فصلنامه چشم انداز مدیریت صنعتی
سال دهم شماره 4 (پیاپی 40، زمستان 1399)

Generally, monitoring and performance assessing procedure systems are methods that managers use to maintain or modify work patterns or organizational resources. This is accomplished by determining goals and planning and, consequently, evaluating performance in order to become aware of the success rate in achieving predetermined goals. The present study is an applied-developmental research, because it aims to design a performance evaluation model for the Iranian Technical & Vocational Training Organization (TVTO) with an emphasis on a financial approach, thus helping the designers of the organization to adopt an optimal organization design. In the present study, based on the goals and hypotheses of the research, the methods of questionnaire, interview and study of documents have been used. To analyze the collected data, first, descriptive statistics was utilized to gain a primary understanding of the questionnaires. Next, on the inferential level, to verify the validity of the hypotheses and the relationships between the variables of the research, the path analysis technique was used. To investigate the model’s goodness of fit, confirmatory factor analysis was used. Then, the condition of the components was investigated using the t-test and, finally, the components were examined and compared. The results of the research show that the determined indicators and components are confirmed with high percentage. If they are considered by managers, they will be effective in improving the organization's performance and resource optimization.

One of the important topics in this field is Customer Lifetime value(CLV) that means how much profit a customer generates in his lifetime for a company. The main goal of this research is presenting a model for clustering and predicting customer lifetime value and customer evaluation in IRAN National Center for Numbering Goods and Services. In this research, 74,385 records of members at a specified time interval were used (from 2011 to 2017). Members are classified by CRISP methodology, resulting in the presentation of a model for predicting them. At first, members are classified into 7 clusters by RFM and K-Means. Next, each cluster is rated by CLV. Next, hidden patterns are discovered inside the data and various segments of members are then predicted through classification algorithms. Finally, the algorithms are evaluated and the final report is prepared. The results of this study exhibit the member’s behavior in each cluster on the organization’s services and membership or extended subscription and also future customer behavior are unveiled. This research helps the managers to come up with marketing strategies to keep loyal members and attract or remove inactive members by analyzing the clusters.

The aim of this research is to investigate the effect of lean and agile supply chain strategies on supply chain responsiveness and firm performance with the mediating role of postponing the order and strategic partnership of suppliers in the automotive industry in Iran. The population of this study consists of the main automotive firms in Tehran. Morgan table was used to select firms as sample. The research questionnaire was distributed and collected among and from the senior managers of the selected firms based on the convenience sampling method. A standard questionnaire was used to measure variables. The research model was tested based on structural equation modeling and LISREL software. The results showed that lean supply chain strategy has no positive effect on supply chain responsiveness. Agile supply chain strategy has a significant positive effect on supply chain responsiveness. Supply chain response has a significant positive effect on firm performance. The strategy of postponing a customer order has a mediating role in the relationship between agile supply chain strategy and supply chain responsiveness. Finally, the positive effect of lean supply chain strategy on the supply chain responsiveness was confirmed through the mediating role of strategic partnership.

Given the importance of implementing and establishing lean higher education, the aim of the present study is to model and rank the affecting factors on lean higher education in terms of faculty members of the University of Tehran. The present study is applied and the collection of data was descriptive correlational.  The population of the study consisted of all members of the faculty of the Humanities Campus of the University of Tehran, of which 147 people were selected by simple random sampling. In order to collect data, a researcher-made questionnaire was used and the validity of the questionnaires was evaluated using content and structural validity. In addition, their reliability was verified using Cronbach's alpha coefficient. The research data were analyzed using regression coefficient tests, confirmatory factor analysis, calculation of t-values, structural equation model and path analysis in Lisrel software. The validation of the model and the results of factor analysis showed that the factor structure of the measuring instruments affecting lean higher education was confirmed and the model has had a favorable fit. In addition, the results of structural equations and path analysis indicated that there has been significant relationships between variables and latent structures. The results show that the commitment of management and leadership, vision and strategy of the university through the selection of appropriate people has been effective on student satisfaction and educational efficiency.

Today, with the development of societies, entrepreneurship is vital, and so is the sustainability of an innovative entrepreneurial company. The main motive of this paper is to present a compilation methodology for estimating the priority of entrepreneurship and innovation indicators using multi-criteria decision-making (MCDM) methods, so that the three key criteria for individual, organizational and cultural dimensions are simultaneously involved in this decision. Then, a combination of the findings was obtained which is introduced in the form of a categorization of indicators. Next, based on the method of analysis, experts from the field of entrepreneurship and innovation were gathered. The process of evaluation, weight identification and prioritization of indicators was also carried out by two methods of analytical network process (ANP) and a decision-making and assessment exam and laboratory (DEMATEL). This study clearly showed that individual abilities are the basis for creating innovation and entrepreneurship in the organization and the capabilities of the organization should provide the appropriate space and facilities to the individual to actualize these two. The most important criteria were job motivation with a weight of 0.3578, and training and learning in the form of individual skill level with a weight of 0.1240, respectively. The most important alternative that can be used as a target and model is the first of three subsidiaries of Kayson International Company, which has the best position in terms of priority with a weight above 0.4498. The next companies were in the second and third places with weights of 0.2579 and 0.2132, respectively.

The oil industry has a great share in the energy structure and the global economy, and the planning of strategic and operational levels of its supply chain is done with the objective of improving the competitive status of countries on the global level and economic development. In this paper, a mathematical model is presented for designing the crude oil supply chain through considering related facility location, demand allocation, transportation planning, and distribution. In the proposed model, environmental requirements for emitted greenhouse gas are considered such that the greenhouse gas emission from the transportation of oil may not be greater than a given limit. Since the exact values of parameters can rarely be determined in the real world, therefore, the uncertainty associated with parameters such as budget, transportation capacity, production units capacity, export volume, the amount of crude oil extraction and production, demand for refinery products and their production rate are considered in the proposed model. To handle the uncertainty of the model parameters, the robust optimization approach is applied. Numerical results verify the efficiency of the proposed model and show that the profitability of oil industry can be guaranteed by handling the uncertainties of parameters and appropriate production and distribution management.

In this study, a multi-product and multi-period lot-sizing and supplier selection problem has been considered. The demand of products is multi-class and uncertain. Due to the interchangeability of products, it is possible to satisfy some part of their demand with the alternatives. In the case of an inventory shortage, a specific part of the shortage will be lost sales and the remainder will be backorder. Suppliers can have an all-units quantity discount policy. For confronting uncertain demand, possible modes are defined as scenarios and the robust optimization approach proposed by Mulvey et al. is applied. The objective function of the problem, which is to be minimized, is made up of the total cost of purchasing, transportation, inventory, demand substitution, lost sales, and backorder. The upper and lower bounds for the number of suppliers per product family are defined as a constraint for the implementation of management policies for supplier selection. Dynamic and multi-class demand in a multi-period horizon, together with allowed backlog and lost sales, are features that, to the best of our knowledge, are not yet considered by other researchers. There are many supply chains that have sold the products and should supply required spare parts. The results of this research help attain optimal ordering of the parts. The performance of the model is examined with a numerical example.