Forensic visibility gaps in fileless malware incidents: An empirical analysis of artefact survival rates across 49 confirmed intrusions

The rapid economic growth during last three decades in China gives rise to many entrepreneurs and newly founded ventures. However, newly founded ventures last only a short time and have a small survival rate. Why do some newly founded ventures survive and thrive while others struggle and die? What factors determine the survival of newly founded ventures? Firm growing theory considers internal factors as the sources of growth while entrepreneurs have found in practice that technology is the moat” of a new firm. Under the current background of economic transformation and mass entrepreneurship and innovation”, it is urgent to study the rules of the survival and growth of new firms in order to improve their survival rate. Newly founded ventures struggle to survive because of the liability of newness”. The previous literature focuses on the early stage of the life cycle and analyzes the overcoming of the liability of newness”. The relatively consistent view is that the founding conditions determine the initial survival rate of newly founded ventures, and have a lasting impact on later growth and performance, i.e., the imprinting” role. Previous studies further examine various types of founding conditions, such as external environmental conditions, internal resource endowments, and strategic choices. Resource-based theory considers an enterprise as a collection of various productive resources, and some scholars have discussed the relationship between resource endowments and the survival of new ventures. In recent years, research based on resource bricolage theory deeply discusses how the new ventures cobble together the existing, scattered, and seemingly useless resources on hand to break through the resource constraints due to initial resource shortage. However, because of the difficulties in obtaining data of founding conditions and measuring resource endowments, there are only a few empirical studies on resource endowments and the survival of newly founded ventures in China. Other scholars have studied the impact of innovative activities on the survival of new ventures. Technological innovation can improve a company’s efficiency and reduce the failure risk. However, there are a few studies that distinguish heterogeneous impacts of different types of innovation. In addition, previous studies have generally discussed only a single aspect of the role of resource endowments or innovative activities. Resources and innovation may be intrinsically linked, so the interactive relationship between innovative behavior and resource endowments is worthy of further exploration. Based on the imprinting role of organizational evolution, this paper uses resource endowments and innovative activities as the objects of the investigation of the founding factors of newly founded ventures. It choses manufacturing firms founded from 2004 to 2006 in Jiangsu province as a sample, investigates the survival of these firms in the first 5 years after their establishment, and analyzes the role of their resource endowments and innovative activities in improving the survival of newly founded ventures. In the empirical analysis, innovative activities are divided into four types to investigate heterogeneity in detail. At the same time, the interaction between resource endowments and innovative activities is analyzed through the introduction of cross items. The results show that on the one hand, newly founded ventures employ resource bricolage by consuming resource endowments to gain the ability to survive; and on the other hand, newly founded ventures gain competitive advantages through innovative activities to consolidate their ability to survive. The survival of newly founded venture depends on the resource endowments while the innovation can increase the survival rate. In the meantime, innovative behavior and resource endowments have a substitution relation. In addition, the different types of innovative activities have different impacts, as the effect of supporting process innovation is stronger than that of productive process innovation, which is, in turn, stronger than the total effect of process innovation, but the effect of product innovation is not significant. From the perspective of resources and innovation, this paper deepens the application of organizational imprinting theory to the evolution of enterprises while providing a new theoretical perspective and new empirical evidence for the interpretation of the survival of newly founded ventures in the Chinese context.

abstractWe investigated regional differences in the contribution of newly founded businesses to regional employment. The analysis was at the spatial level of West German planning regions for the period 1984–2002. We found pronounced differences for the employment contribution of new businesses across regions. Regression analyses of these differences show that the regional level of new business formation explains only a part of the employment effect. More important than the mere presence of startups is their quality in terms of their survival rate and growth rates. A large share of innovation activity in small businesses in a region, a high educational level of the regional workforce, and the wide availability of labor have a significantly positive impact. Our results suggest that the success of newcomers is not necessarily at the expense of incumbents but that the development of both kinds of businesses may be positively interlinked.

PurposeIndependent audit oversight is a prerequisite for restoring public confidence in financial reporting and auditing after the past accounting scandals and the financial crisis. By analysing and comparing the independence of the audit oversight boards of 27 European Member States and the USA, this study aims to provide insights into the question of how independent “independent” audit oversight boards are.Design/methodology/approachIndependence is measured in terms of the organisational compositions and regulatory competences of the audit oversight authorities. The data were collected through an e-mail questionnaire that was sent to all European oversight authorities, and by analysing legal provisions of various regulators. The results are analysed and visualised by a Partial Order Scalogram Analysis with Coordinates, which allows conclusions about the similarities of various systems and their relative levels of independence. Both measurements are then equally combined into one value of material independence, which is used to rank the oversight authorities.FindingsAlthough all countries encounter similar pressures to establish profession-independent oversight systems, this study identifies how differently “independence” has been translated in regulatory outcomes. While all countries claim to possess formal independent oversight bodies, there is a visible gap between countries with comparatively strong independent oversight authorities and systems in which accounting bodies still maintain far-reaching regulatory influence. At the same time, the results question the role of the Public Company Accounting Oversight Board (PCAOB) as the globally perceived benchmark of an entirely independent regulator.Research limitations/implicationsThis study focuses on formal independence rather than de-facto independence. Future research has, therefore, to address how these formal arrangements have evolved in regulatory practice.Practical implicationsPolicy makers around the world perceive independent oversight as one of the essential elements of regulatory reforms aiming at restoring public confidence in the aftermath of past accounting scandals. This study enables the comparison and benchmarking of national specific regulatory designs with other forms of independent oversight.Originality/valueAlthough the role of independent regulation is a recurring theme in accounting research, a systematic and encompassing comparison of the intertwining of audit oversight authorities and the accounting profession has not yet been provided. This study takes a first step towards providing a quantifiable measure of the formal independence of audit oversight authorities by mobilizing concepts, methods and prior findings from the field of public policy research.

Overconfidence in Market Timing or Security Selection

The well‐known Oeppen–Vaupel straight line of maximum female life expectancies showed that the highest life expectancy observed in a given year increased linearly from 1840 to 2000. Their analysis fueled major controversy, especially when used to extrapolate future improvements in life expectancy at the same pace. We improve on the empirical analysis by enriching the dataset, expanding the period to 1750–2005, and considering both maximum life expectancy at birth and lowest age‐specific survival rates. It clearly appears that the original Oeppen–Vaupel straight line must be divided into several segments characterized by different slopes and that each segment corresponds to a major advance in the health transition. There is room to push life expectancy higher, but unless some new breakthrough increases the human life span, progress will very likely decelerate as mortality reduction affects individuals at older and older ages. The main key to the future lies not in knowing whether the observed straight line can be extrapolated but in anticipating the next major health improvement that will lead to an additional increase in life expectancy.

This study conducts empirical analysis on the effects of economic incentives on retaining teachers, both in the late-career and early-career, and improving teacher quality in public schools. The first chapter analyzes whether a large pension enhancement helps to retain late-career teachers in an urban district, St. Louis City in Missouri. Many states enhanced pension benefits of public school teachers during the 1990s. St. Louis followed this trend with a major benefit enhancement in 1999. Descriptive analysis of administrative panel data and simple regression analysis suggest that senior teachers were highly responsive: teaching careers were shortened, and the likelihood of retirement increased. To gain further insight into the long run effect of the plan changes, and the differential effects of various components of the change, I estimate a dynamic structural model, which provides good in-sample and out-of-sample fit. Simulations of retirement behavior based on the estimated model under different pension rules imply a large long-run reduction in the labor supply of senior teachers. The expected years of additional teaching for the current cohort of senior teachers would be increased by nearly 27 percent if they were operating under the pre-enhancement pension rules. The second chapter analyzes late-career teacher turnover induced by pension incentives. Using longitudinal data with performance measures for Tennessee public school teachers, we find higher quality teachers are less likely to retire conditional on age and experience. To quantify the effects of pension incentives, we estimate a structural model for retirement and find that high quality teachers have a lower disutility for teaching relative to retirement. We use the structural estimates to simulate the effect of changes in retirement incentives. Enhancements to traditional plans accelerate teacher retirement, whereas targeted retention bonuses delay retirement and retain high quality teachers at a relatively modest cost. The third chapter focuses on the joint dynamics of attrition behaviors and teaching effectiveness of early-career teachers. Using data from a comprehensive evaluation system in Tennessee, I analyze the factors of attrition, the dynamics of teacher quality, and the retention policies for retaining high-quality teachers. The data suggest teacher attrition is negatively correlated with teacher quality. A sequential probit model of binary attrition and binary rating produces good fits for both survival rate and quality distribution. The model shows the quality of novice teachers increases in experience, salary and education level. Increase in salaries of novice teacher could reduce attrition and improve quality.

The shrimp growth and production can be measured through several components such as the harvest ton, mean body weight, survival rate and feed conversion ratio. According to previous studies, the shrimp feed conversion ratio should have a positive relationship with their mean body weight. Nevertheless, in real scenario, high feed conversion ratio does not necessarily implies maximum increment of mean body weight. The measurement of those components usually can be influenced by many factors such as climates, stocking density and day of culture. This study in particular explores the effect of climates on productivity of the shrimp species, Penaeus Vannamei and investigates whether feed conversion ratio influences the mean body weight when stocking are done at different climate season. First, the one-way MANOVA was used to measure the effect between the climate seasons and P. Vannamei production. Then, the regression analysis was apply to measure the relationship between P. Vannamei feed conversion ratio and mean body weight for different climate seasons. Finally, to find the best season for sustainable production of P. Vannamei, the average score of P. Vannamei production was measured according to their stocking climate season. Result revealed that dry season was more favorable for the growth and production of P. Vannamei compared to wet season.

This article introduces two advanced analytical strategies for analyzing contextual-level outcomes in multilevel models: the multilevel SEM and the two-step approach. Since these strategies are seldom used in comparative survey research, we first discuss their methodological and statistical advantages over the more commonly applied approach of group mean aggregation. We then illustrate these advantages in an empirical analysis of the effect of citizens' support for democratic values at the individual level on a contextual-level outcome – the persistence of democracy – drawing on data from the World Values Survey and the Quality of Government project. Whereas we found no significant effect of support for democratic values in the model using simple group mean aggregation, citizens' support for democratic values was a significant predictor of democracies' estimated survival rate when applying latent aggregation in multilevel SEM and the two-step approach. The article corroborates previous concerns with simple aggregation and demonstrates how researchers can improve the validity of their analyses of contextual-level outcomes by using alternative strategies of aggregation.

Background: Non–small cell lung cancer (NSCLC) is the most common histologic type of lung cancer, accounting for 70–85% of all lung cancers. It has brought a heavy burden of disease and financial cost to families, society, and the nation of China. Patients have differing preferences for treatment because of their varying physical conditions and socioeconomic backgrounds, which ultimately affects the choice of treatment as well as treatment outcomes. For better and sustained health outcomes, it is vital to understand patients' preferences. We can then provide medical services to match these preferences and needs rather than basing treatment on our clinical viewpoints alone.Objectives: The aim of this study was to elicit patient preferences for treatment using a discrete-choice experiment and to explore the value/importance that patients place on the different attributes of treatment in order to provide a basis for clinical decision making and patient health management.Methods: The study was conducted with NSCLC patients from three typical hospitals in southwestern China. After identifying patient-relevant treatment attributes via literature review and qualitative semi structured interviews, a discrete-choice experiment (DCE) including seven patient-relevant attributes was conducted using a fractional factorial SAS design. The empiric data analyses of patients were performed using mixed logit models.Results: NSCLC patients (N = 202) completed a survey via a face-to-face interview. Among the seven attributes, the following were considered important: progression-free survival, disease control rate, cost, weakness/fatigue, and nausea/vomiting; mode of administration and rash were considered less important. A clear preference for an increase in progression-free survival and disease control rate was demonstrated. Compared with 5 months of progression-free survival, respondents were willing to pay more (19,860 RMB) for 11 months of progression-free survival (coef.: 0.687). Compared with a 60% rate of disease control, respondents were willing to pay more (19,940 RMB) for a 90% rate of disease control (coef.: 0.690).Conclusions: This study demonstrates the value of DCEs in determining patient preferences for the treatment of NSCLC. The results indicate that not only efficacy factors (such as progression-free survival and disease control rate) were considered but also other factors (such as side effects and treatment costs) and trade-offs between attributes were held to be important. These results are in accord with expectations and can provide evidence for more effective and efficient treatment results. Furthermore, the current results can increase benefits if the presented therapies can be designed, assessed, and chosen based on patient-oriented findings.

Predictors of Lung Transplant Survival in Eurotransplant

Patzek et al. (2013, 2014) proposed the generalized physics-based scaling curve method as an alternative approach to the empirical decline curve analysis that predicted shale gas well production. Independently, (Patzek, 2019; Patzek et al., 2019) also introduced the Generalized Extreme Value statistics to evaluate cohorts of shale wells and their survival rates. In this work, we built a conceptual reservoir model of a typical, hydraulically fractured well in the northeast Pennsylvania Marcellus shale using a commercial reservoir simulator (CMG-GEM) to validate the generalized master curve numerically. We use the simulated gas production as the input data to estimate the generalized reservoir scaling curve, and we compare it to the master curve presented in Saputra et al. (2022). Our results reveal that the physical scaling method captures the physics behind gas production from mudrock plays. Our reservoir simulations agree with the master curve. We conclude that the simple method is an excellent alternative to the current industrial forecasting methods as it is computationally cost-effective, more flexible, and requires fewer input data. Also, the numerical reservoir simulations confirm the behavior of the generalized scaling curve with the variation of selected input factors. We complemented this study by conducting a global sensitivity analysis (GSA) to systematically examine the impacts of hydraulic fracture half-length and spacing, unstimulated shale permeability and gas adsorption on the variations of two master curve scaling parameters, the gas mass in the stimulated reservoir volume (MSRV), and the characteristic pressure interference time (τ). GSA using a reservoir simulator is prohibitive. Therefore, we implement and validate a Gaussian process emulator that represents probabilistically the scaling parameters estimated from the reservoir simulation output. We calibrate the emulator with a small set of experiments sampled with a space-filling design. The conducted study provides new insights into the relationship between the production scaling variables MSRV and τ and the reservoir parameters. The results reveal the high importance and nonlinear effects of the hydraulic fracture height, half-length, maximum gas volume adsorbed, and matrix porosity in varying the scaling variable MSRV. Also, the unstimulated matrix permeability and the hydraulic fracture spacing contribute significantly to nonlinear variations of the scaling variable, τ. Finally, gas adsorption has a small effect on the cumulative gas produced but significantly affects the scaling factor MSRV. Thus, gas adsorption becomes essential when estimating the ultimate recovery factor in the Marcellus shale wells.

Predicting climate change impacts on population size requires detailed understanding of how climate influences key demographic rates, such as survival. This knowledge is frequently unavailable, even in well‐studied taxa such as birds. In temperate regions, most research into climatic effects on annual survival in resident passerines has focussed on winter temperature. Few studies have investigated potential precipitation effects and most assume little impact of breeding season weather. We use a 19‐year capture–mark–recapture study to provide a rare empirical analysis of how variation in temperature and precipitation throughout the entire year influences adult annual survival in a temperate passerine, the long‐tailed tit Aegithalos caudatus. We use model averaging to predict longer‐term historical survival rates, and future survival until the year 2100. Our model explains 73% of the interannual variation in survival rates. In contrast to current theory, we find a strong precipitation effect and no effect of variation in winter weather on adult annual survival, which is correlated most strongly to breeding season (spring) weather. Warm springs and autumns increase annual survival, but wet springs reduce survival and alter the form of the relationship between spring temperature and annual survival. There is little evidence for density dependence across the observed variation in population size. Using our model to estimate historical survival rates indicates that recent spring warming has led to an upward trend in survival rates, which has probably contributed to the observed long‐term increase in the UK long‐tailed tit population. Future climate change is predicted to further increase survival, under a broad range of carbon emissions scenarios and probabilistic climate change outcomes, even if precipitation increases substantially. We demonstrate the importance of considering weather over the entire annual cycle, and of considering precipitation and temperature in combination, in order to develop robust predictive models of demographic responses to climate change.SynthesisPrediction of climate change impacts demands understanding of how climate influences key demographic rates. In our 19‐year mark‐recapture study of long‐tailed tits Aegithalos caudatus, weather explained 73% of the inter‐annual variation in adult survival; warm springs and autumns increased survival, wet springs reduced survival, but winter weather had little effect. Robust predictions thus require consideration of the entire annual cycle and should not focus solely on temperature. Unexpectedly, survival appeared not to be strongly density‐dependent, so we use historical climate data to infer that recent climate change has enhanced survival over the four decades in which the UK long‐tailed tit population has more than doubled. Furthermore, survival rates in this species are predicted to further increase under a wide range of future climate scenarios.

The authors present a non-altruistic model of demand for children, in the presence of uncertainty about children's survival. Children are seen as assets, as they provide help during old age. If certain conditions are met, both the financial market, and the family network are used to transfer resources to old age. Theoretical predictions relative to the change in the mean, and variance of the survival rate are derived. The empirical analysis is based on data from the Human Development of India (HDI) Survey. Different models for count variables, such as Poisson, Hurdle, and ZI models have been employed in the empirical analysis. The results highlight the importance of the uncertainty about children's survival in determining parental choices, thus showing that realized, or expected children's death, is not the only dimension that links fertility decision to children's mortality. The policy implications of such findings are briefly discussed.

The purpose of this study is to identify the difference in firm performance and employment growth between successful and failed capital procurement through equity-based crowdfunding. We conduct an empirical analysis using entire crowdfunding projects that attempted to raise capital through equity-based crowdfunding in South Korea in 2016. We summarize our findings as follows. Descriptive statistics show that the survival rate, sales growth rate, profitability growth, absolute employment growth, and employment growth rate of companies with successful crowdfunding are higher than those of companies with failed crowdfunding. However, from the difference analysis, we do not find a significant difference in the survival rate, sales growth rate, and profitability growth between companies with crowdfunding success and companies with crowdfunding failure. We find that the absolute employment growth and employment growth rate are significantly higher for companies that succeeded in crowdfunding projects compared to companies that did not. In this study, we find that the characteristics of these firms that are conducting or verifying new projects through equity-based crowdfunding financing are similar to those of prior studies results confirming the short-term effects of entrepreneurial activities or new business activities on economic performance and employment growth. In particular, it is very meaningful to confirm that the direct effect of employment growth is also found in start-up firms that raise capital through equity-based crowdfunding. By investigating the difference in firm performance and employment outcomes according to the results of equity-based crowdfunding investment, this study provides useful insights to investors for their efforts to validate participation in crowdfunding. Also, our study raises important policy implications for regulators in their efforts to resolve unemployment and the lack of capital problem for startups and new businesses.

This study was conducted to analyze to compare the survival rate according to the factors affecting the survival of foreign direct investment companies in Korea between 2013 to 2017. In addition, the survival rate of foreign direct investment companies classified according to the Korean standard industry classification is compared. As a result of impact factors on the survival duration of foreign direct investment companies the characteristics of the firm which the Investment Ratio(IR), firm age(FA), and the number of employees(NE) had positive effects. Return on Assets(ROA) of the financial characteristics had positive effects. But other factors did not produce significant results. In the empirical analysis of the survival rate of companies according to industry classification, the survival rate of companies in the real estate industry and financial insurance industry was relatively lower than that of companies in the manufacturing, wholesale & retail business, specialized science & technology service. And the real estate industry and financial insurance industry was investigated with a relatively short survival rate due to the high possibility of risk exposure.