Tim Straub

How (not) to Incent Crowd Workers - Payment Schemes and Feedback in Crowdsourcing

Crowdsourcing gains momentum: In digital work places such as Amazon Mechanical Turk, oDesk, Clickworker, 99designs, or InnoCentive it is easy to distribute human work to hundreds or thousands of freelancers. In these crowdsourcing settings, one challenge is to properly incent worker effort to create value. Common incentive schemes are piece rate payments and rank-order tournaments among workers. Tournaments might or might not disclose a worker’s current competitive position via a leaderboard. Following an exploratory approach, we derive a model on worker performance in rank-order tournaments and present a series of real effort studies using experimental techniques on an online labor market to test the model and to compare dyadic tournaments to piece rate payments. Data suggests that on average dyadic tournaments do not improve performance compared to a simple piece rate for simple and short crowdsourcing tasks. Furthermore, giving feedback on the competitive position in such tournaments tends to be negatively related to workers’ performance. This relation is partially mediated by task completion and moderated by the provision of feedback: When playing against strong competitors, feedback is associated with workers quitting the task altogether and, thus, showing lower performance. When the competitors are weak, workers tend to complete the task but with reduced effort. Overall, individual piece rate payments are most simple to communicate and implement while incenting performance is on par with more complex dyadic tournaments.

Customer Integration in Service Innovation: An Exploratory Study

Prominent industry projects, as well as an extensive literature suggest the importance of customer integration for companies’ innovation success. This appears to be especially true for service firms, which inherently build on customer interaction. Despite this appreciation of the approach, there are comparably few empirical analyses of the positive and negative effects of customer integration. In this exploratory study, we build on established customer role concepts to study the status quo of customer integration in industry, as well as reservations against the roles and negative experiences from customer integration projects. The study reveals a gap between reservations and actual negative experiences in losing know-how, as well as a positive effect of experience in customer integration on perceived benefits for the company.

Designing a Crowd Forecasting Tool to Combine Prediction Markets and Real-Time Delphi

The FAZ.NET-Orakel is a crowd forecasting tool, made available to readers of the German-based Frankfurter Allgemeine Zeitung. Its main component is a prediction market used for forecasting economic indices as well as current political events. A shortcoming of prediction markets is their inability to exchange qualitative information. Therefore, we elaborate the combination of prediction markets with the Real-time Delphi method. We argue that several synergy effects may be achieved by this approach: First, prediction markets can be used to select experts for the Delphi survey. Second, valuable information and debates, which may be of interest, can be collected qualitatively. Third, the gamified approach of the prediction markets can raise commitment to the survey.

Service Co-creation

This chapter provides an overview on different aspects of co-creation in a service context. The first section introduces the concept of value co-creation in service systems and elaborates on the relationship of co-creation to service value propositions, service encounters, service quality, and service productivity. Furthermore, it introduces the concept of customer relationships, as well as concepts and methods that can be applied in order to manage these relationships for co-creation with customers. The third section elaborates on the different roles a customer can play within service co-creation, and its managerial implications.