Identifying the contribution of financial and non-financial measures in value creation: An exploratory empirical analysis of economic value added and customer satisfaction.

A primary question in the field of marketing strategy involves the role of marketing constructs in the strategic management of an enterprise. A key element of strategy is that firms can choose to follow either a cost or differentiation strategy to create a competitive advantage. Traditional theory suggests that a firm should choose Dose one approach because it is either too difficult to develop a dual cost and differentiation strategy or because the attention of top management is limited in enacting and monitoring a dual strategy. The choice of which performance measures to use to monitor and evaluate the effectiveness of the chosen strategy is an important decision for driving firm performance. Critics have suggested that the exclusive use of traditional financial measures fails to effectively capture the value created in the firm and that non-financial measures need to be added to increase the understanding of new sources of firm value. Research has provided evidence that non-financial measures such customer satisfaction can be linked to increased firm performance and firm value in conjunction with traditional financial measures. In this study, questions about the relationship between economic efficiency, customer satisfaction measures, and firm value metrics are investigated including the size and structure of these relationships. The goal is to relate the value gained by following either a cost strategy or a differentiation strategy or a combination of strategies to assist managers and investors in identifying the relationship between a firm's current condition and its capacity to produce future wealth. In order to explore these relationships, data were gathered from publicly available sources including the American Customer Satisfaction Index (ACSI) and the Stern Stewart Performance 1000. Key variables include the firm's ACSI score, Economic Value Added (EVA), and Market Value Added (MVA). A series of regression models are used to test the structure of how customer satisfaction and financial metrics are reflected in measures of market value added. In addition, a matrix evaluating firms based on their position relative to average EVA and ACSI is created to illustrate the relative effects of cost and differentiation strategies on the level of MVA created over time. The results suggest that the interaction of customer satisfaction measures (ACSI) with the financial metric of economic value added (EVA) is a significant positive predictor of market value added (MVA) and provides incremental value to the sole use of financial measures or non-financial measures in predicting firm value creation. In addition, firms that have both greater than average levels of customer satisfaction and cost efficiency have higher average levels of MVA compared with firms that are lower on either or both cost and differentiation measures. Implications are drawn for marketing practitioners and additional supplemental research topics for strategic marketing analyses are presented.Ph.D.ManagementMarketingSocial SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/132206/2/9959825.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/132206/4/license_rd

Black Box Adversarial Prompting for Foundation Models

Prompting interfaces allow users to quickly adjust the output of generative models in both vision and language. However, small changes and design choices in the prompt can lead to significant differences in the output. In this work, we develop a black-box framework for generating adversarial prompts for unstructured image and text generation. These prompts, which can be standalone or prepended to benign prompts, induce specific behaviors into the generative process, such as generating images of a particular object or generating high perplexity text

Rehearsal: A Configuration Verification Tool for Puppet

Large-scale data centers and cloud computing have turned system configuration into a challenging problem. Several widely-publicized outages have been blamed not on software bugs, but on configuration bugs. To cope, thousands of organizations use system configuration languages to manage their computing infrastructure. Of these, Puppet is the most widely used with thousands of paying customers and many more open-source users. The heart of Puppet is a domain-specific language that describes the state of a system. Puppet already performs some basic static checks, but they only prevent a narrow range of errors. Furthermore, testing is ineffective because many errors are only triggered under specific machine states that are difficult to predict and reproduce. With several examples, we show that a key problem with Puppet is that configurations can be non-deterministic. This paper presents Rehearsal, a verification tool for Puppet configurations. Rehearsal implements a sound, complete, and scalable determinacy analysis for Puppet. To develop it, we (1) present a formal semantics for Puppet, (2) use several analyses to shrink our models to a tractable size, and (3) frame determinism-checking as decidable formulas for an SMT solver. Rehearsal then leverages the determinacy analysis to check other important properties, such as idempotency. Finally, we apply Rehearsal to several real-world Puppet configurations.Comment: In proceedings of ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) 201

On the Choice and Number of Microarrays for Transcriptional Regulatory Network Inference

<p>Abstract</p> <p>Background</p> <p>Transcriptional regulatory network inference (TRNI) from large compendia of DNA microarrays has become a fundamental approach for discovering transcription factor (TF)-gene interactions at the genome-wide level. In correlation-based TRNI, network edges can in principle be evaluated using standard statistical tests. However, while such tests nominally assume independent microarray experiments, we expect dependency between the experiments in microarray compendia, due to both project-specific factors (e.g., microarray preparation, environmental effects) in the multi-project compendium setting and effective dependency induced by gene-gene correlations. Herein, we characterize the nature of dependency in an <it>Escherichia coli </it>microarray compendium and explore its consequences on the problem of determining which and how many arrays to use in correlation-based TRNI.</p> <p>Results</p> <p>We present evidence of substantial effective dependency among microarrays in this compendium, and characterize that dependency with respect to experimental condition factors. We then introduce a measure <it>n</it>_{<it>eff </it>}of the effective number of experiments in a compendium, and find that corresponding to the dependency observed in this particular compendium there is a huge reduction in effective sample size i.e., <it>n</it>_{<it>eff </it>}= 14.7 versus <it>n </it>= 376. Furthermore, we found that the <it>n</it>_{<it>eff </it>}of select subsets of experiments actually exceeded <it>n</it>_{<it>eff </it>}of the full compendium, suggesting that the adage 'less is more' applies here. Consistent with this latter result, we observed improved performance in TRNI using subsets of the data compared to results using the full compendium. We identified experimental condition factors that trend with changes in TRNI performance and <it>n</it>_{<it>eff </it>}, including growth phase and media type. Finally, using the set of known E. coli genetic regulatory interactions from RegulonDB, we demonstrated that false discovery rates (FDR) derived from <it>n</it>_{<it>eff </it>}-adjusted p-values were well-matched to FDR based on the RegulonDB truth set.</p> <p>Conclusions</p> <p>These results support utilization of <it>n</it>_{<it>eff </it>}as a potent descriptor of microarray compendia. In addition, they highlight a straightforward correlation-based method for TRNI with demonstrated meaningful statistical testing for significant edges, readily applicable to compendia from any species, even when a truth set is not available. This work facilitates a more refined approach to construction and utilization of mRNA expression compendia in TRNI.</p

New Species of \u3ci\u3eArostrilepis\u3c/i\u3e (Eucestoda: Hymenolepididae) in Members of Cricetidae and Geomyidae (Rodentia) from the Western Nearctic

Specimens originally identified as Arostrilepis horrida from the Nearctic are revised, contributing to the recognition of a complex of cryptic species distributed across the Holarctic region. Previously unrecognized species are described based on specimens in cricetid (Neotominae) and geomyid rodents. Arostrilepis mariettavogeae n. sp. in Peromyscus californicus from Monterey County, California, and Arostrilepis schilleri n. sp. in Thomomys bulbivorus from Corvallis, Oregon, are characterized. Consistent with recent studies defining diversity in the genus, form, size, and spination (pattern, shape, and size) of the cirrus are diagnostic; species are further distinguished by the relative position and length of the cirrus sac and arrangement of the testes. Species of Arostrilepis have not previously been described in rodents outside of the Arvicolinae or from localities in the Nearctic. These studies emphasize the need for routine deposition of archival specimens and information, from survey, ecological, and biogeographic studies, in museum collections to serve as self-correcting records for biodiversity at local, regional, and continental scales

STRATEGIES TO MODEL AND CIRCUMVENT ACQUIRED RESISTANCE TO THERAPEUTICS IN SMALL CELL LUNG CANCER

Small cell lung cancer (SCLC) is an extremely aggressive, pulmonary malignancy linked to lifetime smoking of cigarette tobacco. Most SCLC is diagnosed in the metastatic setting and surgical resection is rarely performed. However, SCLC is one of the most chemosensitive tumors, with >50% objective responses observed in de novo disease. These responses are impressive, but brief. Median progression free survival remains less than 5 months in current clinical trials. Recent studies have characterized the genome and epigenome of primary, untreated SCLC tumors. These studies have revealed near universal inactivation of the tumor suppressors TP53 and RB1, with frequent alterations in chromatin modifying enzymes, Notch signaling and amplification of MYC family members. Little in known about what factors permit acquired resistance and enable such a rapid shift in chemosensitive to chemorefractory disease within the same patient. No studies to date have comprehensively characterized paired sensitive and resistant disease states. The research presented below describes three studies aimed at determining how acquired resistance to chemotherapy is generated in vivo and targeted therapeutic approaches to chemoresistant disease. The first study details the discovery of genetic and epigenetic mediators of acquired chemoresistance in vivo through the development and characterization of paired chemosensitive and chemoresistant patient derived xenograft (PDX) models of SCLC. This work establishes a central role for EZH2 in promoting resistance to DNA damaging agents by silencing the gene SLFN11 and is highlighted by the impressive efficacy of EZH2 inhibition with first or second line standard of care chemotherapy. The second study describes a targeted approach to overcoming resistance to programmed cell death (apoptosis) by chemically inhibiting a protein-protein interaction between BCL-2 family members in SCLC. This study relied on the small molecule ABT-263 and attempts to explain disappointingly transient responses in SCLC patients observed in clinical testing. Finally, the third study builds on the second study, highlighting the importance of combinatorial strategies to improve the efficacy of this targeted agent in vivo, with a focus on potential mechanisms of acquired resistance, notably genomic loss of BAX. Research presented in these studies is directly informing the design of proposed clinical trials in SCLC

Prospects for studying the mass and gas in protoclusters with future CMB observations

Protoclusters are the progenitors of massive galaxy clusters. Understanding the properties of these structures is important for building a complete picture of cluster formation and for understanding the impact of environment on galaxy evolution. Future cosmic microwave background (CMB) surveys may provide insight into the properties of protoclusters via observations of the thermal Sunyaev Zel'dovich (SZ) effect and gravitational lensing. Using realistic hydrodynamical simulations of protoclusters from the Three Hundred Project, we forecast the ability of CMB Stage 4-like (CMB-S4) experiments to detect and characterize protoclusters with observations of these two signals. For protoclusters that are the progenitors of clusters at $z = 0$ with $M_{200c} \gtrsim 10^{15}\,M_{\odot}$ we find that the S4-Ultra deep survey has a roughly 20% chance of detecting the main halos in these structures with ${\rm SNR} > 5$ at $z \sim 2$ and a 10% chance of detecting them at $z \sim 2.5$, where these probabilities include the impacts of noise, CMB foregrounds, and the different possible evolutionary histories of the structures. On the other hand, if protoclusters can be identified using alternative means, such as via galaxy surveys like LSST and Euclid, CMB-S4 will be able to obtain high signal-to-noise measurements of their stacked lensing and SZ signals, providing a way to measure their average mass and gas content. With a sample of 2700 protoclusters at $z = 3$, the CMB-S4 wide survey can measure the stacked SZ signal with a signal-to-noise of 7.2, and the stacked lensing signal with a signal-to-noise of 5.7. Future CMB surveys thus offer exciting prospects for understanding the properties of protoclusters.Comment: 12 pages, 10 figure