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1 Development and Improving Supply Chain Inventory Control Model for Perishable Items using Just-in-time Logistic I. Nakhae'i Kamal Abadi S. A. Ghasimi R. Ghodsi In this paper, three new three-level Inventory Control models for perishable items with adoption of just-in-time logistics philosophy to obtain the optimal total cost of the whole supply chain including costs of production, freight, maintenance, non-on-time delivery (delayed or early delivery), and perishable goods, are presented. The first model has been developed in a way that in addition to minimizing the costs also gives rise to situations in which all goods will be delivered to the customers within the consumption period and there will be no decaying(this Model is designed for the ideal systems). The second model has been developed so that not only does it minimize the costs, it also adds the costs of the decayed goods (if some goods are not delivered to the customers within their consumption period, since all the goods have expiry date, thus they decay) to the target function and minimizes them as well (This model has been designed for the systems working in the real contexts). The third model has been developed to improve the second model and operates in a way that in addition to minimizing the costs, prevents the goods from decaying in some time before approaching the expiry date of the goods which have not been sold out, this model causes these goods to be sold with special discount so that the costs are minimized, and adds the costs of the discounted amount to the target function and minimizes them as well. All the three proposed models are new. In order to confirm the validation of the models, the methods of solving, the genetic algorithm and CPLEX 10.2 solvent have been employed. The obtained results did verify their validity. Keyword: supply chain management; just-in-time logistic; perishable goods; genetic algorithm. 131
2 A New Method to Estimate the Rate of Physical Development in Projects H. soltanpanah H. farughi H. A. sadeghi Determining the progress of a project is an important phase of "planning", "control" & project management for all stakeholders including employers and contractors. To determine the percentage of actual project progress, in most cases cost and time are the two factors used; while in reality, there are many other factors affecting this issue. The goal of this article, is to estimate project progress with regard to the influential criteria ( i.e. Cost criteria, human resources, other resources, critical degree, state of procurement and construction activities). Also a macro environment that can link Excel to the MS software Project is introduced by the use of some examples. Finally, a numerical example has been considered to illustrate the model. Key words: project control, Project process, earned value management Journal of Industrial Management Faculty of Humanities Islamic 132
3 The Assessments of Gas Distribution Projects Management by PMBOK Method: A Case Study Zanjan Gas Company A. Farahmandian M. Mosakhani A. Mansoori Organizations based on their activities can be divided into different groups including project oriented, product oriented, knowledge based and economic orientated. Each of this organizations use specific tools and standards to accomplish excellence. Project oriented organizations such as oil, gas and petrochemical companies work in both private and governmental sectors. These companies in addition to paying close attention to technical and engineering standards should focus on the project management and evaluation models. This article while reviewing the scope of knowledge management requirements using the PMBOK Guide: 2004 presents an applicable model that can be used for self assessment of such organizations. This model applied in Gas of Zanjan province company which is an active corporation in gas distribution to city and rural areas. Project Management, PMBOK, and Project Management Evaluation. 133
4 Optimization of Multi Response Problems with Quality Answers Regarding the Distribution and Place of the Answers A. Rabani R. Nooralsana Many designed experiments require the simultaneous optimization of multiple responses. After determining the effective variable in responses and using polynomial regression models to estimate the relations between the answers and control factors, the level of the factors should be determined to make sure that responses are near the desired nominal value and their variability are small. In many cases, the responses are qualitative and should be defined in the form of linguistic terms. In this research a method is proposed to deal with qualitative responses considering both location and distribution effects. Multi response problem, Desirability function, Mimetic algorithm, Qualitative response variables, Fuzzy sets Journal of Industrial Management Faculty of Humanities Islamic 134
5 Exploring Critical Success Factors for Value Engineering Studies in Construction in Iran S. Mohammadi Bolbanabad H. Fatehi : Value engineering (VE) studies often face pressure caused by limited time and resources. The identification of key factors for Value engineering success enables appropriate allocation of the limited time and resources in order to achieve better output. Most of the related past work only identified critical success factors for Value engineering studies in general. This paper seeks to distinguish these factors according to their degrees of importance in relation to success. A questionnaire survey was conducted to gather views from experts with experience in Value engineering practice. The findings of the survey reveal the relative importance of the nominated success factors. Two factors that had not been highlighted by previous research are identified as having a significant influence on the success of VE studies. In order to explore the underlying factors among the identified critical success factors (CSFs), factor analysis was adopted to investigate the cluster of the relationship. The results indicate that the success of VE studies requires a combined effort from all parties involved. Keywords : Value Engineering Studies, Critical Success Factors (CSFs), Cluster Analysi. 135
6 QFD Application for Identifying Web Designing Essential Elements with Fuzzy TOPSIS E. Noori A. Bakhtyari Quality Function Deployment is an approach for extending new products to increase customer satisfaction. This study show a way to use the Quality Function Deployment in Web Design. The basis of this study is to design a new product based on user's demand (using Quality Function Deployment to design a Content Management System). Customer's requirements are collected with members (25 members) of a group (internet user that were familiar with electronic purchasing) from a questionnaire. Also, Design elements (Technical Requirements) are obtained from 5 web designing experts. the results show that implementation of Quality Function Deployment can adjoin the number of visits to a website and also increase user's satisfaction. The results show that most important technical requirement based on experts opinions and costumers demands are 'Content Table', 'Website Template' and 'Toolbar'. Content table mostly affects search and ordering speed, website templates which does not have a user friendly interface affects arrangement and website appearance, and finally Toolbar affects user guidance. Quality Function Deployment, Web Design, Fuzzy Set, Fuzzy TOPSIS, Extent Analysis Method. Journal of Industrial Management Faculty of Humanities Islamic 136
7 The Ranking of E-banking Challenges from Banking System's Customers and Managers Perspective by Using Fuzzy AHP S. Khorshid H. Qanea Technology development, particularly Tele-communication and informa-tion technology developments have changed Banking industry. Many studies and researches have explained E-banking developments and its operations. Also, a lot of researches have been conducted on E- banking and factors affecting on it, but there is a few/no research about E-banking challenges. This research wants investigate the E-banking challenges from Banking system's customers and managers, and use fuzzy AHP in order to rank the E-banking challenges. The results of this research shows that from Banking system's managers perspective, the most important of E-banking challenges are: customer's information privacy, internet security, and customer's trust; while from customer's perspective, the most important of E-banking challenges are: Bank's reputation, availability of online banking legal regulations, provide more reliable, faster, easier and diverse service. Although, the results of this research show that there is not agreement between Banking system's managers and customers, apparently; but it can argued that the reputation of a bank is contingent to provide more reliable, faster, easier, diverse service, and also keep customer's information privacy. E-banking, Future challenges, Fuzzy AHP, Fuzzy set theory. 137
8 Investigating the Relationship of Intellectual Capital and Organizational Performance in Banking Industry: A Case Study of Kurdistan A. N. shojaei M. Baghbanian In modern economics, Intellectual capital is described as an intangible asset which can be used as a source of sustainable competitive advantage. However, intellectual capital components have to interact in themselves to create value. Previous studies demonstrate that intellectual capital is positively and significantly associated with organizational performance. The purpose of this empirical study is to consolidate these findings and investigate the three elements of intellectual capital (i.e. human capital, structural capital, and customer capital) and their interrelationships in banking industry in Kurdistan province. The study was conducted by using a psychometrically validated questionnaire which was originally administrated in Canada. To explore the development of items and constructs, principal component analysis (PCA) and linear structural relations (LISREL) were used. The estimated final model in this study shows a positive influence of each component of intellectual capital on organizational performance in banking industry. Respectively; human capital, structural capital and customer capital have the highest effectiveness rate. Intellectual Capital, Human Capital, Structural Capital, Customer Capital, Principal Component Analysis, Linear Structural Relations. Journal of Industrial Management Faculty of Humanities Islamic 138
9 The Survey of Customer Relationship Approach Based on the EFQM Excellence Model Criteria Case study: Mehr Financial and Credit Institution Eastern Azerbaijan Province J. Baygzade A. Behboodi Today many organizations choose customer relationship approach instead of product relationship approach. They try to delight their customers by improving services and the quality of products. The transcendental organizations put the attention of customers, their needs and their loyalty into consideration. Customers are the final and last evaluators for the level of product quality and their feedback can solve problems of the organization. The aim of this research is to show the level of customer relationship for Mehr financial and credit institute in Azarbayjane-sharghi (western Azerbaijan). The model consists of one main criteria and four sub criteria by the use of which we can measure the organization s level of 'Excellence'. The sample is all customers of the Institute, and the chosen sample is 385 customers selected randomly based on Cokeran model. A questionnaire including 30 questions is used for data gathering. For the final conclusion, Cronbach s Alpha test was used with the result of 0/949. The data shows that there is a high correlation between questions and there s also high creditability and reality. For analyzing the obtained results, descriptive and deductive approaches were applied; for classification, inferring and analyzing the results single group way was applied. The results show that there is a significant relationship between Institute s current level of customer relationship and the desired level. Customer, organizational excellence, the model of EFQM, Service Quality, Customer Satisfaction, Customer Loyalty. 139
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