Investment

Drawing on Norton Peirce's (1995) theory of investment and Darvin and Norton's (2015) expanded the model of investment, the present study aims to research investment in second language (L2) learning among Iranian English language learners. The participants included 852 male and female English language learners belonging to different age groups and English language proficiency levels. A 42-item questionnaire, developed and validated by the present authors (forthcoming), was administered online and by hand. The results showed that Iranian English as a Foreign Language (EFL) learners moderately invested to learn English language and that there were significant differences in the extent of investment between male and female participants and different language proficiency levels (low- and high-proficiency learners). Moreover, the results of the study demonstrated that there was no significant difference in the extent of investment between different age groups (teenage and adult ones). The study concludes with suggestions for future research on investment in L2 learning and a discussion of how such research can impact language education policy in EFL contexts.

The present exploratory study aimed to provide a more tangible and comprehensive picture of the construct of investment in language learning through investigating the issue from a quantitative perspective. To this end, the present researchers followed three main phases. First, a hypothesized model of investment in language learning with six components was developed for the Iranian English as a foreign language (EFL) learners based on the extensive readings of the literature on investment, consultations with a panel of experts, three university professors in the relevant fields, and interviews with 20 language learners. Second, a questionnaire was developed and validated based on the proposed model to represent its components. Finally, the data collected through this questionnaire were fed into the model to see to what extent the model fitted the data. The participants were male and female English language learners belonging to different age groups and English language proficiency levels.The initial results showed poor values; however, the model was trimmed by removing one item from the questionnaire, and final statistical indices showed that the model fitted the data.

In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted to improve forecasting models employing a variety of techniques. In this paper, we extend the field of expert systems, forecasting, and model by applying an Artificial Neural Network. ANN model is applied to forecast market volatility. The results show an overall improvement in forecasting using the neural network as compared to linear regression method.

Interlanguage pragmatic learning strategies (IPLS) as particularly tailored language learning strategies for acquiring L2 pragmatic knowledge have been recently paid paramount attention in the pragmatics literature. These strategies are, therefore, related to some other social variables which are central to pragmatic development such as L2 social identity. Because of the importance of the IPLS and the rarity of research about the relationship between IPLS and with L2 social identity as a highly pragmatic-oriented variable, the current study tried to investigate the contribution of various forms of IPLS to L2 social identity among a randomly selected sample of 125 upper-intermediate to advanced EFL learners at a state university in Iran. During the two-phased data collection procedure, first, the participants filled out Locastro’s (2001) L2 social identity questionnaire, and then Malmir and Tajeddin’s (2015) IPLS inventory in two subsequent sessions. Data analysis using multiple regression revealed that all types of IPLS were significant contributors to L2 social identity except for the memory IPLS. Among the other five types of IPLS, social IPLS was a significant and strong contributor to L2 social identity. Affective and compensatory IPLS were significant moderate contributors to L2 social identity; however, metacognitive and cognitive interlanguage pragmatic learning strategies were weak albeit significant predictors of Iranian EFL learners’ social identity in English as an L2. The results of this study imply that L2 teachers can enhance social identity among the learners by fostering the knowledge of various forms of IPLS.

Corporate investment decisions are determined by a variety of factors, including various managerial measures, including overconfidence of managers, which are important determinants of corporate investment decisions. Most corporate executives prefer internal financing, but if internal resources are not sufficient to meet this need, they use external resources with the least degree of information asymmetry. The purpose of this study was to investigate the effect of managerial overconfidence on investment and the moderating effect of the internal financing method is on their relationship. The study consisted of listed companies in Tehran Stock Exchange during the period 2011 to 2016 and using a systematic elimination sampling method, 97 companies were selected. To investigate the research hypotheses, EVIEWS software and panel data regression method was used. The results of the research showed that managers’ overconfidence has a positive and significant effect on investment as well as underinvestment, but internal financing does not have a significant effect on the relationship between the overconfidence of managers and investment as well over-investment. But the effect of internal financing on the relationship between managers’ overconfidence and underinvestment was a significant positive. Finally, it became clear that internal financing had a significant negative impact on investment and over-investment.

The recent global financial crisis once again revealed the harmful effects of interest-based contracts in the conventional financial system. Islamic finance, as an alternative financial system, discourages interest rate and debt financing. This paper investigates the effects of two financial systems, namely the conventional and Islamic systems, on macroeconomic variables. To achieve this goal, a DSGE Model with two monetary rules, one for conventional financial system and the other for Islamic financial system, has been designed. Comparing the dynamics of the models, the results of this study show that, in response to different shocks, investment and output in Islamic finance are less volatile than those of conventional financial system. Moreover, the process of adjustment in Islamic system is faster than that of the conventional system. These results imply that promoting Islamic finance has a great role in macroeconomic stability and covering the effect of financial crises.

One of the most important aspects of investment is determining the “optimal investment portfolio”. To date, scientific research has been conducted to determine the optimal portfolio with “artificial intelligence” and “Fuzzy logic”. However, we determine the optimal portfolio based on Dynamic Stochastic General Equilibrium (DSGE) model. On the other hand, several factors affect returns, which is one of the most important issues in investment decision-makings, and various models have been developed to analyze the return of “capital” and “other assets”. In this regard, some of the most important models include linear and non-linear models, artificial neural network models, Fama–French model, Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model, and optimal stable model. All of these models are indicative of the use of quantitative methods and models in the investment industry. One of the causes of using these models is developing the financial economy. In fact, the development of financial economy has more increased with the concept of “portfolio optimization”. In fact, the portfolio optimization and diversification concept is the basis of developing and expanding classical finance and financial decision-making. Financial markets, especially the capital market, can have a great deal of relevance to other sectors of the economy. In the present study, we design and calibrate a new Keynesian DSGE model in relation to the optimal investment portfolio and effectiveness of shocks (e.g., productivity and foreign exchange earnings fluctuation) on macroeconomics variables.

Financial constraints are one of the influencing factors on investment decisions. Financial constraints put firms under pressure to forgo investment opportunities to finance their working capital needs. Moreover, some variables like working capital needs and liquidity of a firm are likely to affect the relationship between these two variables. Hence, this study seeks to examine the effect of short-term credit constraints on the investment of small and medium-sized enterprises (SMEs), firms with different characteristics in comparison with large-sized firms. In addition, this correlation is tested by considering the effect of mentioned moderating variables (working capital and liquidity). The sample of this study includes the firms listed in Tehran Stock Exchange from 2011 to 2018, which are considered as SMEs based on some criteria. Multivariate regression models and E-views software are used to test the research hypotheses. The results indicated that short-term credit constraints negatively affect corporate investment.  It means that constrained firms invest in fewer investment opportunities because of facing source shortages. Moreover, in companies requiring more working capital, the inverse effect of short-term credit constraints on corporate investment is stronger. Such firms suffer from financial problems and are not able to use their investment opportunities. Additionally, this hypothesis that companies with high liquidity can offset u effects of short-term financial constraints on fixed investment, is not confirmed

The article examines the multiaspected problem of ensuring economic security. An analysis of challenges and threats to Ukraine's economic security during 2010-2019. Strategic goals of economic security have been set. The study of the relationship between public debt, foreign direct investment, and economic growth allows assessing the characteristics of economic security. A system of structural equations is proposed to study the relationship between GDP, public debt, and foreign direct investment. The result of economic security, which can be achieved by achieving the goal, can be considered increased resilience to internal and external factors.

Scientific sources demonstrate different attitudes of researchers to cryptocurrencies because they treat them as a category of currency, virtual money, commodity, etc. Accordingly, the relation to the valuation and risk of cryptocurrency as an investment object is different. The purpose of the article is to identify cryptocurrency value formation factors and determine the risks of investing in cryptocurrency. Cryptocurrency is simultaneously considered a currency, an asset with uncertain income, and a specific product, the price of which is determined by the energy costs for mining new cryptocurrency blocks. Thus, the paper examines the risks of investing in cryptocurrency from several positions. First, the study identifies the factors of formation of the value and risk of cryptocurrency as ordinary money based on comparing cryptocurrency with traditional money. Unlike traditional money, cryptocurrency is not tied to the economic performance of a particular country; also, central banks do not control or regulate their mining. Instead, the cryptocurrency emissions depend on the computational capacity of the equipment used for their mining. As a financial asset, cryptocurrency can be a “financial bubble” because their value increasing often exceeds the cost of mining. On the other hand, given the emergence of cryptocurrency as a phenomenon of the information economy, the paper analyses the impact of specific technical features (cryptographic hashing algorithm, the complexity of creating new blocks, the technology of verification of mining operations, etc.) on the risk of investing in cryptocurrency assets.

One of the biggest shortcomings of urban spaces in most cities of the country is the lack of suitable sports spaces, which in addition to improving the health of the general public, especially the youth, creates a lively environment and can boost the development of the tourism industry. Many projects in the country, especially sports, are slow or stopped due to not evaluating the relevant risks, so the purpose of this study is to identify and prioritize investment risks in the country's sports projects. The present study is a positive research in terms of philosophical foundations and is applied in terms of orientation. The statistical population of the study includes experts in the field of sports tourism and the sampling method has been done judgmentally. To conduct the research, in the first stage, the risks of investing in sports projects were assessed through literature review. The number of these risks was 15, and after screening with a Binominal test, 6 factors were excluded. The remaining 9 factors were evaluated in terms of degree of impact with Dematel technique and 5 factors, i.e. market risks, economic risks, legal risks, financing risks and stakeholder conflict risks were selected as the most effective risks in terms of net effect index. Finally, these 5 risks were ranked by Aras decision technique and it was observed that the economic, market and financing risks, had the highest priority.

Background: Sports Investments is one of the most unique sports events, in the country dealing both with collectors and dealers. Aim : The purpose of this study was to compare the sports investment o Iran in 2016 and 1998. Therefore, we estimate the value of the sports investment sector and share of total investment, GDP, GDSP and compare with 1998 in Iran. Materials and Methods: In this study, national accounts were used. Most of the basic data fare available in a decentralized manner in the Statistics Center and the Program and Budget Organization of Iran. Due to achieving real changes in sports investment between 1998 and 2016, prices in 1998 was considered as the base year and were considered. Then using the price index of the desired years, the effects of inflation were eliminated and growth real was calculated. Results: The results indicate that investment in sport in 1998 was 360 billion Rials, which is 0.43% of total investment, 0.1% GDP, and 26.2% of GDSP. Also, investment in sport in 2016 was 15449 billion Rials, which is 0.46% of total investment, 0.11% GDP and, 73.38% of GDSP. Investment in sport in 2016 compared to 1998 had 2347% real growth. Conclusion : Although, investment in sport in 2016 compared to 1998 has grown, but it is very small compared to the total investments. Results also show the major share of the public sector and the low participation of the private sector.

This paper examines the role of development banks in the fixed investment formation and economic growth of the country with emphasis on the facilities granted by development banks. To do this, quarterly data of the country's development banks in the period 2006-2020 and experimental tests related to the causal relationship of variables and estimating the long-run relationship between variables were used with the Granger causality test and vector autoregression method (var). The results show that the development sector facilities and total banking network facilities (except for development sector facilities) have had positive and significant effects on fixed investment formation and other banking network payment facilities except the development sector and liquidity volume have had no significant effcets. Regarding the relationship between the liquidity and total paid facilities of the banking system, with the variable of fixed investment formation, the results show that all paid facilities have had positive and significant effects and liquidity has insignificant effects on fixed investment formation. According to the results of the long-run relationship, the development sector facilities and the volume of liquidity, in the long run, have had a significant relationship with fixed investment formaton in the Iranian economy. According to the results of the short-run relationship, development sector facilities have had positive and significant impacts on fixed investment formation and investment in the economy. Therefore, it can be concluded that the development sector facilities in both the short-term and long-term have been able to have a positive and significant effect on fixed investment formation

The article justified the feasibility of an investment project by analysing the performance indicators while taking into account risk and uncertainty of the use of information technologies. The impact of the above calculations of the investment project results is due to the fact that the evaluation of the investment performance depends on the projected cash flows. The purpose of the article is to assess the impact of risks on making investment decisions using information technologies in order to increase the financial security of enterprises. Methodological and practical aspects of risk modelling of the investment project were further developed, using the Monte Carlo method, which allows to construct a model by minimizing data, as well as to maximize the value of data used in the model. This model involves the use of probability theory and random number tables. The results show the distribution of probabilities of the successful project variable and the coefficient of variation of the performance indicator, allowing the investor to take uncertainty into account when making a decision.

The Covid-19 outbreak has had a severe effect on the world economy. The company's business operations and profitability are damaged during the covid 19 outbreak. This deterioration is not only threatening the company’s survival position but also destroy the investor’s investment return. Therefore, it is vital to establish an effective early prediction technical method to foresee a corporate distress by a Pro-technical measurement to enhance the corporate sustainability. This study applies Altman Z-Score Model to as a Pro-Technology technique to the financial distress prediction of Malaysia’s Government Linked Plantation Companies (GLC-P) over a period of 10 years starting from 2012 to 2021. The significant contribution of the study is that the Z-Score Model provides an advanced indication tool regarding the financial stability of the respective GLC-P companies. The findings indicate that Financial Distress Prediction was dependent via in-time application of leverage, liquidity, activity, and profitability to the Altman Z-Score Model. Profitability and leverage were found to be superior prediction tool to financial distress.

Nowadays, many companies cannot see the digital investment that plays a main role in the IR 4.0. Therefore, this study is investigating the study of investment as plays a critical role in an analytical activity to assess the benefits and costs of an investment and can be used as an investment justification. Traditional investment appraisal uses a financial approach where the benefits and costs are quantified in a certain amount of value for money and then compared in value. Moreover, this study is revealed the fruitful outcomes because revealed the investment valuation method with NPV (Net Present Value) and ROV (Real Option Valuation). ROV is an alternative to financial valuation. Seeding from the same philosophy as Financial Option, ROV has advantages in handling the flexibility, risk, and volatility that may occur from an investment. Thus, ROV is considered more able to appreciate an investment that has these characteristics. Investment appraisal with ROV is better able to appreciate investment than traditional financial methods, as shown by ROV's NPV results in the case of marketing with Loyalty points through email communication as a digital investment that are greater than ordinary NPV. This is because ROV can appreciate flexibility in investments that have choices of investment plans in the future

Improving the competitiveness of businesses through investment in industrial parks is one of the challenges that managers face for economic development. This study has been done with the aim of identifying, determining relationships and providing a structural model of investment to competitive advantage in industrial parks. The data have been analyzed in two parts, qualitative and quantitative. In the qualitative part, the variables of the model were extracted using the method of content analysis and coding and confirmed by the fuzzy Delphi method, and in the quantitative part, the hierarchical structure model was presented. The statistical population of the research is 25 experts who were selected by non-probability purposeful and snowball sampling and answered the pairwise comparison questionnaire. The findings of the qualitative section showed that the model has eight variables including "infrastructure investment", "motivational investment", "economical investment", "institutional investment", "environmental investment", "support investment", "Political investment" and "competitiveness". The findings of the quantitative section showed that the structural model has six levels, that "political investment" and "infrastructure investment" have the most influence in the model and are in the first priority. We conclude that in order to competitive advantage, managers should pay more attention to technical and informational infrastructure, as well as appropriate policies and providing regulations.

Objective: To identify the components affecting the behavior of investors and to develop a measurement model using a confirmatory factor analysis approach.Method: This is a correlational paper to identifythe dimensions and structures affecting investor behavior first using TOPSIS technique and then with first-order confirmatory factor analysis and second-order factor analysis. The statistical population includes people who have been active in the Tehran Stock Exchange for at least two years with asample of 327. The sampling method is convenience nonprobability sampling. The data was collected through a researcher-made questionnaire. The expert approval and Cronbach's alpha coefficient were used to assess the content validity. Findings: the current paperidentified seven factors as effective factors on investor behavior according to the theoretical literature and research background using TOPSIS technique. In the next stage, the research findings using the confirmatory factor analysis approach indicate that the two factors of investor financial literacy and investor personality traits have the most effective role in investor behavior. Also, the factors of higher expected returns, rules and regulations, security, profitability, position and location of investment are the next effective priorities on the behavior of investors.

Purpose- Rural entrepreneurship is a suitable solution for empowerment and capacity building in rural areas in order to change the current life pattern, create economic, social, environmental and institutional equality.Meanwhile, women play apivotalrole in promoting employment and improving the economic status of rural areas.Thus, a thorough conception of all aspects of entrepreneurship can be an effective factor in increasing the success rate.Design/methodology/approach- In this research, a descriptive survey and correlation method have been used.To analyze the data collected through field study, various descriptive and inferential statistical methods have been employed by SPSS15 software.Using the LISREL 8.5 software, the relationships between independent and dependent variables as well as the structural equation have been determined.Findings- The results indicate that three factors including structural, behavioral, contextual and the most important item of each factor including "paying attention to the social environment", "paying attention to development","Legislating the necessary laws and regulations" could be measured integrally in the structural equation model, respectively.It is also revealed how is possible to create innovatively the identifying and implementing stages of the investing process and creating women's businesses by becoming more detailed and determining the subset of each of the main structural, behavioral and contextual factors.Considering the structural equation model, the importance of these factors in the investing process and creating women's businesses in the southern villages of the country is highlighted.Original/value- Research and training activities can be one of the initiatives of governments and institutions related to the subject. Knowing the market context, the experiences of other regions of the country, obstacles to women's entrepreneurship, and the opportunities for women's entrepreneurship in different rural areas of the south of the country provide suitable opportunities for women's entrepreneurial activities. Furthermore, training programs should be based on women's condition in the village in such a way that the level of education, type of profession, geographical region are of the effective factors in the design and implementation of training programs. Providing training packages and the possibility of distance training is also useful for all entrepreneurs in the southern parts of the country.