Resource -Based, Strategic Group, and Industry Influences on Firm Performance.

This dissertation examines resource-based, strategic group, and industry influences on firm performance. The resource-based view of the firm and strategic groups research are two areas of organizational inquiry that have lacked both theoretical as well as empirical integration. This dissertation provides a critical first step towards that end. Three papers are presented that first develop---and then test---resource-based and strategic group influences on organizational performance. The primary findings of this dissertation are threefold. First, variance in organizational performance exists both within and between strategic groups. Second, the degree to which firm, group, and industry explained variance in organizational performance varied based upon performance measure. Third, in all cases, firms accounted for the lion\u27s share of the variation in organizational performance. In conclusion, the key determinant of organizational performance is manager\u27s capabilities to position their firm within their group as well as industry

The impact of high density receptor clusters on VEGF signaling

Vascular endothelial growth factor (VEGF) signaling is involved in the process of blood vessel development and maintenance. Signaling is initiated by binding of the bivalent VEGF ligand to the membrane-bound receptors (VEGFR), which in turn stimulates receptor dimerization. Herein, we discuss experimental evidence that VEGF receptors localize in caveloae and other regions of the plasma membrane, and for other receptors, it has been shown that receptor clustering has an impact on dimerization and thus also on signaling. Overall, receptor clustering is part of a complex ecosystem of interactions and how receptor clustering impacts dimerization is not well understood. To address these questions, we have formulated the simplest possible model. We have postulated the existence of a single high affinity region in the cell membrane, which acts as a transient trap for receptors. We have defined an ODE model by introducing high- and low-density receptor variables and introduce the corresponding reactions from a realistic model of VEGF signal initiation. Finally, we use the model to investigate the relation between the degree of VEGFR concentration, ligand availability, and signaling. In conclusion, our simulation results provide a deeper understanding of the role of receptor clustering in cell signaling.Comment: In Proceedings HSB 2013, arXiv:1308.572

Hard limits on the postselectability of optical graph states

Coherent control of large entangled graph states enables a wide variety of quantum information processing tasks, including error-corrected quantum computation. The linear optical approach offers excellent control and coherence, but today most photon sources and entangling gates---required for the construction of large graph states---are probabilistic and rely on postselection. In this work, we provide proofs and heuristics to aid experimental design using postselection. We derive a fundamental limitation on the generation of photonic qubit states using postselected entangling gates: experiments which contain a cycle of postselected gates cannot be postselected. Further, we analyse experiments that use photons from postselected photon pair sources, and lower bound the number of classes of graph state entanglement that are accessible in the non-degenerate case---graph state entanglement classes that contain a tree are are always accessible. Numerical investigation up to 9-qubits shows that the proportion of graph states that are accessible using postselection diminishes rapidly. We provide tables showing which classes are accessible for a variety of up to nine qubit resource states and sources. We also use our methods to evaluate near-term multi-photon experiments, and provide our algorithms for doing so.Comment: Our manuscript comprises 4843 words, 6 figures, 1 table, 47 references, and a supplementary material of 1741 words, 2 figures, 1 table, and a Mathematica code listin

Investigating Multilevel Relationships in Information Systems Research: An Application to Virtual Teams Research Using Hierarchial Linear Modeling

Information Systems researchers are often concerned with empirical questions spanning more than one level of analysis. For example, virtual teams research provides a good illustration because such teams are inherently hierarchical entities involving the situated nature of individuals within teams. Despite the importance of multilevel research questions to Information Systems research, the literature has yet to fully engage appropriate techniques for multilevel investigations. Using hierarchical linear modeling (HLM) as a statistical tool that can appropriately test cross-level relationships, we provide an illustration of the differences and advantages of using a multilevel technique over ordinary least squares (OLS) regression. Using data from a study of global virtual teams, we demonstrate that substantive research conclusions differ based on the use of HLM versus OLS regression. Using HLM, we find a significant relationship between individual level task liking and affective commitment; we also find a significant relationship between individual level task liking and satisfaction with the virtual team. When testing the moderating effects of team characteristics, we found a significant positive moderating effect of team work processes on the relationship between task liking and satisfaction. We conclude with recommendations for future research and provide a comparison of empirical techniques available for IS researchers testing relationships at single and multiple levels of analysis

Reducing Bias in Estimates for the Law of Crime Concentration

Objectives The law of crime concentration states that half of the cumulative crime in a city will occur within approximately 4% of the city’s geography. The law is demonstrated by counting the number of incidents in each of N spatial areas (street segments or grid cells) and then computing a parameter based on the counts, such as a point estimate on the Lorenz curve or the Gini index. Here we show that estimators commonly used in the literature for these statistics are biased when the number of incidents is low (several thousand or less). Our objective is to significantly reduce bias in estimators for the law of crime concentration. Methods By modeling crime counts as a negative binomial, we show how to compute an improved estimate of the law of crime concentration at low event counts that significantly reduces bias. In particular, we use the Poisson–Gamma representation of the negative binomial and compute the concentration statistic via integrals for the Lorenz curve and Gini index of the inferred continuous Gamma distribution. Results We illustrate the Poisson–Gamma method with synthetic data along with homicide data from Chicago. We show that our estimator significantly reduces bias and is able to recover the true law of crime concentration with only several hundred events. Conclusions The Poisson–Gamma method has applications to measuring the concentration of rare events, comparisons of concentration across cities of different sizes, and improving time series estimates of crime concentration

Graphic Presentation: An Empirical Examination of the Graphic Novel Approach to Communicate Business Concepts

Graphic novels have been increasingly incorporated into business communication forums. Despite potential benefits, little research has examined the merits of the graphic novel approach. In response, we engage in a two-study approach. Study 1 explores the potential of graphic novels to affect learning outcomes and finds that the graphic novel was related to high levels of learning experiences. Study 2 compares the impact of graphic novels with that of traditional textbooks and finds that verbatim recognition was superior with graphic novel texts. Overall, we provide the first comprehensive examination of the graphic novel as a tool for effective business communication.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Advances in quantum machine learning

Here we discuss advances in the field of quantum machine learning. The following document offers a hybrid discussion; both reviewing the field as it is currently, and suggesting directions for further research. We include both algorithms and experimental implementations in the discussion. The field's outlook is generally positive, showing significant promise. However, we believe there are appreciable hurdles to overcome before one can claim that it is a primary application of quantum computation.Comment: 38 pages, 17 Figure

Mapping graph state orbits under local complementation

Graph states, and the entanglement they posses, are central to modern quantum computing and communications architectures. Local complementation---the graph operation that links all local-Clifford equivalent graph states---allows us to classify all stabiliser states by their entanglement. Here, we study the structure of the orbits generated by local complementation, mapping them up to 9 qubits and revealing a rich hidden structure. We provide programs to compute these orbits, along with our data for each of the 587 orbits up to 9 qubits and a means to visualise them. We find direct links between the connectivity of certain orbits with the entanglement properties of their component graph states. Furthermore, we observe the correlations between graph-theoretical orbit properties, such as diameter and colourability, with Schmidt measure and preparation complexity and suggest potential applications. It is well known that graph theory and quantum entanglement have strong interplay---our exploration deepens this relationship, providing new tools with which to probe the nature of entanglement

Publication Bias in Strategic Management Research

This research explores the domain of strategic management for evidence of publication bias—the systematic suppression of research findings due to the magnitude, statistical significance, or generally accepted direction of effect sizes. We review why publication bias may exist in strategy research as well as report empirical findings regarding the influence of publication bias in the field. Overall, we found evidence consistent with the inference that publication bias affects many, but not all, topics in the strategic management research. Correlation inflation due to publication bias ranged from an average change in magnitude from .00 (no bias) to .19. These results serve to illustrate the robustness of some important empirical findings while also suggesting that caution should be exercised when interpreting other scientific conclusions in the field of strategic management. We discuss how publication bias can be addressed both philosophically and empirically in the domain of strategy

Active Automotive Vents

ME450 Capstone Design and Manufacturing Experience: Winter 2008SMA Actuated Vent SystemGeneral Motors SMART Materials and Structures Laboratoryhttp://deepblue.lib.umich.edu/bitstream/2027.42/58696/1/me450w08project5_report.pd