فصلنامه پژوهش های مدیریت در ایران
سال هفدهم شماره 2 (پیاپی 80، تابستان 1392)

In this study، we developed a Joint Replenishment Problem (JRP) model; In addition، JRP was introduced through capacitated vehicle to send the parts. The model was developed as an Integer-non linear model. Cost function consists of the major ordering cost، the minor ordering cost and the holding cost. Previous studies had not considered transaction cost; therefore، we considered transaction cost، which depends on the number of different parts in the order. Demand for parts was considered as constant and the model was solved by using a genetic algorithm. For calculating variable، we developed the present algorithm in the literature. We solved the model for two conditions، with dispatch volume restriction and without dispatch volume restriction. The results showed that the dispatch volume increases both the cycle time and the total cost. The model was solved for one of the major manufacturers of SAPCO. We considered the problem with 12 strategic parts of this company. The model was investigated through the real data gathered from the SAPCO Company. Finally، for model validation، the results were compared with the traditional ordering system of SAPCO، in which the parts are ordered separately. It was shown that the proposed system has better performance than the traditional ordering system. Validation of Model was performed by the numerical example that has been solved in the literature. Keywords: Joint replenishment، Automotive parts، Genetic algorithm، Inventory.

This research intends to identify the relationship between Individual and Organizational Values with Organizational Commitment in Al-Mahdi Aluminum Company in Hormzgan Proneinc. The research universe included 1000 employee and by using sampling method in a limited universe (Cochran''s formula) a sample of 165 people was selected، Schwartz questionnaire was used to measure individual values، a researcher made questionnaire used to assess organizational values، and Balfour and Wechsler questionnaire was used to measure organizational commitment. Reliability coefficients of these questionnaires were 90%، 81% and 73% respectively. Based on correlation، research data were analyzed with SPSS software and research hypotheses were tested using techniques of inferential statistics. The results confirmed all hypothesis and showed that there is a relatively strong correlation between «individual values» with «continuous commitment». Also a significant and positive correlation between organizational values such as identification commitment and exchange commitment was observed.

Concern about the environment has led to a new segment of consumers called green consumers. Because not all the consumers are equally green، using target marketing for persuading them to buy green product is essential. The first step in target marketing strategy is to segment the market and then develop profiles of the resulting market segments. This study aims to identify distinct green market segments based on demographic، psychographic and behavioral variables and also investigate the relationship between each variable and green consumer behavior. This study uses self-organizing maps (SOM) to segment and then develop profiles of Iranian green consumers. Based on the results four market segments have identified and were named intense greens، potential greens، egoist browns and intense browns. The results of this study also indicate that demographic variables including gender، age and income and psychographic and behavioral variables including personal values، religiosity، environmental attitude and knowledge have significant role in predicting green consumers’ behavior.

In today competitive environment, increasing supply chain efficiency has considerable importance in success of firms. Various factors limit this increase, which are referred as supply chain complexities. Identification of these complexities and dealing with them is essential. This paper attempts to introduce and apply an efficient and effective method for dealing with complexity of supply chain. This method is based on systemic principles of theory of constraints. This research shows how a manager can use logical tools of theory of constraints thinking processes (TOC TP) to identify and deal with root causes of supply chain complexity. This approach was implemented partially in a paper manufacturing firm in Iran. Data were gathered by questionnaires and interviews and analyzed interactively with supply chain managers and experts of the firm in order to get valid results. In this case, three first steps of TOC TP i.e. drawing intermediate objective (IO) map, current reality tree (CRT) and conflict remove diagram (CRD) are performed. The results show that these logical diagrams are useful tools to identify supply chain complexity drivers and determine root causes of them.

Trying for improvement performance as an essential principle، since of preliminary management creation، had been noticeable and more extensive every day. Today، it has prospect behaviors beyond the formal duties that are contextual performance، extra-role behaviors، Spontaneous behaviors or organizational citizenship behaviors. The other wise، the results of studies indicate that strain hinders of this behaviors. Therefore it''s necessary schematization of plans and solutions for decreasing strain and then increasing OCBs. One of the most important of the activities is recognition of the effective variables on the OCBs for its preservation، increasing and reinforcement. This study with meta-analysis approach has recognized and studied the moderator variables that have been effective on this relationship. Statistical society is the hole of the studies that have investigating the relationship between strains and OCBs، total studies are 169 with 893 effect sizes، The results of studies revealed this relationship is moderated by five moderators of the characteristics of the study sample: the kind of job and organization (governmental vs. private)، organizational position (managerial vs. nonmanagerial)، the kind of employee (full time or no full time)، and the number of statistic society.

In recent decades، information technology، especially with all aspects of our life and professional career has been stirred. Because IT applications in different fields and the rapid growth of computers in organizations، to review the level of acceptance and rejection of information technology in organizations have special significance. Hand with the growth of research in various fields related to the IT acceptance and dealing with a scattering of information and information explosion، control over all aspects of this area is largely impossible. Therefore، the combination of research studies conducted in this matter to extract the systematic and scientific results for researchers is very important. In this study using meta-analysis methods with comprehensive meta-analysis (CMA) software، for examining a large number of theses، articles and researches done in connection with the adoption of information technology in Iran، 19 studies with 21 hypotheses and variables have been selected. The results of meta-analysis shows that employee empowerment، extent of use of technology، perceived ease of use and perceived usefulness of IT had the most influence on the acceptance of information technology in the Iranians organizations.

During recent decades، Energy as one of the most important factors of production and also as one of the most important end products، a special place in the country''s economic development and growth development. Hence، the country authorities should try to predict anything more precise energy consumption in the proper planning and guidance consumption، to control the way they desired energy demand and supply parameters. The purpose of this paper is Evaluation Hybrid model of artificial neural networks and genetic algorithms in the forecast consumption energy of Iran. Therefore in this study، data from the annual energy consumption as the output forecasting model range and was used as input variables، data of the annual total population، GDP، imports and exports. The end results were assessed with of different models (RSE)، (ME) and (RMSE). Evaluation results showed that the hybrid model of neural networks and genetic algorithm (ANN-GA)، compared to other models with the highest accuracy in predicting consumption energy of Iran.