Options
Jan Marco Leimeister
Title
Prof. Dr.
Last Name
Leimeister
First name
Jan Marco
Email
janmarco.leimeister@unisg.ch
Phone
+41 71 224 3330
Now showing
1 - 4 of 4
-
PublicationCrowdsourcing: How to Benefit from (Too) Many Great IdeasThis article focuses on how companies can cope with the enormous volume and variety of data (big data) that is acquired on crowdsourcing platforms from the worldwide community of Internet users. We identify the challenges of implementing crowdsourcing platforms and show how CIOs and other organizational leaders can build the absorptive capacity necessary to extract business value from crowdsourced data.Type: journal articleJournal: MIS Quarterly ExecutiveVolume: 12Issue: 4
-
PublicationThe Effect of Rating Scales on Decision Quality and User Attitudes in Online Innovation Communities(Routledge, Taylor & Francis Group, 2013-03)
;Riedl, ChristophKrcmar, HelmutGiven the rise of the Internet, consumers increasingly engage in co-creating products and services. Whereas most co-creation research deals with various aspects of generating user-generated content, this study addresses designing ratings scales for evaluating such content. In detail, we analyze functional and perceptional aspects of two frequently used rating scales in online innovation communities. Using a multimethod approach, our experiments show that a multicriteria scale leads to higher decision quality of users than a single-criterion scale, that idea elaboration (i.e., idea length) negatively moderates this effect such that the single-criterion rating scale outperforms the multicriteria scale for long ideas, and finally that the multicriteria scale leads to more favorable user attitudes toward the Web site. To ensure robustness of our results, we applied a bootstrap-based Monte Carlo simulation based on our experimental data. We found that around 20 user ratings per idea are sufficient for creating stable idea rankings and that a combination of both rating scales leads to a 63 percent performance improvement over the single-criterion rating scale and 16 percent over the multicriteria rating scale. Our work contributes to co-creation research by offering insights as to how the interaction of the technology being used (i.e., rating scale) and the attributes of the rating object affects two central outcome measures: the effectiveness of the rating in terms of decision quality of its users and the perception of the scale by its users as a predictor of future use.Type: journal articleJournal: International Journal of Electronic Commerce (IJEC)Volume: 17Issue: 3 -
PublicationPromoting the Quality of User Generated Ideas in Online Innovation Communities: A Knowledge Collaboration Perspective(Association for Information Systems, 2016-12-11)
;Ye, Jonathan ;Breschneider, Ulrich ;Goswami, SuparnaKrcmar, HelmutEnabled by Internet-based technologies, users are increasingly participating and collaborating in idea generation in online innovation communities. However, with the limited understanding of the phenomenon, few studies have investigated what determines the quality of ideas. This study aims at addressing the knowledge gap. We find that idea experimentation effort, i.e., the effort associated with creating the idea, and idea review, i.e., comments by other users, influence idea quality. Further, idea recombination, i.e. peer users participating in wiki-based edits, have a positive influence on idea Quality, in case idea experimentation effort was low, and a negative influence in case of high idea experimentation effort. These results contribute to idea generation, knowledge collaboration, and user generated content literature by investigating the mechanisms through which collaboration influences the quality of the collaborative outcome (i.e., idea quality) in online contexts for the first time. Advice for organizations running online innovation communities is provided.Type: conference paper -
PublicationThe Effects of Prediction Market Design and Price Elasticity on Trading Performance of Users : An Experimental Analysis(Cornell University Library, 2012-04-18)
;Riedl, Christoph ;Köroglu, OrhanKrcmar, HelmutWe employ a 2x3 factorial experiment to study two central factors in the design of prediction markets (PMs) for idea evaluation: the overall design of the PM, and the elasticity of market prices set by a market maker. The results show that 'multi-market designs' on which each contract is traded on a separate PM lead to significantly higher trading performance than 'single-markets' that handle all contracts one on PM. Price elasticity has no direct effect on trading performance, but a significant interaction effect with market design implies that the performance difference between the market designs is highest in settings of moderate price elasticity. We contribute to the emerging research stream of PM design through an unprecedented experiment which compares current market designs.Type: conference paperVolume: Paper 77