ATTRIBUTION MODELING AND MARKETING RESOURCE ALLOCATION IN AN ONLINE ENVIRONMENT

This dissertation contains one conceptual framework and two essays on the attribution modeling and marketing resource allocation in digital marketing. Chapter II presents the conceptual framework for attribution modeling and hypotheses related to the carryover effects and spillover effects of the information collected during the customer's prior visits through different marketing channels to a firm's website on subsequent visits and purchases. In Chapter III, I propose a method to measure the incremental value of individual marketing channels in an online multi-channel environment. The method includes a three-level measurement model of customers' consideration of online channels, their visits through these channels and subsequent purchase at the firm's website. Based on the analysis of customers' visits and purchases at a hospitality firm's website, I find significant carryover and spillover effects across different marketing channels. According to the estimation results, the relative contributions of each channel are significantly different as compared to the estimates from the widely-used "last-click" metric. A field study was conducted where the firm turned off paid search for a week to validate the ability of the proposed approach in estimating the incremental impact of a channel on conversions. This method can also be applied in targeting customers with different patterns of touches and identifying cases where e-mail retargeting may actually decrease conversion probabilities. Chapter IV analyzes the impact of attribution metric on the overall effectiveness of keyword investments in search campaigns. Different attribution metrics assign different conversion credits to search keywords clicked through the consumers' purchase journey, and the attribution-based credits affect the advertiser's future bidding and budget allocation for keywords, and in turn affect the overall return-on-investment (ROI) of future search campaigns. Using a six-month panel data of 476 keywords from an online jewelry retailer, I empirically model the relationship among the advertiser's bidding decision, the search engine's ranking decision, and the click-through rate and conversion rate, and analyze the impact of the attribution metric on the overall ROI of search campaigns. The focal advertiser changed the attribution metric from last-click to first-click half-way through the data window. This allows me to estimate the impact of the two attribution metrics on budget allocation, which in turn influences the realized ROI under different attribution regimes. Given the mix of the keywords bid by the advertiser, the results show that first-click leads to lower overall revenues and this impact is stronger for the more specific keywords. The policy simulation shows that the advertiser would be able to improve their overall revenue by more than 5% by appropriately changing the attribution metric for individual keywords to account for their actual contribution

Protective effect of astragalus injection against myocardial injury in septic young rats via inhibition of JAK/STAT signal pathway and regulation of inflammation

Purpose: To investigate the protective effect of astragalus injection against myocardial injury in septic young rats, and the underlying mechanism of action. Methods: Seventy-two healthy Sprague Dawley (SD) rats were randomly selected and used to establish a young rat model of sepsis. The young rats were randomly divided into 3 groups: sham, model and astragalus injection groups. Each group had 24 young rats. Serum cardiac troponin I (cTnI), IL-10, IL-6, JAK2 and STAT3 were measured after op. Results: Compared with sham group, serum cTnI level in the model group was significantly higher, while serum cTnI level of the drug group was significantly lower than that of the model group (p < 0.05). Compared with model group, the level of IL-10 in the myocardial tissue of the drug group was significantly elevated, while IL-6 level was lower (p < 0.05). Relative to sham rats, myocardial JAK2 and STAT3 protein levels in model rats were high. However, myocardial JAK2 and STAT3 proteins in the drug-treated rats were significantly downregulated, relative to model rats (p < 0.05). Conclusion: Astragalus injection upregulates IL-10 and IL-6 in rats by inhibiting the activation of JAK/STAT signal pathway, and via maintenance of pro-inflammation/anti-inflammation balance. Thus, astragalus exerts protective effect against myocardial injury in sepsis, and can potentially be developed for use as such in clinical practice. Keywords: Astragalus injection, JAK/STAT signal pathway, Pro-inflammatory/anti-inflammatory imbalance, Sepsis, Myocardial injur

Application of subset simulation in reliability estimation of underground pipelines

This paper presents a computational framework for implementing an advanced Monte Carlo simulation method, called Subset Simulation (SS) for time-dependent reliability prediction of underground flexible pipelines. The SS can provide better resolution for low failure probability level of rare failure events which are commonly encountered in pipeline engineering applications. Random samples of statistical variables are generated efficiently and used for computing probabilistic reliability model. It gains its efficiency by expressing a small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment and compared with direct Monte Carlo simulation (MCS) method. Reliability of a buried flexible steel pipe with time-dependent failure modes, namely, corrosion induced deflection, buckling, wall thrust and bending stress has been assessed in this study. The analysis indicates that corrosion induced excessive deflection is the most critical failure event whereas buckling is the least susceptible during the whole service life of the pipe. The study also shows that SS is robust method to estimate the reliability of buried pipelines and it is more efficient than MCS, especially in small failure probability prediction

Research trends and hot spots in global nanotechnology applications in liver cancer: a bibliometric and visual analysis (2000-2022)

BackgroundLiver cancer (LC) is one of the most common malignancies. Currently, nanotechnology has made great progress in LC research, and many studies on LC nanotechnology have been published. This study aims to discuss the current status, hot spots, and research trends in this field through bibliometric analysis.MethodsThe Web of Science Core Collection (WoSCC) database was searched for papers related to hepatocellular carcinoma (HCC) included from January 2000 to November 2022, and its research hotspots and trends were visualized and analyzed with the help of VOSviewer. In addition, a search was conducted to find LC papers related to nanotechnology. Then we used the visual analysis software VOSviewer and CiteSpace to evaluate the contributions of countries/regions, authors, and journals related to the topic and analyze keywords to understand the research priorities and hot spots in the field as well as the development direction.ResultsThere are 1908 papers in the highly cited literature on LC, and its research hotspots are pathogenesis, risk factors, and survival rate. The literature on the application of nanotechnology in LC had 921 papers. Among them, China (n=560, 60.8%) and the United States (n=170, 18.5%) were the countries with the highest number of published papers. Wang Yan (n=11) and Llovet JM (n=131) were the first authors and co-cited authors, respectively. The International Journal of Nanomedicine was the most prolific academic journal (n=41). In addition to “hepatocellular carcinoma” and “nanoparticles”, the most frequent keyword was “drug delivery”. In recent years, “metastasis” and “diagnosis” appeared in the keyword bursts. This indicates that the application of nanoparticles in the early diagnosis and drug delivery of LC (including liver metastasis) has a good prospect.ConclusionNanotechnology has received more and more attention in the medical field in recent years. As nanoparticles are easily localized in organelles and cells, they can increase drug permeability in tumor tissues, improve drug delivery efficiency and reduce drug toxicity. Our research results were the first scientific evaluation of the application of nanotechnology in LC, providing scholars with research hotspots and development trends

Structural boundary and deep contact relationship between the Yangtze and Cathaysia Blocks from crustal thickness gradients

The deep boundary and contact relationship between the Yangtze and Cathaysia Blocks (the major tectonic units of the Southern China Block), as well as the tectonic attributes of the Jiangnan Orogenic Belt, have remained unknown or controversial. Using data recorded by 128 portable broadband stations and 96 permanent stations, we obtained high-resolution images of crustal thickness and Poisson’s ratio in the study area. The influences of crustal anisotropy and inclined interface were eliminated by using the newly proposed receiver function H–κ–c stacking method. We then used a gradient analysis method to obtain crustal thickness gradients at the boundary of the Yangtze and Cathaysia Blocks for the first time. Our results reveal that the crustal thickness varies from >38 km in the Qinling–Dabie Orogenic Belt to <30 km east of the Tanlu Fault and Cathaysia Block. Areas with high Poisson’s ratios (>0.27) are concentrated on the flanks of the deep fault zone and the continental margin of the study area; those with low Poisson’s ratios (<0.23) are concentrated in the Jiangnan Orogenic Belt. Large crustal thickness gradients are found beneath the eastern part of the Jiujiang–Shitai buried fault (>5 km/°). Combined with the velocity structure and discontinuity characteristics at different depths, these findings suggest that the Jiujiang–Shitai fault may constitute a deep tectonic boundary dividing the Yangtze and Cathaysia Blocks on the lithospheric scale. Moreover, our results support that the Cathaysia Block subducted northwest-ward toward the southeastern margin of the Yangtze Block in the Neoproterozoic, and that the Jiujiang–Shitai buried fault and Jiangshan–Shaoxing fault are the deep and shallow crustal contact boundaries of the two Blocks, respectively; that is, the Yangtze Block overlaps the Cathaysia Block

Evaluating Sampling Biases in Policy Analysis of Environmental Markets

unpublishednot peer reviewe

Reliability analysis of composite sandwich structure for fuselage skin based on surrogate model

Composite structures are characterized by multiple source uncertainties in mechanical properties, geometric dimension, etc., and multiple failure modes, which bring challenges to their design and application. In order to explore the reliability analysis method of composite sandwich structures with multi-source uncertainties and multi-failure modes, a parametric finite element model and an acoustic boundary element model were established for deterministic analysis of a fuselage skin sandwich structure. Considering the randomness of the mechanical properties of composite materials and the laminate thickness, the structural reliability models were established for three typical failure modes of sandwich structures: static strength failure, global buckling and vibration noise. In order to reduce the computational effort, the Kriging surrogate models of failure modes were constructed, and the subset simulation method was used to predict the system failure probability of the sandwich structure of fuselage skin. The proposed computational framework provides support and tool for the fine design of composite sandwich structure

An adaptive PC-Kriging method for time-variant structural reliability analysis

The practical application of time-variant reliability analysis is limited by its computationally expensive models which describe the structural system behavior. This paper presents a new adaptive PC-Kriging (APCK) approach to accurately and efficiently assess the time-variant reliabilities. Time interval is firstly discretized with a series of time instants and then the stochastic process is reconstructed by standard normal random variables and deterministic function of time. PC-Kriging (PCK) models are built at each time instant to predict the instantaneous responses of performance function. To improve the accuracy and efficiency, a new update strategy based on the integration of U- and H- learning functions is developed to refine the PCK models of instantaneous responses. One or two best samples are identified by the proposed learning criterion for updating the PCK models. Finally, Monte Carlo simulation (MCS) is used to estimate the time-variant reliability based on the updated PCK models. Four examples are used to validate the accuracy and efficiency of the proposed method

Identifying the Probability Distribution of Fatigue Life Using the Maximum Entropy Principle

It is well-known that the fatigue lives of materials and structures have a considerable amount of scatter and they are commonly suggested to be considered in engineering design. In order to reduce the introduction of subjective uncertainties and obtain rational probability distributions, a computational method based on the maximum entropy principle is proposed for identifying the probability distribution of fatigue life in this paper. The first four statistical moments of fatigue life are involved to formulate constraints in the maximum entropy principle optimization problem. An accurate algorithm is also presented to find the Lagrange multipliers in the maximum entropy distribution, which can avoid the numerical singularity when solving a system of equations. Two fit indexes are used to measure the goodness-of-fit of the proposed method. The rationality and effectiveness of the proposed method are demonstrated by two groups of fatigue data sets available in the literature. Comparisons among the proposed method, the lognormal distribution and the three-parameter Weibull distribution are also carried out for the investigated groups of fatigue data sets