Variance In Dependent Variable Research Articles

A Hierarchical Linear Models Approach to Explaining Reflective Thinking Skill Through Problem Solving

The purpose of this study is to identify the student and teacher level factors that explain the reflective thinking skills through problem solving of elementary school pupils. The research was conducted in public elementary schools in three Van districts: Pekyolu, Tuşba, and Edremit. The study's sample consists of 52 mathematics teachers and 1126 elementary school pupils. "Participant Information Form," "Reflective Thinking Ability Through Problem Solving Scale," and "Mathematics Problem Solving Attitude Scale" are data gathering tools for pupils. Teachers' data was gathered using the "Participant Information Form," the "Reflective Thinking Tendency Scale for Teachers and Preservice Teachers," and the "Scale for Learner Autonomy Support." According to the results, it is found that the 90 % of variance in dependent variable can be explained by student level variables. Teacher level variables could explain 10% of outcome variance. The gender of students, receiving private tuition, book reading frequency, time devoted to studying mathematics, and attitude through problem solving are significant factors that can predict the dependent variable. Moreover, students' reflective thinking ability can be significantly influenced by teacher-level factors, such as teachers' knowledge of problem-solving steps and their tendency for reflective thinking. The authors recommend education or seminars that develop teachers’ reflective thinking tendency and problem-solving courses be provided in mathematics teaching undergraduate programs. Students should be supported in gaining reading habit and activities that have positive impact on the students’ problem-solving attitude.

Revitalizing Performance of Three Star Hotels in Machakos County, Kenya Through the Application of Turnaround Strategies

This study sought to assess the effect of turnaround strategies on performance of selected three-star hotels in Machakos County, Kenya. The specific objectives were to determine the impact of downsizing, divestiture, price bundling, and repositioning on the performance of three-star hotels in Machakos County, Kenya. The research was grounded on the balance scorecard theory, contingency theory, institutional theory, and resource-based view theory. The study adopted a descriptive research design. A total of 454 (Finance staff, HR staff, and Marketing staff, Guests) involved in operation of three-star hotels were targeted. A stratified random sampling technique was used to select a sample size of 135 respondents. Semi-structured questionnaires were utilized to gather primary data. A pilot study was done using 10 participants who were not involved in the final data gathering to check validity and reliability of study instrument. To explore the impact of the link between the independent and dependent variables, multiple regression analysis was performed. The study findings show that coefficient of correlation was 0.789, an indication that the study variables significantly influenced performance of three-star hotels. Coefficient of adjusted determination was 0.615 which translates to 61.5%. This indicates that variations in dependent variable was explained by the independent variables (downsizing strategy, divestiture strategy, price bundling and repositioning strategy). The findings also established that P-value was 0.001 which is less than 0.05 an indication that the study variables significantly influenced performance of three-star hotels. The study concludes that turnaround strategies significantly affect the performance of selected three-star hotels in Machakos County, Kenya. The hotel administrators should come up with reliable communication channels about the reasons behind the downsizing staff and offer support services for affected employees. The three-star hotels should conduct thorough due diligence before divesting any assets. This includes a comprehensive analysis of the financial implications, potential impact on market share, and considerations of the long-term strategic goals of the organization.

Abundance and Species Richness of Lianas in a Karst Seasonal Rainforest: The Influence of Abiotic and Biotic Factors

Lianas are a crucial component of karst seasonal rainforests, yet research on them has predominantly focused on non-karst regions. Consequently, their abundance and species richness remain relatively understudied within karst ecosystems. We aimed to document the abundance and species richness of lianas and investigate their relationships with abiotic and biotic factors, based on data from a fully mapped 15 ha plot in a karst seasonal rainforest of Nonggang (SW China). Structural equation models (SEMs) were employed to estimate the path coefficients and variation of dependent variables, enabling a comprehensive analysis of the factors affecting the abundance and species richness of liana. Within the 15 ha plot, a total of 23,819 lianas were identified, encompassing 113 species from 34 families. These lianas constituted 24.16% of the total woody plant density and 33.44% of the species present, but only 4.32% of the total woody plant basal area. Lianas are primarily influenced by abiotic factors, especially elevation and phosphorus (P), with less impact from biotic factors. Our findings reveal that lianas, despite constituting a relatively small percentage of the total woody plant basal area, significantly contribute to the density and diversity of the forest. Notably, abiotic factors such as elevation and phosphorus availability predominantly shape the distribution and richness of lianas, highlighting the importance of these environmental variables. The findings offer valuable insights for future liana studies and the preservation of karst forests’ biodiversity.

The Influence of Intellectual Capital and Investment Decisions on Company Value

This study aims to determine the influence of intellectual capital and investment decision on firm value. This type of research is correlational, aimed at proving whether there is a relationship between variables as found in previous studies. The population includes all consumer non-cyclicals companies listed on the Indonesia Stock Exchange for the period from 2013 to 2022. The sampling technique used is Purposive Sampling. The population data consists of 290 companies, and a sample of 130 companies was obtained. The data analysis method used is multiple linear regression analysis. The results of the data analysis show that intellectual capital has a positive effect on firm value, and investment decision have a positive effect on firm value. The adjusted R-Square value of 0.1204 indicates that the ability of independent variables to explain the variation in dependent variables is 12.04%, and the remaining 87.6% is explained by other variables outside the research model.

Contribution of climatic variables and their interactions to reference evapotranspiration changes considering freeze-thaw cycles in the Tibetan Plateau during 1960–2022

While the direct impact of climate change on reference evapotranspiration (ET0) has been extensively studied, there is limited research on the indirect impact resulting from the interaction between climatic variables. This gap hinders a comprehensive understanding of climate change effects on ET0. Additionally, there is scarce exploration into the quantitative effect of freeze-thaw cycles on ET0 variation. In this study, we employed path analysis and dependent variable variance decomposition methods to discern the direct and interactive effects of climatic variables on ET0 in the Tibetan Plateau from 1960 to 2022. Annual ET0 exhibited variation across basins, with the coefficient of variability during the thawed period smaller than that during the non-thawed period. On an annual scale, the largest contribution to ET0 variation came from water vapor pressure deficit (VPD) at 47.7%. This contribution was amplified by its coupled interaction with temperature (T) at 47.1%, although the contribution was partially offset by the interactive effects of VPD with downward shortwave radiation and wind speed at −2.4% and − 27.6%, respectively. During different freezing-thawing periods, VPD primarily controlled ET0 variation, with its interaction with other climatic variables enhancing its impact. Furthermore, soil moisture, influenced by freeze-thaw cycles, exhibited a strong correlation with T and VPD, indicating the significant effect of freeze-thaw cycles on ET0 variation. The weak correlation between ET0 and NDVI suggested that vegetation growth had a limited regulatory effect on ET0. These findings provide valuable insights into the impact of interactions between climatic variables on hydrological processes, enhancing our understanding of the interactive roles of hydrometeorological variables.

Trend-Fourier Time Series Regression Model for Secular-Cyclical Datasets

The study proposed a Trend-Fourier Regression (TFR) model to handle time series datasets with simultaneous trend and cyclical variations. The model steps involve identification, estimation, diagnosis and forecasting. The Nigerian monthly Crude Oil Price (NMCOP) was used to implement the model and NMCOP was identified as trend-cyclical. The model estimation using Ordinary Least Squares method indicates that an increase in time will result in changes in NMCOP. Durbin-Watson statistics, histogram and autocorrelation function of residual plots were used to diagnose and specify the model to be stable. The coefficient of determination (R^2) indicates that over 80% of dependent variable variations were explained, with an adjusted (R^2) indicating a predictive ability exceeding 80%. The model efficiency was confirmed through out-sample and forecast evaluations, revealing superiority due to its smaller MAE, RMSE, and MAPE values, indicating minimal error. Conclusively, the TFR model is suitable for datasets that exhibit trend-cyclical variations simultaneously.

The relationship between muscle quality index and physical function in older adults

BACKGROUND: The muscle quality index (MQI) has been proposed as a diagnostic tool to detect individuals at risk of limited physical function. OBJECTIVE: Our goal was to examine the relationship of the MQI with physical function and compare its predictive ability with other muscle parameters of strength and mass in an older population. METHODS: Sixty-eight healthy older adults (34 male, 34 female) aged between 69 and 89 years were tested for body composition, MQI, maximum isokinetic concentric KES and physical function including sit-to-stand (STS) time, normal and maximum walking speed (WS), Timed Up and Go (TUG) and static balance. Pearson’s correlation was applied to examine the relationship between muscle parameters. Linear regression analysis including age and sex as additional covariates was performed to assess their predictive ability for physical functions. RESULTS: MQI correlated significantly with relative KES (r= 0.611, p< 0.001), total KES (r= 0.829, p< 0.001) and leg lean tissue mass (r= 0.690, p< 0.001). The MQI was not a significant predictor for any physical function (p> 0.05). STS time was a significant predictor for normal WS and TUG time (p< 0.001). Relative KES was a significant predictor for all physical functions except static balance (p< 0.001). No muscle parameter and only age was a significant predictor for static balance. Models explained 20.4%–57.3% of variances of dependent variables. CONCLUSIONS: The MQI is a useful tool to assess leg lean tissue mass and strength of the knee extensor muscles and outperforms STS time. However, STS time and relative KES are more closely related to physical function than the MQI.

Performance of Sugarcane Cultivation in Thiuvannamalai District of Tamil Nadu, India - A Socio-economic Analysis

The core objective of the study is to analyze the performance of sugarcane in terms of cost and returns and resource use efficiency. A sample of 30 Sugarcane growing farmers purposively selected at random from the Vazhavachannur and Perunduraipattu villages of Thandrampattu block of Tiruvannamalai District. Since all the sugarcane farmers use the same cultivation practices, 30 sample farmers are sufficient to represent the entire sugarcane farmers of the study area. Tools like simple average and percentage analyses were used to examine cost of cultivation, labour hours used, quantity of materials used and machine hours used by farmers in each crop production. Regression analysis was employed to measure the influence of selected explanatory variables on independent variables. Result showed that joint family constitutes about 33.00 percent and nuclear family was 67 of the total sample households. Average size of holding is 3.28 acre. Total cost of cultivation for groundnut is Rs.59376.64/acre. Gross income from groundnut is Rs.140962.50/acre. Benefit Cost Ratio (BCR) of groundnut cultivation is 2.37. All the sample farmers wholly depend on the sugarcane cooperatives for selling their produce. The human labors were used for Inter cultural operation, sowing & transplanting, chemicals, fertilizer and Farm Yard Manure (FYM). FYM, chemicals, fertilizer and seed are the major inputs used in crop production. Bund Former and Rotavator is the machines used for crop production. About 89.00 percent of variation in dependent variables explained by the selected independent variables such as quantity of chemicals and labor hours for inter cultural operation.

The Impact of Computerized Systems on Efficiency and Productivity of Cooperatives in Rwanda. A Case Study of Cooperative Management System (CMS) Software Developed by MNK Digital Group Ltd

This research analyzed “Project design and implementation of cooperative management system (CMS) software and its impact on the efficiency and productivity of cooperatives in Rwanda” on 146 cooperatives using Cooperative Management System (CMS) across 19 districts of 4 Provinces of Rwanda (Eastern, Western, Northern, and Southern). The study used a sample of 750 respondents including 730 cooperative members from a total population of 61,320 members of 146 cooperatives plus 19 District Cooperatives Officers and 1 Director of Cooperatives Promotion and Capacity Building Unit in Rwanda Cooperative Agency (RCA). A questionnaire designed in form of five levels Likert scale was used and data was collected and analyzed through KoBo Toolbox and SPSS. The results of descriptive statistics showed that overall appreciation of CMS by cooperatives managers is “Good” (x̄= 3.8; σ = .270). The regression results revealed that CMS Membership management module was positive and significant to Cooperative productivity and efficiency (β1= 0.049; p< 0.05); CMS Payments management module was positive and significant to Cooperative productivity and efficiency (β2= 0.258; p< 0.05); Accounting management module was positive and significant to Cooperative productivity and efficiency (β3= 0.242; p< 0.05); CMS Human resource management module was positive and significant to Cooperative productivity and efficiency (β4= 0.016; p< 0.05); CMS Requisitioning management module was positive and significant to Cooperative productivity and efficiency (β5= 0.020; p< 0.05); CMS Credit management module was positive and significant to Cooperative productivity and efficiency (β6= 0.206; p< 0.05). The coefficient of determination R-squared value for this study is 0.705 (r > 0.7) indicating strong effect size. It shows how that the model fits the data at strong extent. These results indicate that 70.5% of variance in dependent variable was explained by independent variables meaning that 70.5% of change in Cooperative productivity and efficiency come from CMSMembMgtMod, CMSPayMgtMod, CMSAccMgtMod, CMSHrMgtMod, CMSRequisMgtMod, CMSCreditMgtMod. The main CMS challenges outline by the respondents include CMS is not free and requires additional installation and maintenance fees (x̄= 5.0; σ =.000); CMS requires advanced education level (x̄= 4.3; σ =.080); CMS has issue of confidentiality of the data managed by the government which hosts the CMS system (x̄= 5.0; σ =.000); CMS use requires additional cost for internet (x̄= 4.1; σ =.351). Proposed solutions are: Support from the RCA on installation cost and the cooperatives should cover maintenance costs(x̄= 4.8; σ =.070); More training on even members with good primary education on the use of CMS (x̄= 4.3; σ =.380); Confederations should play important role in the management of CMS and the role of the government should be reduced (x̄= 4.9; σ =.290); The government should reduce the cost of internet (x̄= 4.7; σ =.151); More capacity building for cooperative managers.

A Study on Income, Expenditure and Resource Use Pattern of Paddy in Tiruvannamalai District

Recently a study entitled “A study on income, expenditure and resource use pattern of paddy in Tiruvannamalai district” is conducted by a student with a view to analyze the performance of paddy in terms of cost and returns, resource use efficiency, and employment generation. The sample of 30 farmers growing paddy were selected at random from the Thanipadi, Vazhavachannur, Keezhsirupakkam, Perunduraipattu, Thandrampet, Veppur, and Andapattu villages. Average and percentage analyses were used to examine cost of cultivation, labour hours used, quantity of materials used and machine hours used by farmers in each crop production. Regression analysis was employed to measure the influence of selected explanatory variables on independent variables. Joint family constitutes about 43 percent and nuclear family was 57 of the total sample households. Average size of holding of 2.29 acre. Total cost of cultivation for paddy is Rs.17172.08/acre. Gross income from paddy is Rs.38919.09/ac. Benefit Cost Ratio (BCR) of paddy cultivation is 2.27. Farmers sell the produce at aggregators, regulated market and mill owners. The human labors were used for sowing & transplanting, cultural operation and chemicals. FYM, chemicals, fertilizer and seed are the major material used in crop production. Rotavator and harvester are the machine used for crop production. About 77 percent of variation in dependent variables explained by the selected independent variables such as labor hours for inter cultural operation and quantity of seed and hours per irrigation.

Estimation of Income, Expenditure and Resource use Pattern of Groundnut in Thandrampattu Block of Tiruvannamalai District, Tamil Nadu, India

The core objective of the research estimation of income, expenditure and resource use pattern of groundnut in Thandrampattu block of Tiruvannamalai district is to evaluate the performance of groundnut in terms of cost and returns and resource use efficiency. The sample of 30 farmers growing groundnut were selected at random from the Thandrampet, Veppur, Thanipadi and Vanapuram villages of Thandrampattu Block of Tiruvannamalai District. Average and percentage analyses were used to examine cost of cultivation, labour hours used, quantity of materials used and machine hours used by farmers in each crop production. Regression analysis was used to assess the impact of selected explanatory variables on independent variables. Joint families account for around 33% of total sample homes, with nuclear families accounting for 67 percent. Average size of holding is 2.84 acres. Total cost of cultivation for groundnut is Rs.16371.68/acre. Gross income from groundnut is Rs.54000/ac. Benefit Cost Ratio (BCR) of groundnut cultivation is 3.30. Farmers sell the produce at regulated market, mill owners and local traders. The human labors were used for sowing and transplanting, FYM, fertilizer, chemicals, intercultural operations. FYM, chemicals, fertilizer and seed are the major material used in crop production. Harvester, rotavator and bund former are the machine used for crop production. About 69 percent of variation in dependent variables explained by the selected independent variables such as labor hours for inters cultural operation, land holding size and quantity of FYM.

Menganalisis Pengaruh Strategi Bauran Pemasaran Terhadap Pembelian Sertifikat Laik Operasi Tegangan Rendah (SLO-TR)

This research aims to analysis the significant influence between marketing mix strategy on the purchase of Low Voltage Operating Eligibility Certificate (SLO-TR). Marketing mix strategy indicator as independent variable are product (X1), price (X2), location (X3), promotion (X4), people (X5), process (X6) and physical evidence (X7). The purchase decision indicator of Low Voltage Operating Eligibility Certificate (SLO-TR) as the dependent variable is the purchasing decision (Y). Quantitative research methods are described in multiple linear regression analysis models. The population is obtained from customers who make purchasing decision for Low Voltage Operating Eligibility Certificates (SLO-TR) at PT. Serkolinas. Type of research with primary data collected by dissemination of questionnaire. Using the Slovin formula, the number of respondents who became a sample of 100 people for further analysis. Stratified proportionate sampling technique by random sampling. Research results: (1) The estimation model shows an R2 value of 0,534 which represents the value of the coefficient of determination. This means that 53,40% of the dependent variable variation is able to be explained by the independent variable in this model. The remaining 46,60% is explained by other causes that are not included in the model; 2) The regression model on the independent variable simultaneously influence the dependent variable; and (3) This research produces results that product (X1), price (X2), process (X6) and physical evidence (X7) are influential and significant in analysis the influence of marketing mix strategy on purchasing decision (Y). But, place (X3), promotion (X4) and people (X5) had no influential and were not significant in analysis the influence of marketing mix strategy on purchasing decision (Y).

The Analysis of Macroeconomic and Microeconomic Factors in Non-Performing Financing of Sharia Bank in Indonesia

This study aims to analysis of macroeconomic and microeconomic factors in non-performing financing of Sharia Bank in Indonesia. Inflation and the BI7DRR are macroeconomic factors. CAR and BOPO are indicators of microeconomic factors. NPF is a problematic financing indicator. Research methods with quantitative methods described in multiple linear regression analysis models. The population is obtained from the Bank Indonesia and Financial Ratios of Sharia Commercial Banks through the Sharia Indonesia Banking Statistics of the Financial Services Authority. The data is secondary in the form of monthly data for the period January 2018 to November 2022, so that a sample of 59 data was obtained for further analysis. Sampling techniques nonprobability by means of purposive sampling. The results of the study are as follows: (1) The estimation model shows an R2 value of 0,738 which represents the value of the coefficient of determination. This means that 73,80% of the dependent variable variation is able to be explained by the independent variables in this model. The remaining 26,20% is explained by other causes that are not included in the model; 2) The regression model on the independent variable simultaneously influence the dependent variable, so that the independent variable regression model can be used to predict the dependent variable; and (3) This research produced output that the influential and significant ones are Inflation and BI7DRR as macroeconomic factors that can be used to analysis non-performing financing of Sharia Bank in Indonesia. This research also produced an output that CAR and BOPO have no influential as microeconomic factors that cannot be used to analysis non-performing financing of Sharia Bank in Indonesia. Although CAR and BOPO the results are significant.

Anxious and Angry: Early Emotional Adaptation of Medical Students in a Situational Crisis on the Example of the COVID-19 Pandemic.

The COVID-19 pandemic is an example of a situational crisis resulting in emotional destabilization. The aim of the study was to analyze changes in the level of anxiety and anger in medical students during the early adaptation to the situational crisis, and to estimate the risk factors for fear and anger in this group. Participants were 949 medical students (M = 22.88, SD = 4.10) in the first stage on March 2020, and 748 (M = 22.57, SD = 3.79) in the second stage on June 2020. The STAI, STAXI-2, and our own questionnaire were used. First vs the second stage: anxiety state (p < 0.001), anger state (p = 0.326), and feeling angry (p < 0.05). The regression model (F(14.1681) = 79.01, p < 0.001) for the level of anxiety state explains 39% of the dependent variable variance (r2 = 0.39). The model for the anger-state level (F(6.1689) = 68.04, p < 0.001)-19% (r2 = 0.19). During the early adaptation to the situational crisis, the general level of anxiety decreased, but anger was at the same level. The anxiety was explained by contact with potentially or objective infected persons, and the level of anger was based on the need for greater social support.

Latent Inhibition in Schizophrenia and Schizotypy.

The Salience Hypothesis posits that aberrations in the assignment of salience culminate in hallucinations and unusual beliefs, the "positive symptoms" of schizophrenia. Evidence for this comes from studies on latent inhibition (LI), referring to the phenomenon that prior exposure to a stimulus impedes learning about the relationship between that stimulus and an outcome. This article reviewed all published studies examining the relationship between LI and both schizophrenia and schizotypy. Contemporary literature suggests that LI is attenuated in both people with schizophrenia and those loading highly on measures of schizotypy, the multidimensional derivative of schizophrenia. This suggests that these individuals assign greater salience to stimuli than healthy controls and people scoring low on measures of schizotypy, respectively. However, several confounds limit these conclusions. Studies on people with schizophrenia are limited by the confounding effects of psychotropic medications, idiosyncratic parsing of samples, variation in dependent variables, and lack of statistical power. Moreover, LI paradigms are limited by the confounding effects of learned irrelevance, conditioned inhibition, negative priming, and novel pop-out effects. This review concludes with the recommendation that researchers develop novel paradigms that overcome these limitations to evaluate the predictions of the Salience Hypothesis.

METHOD FOR CALCULATION OF DISPERSIONS OF DEPENDENT VARIABLES OF A STOCHASTIC MODEL OF QUASI-STATIONARY OPERATING MODES OF THE MAIN WATER PIPELINE

The subject of research in the article is a stochastic model of quasi-stationary modes of operation of water supply and distribution systems, which adequately describes the actual operating modes of the water supply system for a given time interval and can be used as a basic model for setting and solving problems of optimal stochastic control of the development and operation of supply and distribution systems. water. The goal of the work is to develop a method for calculating estimates of the dispersions of dependent variables depending on the given values of mathematical expectations and dispersions of independent variables for a stochastic model of quasi-stationary modes of operation of the main water conduit as a subsystem of the water supply and distribution system. To achieve this goal, it is necessary to solve the following tasks: to build a deterministic equivalent of a stochastic model of quasi-stationary modes of operation of the main water conduit; calculate estimates of mathematical expectations of dependent variables; calculate estimates of variances of dependent variables. To calculate estimates of the variances of dependent variables depending on the variances of independent variables, we will use the method of statistical linearization. To obtain estimates of mathematical expectations of dependent variables, the deterministic equivalent of the stochastic model of quasi-stationary modes of operation of the main water conduit is solved by the modified Newton method. The following results are obtained: a method for calculating estimates of the dispersions of dependent variables for a stochastic model of quasi-stationary modes of operation of the main water conduit. Conclusions: the paper proposes an approximate method for calculating the statistical properties of dependent variables depending on the statistical properties of the parameters and independent variables of the stochastic model of quasi-stationary modes of operation of the main water conduit. The proposed method is based on the construction of a deterministic equivalent of a stochastic model of quasi-stationary modes of operation of the main water conduit and its use for calculating estimates of variances of dependent variables depending on the given values of mathematical expectations and variances of independent variables. Compared with the simulation method, the proposed approximate method does not require significant time and computational resources. The use of the proposed method was demonstrated by an example.

PENGARUH DISIPLIN DAN MOTIVASI TERHADAP SEMANGAT KERJA PEGAWAI PADA DINAS KOMUNIKASI DAN INFORMATIKA KOTA SIBOLGA

This study aims to determine whether there is an influence of discipline and motivation on employee morale at the Communication and Informatics Office of Sibolga City. The type of research used in this research is a quantitative research method with a descriptive approach. The sample in this study were employees at the Communication and Informatics Office of the City of Sibolga, with a total of 56 respondents distributing questionnaires.&#x0D; &#x0D; Based on the analysis of the coefficient of determination obtained by 0.603 or 60.3%. This means that what occurs in the dependent variable variation is 60.3% morale determined by the independent variables of discipline and motivation simultaneously and the remaining 39.7% is determined by other factors not discussed in this study. From the results of the T-test in the study, it is known that the T-value for discipline is 3.556, and motivation is 3.418&gt; T-table 2.00575, so the hypothesis states that discipline and motivation partially or individually influence employee morale in communication and informatics in the city of Sibolga is acceptable. Meanwhile, from the results of the F test, it is known that the calculated F value is 40,178 &gt; F table 3.17 and a significance of 0.000 &lt;0.05 so that the hypothesis stating that discipline and motivation have a joint or simultaneous significant effect on employee morale in communication and informatics in the city of Sibolga is acceptable.

Determinants of E-Government Implementation in Indonesia

Aims: This study aimed to determine the effect of Regional Original Income, general allocation funds, capital expenditures, audit opinions, and the level of public education on the implementation of e-Government in local governments in Indonesia.&#x0D; Study Design: This study uses secondary data.&#x0D; Place and Duration of Study: Local Government Financial Reports (LKPD) and audit opinions. This information can be found at the Supreme Audit Agency (BPK). The level of community education attainment uses the new Average Years of Schooling (RLS) method from the Central Statistics Agency (BPS) representative of each province from 2018 to 2020.&#x0D; Methodology: The sample used is 347 local governments. The purposive sampling method and multiple regression analysis were used in this study and used the SPSS 25 analysis tool. Before running the regression test, the data was first tested using the classical assumption test.&#x0D; Results: The independent variables in this study consisted of Regional Original Income (PAD), General Allocation Funds (DAU), Capital Expenditures, Audit Opinions, and Community Education Levels. At the same time, the dependent variable is the implementation of e-Government seen from the SPBE index value. This study carried out hypothesis testing with the Coefficient of Determination Test (R2) and the t-Statistical Test. The Coefficient of Determination Test (R2) measured how far the model's ability to explain the variance of the dependent variable was. The value of the coefficient of determination is zero or one. A small R2 value means the ability of the independent variables to provide almost all the information needed to predict the dependent variable variance [1]. At the same time, the t-test statistic shows how far the influence of one explanatory/independent variable individually in explaining the variation of the dependent variable results in a decision to reject or accept H0. This research was processed using IBM SPSS version 25 software.&#x0D; Conclusion: In this study, the variables "Regional Original Income," "General Allocation Funds," "Opinion Audits," and "Community Education Levels" have a positive effect on the implementation of e-Government. On the other hand, the capital expenditure variable does not affect the implementation of e-Government.

Quantifying the Contributions of Climate Change and Human Activities to Maize Yield Dynamics at Multiple Timescales

Under a changing environment, the effect of climate change and human activities on maize yield is vital for ensuring food security and efficient socio-economic development. The time series of maize yield is generally non-stationary and contains different frequency components, such as long- and short-term oscillations. Nevertheless, there is no adequate understanding of the relative importance of climate change. In addition, human activities on maize yield at multiple timescales remain unclear, which help in further improving maize yield prediction. Based on the ensemble empirical mode decomposition method (EEMD), the method of dependent variable variance decomposition (DVVD) and the Sen-slope method, the effect of climate change including growing-season precipitation and temperature (i.e., GSP, GEP, CDD, GST, GSMAT, and GSMT) and human activities including effective irrigation area (EIA) and the consumption of chemical fertilizers (CCF) on maize yield were explored at multiple timescales during 1979–2015. The Heilongjiang Province, a highly important maize production area in China, was selected as a case study. The results of this work indicate the following: (1) The original maize yield series was divided into 3.1-, 7.4-, 18.5-, and 37-year timescale oscillations and a residual series with an increasing trend, where the 3.1-year timescale (IMF1), the 18.5-year timescale (IMF3), and the increasing trend (R) were dominant; (2) the original sequence was mainly affected by human activities; (3) climate change and human activities had different effects on maize yield at different timescales: The short-term oscillation (IMF1) of maize yield was primarily affected by climate change. However, human activities dominated the mid- and long-term oscillations (IMF3 and R) of maize yield. This study sheds new insight into multiple timescale analysis of the role of climate and human activities on maize yield dynamics.

Which Matters More for Migration: Evidence from Russian Regions’ Data

Many researchers of migration in Russia note deficiency of the works directed on modeling of migratory processes taking place in the country. This article is devoted to an assessment of impact power of socio-economic factors on interregional migration in Russia and to its comparison to recently found influence on this process of psychological characteristics of the accepting region population. As the aggregated at regional level estimates of intelligence, personal traits and characteristics of response style were calculated on the basis of results of online testing over 200 thousand respondents in 2012–19, indicators of socio-economic development of regions (n=16) are computed by averaging for the same time interval; the source of data - the Russian Federal Service of State Statistics (reference yearbooks “Regions of Russia” and the Uniform Interagency Information and Statistical System). In the analysis data of 78 subjects of the Russian Federation are included, but after association of capital agglomerations the number of regions was reduced to 76. It is established that the majority of the socio-economic indexes included in the analysis shows significant correlations with regional net migration coefficients. In general, the revealed pattern of correlations is agreed with results of other authors received on data of earlier periods of the analysis. Regression of net migration coefficients on socio-economic variables allowed calculating series of linear multifactor models. Best of these models accounted for about 44 % of a dependent variable variance. Earlier it was shown that the models calculated on the basis of limited number of aggregated psychological characteristics of the accepting region have the same level of accuracy. Moreover, addition of psychological variables to the best models based on socio-economic indexes provides essential increase of accuracy of prediction of regional net migration: the share of variance accounted for increases from 44 to 55–57 %. It is supposed that taking into account of psychological variables of the accepting region will create premises for more effective management of migratory processes.