A Tale of Two Genres?: Knowledge Management in Organizations

This paper suggests that organizational learning phenomena belong to fundamentally two different types: the relatively deterministic industrial genre and the idiosyncratic behavioral genre. These genres differ substantially from each other on key dimensions such as the nature of embedding of learning, cumulativeness of learning, learning orientation and criteria used to evaluate outcomes. Researchers investigating organizational learning phenomena need to be sensitive to these differences to be able to effectively distinguish patterns that would otherwise be masked by variations attributable to the genres

Brother, Can you Spare a Pizza

Using the social media site Reddit.com’s sub forum Random Acts of Pizza, we investigate the effect of the receipt of altruism in the form of tangible goods rather than information or intangible assistance. We find evidence that the receipt of tangible assistance increases the normative adherence of users, the amount of participation, and the breadth of participation across the wider site

The Effect of Peer-to-Peer Tangible Donation on Users’ Engagement in Online Community Platform

Despite the potential value of prosocial activities in enhancing user engagement in online communities, research on the relationship between prosocial activities and online community users’ behavior. In this research, we examine the impact of tangible donation on online community users’ engagement behaviors by using dataset from Reddit, a major online community platform. Our results indicate that, after donating, givers increase their engagement behavior by writing more posts and comments than non-givers. Furthermore, after receiving donation, receivers reduce their engagement behavior by writing fewer posts and comments than non-receivers. Our study serves as one of the first attempts to examine the role of peer-to-peer tangible donation in users’ engagement behavior in online community platform, which is a novel way to help people in needs and effective way to induce user participation

A Bayesian Local Causal Discovery Framework

This work introduces the Bayesian local causal discovery framework, a method for discovering unconfounded causal relationships from observational data. It addresses the hypothesis that causal discovery using local search methods will outperform causal discovery algorithms that employ global search in the context of large datasets and limited computational resources.Several Bayesian local causal discovery (BLCD) algorithms are described and results presented comparing them with two well-known global causal discovery algorithms PC and FCI, and a global Bayesian network learning algorithm, the optimal reinsertion (OR) algorithm which was post-processed to identify relationships that under assumptions are causal.Methodologically, this research formalizes the task ofcausal discovery from observational data using a Bayesianapproach and local search. It specifically investigates theso called Y structure in causal discovery andclassifies the various types of Y structurespresent in the data generating networks. Itidentifies the Y structures in the Alarm,Hailfinder, Barley, Pathfinder and Munin networks andcategorizes them. A proof of the convergence of the BLCDalgorithm based on the identification of Y structures, isalso provided. Principled methods of combiningglobal and local causal discovery algorithms to improve uponthe performance of the individual algorithms are discussed. In particular,a post-processing method for identifying plausible causal relationships from the output of global Bayesiannetwork learning algorithms is described, therebyextending them to be causal discovery algorithms.In an experimental evaluation, simulated data fromsynthetic causal Bayesian networks representing fivedifferent domains, as well as a real-world medical dataset, were used. Causal discovery performance was measured using precision and recall.Sometimes the local methods performed better than the global methods,and sometimes they did not (both in terms of precision/recalland in terms of computation time).When all the datasets were considered in aggregate,the local methods (BLCD and BLCDpk) had higher precision.The general performance of the BLCD class of algorithmswas comparable to the global search algorithms, implying that the localsearch algorithms will have good performance onvery large datasets when the global methods fail to scaleup. The limitations of this research and directions for future research are also discussed

KNOWLEDGE REPOSITORIES AND KNOWLEDGEABLE ACTION

In spite of the importance of knowledge reuse much is still unknown about how knowledge management artifacts influence reuse in practice. In this paper we use the concept of scaffolding to explore how knowledge repositories influence knowledgeable action. We conceptualize anchoring and adjustment as the processes involved in the use of scaffolding such as knowledge repositories. By viewing reuse in terms of these mechanisms, we can begin to consider the reuse processes individually as involving (1) choice of document for reuse and (2) adaptation of the document’s suggested solution applied to a current problem. We suggest the document acts as an anchor to frame the current problem consistent with the problem solved in the document, and that the suggested solution is then adapted through the adjustment process to meet the needs of the current problem. We subsequently explore the factors that influence both anchor choice and adjustment

Relational Embeddedness, Herding, and Tie Persistence

Recent studies on social network structures have focused on tie persistence as a distinct outcome in a tie life cycle. Tie persistence refers to continuity of a network tie across at least two consecutive time periods. We contribute to this body of knowledge by empirically comparing the influence of relational embeddedness and herding on tie persistence. We find that while both the mechanisms increase the likelihood of tie persistence, their co-presence creates a substitution effect. We find that individuals prefer to rely on relational embeddedness of a tie than following the crowd. Lastly, we also demonstrate the distinctiveness of tie persistence from other tie-related outcome by estimating the same effects for tie restoration. We discuss the implications of our findings for literature on social ties

Strategic Action Repertoires and Performance of Firms in the Internet Industry

Researchers have called for new theoretical frameworks and empirical analyses to understand variations in organizational strategies and management practices in the Internet industry, where existing paradigms may have limited applicability. Studies to date have neither articulated the repertoire of key firm actions in this context nor developed theory to relate firm actions to performance. This paper seeks to identify a key set of firm moves in the Internet industry and develop a theoretical model to relate firm actions to two important firm outcomes: sales performance and firm survival. We draw on the construct of dynamic resourcefulness to the firm level and develop a research model linking the actions of firms in the Internet industry underlying dynamic resourcefulness to firm-level outcomes. We test our hypotheses using the action repertoire-year mode of analysis on the actions of 106 leading firms in the Internet industry over a period of 6 years from 1994 to 1999. Our results suggest that firm actions to manage and direct their intellectual, relational, and financial capital resources are associated with higher levels of performance and survival