A survey on existing challenges of BSC implementation for performance measurement

The balanced scorecard (BSC) is a strategic oriented tool used comprehensively in profit and nonprofit organizations all over the world to synchronize routine processes of organizations to the mission and strategy, improve inner and outter communications, control organization performance toward strategic targets. BSC has emerged from a simple performance measurement framework to a comprehensive strategic management system. It changes an organization’s strategic plan from a passive document to an active guideline for the organization on a daily basis and provides a helpful assistance that not only enables performance measurements, but also helps planners identify what should be accomplished and measured. This study focuses on how BSC is adopted as a tool for measuring effectiveness of strategy implementation in these organizations. This study adapts the BSC as a powerful tool for reaching an organization’s performance in four significant areas: Financial perspective, Customer-Market perspective, Internal Processes perspective and Learning & Growth perspective. The results suggest that governmental organizations are somehow successful in achieving their objectives in various degrees

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

Effects of Cultivation Conditions on the Expression Level of Recombinant scFv Antibody against EpEX in Escherichia coli

The EpCAM (epithelial cell adhesion molecule) is a cell surface antigen over expressed in many types of epithelial cell cancers including colon, stomach, pancreas, lung, ovarian, and breast. So, it can be an attractive target for active and passive immunotherapy of cancers. ScFv (single chain fragment variable) fragment is a class of engineered antibodies in which the genes coding for the heavy (VH) and light chains (VL) of an immunoglobulin have been linked with a short flexible peptide linker. Inexpensive media, rapid growth rates, and relatively minimal laboratory set up make Escherichia coli (E. coli) a suitable host for expression of a large variety of recombinant proteins. Here, we assessed the effect of cultivation conditions on the level of expressed scFv against extracellular domain of EpCAM (EpEX) in E. coli. pET22b-antiEpEX-scFv was transformed into prepared E. coli Rosetta™(DE3) competent cells. To evaluate the effect of cultivation conditions on protein expression level, three factors of incubation temperature (25, 30, 37°C), the IPTG (isopropyl-β-D-thiogalactoside) concentration (0.1, 0.25, 0.5, 1 mM), and induction duration (3, 5, 7, 18 h) were considered. SDS-PAGE and western blot analysis demonstrated an estimated 30 kDa-size protein band which was related to the recombinant scFv expressed in E. coli Rosetta™(DE3) strain. At optimal condition (5 h after induction with 0.5 mM IPTG at 25 °C), the final production yield of the antiEpEX-scFv was 403.29 ± 87.50 μg/mL. Our results provide a foundation for the development of scFv-based drugs’ production as effective therapeutic agents in cancers with epithelial origin.   HIGHLIGHTS The antiEpEX-scFv was successfully expressed in E. coli Rosetta™(DE3) strain. The highest concentration of protein was obtained with 0.5 mM IPTG at 30°C. The final yield of recombinant antiEpEX-scFv was approximately 403.29 ± 87.50 mg/L

Survey of Effectiveness Factors on Staff Satisfaction with FQFD and FAHP in Shazand Imam Khomeini Refinery

ABSTRACT This paper proposes an approach for staff wants development based on quality function deployment (QFD). This method considers quality by customer-oriented view and internalizes it in different stages of product/service, and finally concludes to recognition and preparation of priorities of system improvement and customer satisfaction. In this research, fuzzy QFD is used for staff of Imam Khomeiny Refinery as customers, services and rewards as technical specifications, and staff expectations as customers' wants. The staff was divided into four groups and relative weightings of each group were determined by the fuzzy analytic hierarchy process (FAHP) technique. A case in Shazand Imam Khomeini Refinery is given to illustrate the utilization of the proposed approach at this paper

Modified LRFM in order to Bank Customer Clustering based on Genetic Algorithm

AbstractClustering is a common method for analyzing various data that is used in many fields, including statistical pattern recognition, machine learning, data mining, image analysis, and bioinformatics. Clustering The process of grouping objects similar to different groups, or more precisely, partitioning and dividing a set of data, into separate subcategories, the main point of which is not to be specific. The number of classes is in clustering. One of its most widely used uses is in the field of data, the clustering of which is performed by experts in taste. Bank customer clustering has been a challenge from the beginning, and it has been difficult to find consensus among experts to select a feature for grouping.This dissertation seeks to provide a solution for dynamic clustering of bank customers. This clustering will be based on a genetic algorithm and will decide on the number of categories, members of each category, and the similarity criteria used. The dynamics of the method are based on the improvement of the LRFM method using the genetic algorithm. In other words, the genetic algorithm will try to find different information fields about the bank's customers in the database; Put the right fields next to the features used in the LRFM method and get better results for clustering the bank's customers. This process leads to the determination of the criterion of similarity of one customer with another customer and the degree of similarity between them