technical solutions. The electric drive is considered to be a particularly promising approach. Yet, the required battery technology brings new limitations: Besides long charging times and high costs, very limited range is seen as a major disadvantage. While most OEMs focus on charging the battery in the car, some pursue an approach that combines charging with battery swapping. This allows the driver to automatically get an empty battery replaced with a charged one in a switch station. Both the extensive infrastructure as well as the necessity of buying additional batteries result in additional cost for customers and switch station companies. With the help of a simulation model, this paper explores requirements for battery inventory as well as switching station utilization. We find that for a higher number of customers, the pooling effect of stochastic variables will greatly reduce the number of spare batteries per customer. Switching stations therefore provide a well-suited business case for station operators which enables efficient re-use of batteries and contributes to a greener mobility system. Additionally, customers could be incentivized to purchase cars with changeable batteries

Creativity and productivity in product design for additive manufacturing

The present study explores the phenomenon of remixing in product design for additive manufacturing (AM). In contrast to other manufacturing techniques, AM offers unprecedented flexibility in adapting existing product designs to changing requirements. However, in order to benefit from this potential, structured design procedures and tools are indispensable. As a possible solution, online platforms for collaborative 3D model creation are increasingly implementing features for remixing, a concept describing the creation of new models on the foundation of existing design elements. Against this backdrop, the objective of this research is to provide evidence for the value of remixing as an organizational intervention for improving product design processes. To this end, we present a mixed methods approach using data from Thingiverse, the world's largest AM-related online community. In a first step, we investigate qualitative data from 81 individual remix-based designs to identify the underlying mechanisms of remixing. We identify six such mechanisms that can further be grouped by the intended outcome of the respective process (creativity-oriented: inspiration, play, learning; productivity-oriented: speed, improvement, empowerment). In a second step, we turn to a quantitative analysis of platform data, which indicates that remixing may lead to better design process outcomes in terms of quantity and diversity of designs. Furthermore, we find that designs created by remixing designers are significantly more often printed by community members suggesting that remixing helps ensure manufacturing compatibility akin to continuous process improvement. Our research has several implications for individual designers and organizations engaging with product design for AM

Capacity investment choices under cost heterogeneity and output flexibility in oligopoly

We study capacity investment decisions among oligopoly firms under conditions of cost heterogeneity and output flexibility within capacity constraints. Output flexibility causes the value of the firm to be convex in the state of demand, which implies that the firm invests in larger capacity when the economic environment is more uncertain. Under cost heterogeneity among oligopoly firms, a lower-cost firm invests in larger capacity, while a less efficient rival chooses lower capacity as capacities are strategic substitutes. Consequently, higher uncertainty leads to more dispersion of equilibrium capacities and greater industry concentration. More competition thus induces a welfare loss when uncertainty and cost heterogeneity are high