Outsourcing is known as using a supplier outside the organization in a way that this supplier provides the same service or goods provided normally inside the organization. Outsourcing likewise any other strategy has its own effects on the organization. This paper tries to evaluate the impact of a successful outsourcing on organization’s activities in selected universities. In order to reach this purpose, after theoretical studies, first, obtained indexes by the expertise are evaluated and then by the confirmatory factor analysis with the help of Lisrel software, the claimed indexes are confirmed. The results of structural equation show that the questioned relevance is directly available and in some other words the implementation of a successful outsourcing will help improving organization’s activities in the statistical.

The objective of the present study is to determine the start times and ordering plans for two-period projects in project-oriented organizations. The following assumptions are made: orders can be placed in either of a project’s two consecutive periods; and the same raw materials are used, which are ordered at the start of the periods according to their interdependent demands. The main innovation of the present research is to develop a model that is mainly based on the two-period newsvendor problem, but assumes that demand is interdependent, i.e. it is actually a combination of inventory and project management. After presenting the model, numerical meth-ods are used to approximate the order quantities for each period. Near-optimal solutions of a numerical example, in a case study on molding industry, are obtained using a genetic algorithm. Results show that the proposed model with interdependent demand provides a better solution than independent demand. The model is applicable to large-scale industrial and construction pro-jects where the majority of raw materials have of the same nature.

This article discusses the value of sustainable oil maintenance by using submicron high-tech offline filtration based on oil condition monitoring to reduce wear particles and improve system reliability. These activities incorporate broader goals of establishing a proactive maintenance approach, defined as continuous monitoring and controlling of the root causes of machine failure. Among these causes, contamination is the industry's most severe, popular, and most recognized failure cause. In order to ensure all necessary proactive maintenance activities, this paper uses practical analysis for oil contamination monitoring based on ISO 4405. The author applied a 0.1-micron high-tech offline filtration for lubrication systems of ball mills in the Sungun copper mine as an oil maintenance activity to control the system lubrication contamination as a root cause of failures.

Weevils are a type of insect with elongated snouts coming from superfamily of Curculionoidea with approximately 97,000 species. Most of them consider pest and cause environmental damages but some kinds like wheat weevil, maize weevil, and boll weevils are famous to cause huge damage on crops, especially cereal grains. This research proposes a novel swarm-based metaheuristics algorithm called Weevil Damage Optimization Algorithm (WDOA) which mimics weevils’ fly power, snout power, and damage power on crops or agricultural products. The proposed algorithm is tested with 12 benchmark unimodal and multimodal artificial landscapes or optimization test functions. Additionally, the proposed WDOA is employed in five engineering problems to check its robustness for problem solving. Problems are Travelling Salesman Problem (TSP), n-Queens problem, portfolio problem, Optimal Inventory Control (OIC) problem, and Bin Packing Problem (BPP). All tests’ functions are compared with widely used benchmark algorithms of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Harmony Search (HS) algorithm, Imperialist Competitive Algorithm (ICA), Firefly Algorithm (FA), and Differential Evolution (DE) algorithm. Also, all problems are tested with DE, FA, and HS algorithms. The Proposed algorithm showed robustness and speed on all functions and problems by providing precision alongside with reasonable speed.

Sentiment is a powerful psychological force that can significantly affect employee behavior and performance. However, workplace emotions are still an issue to be studied, especially in the field of sales management in project based organizations. The purpose of this study is to investigate the effect of emotional intelligence and flexibility on the tendency of employees to leave the organization. The method of this research is descriptive correlational and in a survey method and it is a practical purpose. The statistical population of this study includes all 108 employees of the representatives of selected insurance firms in city of Zanjan, Iran. Using Cochran formula, 84 people were selected as the statistical sample. The results have indicated that while there was a positive and meaningful relationship between emotional intelligence and flexibility (r = 0.534, Sig. = 0.000), there were negative and meaningful relationships between flexibility and emotion-al intelligence on one side and intend to leave an organization on the other side.

Providing insurance contract with “deductible” is beneficial for both insurer and insured. In this paper, we provide a utility modeling approach to handle insurance pricing and evaluate the tradeoff between discount benefit and deductible level. We analyze four different pricing problems of no insurance, full insurance coverage, insurance with β% deductible and insurance with D-dollar deductible based on a given utility function. A numerical example is also used to illustrate some interesting results.

Cash flow and leverage are two main components of any business firms. A good level of cash flow and leverage shows a desirable performance for business organizations. This paper presents an empirical investigation to study the relationship between combined leverage and cash flow in terms of board of director’s ownership and corporate governance structures. The study selects 86 randomly selected firms listed on Tehran Stock Exchange over the period 2009-2013. Using some statistical tests, the survey has indicated that there was a meaningful relationship between leverage and cash flow for firms with different corporate governance structures. The study has also determined that there was a meaningful relationship between leverage and cash flow for firms with different board of director’s ownerships.

The present study is aimed at investigating the relationship between financial distress and investment efficiency of companies listed in the Tehran Stock Exchange (with emphasis on the role of ownership type). To calculate investment efficiency, the Richardson’s model (2006) [Richardson, S. (2006). Over-investment of free cash flow. Review of Accounting Studies, 11(2-3), 159-189.] was employed. The aim of the present study is applied and its method is correlational- ex post facto. Using the exclusion sampling method and by applying the conditions of selecting the sample, 94 companies were selected from 2008 to 2013. To test the research hypotheses, multiple regression was used. Findings of the research indicate that there was a correlation between financial distress and investment efficiency in companies listed in the Tehran Stock Exchange, and institutional ownership had positive effects on the relationship between financial distress and investment efficiency of companies listed in the Tehran Stock Exchange. Furthermore, management ownership had no effect on the relationship between financial distress and investment efficiency in companies listed in the Tehran Stock Exchange.

One of the most important factors of survival of financial institutes and banks in the current competitive markets is to create balance and equality among resources and consumptions as well as to keep the health of money circulation in these institutes. According to the experiences obtained from recent financial crises in the world. The lack of appropriate management of the demands of banks and financial institutions can be considered as one of the main factors of occurrence of this crisis. The objective of the present study is to identify and classify customers according to credit risk and decisions of predictive models. The present research is a survey research employing field study in terms of the data collection method. The method of collecting theoretical framework was library research and the data were collected by two ways of data of a questionnaire and real customers’ financial data. To analyze the data of the questionnaire, analytical hierarchy process and to analyze real customers’ financial data, the TOPSIS method were employed. The population of the study included files of real customers in one of the branches of RefahKargaran Bank in city of Tabriz, Iran. From among 800 files, 140 files were completed and using Morgan’s table, 103 files were investigated. The final model was presented and with 95% of probability, if the next customer’s data is entered the model, it will capable of identifying accurately the degree of customer risk.

Electron impact (EI) mass spectrometer apparatus has been used to monitor the relative intensities of ion clusters of the type Xn(H2O)n where X is 3-arylpyrimido[4,5-c]pyridazine-5,7(6H,8H)-diones (1a-d), 3-aryl-7-thioxo-7,8-dihydro-6H-pyrimido[4,5-c]pyridazine-5-ones (2a-d) and n = 1, 2. The m/z of selected fragments obtained from 1a-d and 2a-d show a clustered water molecule due to strong intermolecular H-bonding between fragment and clustered water molecule.