Social Preferences under Risk - Peer Types and Relationships in Economic Decision Making

This work considers economic decision making, particularly scenarios in which the decision maker faces the presence of other (private) persons. It draws inferences for the design, operation, and use of e-commerce platforms from an economic and information systems perspective and is oriented along two vital concepts therein: social preferences and risk. The role of the type as well as the relation towards the reference person is explored from an empirical and game theoretical perspective

Trust isn’t blind: Exploring Visual Investor Cues in Equity Crowdfunding

Overcoming informational uncertainty and financial risk remains a challenge for crowd investors to trust and interact within the equity crowdfunding (ECF) market. Based on the theoretical lens of herding behavior, we demonstrate that visual cues in investor profiles impact the investment decision of subsequent investors. Specifically, this paper provides preliminary evidence on the effect of investor profile images and badges on investment behavior and campaign funding. In a first study, we draw on a dataset of over 30,000 individual investment observations from a leading ECF platform to show that profile images in particular exert positive effects on subsequent investments. Study 2 will build on these findings through a discrete choice experiment. Our results indicate that herding is driven by the perception of credible investors triggered by heuristic cues. Implications for platform operators are discussed in the paper

Takeaway Trust: A market data perspective on reputation portability in electronic commerce

Reputation has become a key factor within today’s online platform landscape. In particular for sellers in electronic commerce, the management of reputation as a signal of trustworthiness has become a relevant business activity. Prior studies have focused on either the role of reputation within given (but platform-bound) environments or general data portability between platforms. The question of cross-platform reputation portability, however, has thus far achieved much less attention. With this exploratory work, we present survey data on consumers’ perception of portable reputation in the platform economy and a case study based on actual (seller) market data from an e commerce marketplace. Our results show that consumers are generally receptive for imported seller reputation. However, for seller ratings to function as an effective signaling device across platform boundaries, adequate means of representation have yet to be found

Privacy in the Sharing Economy

Contemporary C2C platforms, such as Airbnb, have exhibited considerable growth in recent years and are projected to continue doing so in the future. These novel consumer-to-consumer marketplaces have started to obliterate the boundaries between private and economic spheres. Marketing personal resources online is inherently associated with the disclosure of personal and sometimes intimate information. This raises unprecedented questions of privacy. Yet, there is so far little research on the role of privacy considerations in the sharing economy literature. Leveraging the theoretical perspective of privacy calculus, we address this gap by investigating how privacy concerns and economic prospects shape a potential provider’s intentions to share via different communication channels. We relate privacy concerns back to the provider’s perceptions of the audience. We evaluate our research model by means of a scenario-based online survey, providing broad support for our reasoning

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

PEER RATINGS AND ASSESSMENT QUALITY IN CROWD-BASED INNOVATION PROCESSES

Social networks – whether public or in enterprises – regularly ask users to rate their peers’ content using different voting techniques. When employed in innovation challenges, these rating procedures are part of an open, interactive, and continuous engagement among customers, employees, or citizens. In this regard, assessment accuracy (i.e., correctly identifying good and bad ideas) in crowdsourced eval-uation processes may be influenced by the display of peer ratings. While it could sometimes be useful for users to follow their peers, it is not entirely clear under which circumstances this actually holds true. Thus, in this research-in-progress article, we propose a study design to systematically investigate the effect of peer ratings on assessment accuracy in crowdsourced idea evaluation processes. Based on the elaboration likelihood model and social psychology, we develop a research model that incorporates the mediating factors extraversion, locus of control, as well as peer rating quality (i.e., the ratings’ corre-lation with the evaluated content’s actual quality). We suggest that the availability of peer ratings de-creases assessment accuracy and that rating quality, extraversion, as well as an internal locus of control mitigate this effect

The Impact of Computerized Agents on Immediate Emotions, Overall Arousal and Bidding Behavior in Electronic Auctions

The presence of computerized agents has become pervasive in everyday live. In this paper, we examine the impact of agency on human bidders’ affective processes and bidding behavior in an electronic auction environment. In particular, we use skin conductance response and heart rate measurements as proxies for the immediate emotions and overall arousal of human bidders in a lab experiment with human and computerized counterparts. Our results show that computerized agents mitigated 1) the intensity of bidders’ immediate emotions in response to discrete auction events, such as submitting a bid and winning or losing an auction, and 2) the bidders’ overall arousal levels during the auction. Moreover, agency affected bidding behavior and its relation to overall arousal: whereas overall arousal and bids were negatively correlated when competing against human bidders, we did not observe this relationship for computerized agents. In other words, lower levels of agency yield less emotional behavior. The results of our study have implications for the design of electronic auction platforms and markets that include both human and computerized actors

In Stars We Trust – A Note on Reputation Portability Between Digital Platforms

Complementors accumulate reputation on an ever-increasing number of online platforms. While the effects of reputation within individual platforms are well-understood, its potential effectiveness across platform boundaries has received much less attention. This research note considers complementors’ ability to increase their trustworthiness in the eyes of prospective consumers by importing reputational data from another platform. The study evaluates this potential lever by means of an online experiment, during which specific combinations of on-site and imported rating scores are tested. Results reveal that importing reputation can be advantageous – but also detrimental, depending on ratings’ values. Implications for complementors, platform operators, and regulatory bodies concerned with online reputation are considered