درخت حوزه‌های تخصصی

The present study aimed to identify and prioritize the factors affecting the marketing of knowledge-based products of basic chemicals. This research is applied in terms of objectives and a data-based cross-sectional survey concerning its method. Initially, the factors affecting the marketing of products in this sector were identified based on library and field studies and by purposive sampling of 15 senior managers of knowledge-based chemical companies (research experts) utilizing a semi-structured interview and in the form of a questionnaire. Cochran’s formula was then employed, and 400 experts and staff working in this department were selected as the study’s statistical population through simple random sampling. Subsequently, confirmatory factor analysis was used to analyze the data and check the final model’s fitting. In the end, each factor’s relative importance was determined by the fuzzy DNAP method. The results led to the identification of 16 sub-criteria under seven main criteria, including technical and managerial, information and knowledge, economic, infrastructural, legal, and support issues, besides supply capabilities. The results revealed that the information and knowledge criterion and the innovation sub-criterion had the highest score, while the supply capability criterion and the knowledge management sub-criterion were ranked last.

The purpose of this study was to design and formulate strategic liquidity management strategies in the banking industry. In this research, in order to combine qualitative and quantitative data, a sequential integrated exploratory method will be used, according to the classification model with emphasis on qualitative data. Therefore, according to its objectives, the present study is part of applied research and in terms of the research process is part of descriptive and exploratory research that was conducted in two parts: qualitative and quantitative. The statistical population of the present study was the qualitative part of the managers of the Welfare Bank. The sampling method was to achieve theoretical saturation and 25 people were selected as the sample size. Therefore, a survey was used to collect information and according to the data collection, two types of tools were used to review documents, interviews, and questionnaires, and the evaluation method of the questionnaire was performed with a 5-point Likert scale. The Cronbach's alpha questionnaire was used. SWOT analysis was used to analyze the data. The results showed that the Welfare Bank has many opportunities to develop appropriate liquidity management strategies. As it was observed, the chart stretches towards the opportunities and strengths of the offensive situation, which requires strategic planning to use the strengths and opportunities, and 11 strategies were developed for this purpose.

Objective: Recent literature emphasizing the importance of income distribution for pollution. The GINI index is the most common indicator for measuring income inequality in previous studies. The new literature has focused on relative redistribution, which is quantified by the GINI coefficientis defined as the difference between the GINI based on market income and GINI based on disposable income. Thus, this study relies on the redistributive effect of taxes and transfers and its impact on carbon dioxide emissions.Methods: The study is conducted using aggregated data from oil-exporting countries including Canada, the United States, the UK, Mexico, the Netherlands, Russia, and China between 2010 and 2020 by using a simultaneous equations system consisting of two equations so that economic growth and pollution emission are as endogenous variables. Elative redistribution, good governance, oil income, trade openness, and CO2 emission are the exogenous variables. Results: Based on model estimates, income inequality, good governance, and oil income have a positive and significant impact on economic growth over the years studied, while inequalities in human development and population growth rates have a negative impact. Economic growth and trade openness also have a negative and significant impact on the spread of pollutionConclusion: Taxes and transfer payments, as redistribution tools can stimulate economic growth. Relative redistribution as a more equitable way can lead to increased economic growth and economic growth reduces carbon dioxide emissions. Therefore, providing an appropriate standard of income inequality can help to better understand and formulate effective policies for income equality.

Objective: Consumers have recently become more concerned about environmental protection and have turned to eco-friendly products, also known as green products. To explore the factors that determine consumers’ green product purchase intentions, this study aims to measure the effects of TPB variables (e.g., perceived behavioural control, attitude, and subjective norms) on green product purchase intentions. Through this study, we build a theoretical framework that combines the ideas and perspectives of previous studies on sustainable consumption.Methods: In order to validate our research hypotheses, questionnaires were used to collect primary data from a sample of 219 participants in Algeria. Therefore, this research uses quantitative study method to design the research model which was tested using structural equation modeling (SEM) method. We analyzed the statistical data using SPSS v22.0 and Statistica v08.Results: The results show that purchasing intention of green products is positively affected by attitude (ATT), subjective norms (SN), and perceived behavior control (PBC). Furthermore, our findings discovered that the influence of PBC on intention to purchase green products was more significant than the effects of SN and ATT, enhancing our understanding of the key drivers of green product purchase intentions.Conclusion: These findings can generate more suitable managerial implications and policy contributions to promote green product consumption. It also highlights the key factors determining consumers’ eco-friendly purchasing intentions in Algeria. Therefore, identifying and understanding these factors enables the organization to develop effective strategies that guide consumers towards sustainable consumption and mitigate the negative repercussions of environmentally harmful consumption.

Financing decisions such as capital structure have gained much attention in literature of financial development over the last decade. Capital structure deviations from its optimal level can occur for various reasons. According to the dynamic trade-off theory, continuous adjustment of capital structure to maximize company value is essential. If companies adjust their capital structure quickly towards the target leverage, past financing activities and historical market conditions will only have short-term effects on the current capital structure. Conversely, if companies adjust their capital structure slowly, the opposite is true. We examine the relationship between organizational and performance characteristics and capital structure, as well as the speed of adjustment, in financial and non-financial firms listed on the Tehran Stock Exchange and compare these effects between the two categories of companies. The statistical population consists of companies listed on the Tehran Stock Exchange from 2017 to 2022. The results show that the speed of capital structure adjustment is lower in the financial sector compared to the non-financial sector. Additionally, three performance variables—profitability, growth opportunities, and liquidity—are statistically significant and impact capital structure and its adjustment speed in both financial and non-financial sectors. However, the growth opportunities variable has a different effect direction in the financial sector compared to the non-financial sector, while the age variable does not have a significant effect. Regarding organizational characteristics—complexity, institutional ownership, and size—only organizational complexity in the financial sector is significant at a 95% confidence level, while all organizational characteristics are significant in the non-financial sector

The present study aims to examine the relationship between cost stickiness and conservatism levels according to the type of industry. This purpose is achieved using the combined data technique and three models of non-operating accruals, the Basu model, and the market value model with a sample consisting of 113 companies listed on the Tehran Stock Exchange (TSE) over the period 2011 to 2020. Findings show that based on the model of non-operating accruals in the automotive, pharmaceutical, chemical, and food industries, cost stickiness decreases the level of conservatism. However, in the machinery industry, the relationship is significantly based on this model, but cost stickiness does not reduce the level of conservatism. According to the Basu model in the chemical, food, and basic metals industries, cost stickiness reduces the level of conservatism. But in the pharmaceutical industry and machinery and equipment, there is a significant relationship according to this model, but cost stickiness does not decrease the level of conservatism in companies. Also, based on the market value model in the automotive, chemical, machinery, and basic metal industries, there is a significant association, but cost stickiness does not decrease the level of conservatism in companies.

In today's world, financial markets, as the main arteries of any country's economic system, have created an attractive environment for investors, and therefore it is necessary to identify the behavior of investors in this space and variables affecting prices and stock returns in these markets. The purpose of this study is to use the method of random dominance analysis and electrification technique as a new method in financial research to investigate the effect of calendar anomalies on the index returns of banks listed on the Tehran Stock Exchange in the period 2016-2020. Findings show that according to the three main hypotheses that there is a significant difference between the returns of the banking industry index on Saturdays to Wednesdays, in the first, second, third and fourth weeks of each month and in the months of April to March based on accuracy Market efficiency assumptions were formulated, all three hypotheses were rejected. It was also found that Wednesdays and the second weeks of each month are the best time to invest in the banking sector. In addition, June is the best and March is the most unsuitable month of the year to invest in this field.