Search results for: nonparametric regression
Commenced in January 2007
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Edition: International
Paper Count: 3200

Search results for: nonparametric regression

2180 Application of Neuro-Fuzzy Technique for Optimizing the PVC Membrane Sensor

Authors: Majid Rezayi, Sh. Shahaboddin, HNM E. Mahmud, A. Yadollah, A. Saeid, A. Yatimah

Abstract:

In this study, the adaptive neuro-fuzzy inference system (ANFIS) was applied to obtain the membrane composition model affecting the potential response of our reported polymeric PVC sensor for determining the titanium (III) ions. The performance statistics of the artificial neural network (ANN) and linear regression models for potential slope prediction of membrane composition of titanium (III) ion selective electrode were compared with ANFIS technique. The results show that the ANFIS model can be used as a practical tool for obtaining the Nerntian slope of the proposed sensor in this study.

Keywords: adaptive neuro fuzzy inference, PVC sensor, titanium (III) ions, Nerntian slope

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2179 Identifying Risk Factors for Readmission Using Decision Tree Analysis

Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

Abstract:

This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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2178 The Effective Operations Competitive Advantages of Mobile Phone Service Providers across Countries: The Case of Middle East Region

Authors: Yazan Khalid Abed-Allah Migdadi

Abstract:

The aim of this study is identifying the effective operations competitive advantages of mobile phone service providers across countries. All Arab countries in the Middle East region were surveyed except Syria, and 27 out of 31 service providers were surveyed. Data collected from corporations’ annual reports, websites and other professional institutions published sources. Multiple linear regression analysis test was used to identify the relationship between operations competitive advantages and market share. The effective operations competitive advantages were; diversity of offers and service accessibility

Keywords: competitive advantage, mobile telecommunication operations, Middle East, service provider

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2177 Prediction of Bariatric Surgery Publications by Using Different Machine Learning Algorithms

Authors: Senol Dogan, Gunay Karli

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Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

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2176 Exploring the Relationship among Job Stress, Travel Constraints, and Job Satisfaction of the Employees in Casino Hotels: The Case of Macau

Authors: Tao Zhang

Abstract:

Job stress appears nearly everywhere especially in the hospitality industry because employees in this industry usually have to work long time and try to meet conflicting demands of their customers, managers, and company. To reduce job stress, employees of casino hotels try to perform leisure activities or tourism. However, casino employees often meet many obstacles or constraints when they plan to travel. Until now, there is little understanding as to why casino hotel employees often face many travel constraints or leisure barriers. What is more, few studies explore the relationship between travel constraints and job stress of casino employees. Therefore, this study is to explore the construct of casino hotel employees' travel constraints and the relationship among job stress, travel constraints, and job satisfaction. Using convenient sampling method, this study planned to investigate 500 front line employees and managers of ten casino hotels in Macau. A total of 500 questionnaires were distributed, and 414 valid questionnaires were received. The return rate of valid questionnaires is 82.8%. Several statistical techniques such as factor analysis, t-test, one-way ANOVA, and regression analysis were applied to analyze the collected data. The findings of this study are as follows. Firstly, by using factor analysis, this study found the travel constraints of casino employees include intrapersonal constraints, interpersonal constraints, and structural constraints. Secondly, by using regression analysis, the study found travel constraints are positively related with job stress while negatively related with job satisfaction. This means reducing travel constraints may create a chance for casino employees to travel so that they could reduce job stress, therefore raise their job satisfaction. Thirdly, this research divided the research samples into three groups by the degree of job stress. The three groups are low satisfaction group, medium satisfaction group, and high satisfaction group. The means values of these groups were compared by t-test. Results showed that there are significant differences of the means values of interpersonal constraints between low satisfaction group and high satisfaction group. This suggests positive interpersonal relationship especially good family member relationship reduce not only job stress but also travel constraints of casino employees. Interestingly, results of t-test showed there is not a significant difference of the means values of structural constraints between low satisfaction group and high satisfaction group. This suggests structural constraints are outside variables which may be related with tourism destination marketing. Destination marketing organizations (DMO) need use all kinds of tools and techniques to promote their tourism destinations so as to reduce structural constraints of casino employees. This research is significant for both theoretical and practical fields. From the theoretical perspective, the study found the internal relationship between travel constraints, job stress, and job satisfaction and the different roles of three dimensions of travel constraints. From the practical perspective, the study provides useful methods to reduce travel constraints and job stress, therefore, raise job satisfaction of casino employees.

Keywords: hotel, job satisfaction, job stress, travel constraints

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2175 Evaluation of Prehabilitation Prior to Surgery for an Orthopaedic Pathway

Authors: Stephen McCarthy, Joanne Gray, Esther Carr, Gerard Danjoux, Paul Baker, Rhiannon Hackett

Abstract:

Background: The Go Well Health (GWH) platform is a web-based programme that allows patients to access personalised care plans and resources, aimed at prehabilitation prior to surgery. The online digital platform delivers essential patient education and support for patients prior to undergoing total hip replacements (THR) and total knee replacements (TKR). This study evaluated the impact of an online digital platform (ODP) in terms of functional health outcomes, health related quality of life and hospital length of stay following surgery. Methods: A retrospective cohort study comparing a cohort of patients who used the online digital platform (ODP) to deliver patient education and support (PES) prior to undergoing THR and TKR surgery relative to a cohort of patients who did not access the ODP and received usual care. Routinely collected Patient Reported Outcome Measures (PROMs) data was obtained on 2,406 patients who underwent a knee replacement (n=1,160) or a hip replacement (n=1,246) between 2018 and 2019 in a single surgical centre in the United Kingdom. The Oxford Hip and Knee Score and the European Quality of Life Five-Dimensional tool (EQ5D-5L) was obtained both pre-and post-surgery (at 6 months) along with hospital LOS. Linear regression was used to compare the estimate the impact of GWH on both health outcomes and negative binomial regressions were used to impact on LOS. All analyses adjusted for age, sex, Charlson Comorbidity Score and either pre-operative Oxford Hip/Knee scores or pre-operative EQ-5D scores. Fractional polynomials were used to represent potential non-linear relationships between the factors included in the regression model. Findings: For patients who underwent a knee replacement, GWH had a statistically significant impact on Oxford Knee Scores and EQ5D-5L utility post-surgery (p=0.039 and p=0.002 respectively). GWH did not have a statistically significant impact on the hospital length of stay. For those patients who underwent a hip replacement, GWH had a statistically significant impact on Oxford Hip Scores and EQ5D-5L utility post (p=0.000 and p=0.009 respectively). GWH also had a statistically significant reduction in the hospital length of stay (p=0.000). Conclusion: Health Outcomes were higher for patients who used the GWH platform and underwent THR and TKR relative to those who received usual care prior to surgery. Patients who underwent a hip replacement and used GWH also had a reduced hospital LOS. These findings are important for health policy and or decision makers as they suggest that prehabilitation via an ODP can maximise health outcomes for patients following surgery whilst potentially making efficiency savings with reductions in LOS.

Keywords: digital prehabilitation, online digital platform, orthopaedics, surgery

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2174 The Lopsided Burden of Non-Communicable Diseases in India: Evidences from the Decade 2004-2014

Authors: Kajori Banerjee, Laxmi Kant Dwivedi

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India is a part of the ongoing globalization, contemporary convergence, industrialization and technical advancement that is taking place world-wide. Some of the manifestations of this evolution is rapid demographic, socio-economic, epidemiological and health transition. There has been a considerable increase in non-communicable diseases due to change in lifestyle. This study aims to assess the direction of burden of disease and compare the pressure of infectious diseases against cardio-vascular, endocrine, metabolic and nutritional diseases. The change in prevalence in a ten-year period (2004-2014) is further decomposed to determine the net contribution of various socio-economic and demographic covariates. The present study uses the recent 71st (2014) and 60th (2004) rounds of National Sample Survey. The pressure of infectious diseases against cardio-vascular (CVD), endocrine, metabolic and nutritional (EMN) diseases during 2004-2014 is calculated by Prevalence Rates (PR), Hospitalization Rates (HR) and Case Fatality Rates (CFR). The prevalence of non-communicable diseases are further used as a dependent variable in a logit regression to find the effect of various social, economic and demographic factors on the chances of suffering from the particular disease. Multivariate decomposition technique further assists in determining the net contribution of socio-economic and demographic covariates. This paper upholds evidences of stagnation of the burden of communicable diseases (CD) and rapid increase in the burden of non-communicable diseases (NCD) uniformly for all population sub-groups in India. CFR for CVD has increased drastically in 2004-2014. Logit regression indicates the chances of suffering from CVD and EMN is significantly higher among the urban residents, older ages, females, widowed/ divorced and separated individuals. Decomposition displays ample proof that improvement in quality of life markers like education, urbanization, longevity of life has positively contributed in increasing the NCD prevalence rate. In India’s current epidemiological phase, compression theory of morbidity is in action as a significant rise in the probability of contracting the NCDs over the time period among older ages is observed. Age is found to play a vital contributor in increasing the probability of having CVD and EMN over the study decade 2004-2014 in the nationally representative sample of National Sample Survey.

Keywords: cardio-vascular disease, case-fatality rate, communicable diseases, hospitalization rate, multivariate decomposition, non-communicable diseases, prevalence rate

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2173 An Application of the Single Equation Regression Model

Authors: S. K. Ashiquer Rahman

Abstract:

Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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2172 Effect of Packaging Material and Water-Based Solutions on Performance of Radio Frequency Identification for Food Packaging Applications

Authors: Amelia Frickey, Timothy (TJ) Sheridan, Angelica Rossi, Bahar Aliakbarian

Abstract:

The growth of large food supply chains demanded improved end-to-end traceability of food products, which has led to companies being increasingly interested in using smart technologies such as Radio Frequency Identification (RFID)-enabled packaging to track items. As technology is being widely used, there are several technological or economic issues that should be overcome to facilitate the adoption of this track-and-trace technology. One of the technological challenges of RFID technology is its sensitivity to different environmental form factors, including packaging materials and the content of the packaging. Although researchers have assessed the performance loss due to the proximity of water and aqueous solutions, there is still the need to further investigate the impacts of food products on the reading range of RFID tags. However, to the best of our knowledge, there are not enough studies to determine the correlation between RFID tag performance and food beverages properties. The goal of this project was to investigate the effect of the solution properties (pH and conductivity) and different packaging materials filled with food-like water-based solutions on the performance of an RFID tag. Three commercially available ultra high-frequency RFID tags were placed on three different bottles and filled with different concentrations of water-based solutions, including sodium chloride, citric acid, sucrose, and ethanol. Transparent glass, Polyethylneterephtalate (PET), and Tetrapak® were used as the packaging materials commonly used in the beverage industries. Tag readability (Theoretical Read Range, TRR) and sensitivity (Power on Tag Forward, PoF) were determined using an anechoic chamber. First, the best place to attach the tag for each packaging material was investigated using empty and water-filled bottles. Then, the bottles were filled with the food-like solutions and tested with the three different tags and the PoF and TRR at the fixed frequency of 915MHz. In parallel, the pH and conductivity of solutions were measured. The best-performing tag was then selected to test the bottles filled with wine, orange, and apple juice. Despite various solutions altering the performance of each tag, the change in tag performance had no correlation with the pH or conductivity of the solution. Additionally, packaging material played a significant role in tag performance. Each tag tested performed optimally under different conditions. This study is the first part of comprehensive research to determine the regression model for the prediction of tag performance behavior based on the packaging material and the content. More investigations, including more tags and food products, are needed to be able to develop a robust regression model. The results of this study can be used by RFID tag manufacturers to design suitable tags for specific products with similar properties.

Keywords: smart food packaging, supply chain management, food waste, radio frequency identification

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2171 Relationship between Depression, Stress, and Life Satisfaction among Students

Authors: Rexa Pasha

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The aim of this study was to examine the relationship between depression, stress and life satisfaction with sleep disturbance among Islamic Azad University Ahvaz Branch students. Samples in the study included 230 students who were selected by stratified random sampling. For data collection, the Beck Depression Inventory, stress, life satisfaction and quality of sleep (PSQI) was used. Which all have acceptable reliability and validity. This study was correlation and Data analysis using Pearson correlation and multivariate regression significance level (pKeywords: depression, life satisfaction, sleep disorder, sleep disturbane

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2170 The Communication of Audit Report: Key Audit Matters in United Kingdom

Authors: L. Sierra, N. Gambetta, M. A. Garcia-Benau, M. Orta

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Financial scandals and financial crisis have led to an international debate on the value of auditing. In recent years there have been significant legislative reforms aiming to increase markets’ confidence in audit services. In particular, there has been a significant debate on the need to improve the communication of auditors with audit reports users as a way to improve its informative value and thus, to improve audit quality. The International Auditing and Assurance Standards Board (IAASB) has proposed changes to the audit report standards. The International Standard on Auditing 701, Communicating Key Audit Matters (KAM) in the Independent Auditor's Report, has introduced new concepts that go beyond the auditor's opinion and requires to disclose the risks that, from the auditor's point of view, are more significant in the audited company information. Focusing on the companies included in the Financial Times Stock Exchange 100 index, this study aims to focus on the analysis of the determinants of the number of KAM disclosed by the auditor in the audit report and moreover, the analysis of the determinants of the different type of KAM reported during the period 2013-2015. To test the hypotheses in the empirical research, two different models have been used. The first one is a linear regression model to identify the client’s characteristics, industry sector and auditor’s characteristics that are related to the number of KAM disclosed in the audit report. Secondly, a logistic regression model is used to identify the determinants of the number of each KAM type disclosed in the audit report; in line with the risk-based approach to auditing financial statements, we categorized the KAM in 2 groups: Entity-level KAM and Accounting-level KAM. Regarding the auditor’s characteristics impact on the KAM disclosure, the results show that PwC tends to report a larger number of KAM while KPMG tends to report less KAM in the audit report. Further, PwC reports a larger number of entity-level risk KAM while KPMG reports less account-level risk KAM. The results also show that companies paying higher fees tend to have more entity-level risk KAM and less account-level risk KAM. The materiality level is positively related to the number of account-level risk KAM. Additionally, these study results show that the relationship between client’s characteristics and number of KAM is more evident in account-level risk KAM than in entity-level risk KAM. A highly leveraged company carries a great deal of risk, but due to this, they are usually subject to strong capital providers monitoring resulting in less account-level risk KAM. The results reveal that the number of account-level risk KAM is strongly related to the industry sector in which the company operates assets. This study helps to understand the UK audit market, provides information to auditors and finally, it opens new research avenues in the academia.

Keywords: FTSE 100, IAS 701, key audit matters, auditor’s characteristics, client’s characteristics

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2169 Tests for Zero Inflation in Count Data with Measurement Error in Covariates

Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

Abstract:

In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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2168 The Role of Psychological Hardiness and Psychological Resilience Employee's Commitment to Change

Authors: Ni Made Dian Swandewi, Wustari L. Mangundjaya

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Employees’ commitment to change are required for the success of organizational change in the company. The objective of this study is to identify the correlation between psychological hardiness and psychological resilience on commitment to change. The respondents of current research are permanent employees and employees that have worked for at least two years in a company that has been experiencing organizational change. Data was collected using Commitment to Change Inventory, Dispositional Resilience Scale (DRS), and Modified CD-RISC. The data were analyzed using regression. The results of the research show that both Psychological Hardiness and Psychological Resilience have positive and significant correlation and contribution on Commitment to Change. This research is important for companies who undergo organizational change in order plan and implement change more effectively.

Keywords: commitment to change, organizational change, psychological hardiness, psychological resilience

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2167 Estimation of Sediment Transport into a Reservoir Dam

Authors: Kiyoumars Roushangar, Saeid Sadaghian

Abstract:

Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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2166 Analysis of the Savings Behaviour of Rice Farmers in Tiaong, Quezon, Philippines

Authors: Angelika Kris D. Dalangin, Cesar B. Quicoy

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Rice farming is a major source of livelihood and employment in the Philippines, but it requires a substantial amount of capital. Capital may come from income (farm, non-farm, and off-farm), savings and credit. However, rice farmers suffer from lack of capital due to high costs of inputs and low productivity. Capital insufficiency, coupled with low productivity, hindered them to meet their basic household and production needs. Hence, they resorted to borrowing money, mostly from informal lenders who charge very high interest rates. As another source of capital, savings can help rice farmers meet their basic needs for both the household and the farm. However, information is inadequate whether the farmers save or not, as well as, why they do not depend on savings to augment their lack of capital. Thus, it is worth analyzing how rice farmers saved. The study revealed, using the actual savings which is the difference between the household income and expenditure, that about three-fourths (72%) of the total number of farmers interviewed are savers. However, when they were asked whether they are savers or not, more than half of them considered themselves as non-savers. This gap shows that there are many farmers who think that they do not have savings at all; hence they continue to borrow money and do not depend on savings to augment their lack of capital. The study also identified the forms of savings, saving motives, and savings utilization among rice farmers. Results revealed that, for the past 12 months, most of the farmers saved cash at home for liquidity purposes while others deposited cash in banks and/or saved their money in the form of livestock. Among the most important reasons of farmers for saving are for daily household expenses, for building a house, for emergency purposes, for retirement, and for their next production. Furthermore, the study assessed the factors affecting the rice farmers’ savings behaviour using logistic regression. Results showed that the factors found to be significant were presence of non-farm income, per capita net farm income, and per capita household expense. The presence of non-farm income and per capita net farm income positively affects the farmers’ savings behaviour. On the other hand, per capita household expenses have negative effect. The effect, however, of per capita net farm income and household expenses is very negligible because of the very small chance that the farmer is a saver. Generally, income and expenditure were proved to be significant factors that affect the savings behaviour of the rice farmers. However, most farmers could not save regularly due to low farm income and high household and farm expenditures. Thus, it is highly recommended that government should develop programs or implement policies that will create more jobs for the farmers and their family members. In addition, programs and policies should be implemented to increase farm productivity and income.

Keywords: agricultural economics, agricultural finance, binary logistic regression, logit, Philippines, Quezon, rice farmers, savings, savings behaviour

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2165 Effects of Polyvictimization in Suicidal Ideation among Children and Adolescents in Chile

Authors: Oscar E. Cariceo

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In Chile, there is a lack of evidence about the impact of polyvictimization on the emergence of suicidal thoughts among children and young people. Thus, this study aims to explore the association between the episodes of polyvictimization suffered by Chilean children and young people and the manifestation of signs related to suicidal tendencies. To achieve this purpose, secondary data from the First Polyvictimization Survey on Children and Adolescents of 2017 were analyzed, and a binomial logistic regression model was applied to establish the probability that young people are experiencing suicidal ideation episodes. The main findings show that women between the ages of 13 and 15 years, who are in seventh grade and second in subsidized schools, are more likely to express suicidal ideas, which increases if they have suffered different types of victimization, particularly physical violence, psychological aggression, and sexual abuse.

Keywords: Chile, polyvictimization, suicidal ideation, youth

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2164 Forecasting Solid Waste Generation in Turkey

Authors: Yeliz Ekinci, Melis Koyuncu

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Successful planning of solid waste management systems requires successful prediction of the amount of solid waste generated in an area. Waste management planning can protect the environment and human health, hence it is tremendously important for countries. The lack of information in waste generation can cause many environmental and health problems. Turkey is a country that plans to join European Union, hence, solid waste management is one of the most significant criteria that should be handled in order to be a part of this community. Solid waste management system requires a good forecast of solid waste generation. Thus, this study aims to forecast solid waste generation in Turkey. Artificial Neural Network and Linear Regression models will be used for this aim. Many models will be run and the best one will be selected based on some predetermined performance measures.

Keywords: forecast, solid waste generation, solid waste management, Turkey

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2163 A Spectrophotometric Method for the Determination of Folic Acid - A Vitamin B9 in Pharmaceutical Dosage Samples

Authors: Chand Pasha, Yasser Turki Alharbi, Krasamira Stancheva

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A simple spectrophotometric method for the determination of folic acid in pharmaceutical dosage samples was developed. The method is based on the diazotization reaction of thiourea with sodium nitrite in acidic medium yields diazonium compounds, which is then coupled with folic acid in basic medium yields yellow coloured azo dyes. Beer’s Lamberts law is observed in the range 0.5 – 16.2 μgmL-1 at a maximum wavelength of 416nm. The molar absorbtivity, sandells sensitivity, linear regression equation and detection limit and quantitation limit were found to be 5.695×104 L mol-1cm-1, 7.752×10-3 g cm-2, y= 0.092x - 0.018, 0.687 g mL-1 and 2.083 g mL-1. This method successfully determined Folate in Pharmaceutical formulations.

Keywords: folic acid determination, spectrophotometry, diazotization, thiourea, pharmaceutical dosage samples

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2162 Injury Prediction for Soccer Players Using Machine Learning

Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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2161 Does Inflation Affect Private Investment in Nigeria?

Authors: Amassoma Ditimi, Nwosa Philip Ifeakachukwu

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This study examined the impact of inflation on private investment in Nigeria for the period 1980 to 2012. Private investment was measured by foreign direct investment and private domestic investment. The study employed the Ordinary Least Square (OLS) technique. The empirical regression estimate showed that inflation had a positive but insignificant effect on private investment in Nigeria; implying that although an increase in inflation rate leads to a corresponding increase in private investment but however the effect was found to be insignificant. Thus, the study recommended that government should prevent high inflation rate that can negatively affect private investment in Nigeria and government should also put in place appropriate facilities that are investment enhancing in order to increase the level of both domestic and foreign private investment in Nigeria.

Keywords: inflation rate, private investment, OLS, Nigeria

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2160 Study of Polish and Ukrainian Volunteers Helping War Refugees. Psychological and Motivational Conditions of Coping with Stress of Volunteer Activity

Authors: Agata Chudzicka-Czupała, Nadiya Hapon, Liudmyla Karamushka, Marta żywiołek-Szeja

Abstract:

Objectives: The study is about the determinants of coping with stress connected with volunteer activity for Russo-Ukrainian war 2022 refugees. We examined the mental health reactions, chosen psychological traits, and motivational functions of volunteers working in Poland and Ukraine in relation to their coping with stress styles. The study was financed with funds from the Foundation for Polish Science in the framework of the FOR UKRAINE Programme. Material and Method: The study was conducted in 2022. The study was a quantitative, questionnaire-based survey. Data was collected through an online survey. The volunteers were asked to assess their propensity to use different styles of coping with stress connected with their activity for Russo-Ukrainian war refugees using The Brief Coping Orientation to Problems Experienced Inventory (Brief-COPE) questionnaire. Depression, anxiety, and stress were measured using the Depression, Anxiety, and Stress (DASS)-21 item scale. Chosen psychological traits, psychological capital and hardiness, were assessed by The Psychological Capital Questionnaire and The Norwegian Revised Scale of Hardiness (DRS-15R). Then The Volunteer Function Inventory (VFI) was used. The significance of differences between the variable means of the samples was tested by the Student's t-test. We used multivariate linear regression to identify factors associated with coping with stress styles separately for each national sample. Results: The sample consisted of 720 volunteers helping war refugees (in Poland, 435 people, and 285 in Ukraine). The results of the regression analysis indicate variables that are significant predictors of the propensity to use particular styles of coping with stress (problem-focused style, emotion-focused style and avoidant coping). These include levels of depression and stress, individual psychological characteristics and motivational functions, different for Polish and Ukrainians. Ukrainian volunteers are significantly more likely to use all three coping with stress styles than Polish ones. The results also prove significant differences in the severity of anxiety, stress and depression, the selected psychological traits and motivational functions studied, which led volunteers to participate in activities for war refugees. Conclusions: The results show that depression and stress severity, as well as psychological capital and hardiness, and motivational factors are connected with coping with stress behavior. The results indicate the need for increased attention to the well-being of volunteers acting under stressful conditions. They also prove the necessity of guiding the selection of people for specific types of volu

Keywords: anxiety, coping with stress styles, depression, hardiness, mental health, motivational functions, psychological capital, resilience, stress, war, volunteer, civil society

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2159 Outcome-Based Education as Mediator of the Effect of Blended Learning on the Student Performance in Statistics

Authors: Restituto I. Rodelas

Abstract:

The higher education has adopted the outcomes-based education from K-12. In this approach, the teacher uses any teaching and learning strategies that enable the students to achieve the learning outcomes. The students may be required to exert more effort and figure things out on their own. Hence, outcomes-based students are assumed to be more responsible and more capable of applying the knowledge learned. Another approach that the higher education in the Philippines is starting to adopt from other countries is blended learning. This combination of classroom and fully online instruction and learning is expected to be more effective. Participating in the online sessions, however, is entirely up to the students. Thus, the effect of blended learning on the performance of students in Statistics may be mediated by outcomes-based education. If there is a significant positive mediating effect, then blended learning can be optimized by integrating outcomes-based education. In this study, the sample will consist of four blended learning Statistics classes at Jose Rizal University in the second semester of AY 2015–2016. Two of these classes will be assigned randomly to the experimental group that will be handled using outcomes-based education. The two classes in the control group will be handled using the traditional lecture approach. Prior to the discussion of the first topic, a pre-test will be administered. The same test will be given as posttest after the last topic is covered. In order to establish equality of the groups’ initial knowledge, single factor ANOVA of the pretest scores will be performed. Single factor ANOVA of the posttest-pretest score differences will also be conducted to compare the performance of the experimental and control groups. When a significant difference is obtained in any of these ANOVAs, post hoc analysis will be done using Tukey's honestly significant difference test (HSD). Mediating effect will be evaluated using correlation and regression analyses. The groups’ initial knowledge are equal when the result of pretest scores ANOVA is not significant. If the result of score differences ANOVA is significant and the post hoc test indicates that the classes in the experimental group have significantly different scores from those in the control group, then outcomes-based education has a positive effect. Let blended learning be the independent variable (IV), outcomes-based education be the mediating variable (MV), and score difference be the dependent variable (DV). There is mediating effect when the following requirements are satisfied: significant correlation of IV to DV, significant correlation of IV to MV, significant relationship of MV to DV when both IV and MV are predictors in a regression model, and the absolute value of the coefficient of IV as sole predictor is larger than that when both IV and MV are predictors. With a positive mediating effect of outcomes-base education on the effect of blended learning on student performance, it will be recommended to integrate outcomes-based education into blended learning. This will yield the best learning results.

Keywords: outcome-based teaching, blended learning, face-to-face, student-centered

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2158 Predictors for Success in Methadone Maintenance Treatment Clinic: 24 Years of Experience

Authors: Einat E. Peles, Shaul Schreiber, Miriam Adelson

Abstract:

Background: Since established more than 50 years ago, methadone maintenance treatment (MMT) is the most effective treatment for opioid addiction, a chronic relapsing brain disorder that became an epidemic in western societies. Treatment includes daily individual optimal medication methadone dose (a long acting mu opioid receptor full agonist), accompanied with psychosocial therapy. It is well established that the longer retention in treatment the better outcome and survival occur. It reduces the likelihood to infectious diseases and overdose death that associated with drug injecting, enhanced social rehabilitation and eliminate criminal activity, and lead to healthy productive life. Aim: To evaluate predictors for long term retention in treatment we analyzed our prospective follow up of a major MMT clinic affiliated to a big tertiary medical center. Population Methods: Between June 25, 1993, and June 24, 2016, all 889 patients ( ≥ 18y) who ever admitted to the clinic were prospectively followed-up until May 2017. Duration in treatment from the first admission until the patient quit treatment or until the end of follow-up (24 years) was taken for calculating cumulative retention in treatment using survival analyses (Kaplan Meier) with log-rank and Cox regression for multivariate analyses. Results: Of the 889 patients, 25.2% were females who admitted to treatment at younger age (35.0 ± 7.9 vs. 40.6 ± 9.8, p < .0005), but started opioid usage at same age (22.3 ± 6.9). In addition to opioid use, on admission to MMT 58.5% had positive urine for benzodiazepines, 25% to cocaine, 12.4% to cannabis and 6.9% to amphetamines. Hepatitis C antibody tested positive in 55%, and HIV in 7.8% of the patients and 40%. Of all patients, 75.7% stayed at least one year in treatment, and of them, 67.7% stopped opioid usage (based on urine tests), and a net reduction observed in all other substance abuse (proportion of those who stopped minus proportion of those who have started). Long term retention up to 24 years was 8.0 years (95% Confidence Interval (CI) 7.4-8.6). Predictors for longer retention in treatment (Cox regression) were being older on admission ( ≥ 30y) Odds Ratio (OR) =1.4 (CI 1.1-1.8), not abusing opioids after one year OR=1.8 (CI 1.5-2.1), not abusing benzodiazepine after one year OR=1.7 (CI 1.4-2.1) and treating with methadone dose ≥ 100mg/day OR =1.8 (CI 1.5-2.3). Conclusions: Treating and following patients over 24 years indicate success of two main outcomes, high rate of retention after one year (75.7%) and high proportion of opiate abuse cessation (67.7%). As expected, longer cumulative retention was associated with patients treated with high adequate methadone dose that successfully result in opioid cessation. Based on these findings, in order to reduce morbidity and mortality, we find the establishment of more MMT clinics within a general hospital, a most urgent necessity.

Keywords: methadone maintenance treatment, epidemic, opioids, retention

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2157 Financial Regulations and Insolvency Risk: Empirical Evidence from Commercial Banks of Pakistan

Authors: Shumaila Zeb

Abstract:

The proposed study aims to investigate insolvency risk of commercial banks of Pakistan. Furthermore, it empirically estimates the effect of already implemented financial regulations on the insolvency risk of banks. To carry out the empirical analysis, a balanced bank-level panel data covering the period 2008-2016 is used. The Z-score is used for calculating the insolvency risk of each bank. The panel regression is used to investigate the relationship between financial regulations and insolvency risk of banks. The empirics reveal that the financial regulations enforced by State Bank of Pakistan have significant impacts on the insolvency risk of banks. The results further indicate that loan ratio and reserve ratio are positively and significantly related to the insolvency risk of banks.

Keywords: insolvency risk, Z-score, financial regulations, banks

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2156 A Meta-Analysis of School-Based Suicide Prevention for Adolescents and Meta-Regressions of Contextual and Intervention Factors

Authors: E. H. Walsh, J. McMahon, M. P. Herring

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Post-primary school-based suicide prevention (PSSP) is a valuable avenue to reduce suicidal behaviours in adolescents. The aims of this meta-analysis and meta-regression were 1) to quantify the effect of PSSP interventions on adolescent suicide ideation (SI) and suicide attempts (SA), and 2) to explore how intervention effects may vary based on important contextual and intervention factors. This study provides further support to the benefits of PSSP by demonstrating lower suicide outcomes in over 30,000 adolescents following PSSP and mental health interventions and tentatively suggests that intervention effectiveness may potentially vary based on intervention factors. The protocol for this study is registered on PROSPERO (ID=CRD42020168883). Population, intervention, comparison, outcomes, and study design (PICOs) defined eligible studies as cluster randomised studies (n=12) containing PSSP and measuring suicide outcomes. Aggregate electronic database EBSCO host, Web of Science, and Cochrane Central Register of Controlled Trials databases were searched. Cochrane bias tools for cluster randomised studies demonstrated that half of the studies were rated as low risk of bias. The Egger’s Regression Test adapted for multi-level modelling indicated that publication bias was not an issue (all ps > .05). Crude and corresponding adjusted pooled log odds ratios (OR) were computed using the Metafor package in R, yielding 12 SA and 19 SI effects. Multi-level random-effects models accounting for dependencies of effects from the same study revealed that in crude models, compared to controls, interventions were significantly associated with 13% (OR=0.87, 95% confidence interval (CI), [0.78,0.96], Q18 =15.41, p=0.63) and 34% (OR=0.66, 95%CI [0.47,0.91], Q10=16.31, p=0.13) lower odds of SI and SA, respectively. Adjusted models showed similar odds reductions of 15% (OR=0.85, 95%CI[0.75,0.95], Q18=10.04, p=0.93) and 28% (OR=0.72, 95%CI[0.59,0.87], Q10=10.46, p=0.49) for SI and SA, respectively. Within-cluster heterogeneity ranged from no heterogeneity to low heterogeneity for SA across crude and adjusted models (0-9%). No heterogeneity was identified for SI across crude and adjusted models (0%). Pre-specified univariate moderator analyses were not significant for SA (all ps < 0.05). Variations in average pooled SA odds reductions across categories of various intervention characteristics were observed (all ps < 0.05), which preliminarily suggests that the effectiveness of interventions may potentially vary across intervention factors. These findings have practical implications for researchers, clinicians, educators, and decision-makers. Further investigation of important logical, theoretical, and empirical moderators on PSSP intervention effectiveness is recommended to establish how and when PSSP interventions best reduce adolescent suicidal behaviour.

Keywords: adolescents, contextual factors, post-primary school-based suicide prevention, suicide ideation, suicide attempts

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2155 Modeling of Coagulation Process for the Removal of Carbofuran in Aqueous Solution

Authors: Roli Saini, Pradeep Kumar

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A coagulation/flocculation process was adopted for the reduction of carbamate insecticide (carbofuran) from aqueous solution. Ferric chloride (FeCl3) was used as a coagulant to treat the carbofuran. To exploit the reduction efficiency of pesticide concentration and COD, the jar-test experiments were carried out and process was optimized through response surface methodology (RSM). The effects of two independent factors; i.e., FeCl3 dosage and pH on the reduction efficiency were estimated by using central composite design (CCD). The initial COD of the 30 mg/L concentrated solution was found to be 510 mg/L. Results exposed that the maximum reduction occurred at an optimal condition of FeCl3 = 80 mg/L, and pH = 5.0, from which the reduction of concentration and COD 75.13% and 65.34%, respectively. The present study also predicted that the obtained regression equations could be helpful as the theoretical basis for the coagulation process of pesticide wastewater.

Keywords: carbofuran, coagulation, optimization, response surface methodology

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2154 The Relationship between the Personality Traits and Self-Compassion with Psychological Well-Being in Iranian College Students

Authors: Abdolamir Gatezadeh, Rezvan K. A. Mohamamdi, Arash Jelodari

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It has been well established that personality traits and self-compassion are associated with psychological well-being. Thus, the current research aimed to investigate the underlying mechanisms in a collectivist culture. Method: One hundred and fifty college students were chosen and filled out Ryff's Psychological Well-Being Scale, the NEO Personality Inventory, and Neff's Self-Compassion Scale. Results: The results of correlation analysis showed that there were significant relationships between the personality traits (neuroticism, extraversion, agreeableness, and conscientiousness) and self-compassion (self-kindness, isolation, mindfulness, and the total score of self-compassion) with psychological well-being. The regression analysis showed that neuroticism, extraversion, and conscientiousness significantly predicted psychological well-being. Discussion and conclusion: The cultural implications and future orientations have been discussed.

Keywords: college students, personality traits, psychological well-being, self-compassion

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2153 Attachment as a Predictor for Cognitive Rigidity

Authors: Barbara Gawda

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Attachment model formed in childhood has an important impact on emotional development, personality, and social relationships. Attachment is also thought to have an impact on construction of affective-cognitive schemas and cognitive functioning. The aim of the current study was to verify whether there is an association between attachment and cognitive rigidity defined as dogmatism and intolerance of ambiguity. The analysis of 180 participants (persons of a similar age and education level, number of men and women was equal) was conducted. To test the attachment styles, the Revised Experiences in Close Relationships Inventory (ECR-R) was used. To examine cognitive rigidity, the Rokeach and Budner questionnaires were used. A multiple regression model was employed to examine whether attachment styles are predictors for dogmatism. The results confirmed that fearful-ambivalent attachment is the main predictor for dogmatism but not for intolerance of ambiguity.

Keywords: attachment styles, cognitive rigidity, dogmatism, intolerance of ambiguity

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2152 Psychopathic Manager Behavior and the Employee Workplace Deviance: The Mediating Role of Revenge Motive, the Moderating Roles of Core Self-Evaluations and Attitude Importance

Authors: Sinem Bulkan

Abstract:

This study introduces the construct of psychopathic manager behaviour and aims for the development of psychopathic manager behaviour (Psycho-Man B) measure. The study also aims for the understanding of the relationship between psychopathic manager behaviour and workplace deviance while investigating the mediating role of a revenge motive and the moderating roles of the core self-evaluations and the attitude importance. Data were collected from 519 employees from a wide variety of jobs and industries who currently work for or previously worked for a manager in a collectivist culture, Turkey. Psycho-Man B Measure was developed resulting in five dimensions as opposed to the proposed ten dimensions. Simple linear and hierarchical regression analyses were conducted to test the hypotheses. The results of simple linear regression analyses showed that psychopathic manager behaviour was positively significantly related to supervisor-directed and organisation-directed deviance. Revenge motive towards the manager partially mediated the relationship between psychopathic manager behaviour and supervisor-directed deviance. Similarly, revenge motive towards the organisation partially mediated the relationship between psychopathic manager behaviour and organisation-directed deviance. Furthermore, no support was found for the expected moderating role of core self-evaluations in the revenge motive towards the manager-supervisor-directed deviance and revenge motive towards the organisation-organisation-directed deviance relationships. Attitude importance moderated the relationship between revenge motive towards the manager and supervisor-directed deviance; revenge motive towards the organisation and organisation-directed deviance. Moderated-mediation hypotheses were not supported for core self-evaluations but were supported for the attitude importance. Additional analyses for sub-dimensions were conducted to further examine the hypotheses. Demographic variables were examined through independent samples t-tests, and one way ANOVA. Finally, findings are discussed; limitations, suggestions and implications are presented. The major contribution of this study is that ‘psychopathic manager behaviour’ construct was introduced to the literature and a scale for the reliable identification of psychopathic manager behaviour was developed in to evaluate managers’ level of sub-clinical psychopathy in the workforce. The study introduced that employees engage in different forms of supervisor-directed deviance and organisation-directed deviance depending on the level of the emotions and personal goals. Supervisor-directed deviant behaviours and organisation-directed deviant behaviours became distinct in a way as impulsive and premeditated, active or passive, direct and indirect actions. Accordingly, it is important for organisations to notice that employees’ level of affective state and attitude importance for psychopathic manager behaviours predetermine the certain type of employee deviant behaviours.

Keywords: attitude importance, core self evaluations, psychopathic manager behaviour, revenge motive, workplace deviance

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2151 The Role of Banks Funding and Promoting the Foreign Trade: Case of Turkey

Authors: Mikail Altan

Abstract:

International trust takes first place in the development of foreign trade in the country. They see an important role in ensuring that trust. Various payment methods that are developed in the banking system provide fast and reliable way to execution and promote foreign trade by financing the foreign trade. In this study, we investigate the influence of bank on foreign trade in Turkey. 26 years of data for 1990-2015 period have been used in this study. After correlation analysis, a simple regression model was established. Payment methods that are developed in the banking system make a positive contribution in Turkey’s foreign trade volume. In addition, the export of Turkey was affected positively more than import’s by these payment methods.

Keywords: banks, export, foreign trade, import

Procedia PDF Downloads 337