فصلنامه پژوهش های مدیریت در ایران
سال شانزدهم شماره 3 (پیاپی 77، پاییز 1391)

The contribution of the service sector in the global economy is rising nowadays and organizations are the key elements of this economical sector. The customer-orientation and attempting to enhance the performance are playing a fundamental role in the organizations success and effectiveness. The present study assesses the organizational effectiveness, using the structural equation modeling (SEM) statistical approach. As the main dependent variable, the organizational effectiveness has considered as a function of customer satisfaction and objectives attainment scales. Data was gathered from two customers population and managers population of the governmental banks of Dezfoul township, using two separate questionnaires. Based on the SEM approach, the 5 and 4 sub-scales of the customer satisfaction and objectives attainment scales were considered as observed variables. The same scales and the main dependent variable, effectiveness, were also defined as unobserved or latent variables and their interrelationship was then analysed constructing a second-order confirmatory factor analysis (CFA) model. Results confirmed the fitness and validity of all two measurment models for customer satisfaction and objectives attainment scales and also the second-order CFA for assessment of effectiveness, based on the gathered data. The precedence of the magnitude and significance of direct and indirect effects of the customer satisfaction and its sub-scales compared to the objectives attainment and its sub-scales on the organizational effectiveness is another part of results.

One of important steps to quality improvement of activities and increasing productivity in manufacturing systems, is noticing and emphasizing on evaluation factors that be Caused to personnel's efficiency reduction. Correct and timely recognition of factors that reduce to personnel's efficiency, especially managers, meets to efficiency improvement. One of major reasons of manager's efficiency reduction is dawdle. in this paper using descriptive statistics, Factor Analysis method and DEMATEL technique, has been purposed a novel model to analyzing existent similarities and diversities between opinions of different group's managers of one company about reasons of dawdle, specifying and classifying most important areas that need to improvement, and specifying cause and effect relation between them. Findings this model show the most effective factor of dawdle and finally manager's efficiency reduction in office is very much visits and sessions with very little results, and least effective factor is be inordinate social. Also most causal factors are job incentive shortage, expert personnel shortage, mistake or incomplete information, and self assurance shortage.

The use of System Dynamics Modeling in Supply Chain Management has only recently re-emerged after a lengthy slack period. the propose of this thesis is to use knowledge and techniques in implementation based on recent research. At first we have given an overview of supply chain management and system dynamics and then presented a taxonomy of research and development in System Dynamics Modeling in supply chain management. In this research we have focused on a supply chain as a case study Which produce and distribute healthy products and its main company is darugar. we used System Dynamics techniques to know effective variables in our supply chain and understand how to improve its performance. we started simulation model design by explaining dynamic hypothesis and continued by creating casual loops, stock & flow diagrams and mathematical formulation. our model was tested by famous dynamics and statistical techniques and then we started to investigate causes of supply chain’s behavior by sensitivity analyses. when we understood the main factors and their interactions completely we started to suggest three policies due to supply chain indexes to improve its performance. the policies are missed sale reduction, inventory reduction and correct information receive which all causes improvement in introduced indexes in our research. what we achieved of this research was our ability of predicting results before any changes in parameters, relationships or structure of supply chain and it is so important due to its high degree of complicity.

In order to ensure sustainable activities, companies independent upon working with defrent suppliers. In the manufacturing industries, raw material and assembly parts main comprise as much as 70 percent of production cost.For that, a purchasing department can play a vital role in reducing costs, and a purchasing manager's skill in performing his/her responsibility of choosing proper suppliers can greatly contribute to achieving that goal.This article focuses on the above-mentioned subject due to the importance of supplier choice for companies. Since the first times in history when the need for choosing proper suppliers was felt, many different methods and strategies have been utilized for such a task. Because of nature of that challenge, decision makers are faced with more than one criteria and high number of such criteria makes the challenge even more complex for them. Multi-criteria decision making has frequently been one of the approaches used by decision makers in the evaluation and selection of suppliers. In the research of this thesis a model of fuzzy multi-criteria and non-additive fuzzy integral has been presented for the supplier selection. The advantage of this model is that with the aid of Fuzzy Analytic Network Process the effects of the criteria on each other can be analyzed and with the fuzzy measure and fuzzy integral methods these interdependent relation between effects can be eliminated.

Today with growing environmental complexity and dynamism, while decision making organizations are forced to consider several issues. Success in issues like evaluating several alternatives and selecting the best depends on both criterias and elternatives full recognition. While efficient soft operation research`s methods like MADM had been developed in order to evaluate alternatives, less attention had been focused on criteria recognition.Cognitive mapping is a new method in management science that could meet this need very well. In addition to providing factor identification, by using algebraic relations, cognitive mapping enabels decision makers to identify cusal relations and their relative strength. In this study we have used cognitive mapping to provide the map of Iranian center for statistics `s operations and then we have provided a solution for performance based budgeting. In order to do that we have identified the continuum of inputs, processes, outputs and outcomes nad the process wear ranked by calculating their indirect effect on different outcomes.

The purpose of this research is to design a fuzzy inference system through the most significant influential factors and indicators on evaluation the success of ERP implementation. The intention has been to provide a comprehensive set of practical indicators in order to evaluate and improve the success of implementing enterprise resource planning (ERP) system based on deeply exploring the broad literature and to identify the most significance factors and indicators of ERP implmenetation. Through evaluating the identified indicators by domain experts, the most influential indicators have been used in designing the fuzzy inference system for evaluating the success of ERP implementation. Using this approach, the fuzzy system is designed so as to evaluate the success of implementing ERP system. The findings include the identification of the most influential indicators on the success of ERP system implementation as well as to design a fuzzy inference system to evaluate the success rate of enterprise resource planning system in organizations. Following the creation of the fuzzy inference system, organizations could measure their success in implementing enterprise resource planning system and thereby reduce their probability of failure in implementing ERP system.

The current study attempted to effect knowledge management quality of organizational culture and its relationship with breeding knowledge workers in governmental organization. In this model for investigate knowledge management, general knowledge in organizations and Hals models is used. Descriptive research method was to collect data from two questionnaires organizational culture model of Dennison (2006) and knowledge management (1388) was used. Statistical population studied in this research includes all employees of total governmental organization and departments West Azerbaijan province, which is four organizations: Commercial, Housing and Urban Development, Finance and Industry and Mines. This study shows, organizational culture on knowledge management aspects can affect the greatest impact on students will use later. This study offers to breed knowledge workers in governmental organization, it is necessary, storage and distribution of knowledge in the upper limit be considered.

Data envelopment analysis (DEA) is an approach to measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs using mathematical programming. The traditional DEA, which is based on the concept of efficiency frontier (output frontier), determines the best efficiency score that can be assigned to each DMU. Based on these scores, DMUs are classified into DEA-efficient (optimistic efficient) or DEA-non-efficient (optimistic non-efficient) units, and the DEA-efficient DMUs determine the efficiency frontier. There is a comparable approach which uses the concept of inefficiency frontier (input frontier) for determining the worst relative efficiency score that can be assigned to each DMU. DMUs on the inefficiency frontier are specified as DEA-inefficient or pessimistic inefficient, and those that do not lie on the inefficient frontier, are declared to be DEA-non-inefficient or pessimistic non-inefficient. In this paper, we argue that both relative efficiencies should be considered simultaneously, and any approach that considers only one of them will be biased. For measuring the overall performance of the DMUs, we propose to integrate both efficiencies in the form of an interval, and we call the proposed DEA models for efficiency measurement the bounded DEA models. In this way, the efficiency interval provides the decision maker with all the possible values of efficiency, which reflect various perspectives. A numeric example about Iranian gas companies will be evaluated using the DEA approach with efficient and inefficient frontiers to show its convenience and usefulness.

Internal branding is a new concept that refers to employees` effects in creating better image of brand in customers` mind. In order to surveying internal branding effects in brand citizenship behavior (BCB) in hotel industry, and also presenting an internalized scale for internal branding, four and five stars hotels located in Tehran have been tested in a model research. by the way of clustering sampling, Sample of 240 hotel customer interface employees` were selected, and questionnaires with five point likert scale have been distributed. 122 out of 136 returned questionnaires were usable (return rate of 56%). Content validity determined as suitable by the approval of marketing experts and hotel indusry professionals`, and Cronbach`s Alpha, AVE, CR, showed a great reliability for questionnaires. Conceptual model testing has been done through partial least square method and correlation test with SMART PLS software V. 1.5. The results showed that internal branding has positive relationship with brand identification (t= 9.537, β=0.563) and brand commitment (t= 2.430, β=0.192), also brand identification has positive relationship with BCB (t= 5.540, β=0.550), and brand commitment (t= 9.141, β=0.718), brand commitment has positive relationship with brand loyalty (t= 11.571, β=0.706), and brand loyalty has positive relationship with brand citizenship behavior BCB (t= 2.555, β=0.295). Correlation test confirmed these results.