فصلنامه مطالعات مدیریت صنعتی
پیاپی 19 (زمستان 1389)

University is an organization with specific mission that needs to be evaluated for optimal using of resources and achieving to goals. To improve the status quo, by performance assessment could recognized weakness and strength and minimized input of resources. Thus, university has to know efficiency of faculties and to study cause of itsefficiency and inefficiency, then to improve and to conduct faculties of inefficiency by using suitable programming. DEA model is nonparametric frontier method for measuring of performance and technical efficiency of comparable sets in converting similar inputs tosimilar outputs. In this paper, according to importance of university, largest higher education center in country, efficiency of Shahid Beheshti University’s faculties is evaluated by DEA using CCR model in two cases and with weights for inputs and outputs based on goal programming (min deviation variable, min sum deviation variables,min max deviation and multi objective LP) in period of 1382-1386.DEA based on goal programming has more power for separating and presenting real weights from classic models (CCR). Finding of research presented law faculty was inefficient, and earth, science and management and account faculties were top faculties based on observed indices in this period.

Creating value for stakeholders with maximum productivity is a goal obtained by leanenterprise. In this paper designing comprehensive and valid assessment model isobserved for lean enterprise. after reviewing literature and comparing assessmentmodels of lean enterprise to each other, the conceptual research models was designedby considering assessment models of lean enterprise and also APQC framework forclassifying the processes in three dimensions: Enablers, Business Processes andBusiness Results. For this, the three main Iranian automakers Iran khodro, SAIPAand Pars khodro have been assessed by performing a field research through theirmanagers’ viewpoints. Next, the research model and impressing the model dimensionon each other have been considered and validated by structural equation modeling.Therefore, it has been used from conformity factor analysis, path analysis and t-value.Shanon Entropy has been used in order to weight the components and variables of themodel. The results obtained shows that enablers impress on business results throughbusiness processes and there are meaningful relations among them. In addition toimpress triple model dimension on each other, their factors have a meaningfulrelationship with each other. In other words, we can not achieve the lean enterprisemodel without making strong links between its factors and components, and it isnecessary to create integration within its components and factors.

The tasks in industrial institutes that managing with mass production system has different based on their “analyzability” and “variability” and this differentiation affecting on human resource practices. This paper uses “Charles pro’s four type of technologies: Repetitive,Engineering, non-repetitive and artifacts in order to explanting HRM practices. Therefore four major industries and 50 tasks based on its “analyzability”, and “variability selected. Then, two type of questionnaires were designed and distributed between 180 managers,results showed that “variability of tasks” affected reward and control modes and “analyzability of tasks” affecting on human resource planning horizon and rewards modes.

This article scrutinizes the Relationship between implementing organizational excellence model and improving human resource productivity in Tehran Oil Refinery. In order to clarify this relationship, one main hypothesis and 5 subsidiary hypotheses aredefined. The main hypothesis states that there is a positive relationship between Implementing Organizational Excellence Model and Improving Human Resource Productivity in the refinery. In this research we studied the relationship over the period June 22th 2008 - June 21th 2009 and the people who were involved in this researchinclude both managers and employees of the Refinery. The data is gathered by using a questionnaire. We have used the stratified sampling approach and the Sample has been composed of 84 people (66 employees and 18 managers). Data were analyzed by usingdescriptive and inferential statistics. Findings verify the main hypothesis. At the end, we propose some ways of using our findings in practice.

Progress towards supporting small and medium organizations, with regards to their effective role in the economy, can lead to positive results for economical-social area. To involve such organizations with (B2B) e-commerce will make the matter more significant. In this survey, the involvement of small and medium oil, gas and petrochemical companies with B2B e-commerce was studied by adopting a conceptual model on the technology acceptance model. Thus, three dimensions, information and communicationsinfrastructures, specifications related to the industry and the capabilities of human power associated with two structures of perceived productivity and utilization ease, with indices defined in the form of 3 main hypotheses and 6 minor hypotheses were tested. Theresults both confirmed all nine discussed hypotheses and indicated that there is the strongest relation between B2B e-commerce settlement and ICT infrastructures dimension. At the same time, investment in ICT infrastructures and equipments and supporting services were identified as the most significant indexes and sufficienthuman power and suitable price were recognized as the most insignificant indices to involve small and medium companies with B2B e-commerce.

Portfolio selection problem is an important field of capital assignment and budgeting in managerial finance and had proposed patterns for optimal selection of portfolio from the past. For this purpose we suggest a fuzzy ranking method with mathematical approach. This research is a survey in Tehran stock exchange. Statistical populationinclusive 50 superior companies of Tehran stock exchange in 1387. By survey of financial data of these companies, 20 companies have selected and weekly returns in 1387 have been calculated for them. In first stage, 20,000 random portfolio has been generated by a computer program. Each of these portfolios is composed of 20 companies thatquantity of investment in each of them are between 0% and 100% and selected randomly. The uncertainty on the returns of each portfolio is approximated by means of a trapezoidal fuzzy number. A rank index that accounts for both expected return and risk is defined, allowing the decision-maker to compare different portfolios and select bestportfolio. Conclusions showed that, according to risk aversion of investor, several optimal portfolios can be selected. In this article we suggested 3 optimal portfolios.

Risk is a potential which causes problems in the implementation of project and fulfillment of objectives. Risk is the innate part of all the projects and it is impossible to eliminate it completely though it can be managed effectively in order to reduce its effects on achieving the project’s objectives. It may occur in the future or not, but itsoccurrence at least affects one objective including area, time, costs or quality. Therefore identification, analysis and ranking of risk would play a significant role in the fulfillment of project. In this paper, we applied PMBOK Standard for identification of project risk for theconstruction of flyover junctions in Boushehr Province, and then we used Fuzzy AHP Technique and Fuzzy TOPSIS Technique for ranking of risk.

In this paper, a hybrid model of artificial neural networks is designed and used to evaluate the prediction ability of this hybrid model with individual Back Propagation feed forward. This study employs hybrid artificial neural networks consisting of Back Propagation andKohonen Self Organizing Map (SOM) for better stock price prediction. Computational experience in predicting stock prices obtained from Tehran Stock Exchange reveals that the combination of Self Organizing Map and Back Propagation leads to betterperformance in comparison with the most popular individual Back Propagation feed forward networks.

One of the most popular approaches to solve multi-objective stochastic problems is Chance Constrained Programming (CCP). Based on this approach, a deterministic equivalent model is presented for multi-objective stochastic problem and then is optimized by a solver model. In this Paper, both CCP approach and the Global Criterion model are combined and a model will be proposed which is called Chance Constrained Global Criterion (min-max) (CCGC(minmax)). The proposed model is able to present a deterministic equivalent model for multi-objective stochastic problem and thereafteroptimizes it. One of the subjects which always planners of manufacturing systems have concerned about, is determining the optimal number of manpower with regard to objectives such as to maximize the output, to minimize the wage cost and to minimize noallowance idle time. Hence to illustrate the proposed model, a multiobjective stochastic problem is presented for to determine the optimal number of manpower in a job shop manufacturing system under uncertainty. The optimization results of this problem using the proposed model and the CCCP(with min-max norm) model under the same conditions, express the proposed model with existence fewer number of variables and constraints compared to the CCCP(min-max) model, presents the wholly same results in fewer number of iterations.

Nowadays quantitative methods have become very important tools for forecasting purposes in markets as for improved decisions and investment. Forecasting accuracy is one of the most important factors involved in selecting method; Artificial Neural Network (ANNs) are flexible computing frameworks that can be applied to a wide range offorecasting with a high degree of accuracy. In this research, Fuzzy logic and Artificial Neural Network are integrated in to the Fuzzy Back- Propagation Network (FBPN) for sales forecasting in Wood and Paper industry. The proposed system is evaluated through the real world data provided by a Wood an d Paper company and experimentalresults indicate that the Fuzzy Back- Propagation approach outperforms are better other two different forecasting models (Linear Regression and ARIMA time series model) in MAPE measures.

This paper aims at studying the strategic alignment among business strategy, financial strategy, investment strategy, financing strategy, dividend strategy, and working capital strategy based on a comprehensive model (based on strategic reference points - SRPs).The comprehensive model is based on process view in strategic management were implementation is a function of formulation (focus internal or external – SRP1) and control (low or high – SRP2). In this paper at first we identify typologies of business, financial andsubsystem strategies based on SRPs, and then study the relationship among these strategies. Survey research strategy used in this study. 273 Tehran Exchange Production Companies were selected for statistical population and 67 Companies included in statisticalpopulation have collaborated in this research. Types of business, financial and subsystem strategies calculated for 67 Companies in 2008. Measurement tools were questionnaire, interviewing and financial statements analyses. Descriptive statistical methods are usedfor data gathering. Analytical statistical methods, parametric and nonparametric were used for data analyses. The results show that, external (vertical) alignment between financial strategy and business strategy, internal (vertical) alignment between financial and subsystem or functional strategies, internal (horizontal) alignment between financial subsystem strategies and external (vertical) alignment between financial subsystem strategies and business strategy and interaction among these strategies affect the performance (ROA). The results reveal that, those companies with higher rate of alignment enjoy better performance (ROA) than those with average or loweralignment.

In this paper the budgeting procedures of a hypothetical bank to enter market and investing activities have been studied on the basis of the three factors; inflation rate, liquidity rate and GDP (Growth Domestic Products) employing General Linear Model. Related information was collected randomly from the year 2001 to 2007, and then analyzed statistically by the software Minitab version 15 and SPSS version11.The result of the research showed that the inflation rate and liquidity grown had noticeable impact on GDP so the analysis proved a correlation coefficient relation between the variables with a range of 96 per cent. According to the analysis on the basis of a linear regression methods in one hand and the variance obtained from theGLM process, some 83 per cent of correlation coefficient could be witnessed between Liquidity and inflation growth; while a 75 per cent of meaningful correlation coefficient can be traced in the effect of inflation rate on liquidity.