290 research outputs found
Modeling and verifying a broad array of network properties
Motivated by widely observed examples in nature, society and software, where
groups of already related nodes arrive together and attach to an existing
network, we consider network growth via sequential attachment of linked node
groups, or graphlets. We analyze the simplest case, attachment of the three
node V-graphlet, where, with probability alpha, we attach a peripheral node of
the graphlet, and with probability (1-alpha), we attach the central node. Our
analytical results and simulations show that tuning alpha produces a wide range
in degree distribution and degree assortativity, achieving assortativity values
that capture a diverse set of many real-world systems. We introduce a
fifteen-dimensional attribute vector derived from seven well-known network
properties, which enables comprehensive comparison between any two networks.
Principal Component Analysis (PCA) of this attribute vector space shows a
significantly larger coverage potential of real-world network properties by a
simple extension of the above model when compared against a classic model of
network growth.Comment: To appear in Europhysics Letter
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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
Executive Quirks in Operational Decisions
We ask if corporate executives have fixed effects (quirks) that explain perational decisions made in firms, independent of firm effects. We replicate the approach in Bertrand et al. (2003), solving the empirical challenge of distinguishing firm and executive effects by constructing a dataset of executives who move from one firm to another. We find that executives indeed exhibit fixed effects separate from firm effects. These quirks are large, although there is a wide dispersion of sizes among executives. The quirks also come in themes, such as a bias toward investing in human rather than physical capital. We also find that quirks mostly lead to inefficient outcomes for firms. Finally, we link quirks to observable characteristics of executives, such as their age or education. We conclude by arguing for an increased focus on individual effects in operations management research
Behavior in behavioral strategy : capturing, measuring, analyzing
Measuring behavior requires research methods that can capture observed outcomes and expose underlying processes and mechanisms. In this chapter, we present a toolbox of instruments and techniques we designed experimental tasks to simulate decision environments and capture behavior. We deployed protocol analysis and text analysis to examine the underlying cognitive processes. In combination, these can simultaneously grasp antecedents, outcomes, processes, and mechanisms. We applied them to collect rich behavioral data on two key topics in strategic management: the exploration–exploitation trade-off and strategic risk-taking. This mix of methods is particularly useful in describing actual behavior as it is, not as it should be, replacing assumptions with data and offering a finer-grained perspective of strategic decision-making
Building Dynamic Capabilities: Innovation Driven By Individual, Firm, and Network Level Effects
Following the dynamic capabilities perspective, we suggest that antecedents to innovation can be found at the individual,
firm, and network level. Thus, we challenge two assumptions common in prior research: (1) that significant variance exists
at the focal level of analysis, while other levels of analysis are assumed to be homogeneous, and (2) that the focal level of
analysis is independent from other levels of analysis. Accordingly, we advance a set of hypotheses to simultaneously assess the
direct effects of antecedents at the individual, firm, and network level on innovation output. We then investigate whether a
firm’s antecedents to innovation lie across different levels. To accomplish this, we propose two competing interaction
hypotheses. We juxtapose the hypothesis that the individual, firm, and network level antecedents to innovation are
substitutes versus the proposition that these innovation mechanisms are complements. We test our multi-level theoretical
model using an unusually comprehensive and detailed panel dataset that documents the innovation attempts of global
pharmaceutical companies within biotechnology over a 22-year time period (1980-2001). We combine these data with
direct field observations conducted prior to, during, and after the completion of the study. We find evidence that the
antecedents to innovation lie across different levels of analysis and can have compensating or reinforcing effects on firm-level
innovative output
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