Increasing attention to environmental problems and social responsibility lead to appear reverse logistic (RL) issues in designing supply chain which, in most recently, has received considerable attention from both academicians and practitioners. In this paper, a multi-product reverse logistic network design model is developed; then a hybrid method including Chance-constrained programming, Genetic algorithm and Monte Carlo simulation, are proposed to solve the developed model. The proposed model is solved for risk-averse and risk-seeking decision makers by conditional value at risk, sum of the excepted value and standard deviation, respectively. Comparisons of the results show that minimizing the costs had no direct relation with the kind of decision makers; however, in the most cases, risk-seeking decision maker gained more return products than risk-averse ones. It is clear that by increasing returned products to the chain, production costs of new products and material will be reduced and also by this act, environmental benefits will be created.

In a market economy, entrepreneurship requires large-scale innovations to maintain competitiveness and high rates of economic growth, and large investments are needed to implement innovations. However, in the process of their activities, investors face increased investment risk and therefore need reliable methods of investment evaluation and investment modeling of innovations in industrial enterprises. In this regard, the purpose of this study is to develop a conceptual model for assessing the investment attractiveness of innovative projects. The article builds a graphical model of investment in an innovative product at different stages of its life cycle. A conceptual structural and mathematical model for assessing the investment attractiveness of innovative projects of industrial enterprises has been developed, which reflected the stages of risk management, phases of the life cycle of the innovation project and the stages of the innovation process. The main idea of the proposed model is to manage investment in innovation based on the impact on the level of specific innovation risks.

This paper was retracted based on the authors' request due to errors in the computations.

This research is conducted to investigate the impact of income diversification on bank liquidity creation and the financial performance of Vietnamese commercial banks from 2007 to 2017. Data were collected from 21 Vietnamese commercial banks. Panel OLS with fixed effects and GMM estimations were employed to process data. The results show that diversification had a negative impact on both bank liquidity creation and bank profitability, and thus support the view that Vietnamese commercial banks should remain focusing on their traditional lines of business rather than diversifying towards nontraditional activities since this may lead to both a lower level of liquidity creation and profitability. The findings of this study could draw broad inferences for researchers, policy makers, and bank managers towards more focusing strategies to ensure the health of the banking system.

In this paper, we attempt to answer the question of whether or not bank capital affects profitability and risk. The paper forms an unbalanced panel with 354 observations using both data of 35 banks over the period 2007-2018. Two-step GMM is used to estimate the impacts of bank capital on profitability and risk in order to eliminate endogeneity and serial correlation issues. As a proxy of bank capital, the bank equity ratio, and equity level are used. Return on assets (ROA), return on equities (ROE), and net interest margin (NIM) are used to measure bank profitability, whereas nonperforming loan ratio and loan loss reserve ratio are used to measure bank risk. Bank capital displays significant impacts on profitability, which is measured by ROA and ROE, whereas capital shows no impact on bank NIM. When the loan loss reserve ratio is considered as proxy of bank risk, bank capital does not affect bank risk. The equity ratio, the proxy of bank capital, displays significant negative impacts on risk, whereas the equity level, the other proxy of bank capital, shows positive impacts on bank risk.

This study aims to investigate the factors that influence consumer satisfaction with e-grocery shopping. Moreover, it also delves into factors that motivate shoppers to buy groceries from online retailers rather than conventional stores. A primary survey was administered to collect data. Initially, 500 questionnaires were circulated to respondents. People who have ordered groceries from online sites were the expected respondents. In this study, convenience sampling was used, and data were analyzed using structural equation modeling (SEM). The findings affirmed the relationship between consumer satisfaction and perceived convenience, risk factors, perceived product quality, and time value. However, perceived value and value for the time have a little significant effect on consumer satisfaction. There have been relatively few academic studies that look at the variables that influence customer satisfaction when shopping for groceries online. Most of the studies look at the variables that influence consumer satisfaction in the life insurance and financial services industries. By analyzing the data from Delhi and the Nation Capital Region (NCR) of Delhi, this research aims to bridge this gap available in the literature.

Measuring the effects of various factors influencing on risk of return in banking system plays essential role on making managerial decisions. This paper investigates the effects of seven factors including equities, leverage, dividend, size, growth domestic products, bank concentration and market return on risk of return in selected banks listed on Tehran Stock Exchange. The study selects the necessary data through financial statements announced on exchange as well as macro-economic figures reported by central bank of Iran to examine the hypotheses of the survey. Using some regression technique, the study has determined that only bank size and growth domestic product influence significantly on risk of return on Tehran Stock Exchange.

Nowadays, the electronic insurance (EI) is one the electronic services, which is used in most countries, and that is one effective factor in developing the exporting products and services. On the other hand, the incurrence industry and very especially EI represent their importance both domestically and internationally. One of the ways for transferring the exporting risks is to transfer the risks to the insurer. This paper examines the characteristics of EI and the effects of decreasing the exporting risk charges. The proposed study designs a questionnaire in the form of Likert scale, the validity of the questionnaire is validated by some the experts & apos; viewpoints and the Cronbach & apos; alpha is measure as 0.794. The results of applying Freedman test have disclosed that facilitating export activities was the most important factor followed by access to target export market information.

This paper determines and ranks financial risk factors in Iranian corporations, using analytical hierarchy process (AHP). The present research includes one main question and four sub- questions. Its universe population includes managers, production and financial personnel of great corporations activating in Tehran Stock Exchange, who were selected to explain importance and weight of economic risks indices. The source of great corporations recognition is the Companies Registration Organization in Tehran Province, and according to this, there are 120 corporations. The results have indicated that financing risk maintains the highest priority followed by credit risk, liquidity risk, inflation risk and exchange risk. In terms of different risks associated with financing risk, risk of profit per share has been the number one priority followed by the risk of divisional profit per share, the risk of recessionary or boom and the risk of increasing partial pay profit rate. In terms of credit risk, the risk of loan has been number one priority followed by the risk of inability of loan payment and interest payment. Liquidity risk is another risk factor where demand has been the most important factor followed by rules and regulations and inflation risk. In terms of inflation, producers price risk has been the most important factor followed by consumer price risk, gross domestic product and producers price risk. Finally, in terms of different factors influencing exchange risk, export related issues are considered as the most important factors.

The Project Portfolio Selection is a complex process that involves many factors and considerations since the project is proposed until the project portfolio is finally selected. Project Portfolio Management is the iterative process of assessment, selection and implementation of projects, and the most important part of that is to select projects for portfolio where the or-ganization is required to identify and prioritize projects with the most objective alignment to its objectives. Since the selection of a suitable projects is very important, it is necessary to develop mathematical models to lead the organization towards the final goal. To achieve this goal, these models should reflect the organization's position, goals and priorities as much as possible. In this paper, we propose a multi - objective model for selecting the project portfolio that maximizes efficiency, quality while minimizes the risk involved in project execution.

During the past few years, there have been several studies for portfolio management. One of the primary concerns on any stock market is to detect the risk associated with various assets. One of the recognized methods in order to measure, to forecast, and to manage the existing risk is associated with Value at Risk (VaR), which draws much attention by financial institutions in recent years. VaR is a method for recognizing and evaluating of risk, which uses the standard statistical techniques and the method has been used in other fields, increasingly. The present study has measured the value at risk of 26 companies from chemical industry in Tehran Stock Exchange over the period 2009-2011 using the simulation technique of Monte Carlo with 95% confidence level. The used variability in the present study has been the daily return resulted from the stock daily price change. Moreover, the weight of optimal investment has been determined using a hybrid model called Markowitz and Winker model in each determined stocks. The results showed that the maximum loss would not exceed from 1259432 Rials at 95% confidence level in future day.