Information technology plays an important role in increasing organizational cooperation both inside an organization and among different firms. In fact, may organizations have shared information though the recent advances of information technology and they have been able to increase the performance of their organizations, significantly. In this paper, we present an empirical study to investigate the relationship between e-business and intra and extra organizational cooperation. The results indicate that e-business directly increase intra organizational performance, indirectly increase organizational cooperation. Extra organizational performance directly increase organization performance, inside cooperation also indirectly influence inside cooperation through extra organization cooperation.

Today, countries compete to gain political, economic, social and cultural advantages. In addition, cities are trying to demonstrate their predominance on local and regional levels and achieve development by using managerial science. Meetings, incentives, conventions and exhibitions tourism (MICE) hosting as a significant element of urban tourism is one of the effective methods to obtain urban development around the world. However, no specialized planning and independent investments in regard to these activities have been organized in Iran. Aiming to identify suitable areas in the northern part of Iran, the present research intends to recognize the necessary physical and location related (P.L) indexes to perform the specialized activities of MICE tourism in this region. So at first, indispensable indicators to accept special role of MICE tourism are identified and then using GIS and fuzzy method, adapted areas are assigned. The result map shows that a ribbon-like area near the Caspian Sea with two wide lands at central and western parts is a proper choice to host MICE activities in the region from the viewpoint of P.L indexes.

There is no doubt that traditional accounting does not provide actual value of assets since they only measure tangible assets. Intellectual capital provides a new concept for measuring actual value of the assets and we can calculate future values of the firm. In this paper, we first calculate intellectual capital based on the ratio of market value/book value for three years period. Then we investigate the relationship between intellectual capital and growth rate of intellectual capital as well as financial performance of some publicly traded petrochemical and pharmaceutical firms. The results of our survey indicate that there is a positive relationship between intellectual capital and equity growth with EVA and return of assets. However, there is no meaningful relationship between intellectual assets with net earnings.

This paper tackles the single machine scheduling problem with dependent setup time and precedence constraints. The primary objective of this paper is minimization of total weighted tardiness. Since the complexity of the resulted problem is NP-hard we use metaheuristics method to solve the resulted model. The proposed model of this paper uses genetic algorithm to solve the problem in reasonable amount of time. Because of high sensitivity of GA to its initial values of parameters, a Taguchi approach is presented to calibrate its parameters. Computational experiments validate the effectiveness and capability of proposed method.

Uncertainty plays an important role on many engineering problems and there is a growing interest in having reliable solutions especially for problems with sensitive parameters. The paper presents a robust optimization (RO) model for multi-objective operation of capacitated P-hub location problems (MCpHLP) under uncertainty set. There are, at least, two parameters in any P-hub problems, which are under uncertainty. The first one is associated with demand and the second one is the amount of time required to process commodities. We present a scenario based robust optimization technique, where these two items are considered under various scenario and a RO is implemented to find reliable solutions. The implementation of the proposed RO model is demonstrated for an example using weighting method.

Railroad industry has received tremendous challenges in the world in terms of handling cost and efficiency. For many years, the railroad business lost money in many countries such as Japan until many governments decided to privatize the industry in an attempt to reduce the cost components and to increase the efficiency of various units, significantly. In this paper, we propose a new goal programming technique to handle two objectives of operating cost and the number of passengers travel by train. We consider different types of trains for public transportation of passengers in order to make the proposed model of this paper more realistic. The implementation of the proposed model is demonstrated using some numerical examples to show the effectiveness of the method.

Railroad transportation planning is strategically a long term and an important decision making problem especially in the area of travelling passengers. There have been literally various methods to use in order to provide optimum traveling schedule such as direct or indirect methods. Direct solutions involve the implementation of mixed integer programming, which is often hard to solve for real-world applications. The proposed model of this paper uses a column generation method to decompose a large-scale railroad passenger-scheduling problem into some smaller scale problems, which are easier to solve. The primary concern with the resulted problem is that final solutions of the method need to be integer and this is in contrast with convexity assumption of column generation techniques. We propose heuristic method to handle this problem and apply the proposed model for some examples. The preliminary results indicate that the proposed model of this paper could provide optimal solutions for small-scale problems and it can reach some reasonable solutions for larger problems when direct implementation fails to do in reasonable amount of time.

In this research, we conduct a reverse study to design a compatible model of share issue privatization for Tehran stock exchange (TSE) development. Privatization and stock market development are known as two representatives of economic growth. Governments use these two economic means to achieve their development goals. In this study, the impact of share issue privatization on stock market development is studied and an optimal model of share issue privatization for Tehran stock exchange (TSE) development is introduced. To study the effect of share issue privatization on key market development variables panel data of privatization index(IPIX), transaction volume, turnover velocity ratio and closing price of each TSE listed company are entered in co integration and error correction models (ECM) during March 2008-June 2011. The result of statistical studies shows a significant relation between privatization index (IPIX) growth and the growth of each of Tehran stock exchange development proxies. Then to design a compatible model of share issue privatization for Tehran stock market development, Delphi survey following Schmitt approach during 4 phases is implemented.

In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.

Clustering plays an important role on developing industries, since business units can take advantage of many existing industries for trouble shooting or sharing their experiences to increase efficiency. One of the primary concerns for developing clustering is to identify and remove important barriers. In this paper, we gather experts' feedbacks on forming clustering in Iran's industries and, using analytical network process, we prioritize the important factors and provide some necessary guidelines to develop clustering. The results of this paper indicate that the existence of a supplier network is the most important factor, followed by the existence of competition between operational units, existence of high-risk investors, existence of suitable infrastructures. There are also other less important criteria including the existence of flexibility, suitable technology and competition, governmental regularities, social background, trust, etc.