Participation, Feedback & Incentives in a Competitive Forecasting Community

Macro-economic forecasts are used extensively in industry and government even though the historical accuracy and reliability is questionable. Over the last couple of years prediction markets as a community forecasting method have gained interest. An arising question is how to design incentive schemes and feedback mechanisms to motivate participants to contribute to such an information exchange. We design a prediction market for economic derivatives that aggregates macro-economic information. We show that the level of participation is mainly driven by a weekly newsletter which acts as a reminder. In public goods projects participation feedback has been found to increase participants\u27 contributions. We find that the induced competitiveness of market environments seem to superpose classical feedback mechanisms. We show that forecast errors fall over the prediction horizon. The market generated forecasts compare well to the Bloomberg-survey forecasts, the industry standard. Additionally we can predict community forecast error by using an implicit market measure

PREDICTIVE MODEL MARKETS: DESIGN PRINCIPLES FOR MANAGING ENTERPRISE-LEVEL ADVANCED ANALYTICS

As advanced analytics penetrate a wide range of business applications, companies face the challenge of managing analytics-based assets, such as predictive models. Tasks ahead include model selection, scoring and deployment planning. One way to optimize model selection is to tap the combined knowledge of company staff through a “prediction market,” a virtual market designed to reveal participants’ aggregate wisdom by seeing where people “invest” their money. In the context of predictive-model selection, this paper refers to such devices as predictive-model markets. This paper examines design possibilities for building experimental markets that can ultimately be used to test whether predictive-model markets will improve model selection and deployment. The researchers test two types of incentives for participation: economic and social. Study results indicate that such markets can effectively work using either; a surprising finding is that social incentives did not improve effectiveness when added to economic incentives

European Journal of Information Systems advance online publication

Abstract Generating sustainable business value from information services is challenging on the web where free information and zero-switching costs are the norm. This study examines the role of free comments given in a commercial information service through the lens of the expectation-confirmation theory and continuance. Data from a question and answer web site are analyzed by structural equations modeling to test the theoretical model whereby customer satisfaction is key to continuance and is predicted largely by social interaction that takes place on the site. The model is supported by the field data retrieved from the site. The data show that people came with equal expectations, received equal service, and continued to use the system if they were satisfied with it. Satisfaction was predicted by conversation. Free activity emerges as an integral part of the service in a fee-based information market, improving satisfaction and continuance, and thereby leading to measurable outcomes for the commercial owners of the site. The findings, based on unobtrusive field data rather than self-report questionnaires, extend expectation confirmation theory by adding a social dimension to it

Buying Love Through Social Media: How Different Types Of Incentives Impact Consumers’ Online Sharing Behavior

A key issue in social media marketing is insufficient consumer participation and engagement. Oftentimes companies have to devise tactics to encourage more social sharing of brand messages, such as through the use of incentives and rewards. Previous research has investigated incentive effects under the traditional offline context, which addresses mostly economic exchanges and fails to consider the social dynamics of the social media environment. Addressing this gap, this research aims to answer the following research question: how can companies target different consumers with different incentives to maximize consumer sharing through social media? Specifically, the present research proposes three factors that can affect the relative appropriateness of monetary versus non-monetary incentives in driving consumer sharing: consumer loyalty, audience size and brand personality. Three experimental studies were conducted to examine these factors. The findings of study 1 indicate that consumers with high loyalty are more likely to engage in social sharing when faced with non-monetary incentives. In contrast, non-loyal consumers are more likely to engage in social sharing when offered monetary incentives. Study 2 shows that non-monetary incentives are more effective when sharing to a wide audience is requested, but incentive type does not make a difference when sharing is limited to specific individuals. The results of Study 3 show that, for a brand characterized by sincerity, consumers are more likely to engage in social sharing when a non-monetary incentive is used than when a monetary incentive is used. For an “exciting” brand, the incentive type does not matter. By examining these moderators, this dissertation contributes to a better understanding of how to use incentives more appropriately to increase social sharing under different situations. Moreover, the research findings here can help marketers define the appropriate strategies to target different types of social interactions, and allow them to restore some control in the co-creation of brand stories in the social media context

Forecasting Economic Indices - Design, Performance, and Learning in Prediction Markets

Macroeconomic forecasts are used extensively in industry and government even though the historical accuracy and reliability is disputed. This thesis develops and studies a prediction market designed to forecast macro-economic indicators in Germany. The market forecasts performed well in comparison to the \u27Bloomberg\u27-survey forecasts. Distinguishing between trading behavior and performance the thesis provides insights into the interplay between interface, information and decision-making

Chat more and contribute better: An empirical study of a knowledge-sharing community

We analyze whether an informal second channel for communication can improve the efficiency of knowledge transfer in an electronic network of practice. We explore this question by analyzing the effect of chat rooms in the well-known Q&A forum Stack Overflow. We identify the causal effect using a difference-in-differences approach, which exploits a feed functionality that non-selectively pushed all questions from the Q&A into the relevant chat rooms. We report two main findings: First, chat rooms reduced the time until a question in the main Q&A received a satisfactory answer. Second, chat rooms disproportionately benefited new users who asked low-quality questions. Our study has clear managerial implications: A second channel for communication can complement the main channel in online communities to enhance both efficiency and inclusion

Examining differences among member satisfaction within a self-organized virtual community of professionals: A model of satisfaction based on the self-selection process participants engage in and their ability to fulfill their basic psychological needs

The research related to what motivates member participation within peer production enterprises as a whole has not produced a reliable list of motivations present among peer production participants. Instead, motivations are often defined idiosyncratically (e.g., Butler et al., 2007; Oreg & Nov, 2009) and participation is simplified to a dichotomous variable or crudely measured by frequency (e.g., Chen & Hung, 2010). This makes it difficult to compare and contrast peer production efforts or understand the larger theoretical contribution of these studies of motivation. In an effort to rethink how member motivation is understood within peer production enterprises, this research develops and tests a model of member satisfaction within a self-organized virtual community (SVC) of professionals that conceptualizes member satisfaction as being (1) directly connected to person-community and demands-abilities fit and (2) indirectly connected to fit through the fulfillment of members’ basic psychological needs for competence, relatedness, and autonomy (Deci & Ryan, 2000). Additionally, individual filtering, a cognitive heuristic members of SVCs may utilize to personalize the information environment within an SVC, is introduced as a moderator in order to understand how these direct and indirect effects are conditioned on this participation management strategy. One of the main advantages of this theoretical model is that it does not require quantifying the amount or categorizing the type of member participation in order to understand member motivations and satisfaction, making it suitable for use in most peer production contexts (Benkler, 2006), even those scattered across multiple online platforms. In order to test this model, members of the SVC KM4Dev were solicited to take part in an online survey (N = 212) from July – October 2016. KM4Dev (Knowledge Management for Development) is a SVC of international development practitioners and other professionals interested in knowledge management and knowledge sharing issues and approaches, with a membership of over 4000 people from around the world. Path analysis was employed to analyze the model.Analyses revealed the model explained approximately two-thirds of the variance in satisfaction (R2=.65) and a similarity of importance (i.e., similar sized total effect) placed on PC fit and DA fit by members, in relation to satisfaction. The strongest path to satisfaction within this community is the indirect path from person-community fit through competence fulfillment to satisfaction, even when it is conditioned upon the moderator individual filtering. The need for autonomy had the lowest amount of variance explained in the model (R2=.24). Overall, the statistical support found for this model corroborates the use of a model of satisfaction premised on the assumptions of peer production (i.e., participant self-selection, Benkler, 2006). Furthermore, it simplifies the study of motivation by conceptualizing motivation as members’ ability to fulfill their basic psychological needs for autonomy, relatedness, and competence, instead of any want or desire a person may identify. Finally, through the introduction of moderating variables, such as individual filtering, this model is a tool to more precisely explain differences among members’ ability to fulfill their basic psychological needs and be satisfied with their overall community experience within a peer production enterprise