Untangling knowledge creation and knowledge integration in enterprise wikis

A central challenge organizations face is how to build, store, and maintain knowledge over time. Enterprise wikis are community-based knowledge systems situated in an organizational context. These systems have the potential to play an important role in managing knowledge within organizations, but the motivating factors that drive individuals to contribute their knowledge to these systems is not very well understood. We theorize that enterprise wiki initiatives require two separate and distinct types of knowledge-sharing behaviors to succeed: knowledge creation (KC) and knowledge integration (KI). We examine a Wiki initiative at a major German bank to untangle the motivating factors behind KC and KI. Our results suggest KC and KI are indeed two distinct behaviors, reconcile inconsistent findings from past studies on the role of motivational factors for knowledge sharing to establish shared electronic knowledge resources in organizations, and identify factors that can be leveraged to tilt behaviors in favor of KC or KI

Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated

ICAR: endoscopic skull‐base surgery

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The Effects of MiFID II on Sell-Side Analysts, Buy-Side Analysts, and Firms

This paper provides early but broad empirical evidence on a major new investor protection regulation in Europe, MiFID II, which requires investment firms to unbundle investment research from other costs they charge to clients. We predict that the price separation resulting from unbundling and a hard-dollar system leads to a shrinking of the market for sell-side investment research, manifested in lower quantity of sell-side coverage that is of higher quality than before the regulation. We test our predictions in difference-in-differences matched-sample research designs with firm fixed effects. We find a decrease in the number of sell-side analysts covering European firms after MiFID II implementation, particularly for firms that are less important to the sell-side. However, research quality improves; specifically, individual analyst forecasts are more accurate and stock recommendations garner greater market reactions. In addition, sell-side analysts seem to cater more to the buy-side after MiFID II by providing industry recommendations along with stock recommendations. Importantly, we predict and find evidence that buy-side investment firms turn to more in-house research after MiFID II implementation. Equally interesting, buy-side analysts increase their participation and engagement in earnings conference calls compared to the control group. Finally, we find some evidence that stock-market liquidity decreases post-MiFID II. Our findings have implications beyond Europe, as investors are currently pressuring the U.S. Securities and Exchange Commission to adopt a similar regulation

Obelix vs. Asterix : size of US commercial banks and its regulatory challenge

Big banks pose substantial costs to society in the form of increased systemic risk and government bailouts during crises. So the question is: Should regulators limit the size of banks? To answer this question, regulators need to assess the potential costs of such regulations. If big banks enjoy substantial scale economies (i.e., average costs get lower as bank size increases), limiting the size of banks through regulations may be inefficient and likely to reduce social welfare. However, the literature offers conflicting results regarding the existence of economies of scale for the biggest US banks. We contribute to this literature using a novel approach to estimating nonparametric measures of scale economies and total factor productivity (TFP) growth. For US commercial banks, we find that around 73 % of the top one hundred banks, 98 % of medium and small banks, and seven of the top ten biggest banks by asset size exhibit substantial economies of scale. Likewise, we find that scale economies contribute positively and significantly to their TFP growth. The existence of substantial scale economies raises an important challenge for regulators to pursue size limit regulations