Online communities heavily rely on voluntary participation and continued engagement from users because these sites can flourish only if there are meaningful contributions from community members. Gamifying the underlying incentive mechanism can be a solution to elicit and sustain the desired user behavior. In this paper, we develop a theory of gamification and study the impact of a hierarchical badges system, a reward mechanism based on gamification principles, on user participation and engagement at Stack Overflow Q&A site. Specifically, we assess the extent to which users are incentivized by earned badges in their contributions to the answering activity. Our initial results present strong empirical evidence that confirms the value of the badges and the effectiveness of gamification in stimulating voluntary participation.

Research summary: This article applies data from LinkedIn to advance strategy research into the effect of human capital on mobility of engineers and scientists. Through an inventor survey, we show that LinkedIn provides more accurate career histories than patents. Compared to LinkedIn, patent measures of mobility generate 12 percent false positives and 83 percent false negatives. Using LinkedIn, we review findings from previous research using patents to track the effect of human capital on mobility. One previous finding is robust: that mobility is higher in Silicon Valley than elsewhere. Other findings are possibly sensitive to the measure of mobility or sample selection. We interpret our results as the outcome of targeted retention of human capital. Data for this study may be accessed at FIVE, five.dartmouth.edu. Managerial summary: How does the mobility of engineers and scientists depend on their human capital? Previous research used patents to track inventor mobility and concluded that employers targeted inventors for recruitment by their human capital. Here, we introduce data from LinkedIn to review the previous research. Through an inventor survey, we show that LinkedIn provides more accurate career histories than patents. Compared to LinkedIn, patent measures of mobility generate 12 percent false positives and 82 percent false negatives. Among the previous findings, we show that one is robust: mobility is higher among inventors in Silicon Valley than elsewhere. Other findings are possibly sensitive to the measure of mobility or sample selection. Our results suggest that current employers target engineers and scientists for retention according to their human capital. Copyright © 2015 John Wiley & Sons, Ltd.

We thank Yuxin Chen, Roy Radner, Uday Rajan, Arun Sundararajan, and participants at the

This study develops, implements, and evaluates a multilabel text classification algorithm called the multilabel categorical K-nearest neighbor (ML-CKNN). The proposed algorithm is designed to automatically identify 25 types of risk factors with specific meanings reported in Section 1A of SEC form 10-K. The idea of ML-CKNN is to compute a categorical similarity score for each label by the K-nearest neighbors in that category. ML-CKNN is tailored to achieve the goal of extracting risk factors from 10Ks. The proposed algorithm can perfectly classify 74.94% of risk factors and 98.75% of labels. Moreover, ML-CKNN is empirically shown to outperform ML-KNN and other multilabel algorithms. The extracted risk factors could be valuable to empirical studies in accounting or finance.

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