• Economic and Environmental Geology
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• v.55 no.6
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• pp.617-632
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• 2022

In recent years, environmental pollution and determining the main factors causing this pollution have become an important issue. This study investigates the relationship between the agricultural sector and environmental pollution in Azerbaijan for 1992-2018. The dependent variable in the study is the agricultural greenhouse gas emissions (CO₂ equivalent). Eight variables were selected as explanatory variables: four agricultural inputs and four agricultural macro indicators. Unit root tests, ARDL boundary test, FMOLS, DOLS and CCR long-term estimators, Granger causality analysis, and variance decomposition analyses were used to investigate the effect of these variables on agricultural emissions. The results show that chemical fertilizer consumption, livestock number, and pesticide use positively and statistically significantly affect agricultural emissions from agricultural input variables. In contrast, agricultural energy consumption has a negative and significant effect. From agricultural macro indicator variables, it was found that the crop and animal production index had a positive and significant effect on agricultural emissions. According to the Granger causality test results, it was concluded that there are a causality relationship from chemical fertilizer consumption, livestock number, crop and livestock production index variables towards agricultural emissions. Considering all the results obtained, it is seen that the variables that have the most effect on the increase in agricultural emissions in Azerbaijan are the number of livestock, the consumption of chemical fertilizers, and the use of pesticides, respectively. The results from the research will contribute to the information on agricultural greenhouse gas emissions and will play an enlightening role for policymakers and the general public.

• Journal of Dental Rehabilitation and Applied Science
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• v.34 no.3
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• pp.147-156
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• 2018

On the reliability of occlusal contact marks with occlusal indicators, it must be important to consider the affecting results of using methods. With affecting the accuracy and validity of results, there are many variables such as thickness and material of indicator, occlusal force, number of usage and etc. Nevertheless, researches on the occlusal contact marks have limited to focusing thickness of indicators and occlusal force. For the control of variables, it is clinically recommended to do use new indicators in every trial and to secure dry condition and to use thinner ones. In addition, alternatives might be helpful to understand more appropriate results.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.71-84
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• 2017

Over the past decade, we have witnessed Serious Debates in MISQ and Other Journals Between Two Camps that have Differing Views on the use of Causal Indicators to Measure Constructs. There is the Camp that advocates Causal Indicators (ADVOCATE) and the Camp that opposes Their Usage (OPPONENT). The Debates have been primarily centered on the OPPONENT's Argument that the Meaning of a Latent Variable is determined by its Outcome Variables. However, Little Effort has been made to Validate the ADVOCATE's Dispute (Against the OPPONENT's Arguments) that the Meaning of a Latent Variable is decided by its Causal Indicators if there is no Misspecification. Our Study precisely examines the Integrity of the Argument. For this, we empirically examine how the two Primary Psychometric Properties-Comprehensiveness and Interrelationship-of Causal Indicators Influence Theory Testing between Latent Variables through Three Different Tests (i.e., Comprehensive Test, Interrelationship Test, and Mixed Test). Conducted on Two Different Datasets, Our Analysis Consistently Reveals that Structural Path Coefficients are Hardly Sensitive to the Changes (i.e., Misspecification) in the Properties of Causal Indicators. The Discovery offers Important Evidence that the Sound Theoretical Logic of a Causal Model is not in Sync with the Empirical Mechanism of Parameter Estimation. This Underscores that a Latent Variable Formed by Causal Indicators is empirically an elusive notion that is Difficult to Operationalize. As Our Results have Significant Implications on the Integrity of Numerous IS studies which have conducted Theory or Hypothesis Testing Using Causal Indicators, we strongly advocate Open Discussions among Methodologists regarding Our Findings and Their Implications for Both Published IS Research and Future Practices.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.117-127
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• 2021

This study was conducted to comprehensively identify factors that potentially influence corporate investment behavior, including micro, macro, and sectoral variables. Furthermore, investment behavior was studied across nations based on their participation in the global value chain (GVC), which was evaluated based on commodities, limited manufacturing, advanced manufacturing, and innovative activities. The study uses the dynamic panel data analysis and Generalized Method of Moment (GMM) estimation for a sample of 800 corporations, with data spanning over 2000-2019. The study result shows that in all types of countries, the coefficient lag indicator of capital expenditure statistically has a significant effect on capital expenditure. Sales growth, exchange rate, and GDP have a significant positive effect on corporate investment growth, while DER has a negative effect. In commodity countries, corporate investment is influenced by sales growth, exchange rate, and FCI. The variables that influence corporate investment in manufacturing countries are the FCI, exchange rate, sales growth, GDP, and DER. In innovative countries, variables that significantly affect capital expenditure are DER, GDP, and Tobin Q. In each type of country, the interaction terms between exchange rate and commodity price are positive and statistically significant.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.657-665
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• 2021

The study aims to assess the acceptance of social commerce and participate in social commerce amongst Omani people. The questions of the survey Instrument were prepared in English later converted into Arabic. The survey instrument was having two parts; the first part sought the demographic information like age, gender, education, occupation etc. The second part of the instrument was related to the variables, which was in 5-point Likert scale, where 5 means strongly agree while 1 meaning strongly disagree. The data was collected using online and offline surveys, making the number of the valid responses to 478. A conceptual model was developed using the following variables. The selected variables such as "Familiarity" (F), "Trust" (T), "Perceived usefulness" (PU), "Perceived ease of use" (PEU), "Intention to Purchase" (IP). The hypothesis was tested using structural equation modelling. The results indicate that all six hypotheses were supported. The F, T and PEU, and PU was found to be positive and significant related to intention to purchase (p-value 0.003, 0.001, 0.000. & 0.007). Amongst the four, p value of F was found to be the lowest and PU was found to be the highest. This indicate F was strong indicator of IP as compared to others. PUE relates to PU, and F was related to IP.

• Physical Therapy Korea
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• v.29 no.3
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• pp.200-207
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• 2022

Background: The oxygen uptake efficiency slope (OUES) is the most important index for accurately measuring cardiopulmonary function in patients with acute ischemic heart disease. However, the relationship between the OUES variables and important cardiopulmonary function parameters remain unelucidated for patients with acute ischemic heart disease, which accounts for the largest proportion of heart disease. Objects: The present cross sectional clinical study aimed to determine the multiple relationships among the cardiopulmonary function variables mentioned above in adults with acute ischemic heart disease. Methods: A convenience sample of 110 adult inpatients with ischemic heart disease (age: 57.4 ± 11.3 y; 95 males, 15 females) was enrolled at the hospital cardiac rehabilitation center. The correlation between the important cardiopulmonary function indicators including peak oxygen uptake (VO₂ peak), minute ventilation (VE)/carbon dioxide production (VCO₂) slope, heart rate recovery (HRR), and ejection fraction (EF) and OUES was confirmed. Results: This study showed that OUES was highly correlated with VO₂ peak, VE/VCO₂ slope, and HRR parameters. Conclusion: The OUES can be used as an accurate indicator for cardiopulmonary function. There are other factors that influence aerobic capacity besides EF, so there is no correlation with EF. Effective cardiopulmonary rehabilitation programs can be designed based on OUES during submaximal exercise in patients with acute ischemic heart disease.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.906-917
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• 2022

This study aimed to compare differences according to categories of fishery and marine environmental policies for the (estimated) amount of fishery waste generated by fishing, and to analyze the correlation between associated independent and dependent variables. The independent variables were divided into three dif erent sectors. The first sector included precautionary policies that observed eco-friendly fishing support program, institutional prevention activities, and physical barriers installation. The second sector with the current management policies included the relevant vessel operations, establishment of fishery order, fishery restructuring, and fishery ground clean-up. Thirdly, post-response policies comprised the litter purification from river to shoreline, the collection and removal of marine, sedimentary, and floating debris, purchasing salvaged debris generated while fishing, fishery waste disposal, and repairing damage caused by marine litter. The indicator used was the settlement amount by each program. The dependent variable was the estimated amount of fishery waste and the indicator was the sum of the loss of traps and gill nets and the loss of their appendages. According to the results of Kruskal-Wallis Test, the estimated amount of fishery waste was highest in the East Sea in terms of sea area and the highest in the Si(city) according to basic local municipality. The settlement amount related to the marine environment services was largest in the Gun(county). Further, there were significant differences between Gun(county) and the other regions(Si(city) and Gu(autonomous district)) with respect to most variables. The variables related to the estimated amount of fishery debris were the project purchasing salvaged debris generated while fishing and fishery waste disposal program in the post-response policies.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1245-1246
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• 2022

Walkability is an indicator of how much pedestrians are willing to walk and how well a walking environment is created. As walking can promote pedestrians' mental and physical health, there has been increasing focus on improving walkability in different ways. Thus, plenty of research has been undertaken to measure walkability. When measuring walkability, there are many objective and subjective variables. Subjective variables include a feeling of safety, pleasure, or comfort, which can significantly affect perceived walkability. However, these subjective factors are difficult to measure by making the walkability index more reliant on objective and physical factors. Because many subjective variables are associated with human emotional states, understanding pedestrians' emotional states provides an opportunity to measure the subjective walkability variables more quantitatively. Pedestrians' emotions can be examined through surveys, but there are social and economic difficulties involved when conducting surveys. Recently, an increasing number of studies have employed physiological data to measure pedestrians' stress responses when navigating unpleasant environmental barriers on their walking paths. However, studies investigating the emotional states of pedestrians in the walking environment, including assessing their positive emotions felt, such as pleasure, have rarely been conducted. Using wearable devices, this study examined the various emotional states of pedestrians affected by the walking environment. Specifically, this study aimed to demonstrate the feasibility of monitoring biometric data, such as electrodermal activity (EDA) and heart rate variability (HRV), using wearable devices as an indicator of pedestrians' emotional states-both pleasant-unpleasant and aroused-relaxed states. To this end, various walking environments with different characteristics were set up to collect and analyze the pedestrians' biometric data. Subsequently, the subjects wearing the wearable devices were allowed to walk on the experimental paths as usual. After the experiment, the valence (i.e., pleasant or unpleasant) and arousal (i.e., activated or relaxed) scale of the pedestrians was identified through a bipolar dimension survey. The survey results were compared with many potentially relevant EDA and HRV signal features. The research results revealed the potential for physiological responses to indicate the pedestrians' emotional states, but further investigation is warranted. The research results were expected to provide a method to measure the subjective factors of walkability by measuring emotions and monitoring pedestrians' positive or negative feelings when walking to improve the walking environment. However, due to the lack of samples and other internal and external factors influencing emotions (which need to be studied further), it cannot be comprehensively concluded that the pedestrians' emotional states were affected by the walking environment.

• The Journal of Information Systems
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• v.16 no.1
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• pp.91-109
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• 2007

This study investigates the extent to which the implementation of enterprise resource planning(ERP) systems enhance the corporate performance by examining financial variables of the implemented firms against those of the control fm. A total of 346 observations were obtained from 160 firms, 80 implemented firms and 80 control firms, for the period of 1998-2002. Results from the study partly support the assertion that ERP improves the full spectrum of business functions such as selling, marketing, purchasing, warehousing, accounting and human resources by tightly integrating enterprise-wise information databases. First the profitability of the implemented group was different from that of the control group. The indicator (dummy) variable was able to explain the differences in total cash flows between the implemented group fm and the control group firms. Second, ERP turned out In improve the efficiency in managing assets. The indicator variable has the power in explaining the differences in the amount of accounts receivables between the implemented group firms and the control group firms. Third, the product turnover ratio of the implemented group was different from that of the control group. Fourth, the average value added per employee and the net income per employee of the implemented group firms were greats- than those of the control group firms. Finally, the average magnitude of the administrative expenses of the implemented group firms was smaller than that of the control group firms.