Response Variance Research Articles

Forecasting Coal Prices Using Decision Tree Approach

Coal is an important fuel in the world's energy systems. Today's world depends heavily on coal. It contributes to 41% of the world's power and acts as a key ingredient in the production process of 90% of cement and 70% of the world's steel. An accurate prediction model for forecasting future coal prices would provide critical information and a timely caution to governments to ensure a steady energy supply. Studies on forecasting coal prices regarding related commodities such as crude oil, iron, natural gas, and paper are rare. Hence, this research aims to forecast coal prices using historical data for the 2013-2016 period. The study uses a decision tree model to anticipate the coal prices, and the impulse response function and variance decomposition are used to show the dynamic connections of coal prices with various variables. The model in predicting coal prices performs well with mean absolute percentage errors of around 5%. The study results will likely enable new insights in providing valuable inputs for all the stakeholders.Keywords: Coal price forecasting, decision tree, prediction

CompCorona: A web application for comparative transcriptome analyses of coronaviruses reveals SARS-CoV-2-specific host response.

Understanding the mechanism of host transcriptomic response to infection by the SARS-CoV-2 virus is crucial, especially for patients suffering from long-term effects of COVID-19, such as long COVID or pericarditis inflammation, potentially linked to side effects of the SARS-CoV-2 spike proteins. We conducted comprehensive transcriptome and enrichment analyses on lung and peripheral blood mononuclear cells (PBMCs) infected with SARS-CoV-2, as well as on SARS-CoV and MERS-CoV, to uncover shared pathways and elucidate their common disease progression and viral replication mechanisms. We developed CompCorona, the first interactive online tool for visualizing gene response variance among the family Coronaviridae through 2D and 3D principal component analysis (PCA) and exploring systems biology variance using pathway plots. We also made preprocessed datasets of lungs and PBMCs infected by SARS-CoV-2, SARS-CoV, and MERS-CoV publicly available through CompCorona. One remarkable finding from the lung and PBMC datasets for infections by SARS-CoV-2, but not infections by other coronaviruses (CoVs), was the significant downregulation of the angiogenin (ANG) and vascular endothelial growth factor A (VEGFA) genes, both directly involved in epithelial and vascular endothelial cell dysfunction. Suppression of the TNF signaling pathway was also observed in cells infected by SARS-CoV-2, along with simultaneous activation of complement and coagulation cascades and pertussis pathways. The ribosome pathway was found to be universally suppressed across all three viruses. The CompCorona online tool enabled the comparative analysis of 9 preprocessed host transcriptome datasets of cells infected by CoVs, revealing the specific host response differences in cases of SARS-CoV-2 infection. This included identifying markers of epithelial dysfunction via interactive 2D and 3D PCA, Venn diagrams, and pathway plots. Our findings suggest that infection by SARS-CoV-2 might induce pulmonary epithelial dysfunction, a phenomenon not observed in cells infected by other CoVs. The publicly available CompCorona tool, along with the preprocessed datasets of cells infected by various CoVs, constitutes a valuable resource for further research into CoV-associated syndromes.

The Influence of Labor Market Determinants on Economic Inequality Measured by Gini Coefficient in Montenegro

In this paper an analysis is conducted with the aim of a better understanding how the labour market and income inequality in society are connected, examining the relationships between the variables that describe economic inequality and the labour market in Montenegro. The analysis involves the use of econometric techniques and VAR models, which, with the use of impulse response functions and variance decomposition, best reflect the impact of selected labour market variables on economic inequality. The results of the analysis show that the variables of the labour market, namely the unemployment rate and the long-term unemployment rate, proved to be significant in explaining economic inequality, measured by the Gini coefficient. The results of the research can be useful to various researchers dealing with the issue of economic inequality in Montenegro, providing an additional mechanism for analyzing flows and predicting the future values of the determinants of economic inequality. The results also enable a different approach in the analysis of the labour market and the economic inequality in Montenegrin society, which can serve as a basis for many future analyses.

E-commerce mineral resource footprints: Investigating drivers for sustainable mining development

As global economies surge, the escalating demand for precious mineral resources raises environmental concerns regarding mining activities. This study explores factors influencing e-commerce mineral resource footprints in six resource-rich economies from 1996 to 2022. Analyzing relationships between various factors and e-commerce mineral resource footprints, the study identifies key drivers of sustainability in the mining industry, informing policy decisions for responsible resource management. The findings reveal that mining resource incentives, combustible renewable waste, renewable energy demand, and economic growth contribute to increased footprints, while mining resource information has the opposite effect. Causality estimates confirm that resource incentives, combustible renewable waste, and renewable energy cause e-commerce mining footprints. The study corroborates hypotheses, such as mining resource incentives driving green energy development. Impulse response function and variance decomposition analysis predict future trends, offering valuable insights for policy decisions promoting responsible resource management and a sustainable future.

Trading Behaviour Exhibited by Institutional Investors During Calm and Volatile Periods in the Indian Scenario

The stock market is the reflection of the trading pattern of various investors. The present study attempts to examine the trading behaviour followed by foreign institutional investors, domestic institutional investors and mutual funds during 2010–2020 in the Indian stock market. The whole time period is divided into two subperiods using the chow breakpoint test. Two vector autoregression framework models accompanied with impulse response function and variance decomposition analysis are employed in both the subperiods, namely calm period and volatile period. It is found that the institutional investors do not pay heed to the market returns in the calm period, while the interdependency among the institutional investors increases in the volatile period. The structural break enhances the forecasting accuracy of the model significantly. This study will help the government to understand the impact of calm period and volatile period on the trading behaviours of the institutional investors and thereby their sentiments in the Indian stock market. JEL Codes: G1, G23

A precision neuroscience approach to estimating reliability of neural responses during emotion processing: Implications for task-fMRI

Recent work demonstrating low test-retest reliability of neural activation during fMRI tasks raises questions about the utility of task-based fMRI for the study of individual variation in brain function. Two possible sources of the instability in task-based BOLD signal over time are noise or measurement error in the instrument, and meaningful variation across time within-individuals in the construct itself—brain activation elicited during fMRI tasks. Examining the contribution of these two sources of test-retest unreliability in task-evoked brain activity has far-reaching implications for cognitive neuroscience. If test-retest reliability largely reflects measurement error, it suggests that task-based fMRI has little utility in the study of either inter- or intra-individual differences. On the other hand, if task-evoked BOLD signal varies meaningfully over time, it would suggest that this tool may yet be well suited to studying intraindividual variation. We parse these sources of variance in BOLD signal in response to emotional cues over time and within-individuals in a longitudinal sample with 10 monthly fMRI scans. Test-retest reliability was low, reflecting a lack of stability in between-person differences across scans. In contrast, within-person, within-session internal consistency of the BOLD signal was higher, and within-person fluctuations across sessions explained almost half the variance in voxel-level neural responses. Additionally, monthly fluctuations in neural response to emotional cues were associated with intraindividual variation in mood, sleep, and exposure to stressors. Rather than reflecting trait-like differences across people, neural responses to emotional cues may be more reflective of intraindividual variation over time. These patterns suggest that task-based fMRI may be able to contribute to the study of individual variation in brain function if more attention is given to within-individual variation approaches, psychometrics—beginning with improving reliability beyond the modest estimates observed here, and the validity of task fMRI beyond the suggestive associations reported here.

BETWEEN-PERSON AND DAILY WITHIN-PERSON VARIATION PATTERNS IN MEASURES OF VIEWS OF AGING

Abstract Despite increasing evidence of daily associations between individuals’ health and their age-related thoughts, beliefs, feelings and experiences (collectively referred to as views of aging, VOA), we know little about daily variation in VOA more generally. We used data from an online sample of 122 adults (aged 26 to 78 years) who completed multiple measures of VOA (subjective age, age group identity, aging attitudes, implicit theories of aging, awareness of age-related change) on each of 7 consecutive days, partitioning variance in responses to each measure at the person and day levels to assess between- and within-person variability, respectively. Results showed that, in all measures, between-person variability accounted for most of the total observed variation (62% to 92%) whereas within-person variability accounted for a significant but smaller amount (8% to 38%). The ratio of between- to within-person variation, however, depended on the specific measure and age group assessed, with the highest ratios observed for subjective age (versus other measures) and older adults (versus young adults). Findings suggest that VOA are relatively stable in daily life and may become more stable with advanced age. Further study of measures and age groups that exhibit the most within-person variability can yield insights that help increase understanding about the dynamics of VOA (i.e., which VOA constructs are most sensitive to fluctuating contexts and for whom?) and therefore inform future work linking VOA to other phenomenon in daily life.

An Analysis of the Impact of Insider Trading on Executive Compensation in Listed Companies Based on VAR Modeling

Abstract In this paper, we first establish a VAR model, screen the variables using the CSIS method so as to achieve fast dimensionality reduction, and use the cointegration theory to model non-stationary time variables to determine the pseudo-regression analysis between variables. Impulse response functions and variance decomposition are then used to analyze the dynamic effects of changes in random disturbance terms on the whole system and other variables. Finally, the effects of insider trading on executive compensation are explored using corporate performance and market-based executive pay entitlement as references, respectively. The results show that the regression coefficients of executive compensation level and cumulative excess turnover rate of the event announcement period are 0.805 and 0.018 for corporate performance and market-based compensation, respectively, and the higher the level of executive compensation based on corporate performance and market-based compensation, the lower the impact of insider trading on executive compensation. Equity incentives reduce the impact of insider trading on executive compensation, and the regression coefficient of excess turnover on executive compensation is less than 0 in firms with shareholding levels higher than 10%.

Associations between attitudes towards and reported intakes of sugars, low/no-calorie sweeteners, and sweet-tasting foods in a UK sample

Public health initiatives are currently aiming to lower free sugar intakes for health benefits, but attitudes towards sugars, their alternatives such as low/no-calorie sweeteners (LNCS), and towards sweet-tasting foods may be hampering efforts. This work investigated associations between attitudes towards and the reported intakes of sugars, LNCS and sweet-tasting foods, and identified latent attitude profiles in subpopulations of adults in the United Kingdom. A total of 581 adults completed a questionnaire assessing their usual intake of sugars, LNCS and sweet-tasting foods, attitudes towards these foods and various demographic characteristics. Six principal components explained 39.1% of the variance in the attitude responses, named: ‘Personal Impact’, ‘Personal Management’, ‘Apathy’, ‘Negativity’, ‘Perceived Understanding’ and ‘Perceived Nonautonomy’. Personal Impact was negatively associated with reported consumption of sugar-food and sweet-tasting food groups more frequently (smallest β = −0.24, p < .01). Personal Management was positively associated with reporting adding sugar and consuming sugar-food and sweet-tasting food groups more frequently (smallest β = 0.14, p < .01). Three latent classes of participants with distinct patterns of attitudes were identified, labelled: ‘Feeling Ill-equipped’ (n = 52), ‘Actively Engaged’ (n = 162) or ‘Unopinionated’ (n = 367). Individuals who were classed as Actively Engaged reported adding LNCS more frequently than those classed as Feeling Ill-equipped (t(212) = -2.14, p<.01), who reported consuming sweet-tasting food groups more frequently than those classed as Unopinionated (t(417) = 2.65, p < .01). These findings suggest the need for personalised approaches within public health initiatives, to reduce free sugar intakes.

Adolescent General Efficacy Scale for Parents (AGES-p): Adaptation and Spanish Validation

It has been well documented in the literature that parental cognitions contribute in central ways to child development and adjustment. Nevertheless, there are no other questionnaires in the Spanish context that measure parents’ perceptions toward their adolescent children’s efficacy. This study aims to develop and validate a new scale to measure parents’ perceptions toward their adolescent children’s efficacy. A total of 594 Spanish parents and their children aged between 11 and 16 years completed the General Self-Efficacy Scale (GSE), the Adolescent General Efficacy Scale for Parents (AGES-p), and the Adolescent Future Expectations Scale for Parents (AFES-p). Non-probability convenience sampling was used. We kept similar proportions in our sample when selecting participating schools (75.90% State schools and 24.10% private schools). The psychometric properties of the AGES-p scale were examined using Exploratory and Confirmatory Factor Analysis. We obtained a unidimensional factor structure, which explains 66.77% of the variance. This means that most of the observed variance in item responses is explained by a single latent construct. The reliability (α = 0.926) and convergent validity of the scale were found to be high. It can be observed that there are positive and significant correlations between AGES-p and the questionnaires used: GSE (r = 0.268) and AFES-p (r = 0.508).The AGES-p has the potential for evaluating parents’ perception toward their children’s efficacy. This scale in the Spanish context provides a new measurement instrument to the field of family evaluation, applicable both to research and psychoeducational, clinical, and social interventions.

Source credibility plays the central route: an elaboration likelihood model exploration in social media environment with demographic profile analysis

PurposeThis study aims at building a framework for the electronic word-of-mouth (eWOM) response under the social media environment. The elaboration likelihood model was adopted to explain how message source credibility and message appeal jointly influence the eWOM response process, while source credibility provides a central route and message appeal plays a peripheral route for information processing.Design/methodology/approachThis study used a scenario design to test the decision behavior in the Facebook environment through message content manipulation. A convenience sampling method was adopted in this study. We collected 203 valid questionnaires and tested this research model with LISREL 8.8. This study used a two-stage structural equation modeling data analysis method with LISREL 8.8, by which the measurement model was assessed through confirmatory factor analysis for the reliability and validity of the research model, and the causal relationship among factors was assessed through exploratory factor analysis .FindingsThe results showed that 53% variance of eWOM responses could be explained by message source credibility and emotional message appeal from the elaboration likelihood model perspective. Message source credibility plays a central role in the social media environment. The model was further tested with a demographic profile analysis for both gender and age. It is found that a female user is influenced by both source credibility and emotional appeal, but a male user is only influenced by message source credibility. The mature age group is more responsive to eWOM messages.Research limitations/implicationsThe sample might not represent all social networking sites (SNS) users. The participants represent a small segment of the Facebook population around the globe. Secondly, this research design could be improved by using more recreational messages to test the effects of message appeal and message source credibility. Thirdly, the mobile phone is a type of physical product rather than an experiential product. Future studies could try to identify the same eWOM determinants with different SNS functions, for example, the inbox message function. Similarly, Facebook users are allowed to use both text and pictures to disseminate promotional messages.Practical implicationsThis study provides an insight for SNS administrators regarding the determinants of driving more customer responses toward a message. Message source credibility and message appeal are identified as the antecedents for eWOM responses in SNS. Companies could make use of this finding to improve their marketing communication strategy in SNS. The finding can inform administrators of the importance of focusing on both customers’ psychological state and message attributes during the dissemination of promotional messages to improve the efficiency of the promotional effort. Companies aimed at receiving different types of eWOM responses in SNS may need to consider other factors for creating their promotional messages.Originality/valuePrevious studies have mainly identified factors influencing eWOM responses from the people-centered variables such as personal traits and social relationships. This study proposes that the eWOM response is a dual information processing process that can be explained by the ELM. When a user processes information in SNS, he follows both the central route and the peripheral route (i.e. source credibility and message appeal) which can influence the eWOM response. It is the first time that the source credibility is investigated as the central route in ELM model.

Study on the Relationship Between the Number of Adverse Drug Reactions of Essential Drugs and Visits: Based on Vector Autoregressive Model.

To analyse the relationship between the adverse drug reactions (ADRs) of essential drugs and visits, based on the recorded annual increase in ADRs associated with essential medicines in China, to provide a reliable theoretical basis for further analysis and optimization of the safety of essential drugs. The data of adverse reactions of essential drugs in China from 2011 to 2020, time series analysis was conducted, and vector autoregressive (VAR) model was established. The relationship between the number of ADRs and visits was explored empirically through Granger causality test, impulse response function and variance decomposition. There was a long-term cointegration relationship and one-way causality between the number of visits and ADRs caused by essential medicines. In the initial stage, the ADR response to the number of visits increased sharply, but with an increase in the number of lag periods, the impact remained basically stable, even showing a slight decreasing trend. The number of visits impacts ADRs caused by essential medicines, but this impact remains basically stable after reaching a certain level.

Political Stability, Quality of Governance and Stock Market Performance in Nigeria: A VECM Approach

Governance structure is riddled with rent-seeking behaviour by public agents, public institutions are not only ineffective and retroactive but there is also no regards to rule of law, no accountability and above policy inconsistencies which affects the economy including vibrant development of the stock market. This paper examined the impact of political stability and quality of governance market performance in Nigeria from 1986-2022. The variables of this study are credit to the private sector, gross domestic product, inflation, and investment (domestic), and broad money supply. The other variables are political stability, quality of governance government expenditure, unemployment and value of stocks traded. The data for these variables were sourced from the Central Bank of Nigeria Statistical Bulletin and the National Bureau of Statistics of various years. This paper was anchored on the efficient market hypothesis and the impulse response function and variance decomposition was used. The result suggested that market capitalization was strongly endogenous in the short-run predicting itself about 93 percent and 86 to 85 percent in the long-run while a one standard deviation of shock from gross domestic product to market capitalization continuously decreased from periods 1 to 10. The conclusion from the analysis of the findings is that political stability and quality of governance impacted on stock market performance. This paper recommended economy-wide reforms tom stem the impact of negative shock on the economy and stock market.

Interaksi Bank Syariah dan Variabel Makroekonomi dalam Mendorong Pertumbuhan Ekonomi di Negara Berkembang

This study aims to examine the empirical impact of the Islamic banking sector, inflation rate, and currency exchange rate on the economic growth of Saudi Arabia, United Arab Emirates, Kuwait, Malaysia, Qatar, Bahrain, and Bangladesh from 2014 to 2022. For the purpose of further investigation, a total of 717 observations were selected according to certain criteria. The sample consisted of 24 banks from seven countries that have the highest aggregate assets on a global scale. Data is collected quarterly. This research approach is quantitative research using the Vector Error Correction Model as an analysis technique. Long-term analysis is tested using cointegration analysis. Impulse response function (IRF) and variance decomposition (VD) techniques were used in this study to show how each macroeconomic variable shock affects the short-term dynamic path of all system variables. The results of the study found that the shock of the majority of research variables was responded positively by GDP except for inflation which in the initial period of the shock was responded negatively by GDP. The results of the Variance Decomposition GDP analysis can be explained that in the initial period GDP variance was formed sequentially from the exchange rate variance, inflation, Total Assets of Islamic Banks, Total Assets of Islamic Banks, and the contribution of Islamic bank assets continued to increase during the observation period.

Vibration reduction performance for the novel grounded inerter-based dynamic vibration absorber controlling a primary structure under random excitation

This paper investigates the control performance of a novel grounded inerter-based dynamic vibration absorber (GI-DVA) for random vibration reduction. First, the dynamics equations of the coupled system are written and the transfer function is obtained based on the Laplace transform. Then, assuming that the primary structure is under random white noise excitation, the displacement variance of the primary structure is calculated based on the exact definition of the H2 norm, by solving the Lyapunov equation. By imposing that the partial derivatives of the response variance of the primary structure with respect to the system parameters are simultaneously equal to zero, the optimum design values of the H2 optimized GI-DVA were derived numerically for given different mass ratio. It can be found that the optimal design parameters as the inerter-to-mass ratio, the stiffness ratio and the damping ratio increase, while the frequency ratio decreases with the increase in the mass ratio. Under the optimal conditions, the response analysis showed that the primary structure response controlled by the H2 optimized GI-DVA can decrease with the increase in the mass ratio, but is less sensitive to large mass ratios, and can be robust to the mistuning on the optimum design parameters. Then, the control performance evaluation is first performed in the frequency domain, which reveal that the dynamic response reduction capacity of the H2 optimized GI-DVA are significantly 62% and 48% superior to the H2 optimized classic DVA (CDVA) and high-performance passive nontraditional inerter-based DVA (NIDVA-C4), respectively. Furthermore, for the root mean square response evaluation (H2 performance), the H2 optimized GI-DVA can provide significantly H2 performance 58% and 50% than the H2 optimized CDVA and NIDVA-C4, respectively. To obtain more realistic results, the time domain simulation is performed, which showed that the GI-DVA can provide significantly performance for random vibration reduction.

Information Transfer Among Grape Producers in the Western United States on Pest and Disease Management

Knowledge about how producers subjectively assess and communicate about different information resources can help optimize Agricultural Extension efforts. In particular, how do growers use different information resources when making decisions on pest and disease management? Using pest and disease management in wine grapes ( Vitis vinifera) as a case study, three surveys were conducted among grape producers in the western United States to qualitatively explore resource options ( n = 15), examine the relative importance of the 23 different information resources identified ( n = 63), and investigate the social networks where information is passed within and between regions ( n = 65). Five different informational archetypes emerged, demonstrating different preferences for information resource use, which explained 66% of the variance in survey responses. Personal connections (e.g., discussion with professional network, with field foreman and supervisors, and with an Extension agent) were extremely important to the participants. In the communication network analysis, 65 participants were used to form a 324-actor network with 448 links, which were then subdivided into intra-state networks. The networks show evidence of structures that facilitate information diffusion and cooperation between independent producers. Additionally, even with networks much smaller than the grape producer populations in these states, influential individuals could be identified. These individuals, when targeted by outreach professionals, could assist with information dissemination and facilitate changes in opinion or behaviors in the region. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.

Banking Transparency, Financial Information and Liquidity Risk Management: Case of Saudi Banks

The article aims to assess the impact of banking transparency on liquidity risk. To do so, we first test the determinants of Liquidity Coverage Ratio (LCR) as well as ensure the resilience of the Saudi banking system over the period from 2014 to 2021. Using System GMM with bank-specific and macroeconomic variables, results show that capital adequacy ratio, SIZE, GDP growth as well as past LCR levels significantly influence the LCR.&amp;nbsp; Secondly, we adopt the Panel Vector Auto Regression (PVAR) approach to assess the response of the LCR to various shocks. Impulse Response Functions (IRF) and variance decomposition demonstrate that the shocks to past LCR, AQ, CAR and GDP increase future liquidity risk. Thirdly, we prove that Saudi banks implement less than 50% of the transparency dimensions. They mainly disclose financial information and information on information credibility. Barely 18% of information on non-financial components of banking activity is made available to the public. Information on liquidity risk and on the timeliness of information is not available either in annual reports or on the bank&amp;#39;s website. On average, the banks in the sample do not give importance to the publication of reports. These results may undermine the effectiveness of the guidelines of the Basel Committee agreements to reduce risk-taking by Saudi banks.

THE EFFECT OF SELECTED MACROECONOMIC VARIABLES ON THE HOUSING PRICE INDEX IN TURKEY

This study investigates how the house price is affected by macroeconomic variables such as interest rate, exchange rate, money supply and inflation rate. Housing supply and housing demand determines house price. On the one hand, housing supply dimensions covers contruction cost, existing land, housing stock. On the other hand, housing demand dimension involves interest rate, consumer price index as the indicator of inflation, income, population growth and employment rate. In order to measure the effects of macroeconomic variables more accurately, the housing price index variable determined by the Central Bank was used. Depending upon monthly data for the period 2010-2023 in Turkey, VAR models are used. In this way it is intended to find the direction and degree of the effect of selected macroeconomic variables on the house price index by performing impulse response function and variance decomposition analysis. According to this analysis findings, interest rate and exchange rate had a significant effect on the house price index. In line with the results obtained after the variance decomposition analysis, it was determined that the interest rate had a 19% effect and the exchange rate had a 14% effect on the house price index at the end of the 10th period.

무역과 ESG가 상호 미친 영향에 관한 연구

When infused with ESG principles, Trade transforms into a force for positive change, driving economies while safeguarding our planet's future. Trade and ESG form a powerful alliance, where economic growth is nurtured in the embrace of environmental stewardship, social responsibility, and ethical governance. So this article examine on the mutual influence between ESG index and trade index in South Korea. For this purpose, we employ the vector-autoregression of ESG index and trade index in Korea, impulse response function and variance decomposition of ESG index and trade index in South Korea, Granger causality test of ESG index and trade index in South Korea using weekly data on the amount of ESG index and trade index in South Korea. The sample period of ESG index and trade index in South Korea is covering from January 7, 2012 to Jun 10, 2023. This paper showed following main results. First, ESG index and trade index in South Korea have unit roots. Second, the first differential data of ESG index and trade index in South Korea have no unit roots. Third, there is no at least one cointegration between the level data of ESG index and trade index in South Korea and there is at least one cointegration between the first differential data of ESG index and trade index in South Korea. Fourth, ESG index and trade index in South Korea is –0.41573. In addition, we find that ESG index granger cause the trade index and the trade index granger cause the ESG index in South Korea.

Dynamic analysis of damping structures considering support stiffness

An analysis method for the random seismic response of viscoelastic damper structures with support is proposed. This method considers the influence of support stiffness and analyzes the dynamic characteristics associated with support stiffness. It also combines the advantages of the complex modal method (CMM) and the pseudo-excitation method (PEM), improving the complex integration operation in calculating the spectral moments and variances of random seismic responses. The support and the viscoelastic damper constitute the equivalent damper. The damper's constitutive relationship and structural dynamic equations are decoupled to calculate conveniently the frequency domain solution of the responses. Second, the quadratic decomposition of the power spectral density function (QD-PSDF) is applied to simplify the power spectrum and obtain the closed-form solution of spectral moments and variances. Finally, the structural dynamic characteristics and the influence of support stiffness on the vibration control effect of the equivalent damper are investigated based on the closed-form solution. The structural dynamic reliability is also discussed according to the first excursion failure criterion. The results demonstrate that the damper's control effect and structural reactions are reduced, while the dynamic reliability is also enhanced when increasing support stiffness. The performance of the structure and damper tends to stabilize when the support coefficient reaches a specific level.