We study a location-inventory problem in a three level supply chain network under uncertainty, which leads to risk. The (r,Q) inventory control policy is applied for this problem. Besides, uncertainty exists in different parameters such as procurement, transportation costs, supply, demand and the capacity of different facilities (due to disaster, man-made events and etc). We present a robust optimization model, which concurrently specifies: locations of distribution centers to be opened, inventory control parameters (r,Q), and allocation of supply chain components. The model is formulated as a multi-objective mixed-integer nonlinear programming in order to minimize the expected total cost of such a supply chain network comprising location, procurement, transportation, holding, ordering, and shortage costs. Moreover, we develop an effective solution approach on the basis of multi-objective particle swarm optimization for solving the proposed model. Eventually, computational results of different examples of the problem and sensitivity analysis are exhibited to show the model and algorithm & apos; s feasibility and efficiency.

The organizational employees take some actions called influential tactics to achieve their goals. Influential tactics discuss the ways to influence power bases and help employees understand how to utilize these bases. This research aims at analyzing the effect of managers’ influential tactics on employees. The influential tactics used in the research include friendship, reasoning (reasonable encouragement), coalition, pressure (courage), resorting to superiors and interaction. The research has been accomplished through quantitative descriptive method and the sample size is selected from the private and state banks of an Iranian city named Ilam. The statistical sample consists of 265 randomly chosen people determined using Morgan Table. The collected research data has been analyzed using Spearman correlation test. The research results showed that the effect of managers’ influential tactics was not the same on male and female employees.

Improving livelihood and increasing in welfare and life quality of people always have been some of the most important concerns among politicians in each country. Therefore, addressing economy and trying to reach maximum growth play essential role on having sustainable growth. One of the determinant factors in the economic growth is attraction of direct foreign investments, successfully. Direct foreign investment not only leads to capital and modern technology in absorbent country but also it causes increasing in production capacities particularly in export products. Therefore, it helps host country in context of communicating with international economy through development of export markets and research and development (R & D). In this paper, we present an empirical study to find important factors influencing foreign direct investment based on factor analysis. The study designs and distributes a questionnaire consist of 30 questions among some experts. The proposed study uses Skewness analysis to reduce the factors into 22 items and reports 5 important factors including Economic, Feasibility, Infrastructure, Incentive and Resource.

During the past few years, there have been growing interests in developing tourism industry in developing tourism economy. This paper presents an empirical investigation to study the effects of different factors including brand awareness, quality perception, brand associate and brand loyalty on developing tourism economy. The proposed study was accomplished in city of Karaj located in province of Alborz, Iran. The study designed a questionnaire consist of 27 questions designed in Likert scale and distributed it among 400 randomly selected people who visited this city during the year of 2012. Using Spearman correlation, they study confirmed that there were some positive relationship between brand awareness and tourism economy (r=0.434, Sig.=0.02), a positive relationship between quality perception and tourism economy (r=0.198, Sig.=0.008), a positive relationship between brand associate and tourism economy (r=0.261, Sig.=0.000) and finally there was a positive and relationship between brand loyalty and tourism economy (r = 0.302, Sig. = 0.05). In addition, the implementation of stepwise regression model has indicated that brand awareness played essential role on tourism economy followed by brand loyalty and quality perception.

Nowadays, selection of an optimal project has become a challenging task for managers and decision makers. Project selection for a decision maker can be viewed as a complicated multi-criteria decision making (MCDM) problem, which requires consideration of a number of conflicting, tangible and intangible selection criteria. Moreover, decision makers tend to use linguistic terms for expressing their assessments because of their different backgrounds and preferences, some of which may be uncertain and incomplete. Hence, this paper focuses on developing a hybrid fuzzy MCDM approach by combining AHP and VIKOR for solving the project selection problem. Finally, A numerical example is proposed to illustrate an application of the proposed method.

A model is a simple and straightforward performance of structure and behavior of the system under study expressed as mathematical relations. In fact, with a model, knowledge and information on modeled phenomenon are prepared and the cost and risk of applying actual phenomenon are eliminated. Petri nets, on the other hand, are used to determine the important information on structure and behavior in modeled system and formal models are mainly state dependent requirements. These requirements are significantly indefinite and can be expressed by language variables. If XML labels can express the formal models (Fuzzy Petri net) as the most valid data format, then we will have relationships with other data format. In this study, characteristics of a Fuzzy Colored Petri Net are expressed by fuzzy developed Markup Language labels. Therefore, in addition to fuzzy XML labels, the concept “color” will be used for them. Application and advantages of suggested method will be determined by a case study in bank facility system. The results of the evaluation indicate the advantages of the suggested grammar for supporting elements available in fuzzy formal models.

Although supply chains disruptions rarely occur, their negative effects are prolonged and severe. In this paper, we propose a reliable capacitated supply chain network design (RSCND) model by considering random disruptions in both distribution centers and suppliers. The proposed model determines the optimal location of distribution centers (DC) with the highest reliability, the best plan to assign customers to opened DCs and assigns opened DCs to suitable suppliers with lowest transportation cost. In this study, random disruption occurs at the location, capacity of the distribution centers (DCs) and suppliers. It is assumed that a disrupted DC and a disrupted supplier may lose a portion of their capacities, and the rest of the disrupted DC & apos; s demand can be supplied by other DCs. In addition, we consider shortage in DCs, which can occur in either normal or disruption conditions and DCs, can support each other in such circumstances. Unlike other studies in the extent of literature, we use new approach to model the reliability of DCs; we consider a range of reliability instead of using binary variables. In order to solve the proposed model for real-world instances, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied. Preliminary results of testing the proposed model of this paper on several problems with different sizes provide seem to be promising.

This paper presents an empirical investigation to the study the effects of various factors such as free cash flow, earnings, Tobin’s Q on predicting stock performance on Tehran Stock Exchange (TSE) over the period 2005-2012. The study is performed on data from different industries including basic metals, cements, chemical, auto industry, etc. The proposed model gathers the necessary data from TSE and using various regression models, the study has determined that there was a meaningful relationship between cash value added, Earnings and Tobin’s Q when the level of significance was five percent but there was not any meaningful relationship between stock earnings and free cash flow.

Export is one of the most important indicators of a growing economy and it is the primary source of reaching sustainable growth on the market. This paper presents an empirical study to determine important factors influencing electronic banking in export development of Iranian organizations. The proposed study designs a questionnaire and distributes it among some regular customers who do internet banking with Parsian bank in city of Tehran, Iran. Cronbach alpha is calculated as 0.82, which is well above the minimum desirable limit of 0.70. In addition, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Approx. Chi-Square are 0.71 and 1955 with Sig. = 0.000, respectively. Using principal component analysis, the study has detected six factors including customer’s information, building trust, secure internet access, having good internet infrastructure and internet users.

This paper presents an empirical investigation for the implementation of enterprise resource planning among 58 production units in province of Ilam, Iran. The proposed study of this paper considers the readiness in terms of six factors including human resources, financial resources, infrastructures, quality control, and information systems and communication technology. Using structural equation modeling, the study examines six hypotheses and the implementation is accomplished on LISREL software package. Cronbach alpha has been calculated as 0.91, which is well above the minimum desirable level. The results of the survey have indicated that all six mentioned factors influence positively on ERP implementation and for a successful implementation of ERP, it is suggested to consider these factors, seriously.