Design and Marketing of New Products

Future software systems will operate in a highly dynamic world. Systems will need to operate correctly despite of unespected changes in factors such as environmental conditions, user requirements, technology, legal regulations, and market opportunities. They will have to operate in a constantly evolving environment that includes people, content, electronic devices, and legacy systems. They will thus need the ability to continuously adapt themselves in an automated manner to react to those changes. To realize dynamic, self-adaptive systems, the service concept has emerged as a suitable abstraction mechanism. Together with the concept of the service-oriented architecture (SOA), this led to the development of technologies, standards, and methods to build service-based applications by flexibly aggregating individual services. This article discusses how those concepts came to be by taking two complementary viewpoints. On the one hand, it evaluates the progress in software technologies and methodologies that led to the service concept and SOA. On the other hand, it discusses how the evolution of the requirements, and in particular business goals, influenced the progress towards highly dynamic self-adaptive systems. Finally, based on a discussion of the current state of the art, this article points out the possible future evolution of the field.

A journey to highly dynamic, self-adaptive service-based applications

This article compares the forecast accuracy of different methods, namely prediction markets, tipsters and betting odds, and assesses the ability of prediction markets and tipsters to generate profits systematically in a betting market We present the results of an empirical study that uses data from 678–837 games of three seasons of the German premier soccer league Prediction markets and betting odds perform equally well in terms of forecasting accuracy, but both methods strongly outperform tipsters A weighting-based combination of the forecasts of these methods leads to a slightly higher forecast accuracy, whereas a rule-based combination improves forecast accuracy substantially However, none of the forecasts leads to systematic monetary gains in betting markets because of the high fees (25%) charged by the state-owned bookmaker in Germany Lower fees (eg, approximately 12% or 0%) would provide systematic profits if punters exploited the information from prediction markets and bet only on a selected number of games Copyright © 2008 John Wiley & Sons, Ltd

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Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters

https://www.ecm.bwl.uni-muenchen.de/publikationen/pdf/idea_markets.pdf

Sourcing, filtering, and evaluating new product ideas: an empirical exploration of the performance of idea markets

European Economic Review

Accurate forecasts are essential in many areas such as business and sports forecasting. Prediction markets are a promising approach for forecasting future events and are increasingly used to aggregate information on particular future events of interest such as elections, sports events, and Oscar winners. In this paper, we present the results of an empirical study that compares the forecast accuracy of a prediction market for the FIFA World Cup 2006 to predictions derived from the FIFA world ranking and to a random predictor. We find that prediction markets for the FIFA World Cup outperform predictions based on the FIFA world ranking as well as the random predictor in terms of forecast accuracy.

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On the Forecast Accuracy of Sports Prediction Markets

Prediction markets for foresight

Electronic markets and especially online auctions gain more and more importance and a plethora of market mechanisms is emerging on the Internet. The great variety of trading rules hinders agents easily switching between different marketplaces and, therefore, fragments the overall market – supply and demand might fail to meet due to agents' inability to interact with the same market mechanism. The problem can be overcome by a descriptive auction language (DAL) allowing for the machine‐readable specification of arbitrary auction mechanisms. The implications are twofold: on the one hand a market engineer can coherently describe a mechanism by means of the language and automatically deploy it via an auction runtime environment and, on the other hand, a (software) agent can automatically deduce valid and reasonable actions from the description of a previously unknown auction mechanism. All four authors are affiliated with the Institute of Information Systems and Management in the School of Economics and Busine...

https://www.econbiz.de/archiv/ka/uka/information/auction_language.pdf

A Descriptive Auction Language

The results of recent studies on prediction markets are encouraging. Prior experience demonstrates that markets with different incentive schemes predicted uncertain future events remarkably accurately. In this paper, we study the impact of different monetary incentives on prediction accuracy in a field experiment. In order to do so, we compare three groups of traders, corresponding to three treatments with different payment schemes, in a prediction market for the FIFA World Cup 2006. Somewhat surprisingly, our results show that performance-related payment schemes do not necessarily increase the prediction accuracy. Due to the risk aversion of traders the competitive environment in a rank-order tournament leads to the best results in terms of prediction accuracy.

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How to pay traders in information markets: results from a field experiment

Over the last couple of years, interest in prediction markets as a forecasting method has continuously increased in the scientific world and in industry. Markets provide incentives for information revelation and can be used as a mechanism for aggregating information. So far, prediction markets have done well in every known comparison with other forecasting methods. Whereas information aggregation is only a byproduct of most traditional markets, prediction markets are set up with the explicit purpose of soliciting information. Engineered carefully, prediction markets can directly guide decision making. This paper describes the fundamentals of prediction markets as well as their key design elements. We thereby aim at giving insights into design decisions which have to be made by prediction market operators. Moreover, we contribute to the literature by giving an extensive overview on fields of application of prediction markets which have been discussed in academic literature.

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Stefan Luckner

Papers

On the Forecast Accuracy of Sports Prediction Markets

Prediction markets for foresight

A Descriptive Auction Language

How to pay traders in information markets: results from a field experiment

Prediction Markets: Fundamentals, Key Design Elements, and Applications